i

CATECHOLAMINES AS INDEPENDENT

PREDICTORS OF OUTCOME IN MODERATE AND

SEVERE TRAUMATIC BRAIN INJURY (TBI). THE

COMA-TBI STUDY

By

Luis Teodoro da Luz

A thesis submitted in conformity with the requirements

for the degree of Master of Science

Institute of Medical Sciences

University of Toronto

© Copyright by Luis Teodoro da Luz 2015

ii

Catecholamines as Independent Predictors of Outcome in

Moderate and Severe Traumatic Brain Injury (TBI). The

COMA-TBI Study

Luis Teodoro da Luz

Master of Science

Institute of Medical Sciences

University of Toronto

2015

1. Abstract

Introduction: High levels of catecholamines post brain trauma are associated with

severity of injury and neurological outcome. We aimed to overcome methodological

limitations of previous studies and demonstrate an independent association between

circulating catecholamine levels with neurological outcome in patients with isolated brain

injury. Methods: Multi site, prospective observational blinded cohort study. After

enrollment, patients had catecholamine levels measured on admission and the independent

association with a 6-month neurological outcome was assessed using the Glasgow

Outcome Scale Extended. Multivariate logistic regression models estimated the adjusted

odds ratio for prediction of unfavorable outcome. Results: 181 patients were enrolled and

admission catecholamines were measured. High admission levels were independently

associated with severity of injury and with unfavorable outcome. Conclusion: We

demonstrated the natural history of catecholamine release early post brain injury and an

independent association with unfavorable outcome in a dose response fashion.

Catecholamines are biomarkers of outcome in moderate to severe traumatic brain injury.

iii

2. Acknowledgments

This thesis is dedicated to Flavio Henrique Duarte de Araujo, my partner of life,

for showing me that there is much more to discover and achieve when leaving our comfort

zone. Thanks for the constant emotional support, respect, companionship and love.

I also dedicate this thesis to my parents Sebastião Teodoro da Luz (in memoriam)

and Inácia Rosa da Luz, both very simple and respectful people. From mom and dad I

learned how to be humble and strong at the same time, characteristics I think are important

to face difficulties in life.

I would like to express my deep gratitude to my supervisor Dr. Sandro Rizoli for

his continuous support, patience, and helpful advice, for opening the door to a wide range

of opportunities. His continuous efforts have made this project possible. I would also like

to thank Dr. Andrew Baker and Dr. Leodante da Costa for their insightful feedback and

strong guidance to ensure my work was moving in the right path. I would also like to

extend my thanks to the members of my outstanding thesis committee members Dr. John

Marshal, Dr. Sunit Das, and Dr. Eric Ley.

The COMA-TBI study would not have been possible without a large team of

experts that was fundamental in all phases of the study. I would like to express my

immense gratitude to the strong work of all members. This unique team is represented by

Dr. Capone Neto, Dr. Bartolomeu Nascimento, Dr. Gordon Rubenfeld, Dr. Kenji

Inaba, Dr. Alex Di Battista, Dr. Jane T-Vranic, Dr Adic Perez, Dr. Mitra Arjang,

Shawn Rhind, Sandy Trpcic, Brandon Lejnieks, Arimie Min, Yangmei Li and Monica

Wong.

iv

3. Contributions

The idea of the COMA-TBI study initiated around 2010. In 2011 the project was

written and applications for funding and Research Ethics Board approval were submitted.

Patient enrollment started in late 2011. Dr. Luis Teodoro da Luz initiated his contribution

to the study in 2013 when enrollment was finalizing. Dr. da Luz was involved in updating

the research project, reviewing, cleaning and critically analyzing clinical data, coordinating

finalization of the data with the research assistants and managers from the 3 study sites. Dr.

da Luz was involved in the team effort of performing the statistical analysis and fully

responsible for the production of the thesis dissertation. Dr da Luz is also an important

contributor in writing the main manuscripts using the COMA-TBI study data.

Dr. Sandro Rizoli was the principal investigator of the study, contributing with all

aspects of the trial, from generating the research question, to study design, production of

study protocol and application for funding. Dr. Rizoli also coordinated the diverse teams

from the 3 different centers, and was involved in all phases of the study and reviewed the

statistics analyses, results, the thesis dissertation and the COMA-TBI manuscript.

Dr. Capone Neto contributed to the research question, design, study protocol

production, consent forms, application for funding, and for REB approval. Dr. Capone

Neto also reviewed the statistical approach and results.

Dr. Alex Di Battista and Dr. Shawn Rhind were instrumental in all phases of the

trial, from concept to creation to analysis and more recently, in writing and disseminating

the results of the trial. Dr Rhind participated in the concept and writing of the project,

arranging for funding, managed the conduction of all laboratorial experiments from sample

v

collection to results. Drs Di Battista and Rhind have a major role in the analysis of the data,

particularly that of the laboratorial results, and writing of the main manuscripts using the

COMA-TBI data. Dr Di Battista is using part of the COMA-TBI data for his PhD work.

Dr. Gordon Rubenfeld and Dr. Martin Chapman made important contributions

to the initial concept and its writing by critically reviewing it. Their major contribution was

to the methodology for the trial. They participated in the applications for funding and

Research Ethic Board approval. They also participated on the initial phases of the clinical

trial.

Mrs. Sandy Trpcic was instrumental in managing the entire project, from

conception to finalization. Mrs. Trpcic has coordinated the efforts from the 3 sites and

ascertained that all regulations were followed and all aspects of the work were done.

At SHSC: Dr. Adic Perez was the research coordinator with the important role of

acquiring the data, storing it and making the results available whenever needed.

At SMH: Dr. Jane Topolovec-Vranic was the Principal Investigator and was

heavily support by Dr. Andrew Baker. Dr Baker was instrumental in all phases of the

study, from its conception and writing, to final analysis. Mrs. Yangmei Li and Marlene

dos Santos were the research coordinators responsible for all aspects of the trial, including

all regulatory steps, from patient enrollment, consenting, data acquisition, and blood

sample handling.

At LA County: Dr. Kenji Inaba was responsible for coordinating all aspects of the

trial. Mrs. Monica Wong was the local research coordinator, coordinating enrollment,

consenting, data acquisition and blood sample handling.

vi

4. Table of Contents

Page

1. Abstract __________________________________________________ ii

2. Acknowledgements _________________________________________ iii

3. Contributions ______________________________________________ iv

4. List of Tables _____________________________________________ viii

5. List of Figures _____________________________________________ ix

6. List of Appendices _________________________________________ x

7. List of Abbreviations ________________________________________ xi

CHAPTER 1 – LITERATURE REVIEW ____________________________ 1

1.1 Introduction _________________________________________ 1

1.2. Catecholamines _____________________________________ 3

1.2.1. History of catecholamine Research _____________________ 3

1.2.2. Pharmacology _____________________________________ 3

1.2.2.1. Epinephrine and Norepinephrine Synthesis _____________ 3

1.2.2.2. Epinephrine and Norepinephrine Storage _______________ 4

1.2.2.3. Epinephrine and Norepinephrine Release ______________ 4

1.2.2.4. Termination of Action ______________________________ 4

1.2.2.5. Receptors and Specific Actions ______________________ 5

1.2.3. Catecholamines in Traumatic Brain Injury ________________ 8

1.2.3.1. Effects in the Brain ________________________________ 8

1.2.3.2. Paroxysmal Sympathetic Storm ______________________ 12

1.2.3.3. Effects in the Cardiovascular System __________________ 14

1.2.3.4. Effects in the Lungs _______________________________ 15

1.2.3.5. Effects in Inflammation _____________________________ 16

1.3. Catecholamines and Current TBI Therapeutic Strategies ______ 20

1.4. Prediction of Outcome after TBI _________________________ 26

1.4.1. Age ______________________________________________ 26

1.4.2. Pupillary Diameter and Light Reflex _____________________ 28

1.4.3. Hypotension _______________________________________ 29

vii

1.4.4. Glasgow Coma Scale _______________________________ 32

1.4.5. Computed Tomography (CT) Findings __________________ 33

1.4.5.1. Abnormal CT _____________________________________ 33

1.4.5.2. Classification of TBI according to CT findings ___________ 34

1.4.6. Additional Strategies to Determine Outcome ______________ 37

1.4.6.1. Clinical Assessment _______________________________ 37

1.4.6.2. Neuroimaging ____________________________________ 41

1.4.6.3. Brain Physiology/Metabolism ________________________ 42

1.4.6.4. Electrophysiology _________________________________ 43

1.4.6.5. Serum Biomarkers ________________________________ 44

1.4.6.6. Laboratory Parameters _____________________________ 46

1.4.6.7. Therapeutic Interventions ___________________________ 47

1.4.7. The Role of Catecholamines as Outcome Predictors _______ 48

CHAPTER 2 – THE COMA-TBI STUDY____________________________ 51

2.1. Rationale ___________________________________________ 51

2.2. Hypothesis and aims __________________________________ 50

2.2.1. Hypothesis ________________________________________ 51

2.2.2. Specific aims ______________________________________ 51

2.2.2.1. Specific aims for the initial analysis ___________________ 51

2.2.2.2. Specific aims for the primary outcome analysis __________ 52

2.2.2.3. Specific aims for the secondary outcome analysis ________ 53

2.2.2.4. Specific aims for the catecholamine analysis ____________ 53

CHAPTER 3 – METHODS ______________________________________ 55

3.1. Setting _____________________________________________ 55

3.2. Study Design ________________________________________ 56

3.3. Study Definitions _____________________________________ 56

3.4. Data Acquisition _____________________________________ 65

3.5. Study Outcomes _____________________________________ 70

viii

3.6. Statistical Analysis ___________________________________ 71

CHAPTER 4 – RESULTS ______________________________________ 74

4.1. Initial Analysis _______________________________________ 74

4.1.1. Centers and Study Participants Enrollment _______________ 74

4.1.2. Blood Samples Flow in the Study ______________________ 75

4.1.3. Association between demographics, clinical, laboratory and

radiological characteristics with unfavorable outcome ____________

76

4.1.4. Distribution of patients according to injury severity scores

(GCS, AIS, Marshall) and GOSE ____________________________

81

4.2. Primary Study Outcome _______________________________ 84

4.3. Secondary Study Outcomes ____________________________ 88

4.3.1. Hospital/ICU length of stay, ventilation and mortality ________ 88

4.3.2. Catecholamine levels in pooled TBI patients ______________ 90

4.3.3. Catecholamine levels according to severity of injury (GCS, AIS

and Marshall) ___________________________________________

4.3.4. Catecholamine levels according to death, MODS, sepsis and

ICP ___________________________________________________

90

98

CHAPTER 5 – DISCUSSION AND FUTURE DIRECTIONS ____________ 100

5.1. Discussion _________________________________________ 100

5.1.1. Summary of Key Findings ____________________________ 100

5.1.2. Primary Study Outcome and Previous Data ______________ 102

5.1.3. Secondary Outcomes and Previous Data ________________ 106

5.2. Future Directions ____________________________________ 110

5.2.1. Pathophysiology ___________________________________ 110

5.2.2. Tools for Prediction of Outcome _______________________ 111

5.2.3. Modulation of the Hyperadrenergic State ________________ 113

5.3. Limitations __________________________________________ 113

ix

5.3.1. Risk of information bias ______________________________ 113

5.3.2. Risk of confounding _________________________________ 114

5.3.3. Dichotomization of variables __________________________ 115

5.3.4. Practice variability __________________________________ 116

5.4. Conclusions ________________________________________ 116

8. Disclaimer ________________________________________________ 117

9. Conflicts of Interest _________________________________________ 117

10. Reference List ____________________________________________ 118

11. Appendices ______________________________________________ 155

12. Copyright Acknowledgements _______________________________ 163

x

4. List of Tables

Page

Table 1 – The Full Outline of Unresponsiveness (FOUR) Score ______________ 39

Table 2 – The Injury Severity Score ____________________________________ 55

Table 3 – The Glasgow Coma Scale (GCS) _______________________________ 56

Table 4 – The Glasgow Outcome Scale (GOSE) ___________________________ 57

Table 5 – The post discharge structured interview for GOSE _________________ 58

Table 6 – The Abbreviated Injury Scale (AIS) ____________________________ 61

Table 7 – The Marshall Classification ___________________________________ 62

Table 8 – Association between demographics, clinical, laboratory and radiological

characteristics with unfavorable outcome _________________________________

76

Table 9 – Multivariate logistic regressions for median E and NE admission levels

including age (in decades), hypotension (<100mmHg), severe TBI (GCS 3-8),

severe head injury (AIS 4-5), coagulopathy (INR>1.2) and vasopressors for

predicting unfavorable outcome (GOSE 1-4) at 6 months.___________________

83

Table 10 – Multivariate logistic regression for tertiles of median admission E and

NE levels, including age (in decades), hypotension (<100mmHg), severe TBI

(GCS 3-8), severe head injury (AIS 4-5), coagulopathy (INR>1.2) and

vasopressors for predicting unfavorable outcome (GOSE 1-4) at 6 months.______

84

Table 11 – Association between secondary outcome variables and unfavorable

outcome ___________________________________________________________

85

Table 12 – Statistically significant comparisons of the log base-10 scale of median

E levels according with each time point in the Marshall Classification __________

90

xi

Table 13 – Statistically significant comparisons of the log base-10 scale of median

NE levels according with each time point in the Marshall Classification ________

91

xii

5. List of Figures

Page

Figure 1 – Adrenergic receptor signaling pathways ________________________ 8

Figure 2 – The CRASH prediction model ________________________________ 37

Figure 3 – The IMPACT prediction model _______________________________ 38

Figure 4 – Study flow _______________________________________________ 67

Figure 5 – Flow diagram of the screening process _________________________ 72

Figure 6 – Flow diagram of blood samples collection and manipulation ________ 73

Figure 7 – Distribution of patients according to the Glasgow Coma Scale on

admission _________________________________________________________

79

Figure 8 – Distribution of patients according to the abbreviated injury score (AIS) 79

Figure 9 – Distribution of patients according to Marshall score on admission CT

scan ______________________________________________________________

80

Figure 10 – Distribution of patients according with GOSE categories at discharge

and at 6 months post injury ____________________________________________

81

Figure 11 – Median admission E and NE levels according to the dichotomization

of GOSE at 6 months (favorable and unfavorable outcomes) _________________

82

Figure 12 – Profile of median E and NE levels over the 4 time points (admission,

6, 12 and 24h) ______________________________________________________

86

Figure 13 – Median admission E and NE levels according to the Glasgow Coma

Scale in patients with moderate (GCS 9-12) or severe (GCS 3-8) TBI __________

87

Figure 14 – Median admission E and NE levels according to the Abbreviated

Injury Scale in patients with severe head (AIS>3) and non-severe head (AIS≤2) _

88

Figure 15 – Profile of median E and NE levels according to the Marshall

categories in all 4 time points (admission, 6, 12, 24 hours) ___________________

89

xiii

Figure 16 – Profile of median E and NE admission levels across the GOSE

categories _________________________________________________________

93

Figure 17 – Profile of median E levels across all 4 time points (admission, 6, 12,

24 hours) in unfavorable and favorable outcome patients by GOSE at 6 months __

94

Figure 18 – Profile of median NE levels across all 4 time points (admission, 6, 12,

24 hours) in unfavorable and favorable outcome patients by GOSE at 6 months __

94

Figure 19 – Median admission E and NE levels according to ICP, sepsis, MODS

and death __________________________________________________________

96

xiv

6. List of Appendices

Page

Appendix 1 – Informed Consent to Participate in a Research Study ___________ 113

Appendix 2 – Case Report Form _______________________________________ 119

xv

7. List of Abbreviations

6-OHDA – 6-hydroxydopamine

ACTH – Adrenocorticotropin hormone

ADC – Apparent diffusion coefficient

AIS – Abbreviated injury scale

ATP – Adenosine triphosphate

AUC – Area under the curve

BB – Beta blocker

BBB – Blood brain barrier

BDNF – Brain derived neurotrophic factor

CaMKII – Calcium/calmodulin dependent protein kinase II

cAMP – Cyclic adenosine monophosphate

CARS – Compensatory anti-inflammatory response syndrome

CBF – Cerebral blood flow

CI – Confidence interval

CIDS – Central nervous system injury-induced immunodepression

CNS – Central nervous system

COMT – Catechol-O-methyltransferase

CPP – Cerebral perfusion pressure

CRASH – Corticosteroid Randomization after Significant Head Injury

CREB – cAMP response element binding protein

CSF – Cerebral spinal fluid

CT – Computed tomography

DA – Dopamine

DAI – Diffuse axonal injury

DTI – Diffusion tensor imaging

E – Epinephrine

ED – Emergency department

EDH – Epidural hematoma

EEG – Eletroencephalography

EIA – Enzyme immunoassay

ERK – Extracellular signal-regulated kinase

FOUR – Full Outline of UnResponsiveness

GPCR – G protein coupled receptor

HDS – Hypertonic saline plus dextran

HLA – Human leukocyte antigen

ICAM – Intercellular adhesion molecule

ICH – Intra cerebral hematoma

xvi

ICP – Intra cerebral pressure

ICU – Intensive care unit

IL – Interleukin

IMPACT – International Mission on Prognosis and Clinical Trial Design in TBI

IP3 – Inositol trisphosphate

ISS – Injury severity score

IVH – Intra ventricular hemorrhage

GCS – Glasgow coma scale

GFAP – Glial fibrillary acidic protein

GOS – Glasgow outcome scale

GOSE – Glasgow outcome scale extended

HSD – Hypertonic saline plus dextran

LA – Los Angeles

LOC – Level of consciousness

L/P – Lactate/Pyruvate ratio

MAO – Monoamino oxydase

MAPK – Mitogen activated protein kinase

MCP – Monocyte chemoattractant protein

MHC – Major histocompatibility complex

NE – Norepinephrine

NFkB – Nuclear factor kappa-light-chain-enhancer of activated B cells

NGF – Nerve growth factor

NPE – Neurogenic pulmonary edema

NPV – Negative predictive value

NSE – Neuron-specific enolase

OR – Odds ratio

PET – Positron emission tomography

PKA – Activating protein kinase A

PKC – Activating protein kinase C

PPAR-γ – Peroxisome proliferator-activated receptor gamma

PPV – Positive predictive value

PRDX – Peroxiredoxin

PSS – Paroxysmal sympathetic storm

PTX3 – Pentraxin 3

RCT – Randomized controlled trial

RNA – Ribonucleic acid

ROC – Receiver operating curve

S100ß – S100 beta protein

S100ßß – Monomer of S100 beta protein

SAH – Subarachnoid hemorrhage

xvii

SDH – Subdural hematoma

SHSC – Sunnybrook Health Sciences Centre

SIRS – Systemic inflammatory response syndrome

SMH – Saint Michael`s Hospital

SNS – Sympathetic nervous system

SSEP – Somatosensory evoked potentials

T3 – Triiodothyronine

T4 – Thyroxine

TBI – Traumatic brain injury

TCDB – Traumatic coma data bank

TNFα – Tumor necrosis factor alpha

UCH-L1 – Ubiquitin C-terminal hydrolase

USC – University of south California

VCAM – Vascular adhesion molecule

VMAT-2 – Vesicular aminotransporter

1

Catecholamines as Independent Predictors of Outcome in

Moderate and Severe Traumatic Brain Injury (TBI). The

COMA-TBI Study

CHAPTER 1 – Literature Review

1.1. Introduction

Trauma is a major public health problem responsible for over 6 million deaths and

three times as many disabled patients across the world. Traumatic brain injury (TBI) plays

a significant role in this onus across all age groups [1]. There is clinical evidence that even

mild head injuries can negatively impact on physical, cognitive and social performance [2,

3]. Furthermore, the overall mortality in patients with TBI is approximately 10%, but can

reach 40% in patients with severe head injury, specifically [4]. According to the most

recent CDC estimates (2004-2006) [5], there are 1.7 million new cases of TBI annually,

with 52,000 deaths, 275,000 hospitalizations, and 1.4 million people treated in emergency

departments (ED), with approximately 1.4 times as many TBIs occurred among males as

among females [5]. In Canada, while the total number of hospitalization for head injuries

decreased in the last decade, hospital admissions due to severe TBI have increased. The

number of admissions to trauma facilities for severe trauma (all causes) grew from 8,784 in

2000-01 to 10,249 in 2003-04, representing a 17% increase. However, the number of

admissions to trauma facilities for severe TBI increased by 46% [4].

Only 5% of patients sustaining a head injury present with a low level of

consciousness, with a Glasgow Coma Scale (GCS) less than 12, and the majority of deaths

occur exactly in these patients. Consequently, EDs care for large number of patients with

minor head injuries, but are challenged when managing patients with moderate and severe

TBI who carry enormous chances of dying or becoming disabled [6]. Therefore, our study

focused on the latter group of TBI patients with moderate and severe injuries.

The ability to predict outcome in brain injury may significantly impact in patient

2

management, such as in invasive monitoring (ICP monitoring, tissue brain oxygen

monitors, microdialysis, etc), in specific therapeutic strategies and in long-term care,

especially in patients suffering moderate and severe TBI. Furthermore, outcome prediction

after TBI may facilitate research, improve quality of care and assist with goals of care and

end-of-life decisions. However, prediction of outcome after TBI is still inconsistent and

difficult. While well-known markers have long been used in clinical practice to help predict

outcome, there is controversy regarding how they should be utilized and evaluated.

Therefore, identification of other reliable biomarkers or predictors of outcome in severe

TBI patients is still needed.

Small observational cohort studies have demonstrated that plasma catecholamine

levels (norepinephrine – NE and epinephrine – E) measured at hospital admission in

patients with brain injury, rise exponentially as a function of severity [7-11]. Furthermore,

levels of plasma catecholamines have been correlated with outcome in this population [7-

11]. Clinical studies show a significant association between high levels of both E and NE in

TBI patients on admission, and clinical indices, such as GCS score, duration of mechanical

ventilation, myocardial damage, endocrine abnormalities, length of stay and neurological

outcome [7-11]. However these studies have important methodological limitations such as

small sample sizes and no adjustment for confounders. Furthermore, the levels of

catecholamines on those studies are not measured early post trauma, especially within the

first 24 hours, and this approach is important as we believe that the initial levels have the

strongest association with outcome. Another limitation is that the studies generally enroll

patients with multisystem trauma and not patients with isolated brain injury exclusively.

Our study intends to overcome these limitations with a proper power to detect differences,

adjusting for confounders, enrolling patients with isolated moderate to severe TBI direct

from the scene of the accident, and measuring catecholamines since the early admission to

the hospital. The objective is to demonstrate the natural history of catecholamine release

early post traumatic brain injury and the association of the high levels with unfavorable

outcome in patients with moderate to severe isolated TBI.

This literature review will provide the following: 1) pharmacology of

catecholamines, 2) the role of catecholamines in TBI pathophysiology, 3) catecholamines

and current TBI therapeutic strategies, 4) current tools used for prediction of outcome in

3

brain injury and 5) the role of catecholamines in predicting outcome in TBI.

1.2. Catecholamines

1.2.1. History of Catecholamine Research

Collectively, the term catecholamines comprise the endogenous amines nor

adrenaline (norepinephrine), adrenaline (epinephrine) and dopamine. Their investigation

constitutes a prominent chapter in the history of physiology, biochemistry and

pharmacology. Adrenaline was the first hormone isolated from the adrenals and obtained in

pure form, even before the word hormone was coined [12]. It was also the first hormone to

have its structure and biosynthesis depicted. Acetylcholine, E and NE were the first

neurotransmitters to be demonstrated, and had their intercellular biochemical signals found

in intracellular vesicles described. In addition, the β-adrenoceptor was the first G protein-

coupled receptor gene to be cloned. More focused catecholamine research began with the

preparation by George Oliver and Edward Albert Sharpey-Schafer of a pharmacologically

active extract from the adrenal glands [12].

1.2.2. Pharmacology

1.2.2.1. Epinephrine and Norepinephrine Synthesis

Catecholamines are derived from Tyrosine. Tyrosine is sequentially 3-hydroxylated

and decarboxylated to form dopamine. Dopamine is ß-hydroxylated to yield

norepinephrine, which is N-methylated in chromaffin tissue to generate epinephrine [13].

The hydroxylation of tyrosine by tyrosine hydroxylase is generally regarded as the rate-

limiting step in the biosynthesis of catecholamines [14]. This enzyme is activated following

either direct stimulation of sympathetic nerves or via the actions of adrenocorticotropic

hormone (ACTH) on the adrenal medulla. The enzyme is a substrate for activated protein

kinase A (PKA), activated protein kinase C (PKC), and calcium/calmodulin dependent

protein kinase (CAM Kinase). Kinase-catalyzed phosphorylation may be associated with

increased hydroxylase activity [14, 15]. This is an important acute mechanism for

increasing catecholamine synthesis in response to elevated nerve stimulation. In addition

there is a delayed increase in tyrosine hydroxylase gene expression after nerve stimulation.

4

This increased expression can occur at multiple levels of regulation, including

transcription, RNA processing, regulation of RNA stability, translation, and enzyme

stability [16]. These mechanisms serve to maintain the content of catecholamines in

response to increased transmitter release. Finally, tyrosine hydroxylase is subject to

feedback inhibition by catechol compounds, which allosterically modulate enzyme activity.

1.2.2.2. Epinephrine and Norepinephrine Storage

Epinephrine and norepinephrine are stored in vesicles ensuring their regulated

release; this storage decreases intraneural metabolism of these transmitters and their

leakage outside the cell. The vesicular amine transporter (VMAT-2) appears to be

extensively driven by pH and potential gradients created by an ATP-dependent proton

translocase. For every molecule of E or NE taken up, two H+ are extruded [17].

Monoamine transporters are relatively promiscuous, and beyond E and NE they also

transport dopamine and serotonin besides E and NE [18]. These amines are also transported

by other neuronal membrane transporters which are present in the adrenal medulla, liver,

placenta, stomach, pancreas and kidney [19].

1.2.2.3. Epinephrine and Norepinephrine Release

The full sequence of steps by which the nerve impulse affects the release of NE

from sympathetic neurons is not known. The triggering event in the adrenal medulla is the

liberation of acetylcholine by the preganglionic fibers and its interaction with nicotinic

receptors on chromaffin cells to produce a localyzed depolarization [20]. A subsequent step

is the entrance of calcium into these cells, which results in extrusion by exocytosis of the

granular contents, including E. Influx of calcium likewise plays an essential role in release

of NE at sympathetic nerve terminals. Calcium-triggered secretion involves interaction of

highly conserved molecular scaffolding proteins leading to docking of granules at the

plasma membrane and ultimately leading to secretion [20].

1.2.2.4. Termination of Action

The actions of E and NE are terminated by reuptake into the nerve terminal by

amine transporters; dilution by diffusion out of the junctional cleft and uptake at

extraneuronal sites by other amine transporters and by metabolic transformation. Two

5

enzymes are important in the initial steps of catecholamine transformation – monoamino

oxydase (MAO) and catechol-O-methyltransferase (COMT). In addition, E and NE are

metabolized by sulfotransferases [21]. The termination of actions by a powerful

degradative enzymatic pathway, such as that provided by acetylcholinesterase at sites of

cholinergic transmission, is absent from the adrenergic nervous system. Thus, the neuronal

reuptake process becomes important and this is observed by the inhibitors of this process

(e.g., cocaine and imipramine) that potentiate the effects of the neurotransmitter, while

inhibitors of MAO and COMT have relatively little effect. However, MAO metabolizes a

transmitter that is released within the nerve terminal. COMT, particularly in the liver, plays

a major role in the metabolism of endogenous circulating and administered catecholamines.

1.2.2.5. Receptors and Specific Actions

On Figure 1 we illustrate the adrenergic receptors signaling pathways. Adrenergic

receptors are G protein coupled receptors (GPCRs) and consist of 7 transmembrane

domains, with an intracellular catalytic domain that interacts with subunits. When the

receptors are bound by E or NE, their effects are initiated by secondary messenger systems.

The receptors subtypes consist of two types, α type (α1 and α2) and β type (β1, β2, β3),

named primarily on the basis of their specific effects following stimulation [22]. Alpha

receptors mediate excitation, while beta receptor activation generally results in relaxation

(with the exception of the heart) [22]. What is observed is that alpha receptor activation

leads to constriction of blood vessels, while beta receptor activation leads to vasodilation.

In the heart, beta receptor activation (mainly β1) results in increased contractility and

cardiac output, and in the lungs (mainly ß2), causes bronchodilation.

The most documented effects of adrenergic receptor activation are related to the

cardiovascular system, although the receptors are ubiquitously expressed throughout the

body. Ahlquist [23] demonstrated that in the brain, the greatest density of β receptors is

found in the cerebral cortex and corpus striatum. In these both areas, NE acts on β

adrenergic receptors to increase glutamate reuptake, glucose uptake, and glycolysis. The

same author showed that systemic sources of NE are the adrenal medulla and the

sympathetic nerve tissue. Sympathetic neurons secrete only NE, and not E and NE is

produced by noradrenergic neurons in the locus coeruleus in the brain stem. It seems that

6

severity of brain damage denotes higher levels of NE in the brain. Abercrombie [24]

reported that NE levels measured in the microdialysate from the hippocampus remain

normal until >50% of the neurons are destroyed. Higher release of NE was achieved when

simulation of excitotoxicity was induced, even when <50% of the cells were depleted.

Xiao [25] reported that the β1 receptor couples exclusively with Gs proteins, while

the β2 receptor can couple with either Gs or Gi. When coupled with Gs, adenylate cyclase

is activated, which catalyzes the synthesis of cyclic adenosine monophosphate (cAMP) and

activates protein kinase A (PKA). Increased cAMP levels catalyze ATP formation. PKA

phosphorylates the membrane bound L, N, P, Q, and R type calcium channels, leading to

increased calcium influx and membrane depolarization. Increasing calcium causes a

phenomenon called calcium induced calcium release, in which inositol trisphosphate (IP3)

and ryanodine receptors are stimulated to release calcium stored in the endoplasmic

reticulum [26, 27]. The voltage regulated calcium channels poses an auto-inhibitory

feedback mechanism that regulates calcium influx. In thalamo-cortical relay neurons,

adrenergic stimulation prevents normal deactivation of high voltage activated calcium

channels, potentiating calcium entry into the cell [28]. Increased cAMP levels have been

shown to prevent the activation of microglia and inhibit the expression of the major

compatibility complex (MHC) on astrocytes [28]. A study [28] using porcine corneal

epithelial cells observed that isoproterenol increased cellular cAMP concentration, and

decreased intracellular calcium. Finally, PKA activates the peroxisome proliferator-

activated receptor gamma (PPAR-γ) transcription factor, which couples with retinoic acid

receptor in the nucleus to initiate transcription. PPAR-γ transcription is largely anti-

inflammatory, and PPAR-γ agonists have been shown to improve insulin sensitivity and

reduce blood pressure [29]. PPAR-γ is also involved in the transcription of IL-6, and

angiogenic factors. Furthermore, as described by several other studies [30-32], adrenergic

agonists can also bind to β1 or β2 adrenergic receptors to activate the calcium/calmodulin

(CaM) dependent protein kinase II (CaMKII) which is activated by calmodulin when

bound to calcium. Activated, CaMKII phosphorylates the L, N, P, Q, and R type receptors,

leading to high levels of cytosolic Ca2+ and phosphorylation of the cAMP response

element binding protein (CREB). This process induces the transcription of growth factors

such as brain derived neurotrophic factor (BDNF).

7

Protein kinase A is part of a negative feedback loop, and phosphorylates the β

receptor, causing the coupling process to switch to a Gi coupled. Activated Gi protein

induces the sequestration of adenylyl cyclase, leading to reduced levels of cAMP and

inhibition of PKA. The Gi pathway also activates the mitogen activated protein kinase/

extracellular signal-regulated kinase (MAPK/ERK) pathway, switching to a

pro-inflammatory nuclear factor kappa-light-chain-enhancer of activated B cells (NFkB)

transcription profile where tumor necrosis factor alpha (TNFα) and interleukin (IL)-1B are

produced. Dvoriantchikova [33], in an animal study, demonstrated that inhibition of NFkB

lead to improved neuronal survival after ischemic injury. At high enough NE

concentration, surface receptor expression is diminished as the receptors are endocytosed

for recycling. Pippig [34], in a study with A431Stimulation of β2 receptors, demonstrated

rapid decoupling from Gs, triggered by receptor phosphorylation and a delayed

sequestration of the receptors to an internal compartment. Upon removal of the agonist, β2

receptors were recycled to the membrane surface, dephosphorylated, and the receptor

function was restored.

8

Legend: α1 – alpha 1 receptor, AC – adenylyl cyclase, AKT – serine/threonine kinase, ß1/2 – beta 1/2 receptor, ßy – beta gamma complex, Ca

2+ – calcium, CaMKII – calcium/calmodulin

dependent protein kinase II, cAMP – cyclic adenosine monophosphate, CREB – cAMP response element binding protein, Gi/o/s – G protein coupled receptors, IP3R – inositol trisphosphate, MAPK – mitogen activated protein kinase, NFKPP – nuclear factor kappa-light-chain-enhancer, PI – phosphatidylinositol, PI3K – phosphoinositol-3 kinase, PIP3 – phosphatidylinositol-3 phosphate, PKA – protein kinase A, PLC – phospholipase C.

1.2.3. Catecholamines in Traumatic Brain Injury

1.2.3.1. Effects in the Brain

Severe trauma elicits a complex stress response, characterized by profound

alterations in neuro-endocrine and immune function geared towards re-establishing

9

homeostasis. Activation of the hypothalamic-pituitary-adrenal axis and the sympathetic

nervous system (SNS) via the secretion of glucocorticoids and catecholamines, along with

intricate neuro-immune interactions, are recognized as central pathways in the pathogenesis

of post-traumatic complications [35, 36]. TBI in particular leads to immediate and

profound SNS activation with massive release of both central and peripheral

catecholamines [37]. Patients who have sustained head injury, particularly those with

elevated ICP, often exhibit hypertension, tachycardia and other signs of increased

sympathetic nervous system activity [37, 38].

Levels of E and NE increase several fold in patients with TBI compared with

controls [39-43]. The initial surge is followed by a hyperadrenergic state lasting for a

variable time period after the initial trauma, what is also demonstrated in patients with non-

traumatic SAH [44]. Several studies have noted a correlation between the increase in

catecholamine levels, the severity of TBI, and clinical outcome [37, 39, 42, 43]. In a study

by Woolf [45] patients who achieved normalization of their GCS score after injury also had

concomitant normalization of their NE levels. Furthermore, those that remain comatose

have persistently elevated NE levels, up to seven times normal. Plasma NE levels at 48

hours after TBI may also be predictive of GCS, survival, length of stay, and number of

days on a ventilator [45].

Whether the initial catecholamine surge is detrimental or beneficial to the patient

who has sustained a TBI is currently unknown. The current evidence, however, suggests

that an exaggerated adrenergic response may be harmful to patients with isolated moderate

to severe TBI [46]. Certainly, from an evolutionary medicine point of view, maintenance of

cerebral blood flow and metabolism would seem to afford a survival advantage. Current

evidence shows clinically relevant systemic effects of the catecholamine surge following

systemic trauma, in TBI and in non-traumatic brain injury. Deleterious effects to the

cardiac, pulmonary, endocrine, and immune systems have been described [47-59].

However, the effects of catecholamine surge and hyperadrenergic state on the brain are less

clear. Adrenergic receptors have been identified in the brain [60, 61] and cerebral

vasculature, but there is little clinical evidence of the effects of the catecholamine surge on

the brain itself. Bryan [62], in a review of the effects of stress (but not specifically that of

TBI) on cerebral blood flow and energy metabolism, emphasized the role of beta

10

adrenergic receptors within the brain as a key mediator of the effects of stress on cerebral

blood flow and energy metabolism. The author identified that there are 3 main sources of

catecholamines that may stimulate the cerebral beta adrenergic receptors: systemic, from

the adrenal medulla; central, from the locus coeruleus; and sympathetic, from the superior

cervical ganglia.

In the brain, the direct toxicity of catecholamines intrinsic to the CNS was

investigated by Rosenberg [63] in an animal model. The author found that E, NE and

dopamine were toxic to neurons and glia. Toxicity was evident after exposure to NE, which

was monitored by loss of cells from the cultures. It appeared that toxicity was not mediated

by adrenergic receptors because, although isoproterenol (but not phenylephrine) was

similar in its toxic effect to NE, and atenolol did not block the toxic effect of NE. The

author was able to simulate toxicity by a metabolite of the oxidative degradation of

catecholamines, hydrogen peroxide and catalase blocked the toxicity of NE. The

neurotoxin 6-hydroxydopamine (6-OHDA) was toxic over the same concentration range as

NE. The study suggests that endogenous catecholamines may participate in normal and

abnormal cell death, and suggest that caution should be taken on the specific 6-OHDA

other supposedly selective neurotoxins.

The blood brain barrier (BBB) normally prevents circulating catecholamines from

entering the brain [64, 65]. The BBB is damaged following brain injury as demonstrated by

Schoultz [66] who found that trauma to the spinal cord damages the BBB possibly leading

to the accumulation of catecholamines in the central nervous system (CNS) from the

circulation. Such accumulation could affect the local microcirculation and directly affect

cellular function in the brain [67]. Over time, sustained levels of NE lead to a leaky barrier

and may induce cerebral edema and ischemia [68]. Furthermore, it has been found that

sympathetic activation after experimental TBI may adversely influence cerebral perfusion

[69]. Other animal studies have shown that catecholamines enhance the inflammatory

response in the brain and further increase edema [70-72]. Han [73] and Ueyama [74]

reported that sympathetic stimulation is associated with lower levels of cerebral heat-shock

protein 72, an antiapoptotic protein, and increased expression of the so-called immediate

early genes indicating cellular activation in response to stress [74, 75]. In line with these

findings, neuroprotective effects of ß-blockers have been suggested based on attenuation of

11

cerebral metabolic activity, decreased infarct size, and improved functional outcome in

animals subjected to cerebral ischemia and TBI [67, 72, 73, 75]. Administration of

propranolol to a murine model of blunt head injury led to a 152% improvement in cerebral

perfusion and a 24% reduction in cerebral hypoxia [76]. The authors propose therefore that

adrenergic-mediated cerebral vasoconstriction is a mechanism contributing to the

secondary events after TBI. Liu [72] demonstrated a protective effect of propranolol after

blunt trauma, including better neurologic recovery, better grip test scoring, and reduced

brain edema. It was postulated that the effects were a result of propranolol on the

vasomotor centers in the hypothalamus.

The catecholamine surge is not unique to TBI and has also been observed after

other intracranial processes such as subarachnoid hemorrhage (SAH) [57] and in non-

cerebral insults such as burn injuries [47, 77]. Many other investigators have found a clear

association between intense sympathetic activity in animal and human studies with SAH,

and cerebral arterial vasospasm [78-80]. In experimental studies, both cervical sympathetic

gangliectomy and lesioning the ascending catecholaminergic pathways from the pons and

medulla oblongata prevented vasospasm in animal SAH models [78, 79]. In a human study

[80], it was found that higher levels of catecholamines in cerebrospinal fluid (CSF) were

associated with ischemic deficits.

It appears that some regions of the mid brain are associated importantly with the

hyperadrenergic storm. Hypothalamic dysfunction, for example, is frequently identified in

patients with brain injury. Post-mortem studies have reported that 70% of deaths display

hypothalamic injury [81]. The dysfunction in the hyperadrenergic state occurs within the

autonomic centers in the diencephalon (thalamus or hypothalamus) or their connections to

cortical, subcortical, or brain stem loci that mediate autonomic function. Initially, it was

suggested that a loss of cortical and subcortical control of basic functions occurs, including

blood pressure and temperature regulation [82]. Later, a mechanism involving activation

(or loss of inhibition) of central sympathoexcitatory regions such as the paraventricular

hypothalamic nucleus, lateral periaqueductal gray substance, lateral parabrachial nucleus,

or rostral ventricular medulla was demonstrated [83]. The subsequent release of

adrenomedullary catecholamines during the hyperadrenergic episodes may lead to

hypertension, tachycardia, and tachypnea [84, 85].

12

In summary, the physiopathology of the adrenergic storm in the CNS of patients

with brain injury is not completely understood. The existing evidence, however, suggests

that an exaggerated adrenergic response may be harmful to patients with brain injury, as

some studies have shown an association between catecholamine levels, the severity of

brain damage, and functional neurological outcome. High levels of circulating

catecholamines seem to be associated with more cerebral ischemia, edema and high

intracranial pressures, with consequent worse outcomes.

1.2.3.2. Paroxysmal Sympathetic Storm

The overt early sympathetic response after brain injury is responsible for early local

cerebral effects, systemic effects and a syndrome that is characterized by later clinical

manifestation. One third of all patients with severe TBI die within the first 3 days of injury.

Following this period, the underlying causes of death are mostly the result of sepsis and

non-neurologic organ damage that is primarily represented by respiratory failure and

cardiovascular dysfunction, the late manifestation of the sympathetic surge. Several studies

[59, 86, 87] have demonstrated that non-neurologic multiple organ dysfunction is the result

of the interaction between the brain injury and an overt adrenergic response. Patients may

develop a syndrome of intermittent agitation, diaphoresis, hyperthermia, hypertension,

tachycardia, tachypnea, and extensor posturing. Penfield [88] (1929) first described these

symptoms in a 41-year-old man in whom the ensuing post-mortem examination revealed a

tumor involving the foramen of Monro. Following this, the author collected a series of

patients who had suffered TBI and described the manifestation of symptoms very similar to

this initial individual. Later, Rossitch [88] detailed cases of individuals suspected of

autonomic dysfunction syndrome. The patients presented signs of sympathetic discharge

and extensor posturing after severe closed TBI and acute hydrocephalus. Examining the

responses to medications, the authors proposed that TBI was somehow inducing alterations

in the opiate and dopaminergic pathways. With a better understanding of the

pathophysiology of the sympathetic storm and non-neurologic manifestations of TBI,

investigators have studied more closely the potential for beta-adrenergic blocking

medications. Despite this, adrenergic hyperactivity after TBI, a condition with high

morbidity and mortality, remains poorly elucidated and undertreated.

13

The etiology and pathophysiology of the sympathetic storm is still being defined. It

is believed that TBI may in some patients initiate an overt (exaggerated) activation of the

SNS with central and peripheral release of catecholamines. The exaggerated activation of

the SNS leads to effector organ activation, including the adrenal gland, initiating the

release of catecholamines which causes the manifestation of non- neurologic symptoms.

Previous studies have reported a loss of inhibition of central sympathoexcitatory regions.

As evidence mounts, it is becoming more apparent that there is little evidence to support

the storm being caused by a cerebral disconnection [89]. Disconnection theories state that

dysautonomia occurs due to loss of superior control over one or more excitatory centers.

Conventional disconnection theories suggest that there is a loss of cortical regulation of the

upper brain stem and diencephalic regions (which are the central excitatory foci driving the

paroxysms) when pathways from the cerebral cortex to the midbrain are injured [90, 91,

92]. The excitatory: inhibitory ratio (EIR) model, another disconnection theory, suggests

that damage to the brain stem and diencephalic centers release the excitatory spinal cord

processes from their inhibitory effects [93]. In essence, the spinal cord is responsible for

modulating both the afferent stimuli from the periphery as well as the efferent centrally

originating signals. Sympathetic output activity in the brain is regulated by the spinal cord,

which modulates the EIR, thus protecting the end organ. When the brain stem EIR is

overwhelmed by sympathetic cerebral hyperactivity, as seen in TBI, then the neighboring

spinal EIR is also overwhelmed, losing its protective effect, and is unable to inhibit or

balance large catecholamine surges to the peripheral organs [91, 94]. This is manifested by

end-organ dysautonomia of multiple end organs. Sympathetic overactivity (hyperthermia,

tachycardia, hypertension, tachypnea, and sweating) and motor overactivity (rigidity,

spasticity, and dystonias) may manifest simultaneously [93]. Other potential sources of

catecholamines namely from the adrenal medulla, and from the superior cervical ganglia,

may be activated by injury completely independent of central activity. The catecholamines

released from these areas could circulate centrally back to the cortex resulting in more

hyperadrenergic symptoms and further brain injury.

Kupferman [95] demonstrated that hyperthermia in the hyperadrenergic state is

produced by hypothalamic disturbances. However, it may also be induced by the

hypermetabolic state that is seen in conjunction with sustained muscular contractions.

14

Brain injury increases the local metabolic demands locally in the brain and is superimposed

on the extra metabolic demands caused by the post hyperadrenergic state; events notable

for profound catabolism. This hypermetabolic state is characterized by an increase in

energy expenditure by up to 75% [96, 97], resistance to nutritional support and ensuing

weight loss, which worsens the outcome of patients with TBI [98]. Patients with severe

burns for example, who have marked elevated levels of circulating catecholamines, have

been shown to have an increased metabolic rate, that can be decreased substantially by the

administration of beta adrenergic blocking agents [99].

In summary, the overt hyperadrenergic surge derived from TBI causes cerebral and

systemic damage, represented mostly by cardiorespiratory failure and infection. This

systemic, non-neurologic damage is harmful in patients with brain injury and worsens

outcome. The etiology and pathophysiology of the paroxysmal sympathetic storm is still

being characterized, however, disconnection theories state that there might be a stimulation

or loss of inhibition of the sympathetic output from the CNS.

1.2.3.3. Effects in the Cardiovascular System

As stated before, the hyperadrenergic surge post TBI can cause significant and

harmful cardiovascular dysfunction, leading to hypotension and hypoxia and consequently

having a negative impact on the outcome of TBI patients. In patients with the early

hyperadrenergic storm, the most common ECG changes are sinus tachycardia [100].

Bradycardia, ST segment changes, and fatal ventricular dysrhythmia occur in only 5% of

all patients [101]. The ECG changes due to the sympathetic storm tend to be asymptomatic,

and normalization of repolarization occurs in association with resolution of the neurologic

insult. However, more extensive neurologic injury resulting in a sustained sympathetic

discharge may result in permanent ECG changes, including the development of Q waves

[102].

Circulating markers of myocardial damage are elevated in a variety of acute

neurological diseases, including ischemic and hemorrhagic stroke, SAH, and TBI.

Evidence of myocardial damage demonstrated by increased troponin has been reported in

10–34% of patients with acute stroke [103]. Furthermore, cardiac troponin seems to be

elevated in patients with high levels of catecholamines. Rhind [104] in a study with use of

15

hypertonic saline in TBI patients, demonstrated that cardiac troponin concentrations were

significantly correlated (r=0.455; p=0.0002) with the Injury Severity Score (ISS), and

patients with high cardiac troponin (>0.02 ng/mL) levels also had the greatest

concentrations of E, NE and DA. In the same study, patients with fatal outcome had

significantly higher serum concentrations of all three catecholamines and cardiac troponin

compared to survivors.

It has been hypothesized that myocardial damage in acute neurological events is a

result of “massive” activation of the sympatho-adrenal axis resulting in myocytolysis with

band necrosis instead of acute coronary thrombosis [105, 106]. Furthermore, the

deleterious effects on the myocardium may lead to ventricular hypokinesis [107, 108]. In

studies utilizing transesophageal echocardiography or scintigraphy [109-111], a 50%

reduction in left ventricular function has been demonstrated. Myocardial necrosis is usually

found in patients with premortem ECG disturbances and/or elevated cardiac enzymes.

Indeed, such necrosis is a common autopsy finding in patients with severe TBI [112, 113].

In summary, the early recognition of the cardiovascular dysfunction due to the

hyperadrenergic state post TBI is fundamental to avoid more systemic complications,

especially in patients with extensive neurologic injury which may result in permanent

myocardial damage.

1.2.3.4. Effects in the Lungs

Neurogenic pulmonary edema (NPE) is a condition also caused by massive release

of E/NE following TBI. It is an under-diagnosed complication reported in only 20% of

cases of severe TBI [114], in 32% of those with isolated TBI that die at the scene, and in

50% of TBI victims dying within 96 hours post admission [115].

Regarding its pathophysiology, two different mechanisms seem to coexist, triggered

by a sudden increase in ICP (and global decrease in brain perfusion) or a localized

ischemic insult in suspected trigger zones (vasomotor centers and pulmonary input and

output locations) [116]. The importance of pulmonary dysfunction during elevated ICP has

been particularly well described in brain death cases. In these patients, high ICP appears to

be associated with the initiation and worsening of the massive catecholamine storm. The

16

hemodynamic mechanism involves catecholamine-induced intense pulmonary

vasoconstriction resulting in an increase in pulmonary hydrostatic pressure, followed by an

increase in permeability of pulmonary capillaries compounded by inflammatory

mechanisms (also catecholamine-dependent) that further increases the pulmonary

capillaries permeability [117]. The entire process may be related to the massive and early

release of catecholamines after injury. Several mediators have been implicated in the

genesis of NPE, the ensuing sympathetic activation and the resulting endothelial injury

[118, 119]. The Neuropeptide Y and NE, which are co-located in large dense vesicles in the

sympathetic nerve endings, are secreted in the lungs in large quantities in response to a

sympathetic storm [119, 120]. They play an important role in the development of NPE by

their vasoconstrictive action and by increasing pulmonary vascular permeability [121, 122].

Vascular endothelial pressure-related insults cause the local release of endothelin-1, which

also causes vasoconstriction and are suspected to be involved in experimental TBI models.

Inflammatory mechanisms were also linked to the initialization or perennialization of NPE

[123].

In summary, NPE is a non-neurological manifestation of the sympathetic surge

following TBI, and is under-recognized. There appears to be an association between

increased ICP and consequent global cerebral hypoperfusion and NPE, and as well as an

association with local ischemic insult in possible trigger zones and inflammatory process.

1.2.3.5. Effects in Inflammation

The exacerbated catecholamine release that occurs after brain injury triggers the

inflammatory response, since cellular activation at the molecular level until the

mobilization of the neutrophils in the peripheral circulation [124]. Traumatic brain injury is

followed by a systemic inflammatory response syndrome (SIRS), where inflammation

causes the disruption or dysfunction of one or more organ systems [124]. For example, in

patients with severe TBI, the presence of at least one organ system dysfunction occurred in

89% of subjects [125]. SIRS results from the release of inflammatory mediators that cause

early, delayed, and systemic effects of TBI, including subsequent complement deficit and

coagulopathy. Once SIRS is triggered by acute inflammation, it can detrimentally self-

propagate [124]. Systemic inflammation causes tissue damage leading to further

17

inflammation and damage, leaving the body in a vicious cycle of hyperinflammation.

Therefore, important inflammatory mediators like interleukin (IL)-1 beta, IL-6

and tumour necrosis factor (TNF) alpha, are targeted in compensatory anti-inflammatory

response syndrome (CARS), in an attempt to control the development of SIRS. However,

the activation of CARS often leads to immunosuppression and subsequent MODS [124].

Catecholamines can activate both alpha and beta adrenergic receptors, although the

general preference for E is beta, and for NE is alpha. In general, α-adrenoreceptor

stimulation has immunostimulating effects, while stimulation of the β-adrenoreceptor may

be immunosuppressive [126, 127]. As consequence, there is a great deal of uncertainty in

regards to the pro vs. anti-inflammatory effects of catecholamines on innate immunity in

general, and their specific effects in trauma [128].

After brain injury, particularly, the huge catecholamine surge can render the

immune system anergic, and lead to an inability to fight sepsis, possibly culminating in

organ failure. The exaggerated release of catecholamines can alter the production of

multiple inflammatory mediators (they induce interleukin [IL]-10 release from monocytes,

for example) in peripheral blood immune cells and in various organs (spleen, pancreas,

lungs and the diaphragm). These immunomodulatory effects have increasingly received

attention, especially due to the potential for pharmacological intervention. For example,

patients with sympathetic storm post TBI have higher levels of IL-10 and severely

depressed monocytic HLA-DR expression, 62% of whom develop severe infections [128].

Another example is shown in a study using isolation of splenic macrophages of a

polymicrobial sepsis model, in which further adrenergic stimulation inhibits TNF and IL-6

production by the macrophages [129]. Meisel [130], in a very detailed review article

published in 2005, stated that infections post brain injury impede neurological recovery and

increase morbidity and mortality. The normal balanced relationship between the CNS and

the immune system is deranged leading to the CNS injury-induced immunodepression

(CIDS) and infection, a secondary immunodeficiency. The reason why CNS injury initiates

a reaction with such a maladaptive response is not understood currently. CIDS can be seen

as a consequence of a dysregulation in CARS [130]. Alternatively, CIDS may have

evolved as a protective response helping to prevent postinjury auto-agression to CNS [131-

133]. However, the interpretation of CIDS ‘function’ is complicated by the fact that a

18

certain degree of autoimmunity may be needed for regeneration of CNS post injury. More

specifically, injury of the CNS would evoke a T-cell-mediated autoimmune response that

would reduce the degeneration in the CNS induced by injury [134]. The association

between CIDS and the protection of autoimmunity is not known.

As discussed before, sympathetic hormonal regulation of cytokine production and

release is highly dependent on which type of receptor is being stimulated and its location. It

was recently demonstrated that phagocytic cells (i.e., polymorphonuclear neutrophils and

monocyte-macrophages) are sources of catecholamines themselves and that both E and NE

directly activate macrophages causing enhanced release of pro-inflammatory cytokines

(TNF-α, IL-1β, IL-6) [135-137]. Experimental studies have shown that catecholamines are

not only potent inflammatory activators of macrophages but also that increased levels of

phagocyte-derived catecholamines are associated with intensification of the acute

inflammatory response, including increased plasma leak of albumin, myeloperoxidase

content in lungs, levels of pro-inflammatory mediators in bronchoalveolar lavage fluids,

and expression of pulmonary intercellular and vascular cellular adhesion molecules

(ICAM-1 and VCAM-1, respectively) [138, 139].

Until recently, the brain was considered an immunologically “privileged” site, but

evidence to the contrary exists and is rising, particularly following TBI. Transmigration of

leukocytes after blood brain barrier disruption results in the activation of immuno-

functioning resident cells of the central nervous system, and both infiltrating peripheral

immune cells and activated resident cells subsequently engage in the intrathecal production

of cytokines. Cytokines can either support neurotoxicity by promoting excitotoxicity and

inflammation, or attenuate the damage through neuroprotective and neurotrophic

mechanisms, including the induction of cell growth factors. Interleukin-6 (IL-6) would be a

typical cytokine exerting a ‘dual role’ in neuroinflammation. Its specific anti-inflammatory

properties include the inhibition of TNF, induction of IL-1RA and stimulation of NGF

production, decreasing glutamate-mediated toxicity and oxidative stress, while its

proinflammatory properties include inducing chemotaxis and up regulation of chemokine

production and adhesion molecule expression. This duplicity of function reflects the

contradictory findings in patient outcome studies to date: microdialysate and CSF levels of

IL-6 have been shown to be associated with a favorable outcome measured by the Glasgow

19

outcome scale extended (GOSE) (Table 3), whereas serum measurements have

demonstrated a relationship with unfavorable outcome [105, 106].

Based on the role of catecholamines on inflammatory response and the concept of

TBI being an inflammatory condition of the CNS, growing evidence suggests that the

hyperadrenergic state resulting from severe TBI may cause further impairment of the

already damaged brain [53, 124]. Additionally, experimental and clinical studies on the

neuroprotective effects of β-blockers and alcohol offer indirect evidence to support the

hypothesis that high catecholamine levels are not only predictors of outcome, but in fact,

may contribute to the pathogenesis of TBI.

Some experimental TBI studies have suggested that β-adrenergic receptor

antagonists can improve functional outcome and lessen cerebral edema [140].

Retrospective studies of TBI patients suggest that β-blockers limit mortality [141],

although the exact mechanism(s) of this effect is unknown. In vitro studies demonstrated

that E pretreatment significantly increased TNF-α production with lipopolysaccharide

stimulation and β2-receptor blockade significantly attenuated it. In vivo studies have

demonstrated a significant decrease in TNF-α and IL-6 production in patients treated with

β-blockers. A retrospective study evaluated the effect of β-blockers on survival in 174 TBI

patients compared to 246 TBI patients not using beta-blockers [142]. This study showed

that β-blocker exposure was associated with a significant reduction in mortality in patients

with severe TBI, in spite of being an older group of patients and having a lower predicted

survival.

Experimental studies have also investigated the beneficial effects of alcohol on TBI

and have shown that alcohol can be neuro-protective in low to moderate doses

(<240mg/dl). The proposed neuro-protective mechanisms involve a reduction in immediate

hyperglycolysis, inhibition of the Nmethyl-D-aspartate receptor, which is involved in

excitotoxicity, and decreased pro-inflammatory cytokine production. However, these

beneficial effects seemed to be lost at higher doses. Indeed, a study by Tien [143] suggests

potential neuro protective effects of alcohol (survival benefit) in low to moderate

concentrations (<230mg/dL) compared to an alcohol concentration of zero. However, in

higher concentrations it seemed to be detrimental by affecting the host homeostatic

20

compensatory response to shock. A retrospective study [144] evaluated 14,419 patients

with isolated moderate or severe TBI who were tested positive for blood alcohol. After

logistic regression analysis, ethanol was associated with reduced mortality (adjusted odds

ratio [OR], 0.88; 95% confidence interval [CI], 0.80-0.96; p=.005) but with higher

complications (adjusted OR, 1.24; 95% CI, 1.15-1.33; p<.001). Interestingly, studies

published in 1990 and 1991 [145, 146] evaluated the effects of alcohol on catecholamine

levels in patients with blunt TBI and multisystem injury within 5 hours of injury. They

showed that NE levels had a significant direct correlation with GCS and ISS, and that

alcohol intoxication significantly lowered the NE response in patients with lower GCS and

with a higher ISS. In those studies, the blunting of the catecholamine response was most

marked in those severely injured. Considering the pro-inflammatory effect of sympathetic

activation after TBI, the anti-inflammatory effect of alcohol and its ability to decrease

catecholamine release after TBI, one can speculate that blunting the catecholamine

response would be one of the neuro-protective mechanisms involved in alcohol

intoxication as well as in its detrimental effect on shock response.

In summary, injury to the brain causes not only a local inflammation, but also

SIRS and systemic tissue damage. Subsequently, CARS occurs in attempt to control the

development of SIRS providing negative feedback for the production of inflammatory

mediators. However, the activation of CARS often leads to immunosuppression and

infection which may result in CIDS, MODS and contribute to a high mortality rate. The

various inflammatory mediators play a pivotal role in the activation, development

and prognosis of SIRS following acute TBI. A fuller understanding of the

pathophysiological processes will undoubtedly help in developing strategies for early

diagnosis and therapy, contributing to a decrease in the mortality rate of patients with brain

injury.

1.3. Catecholamines and Current TBI Therapeutic Strategies

Currently, there is growing interest in studying adrenergic agonists and antagonists

for the treatment of brain injury. Several studies in animals and in humans have

investigated the administration of different types of ß-blockers and alpha

agonists/antagonists. Many studies demonstrate that the use of agonist [147-149] and

21

antagonist [70, 71, 72, 150-152] medications have protective effects and many other

studies [153-156] have reported efficacy with both. This apparent paradox may be

explained by the fact that the use of agonist medications also downregulates the receptor

activity through negative feedback mechanisms. Brain injury also causes upregulation of

expression in some receptors, such as ß2 [157]. Current experimental evidence suggests that

the modulation of early adrenergic response to brain injury may improve functional

outcome and cerebral edema after treatment with ß-blockers.

The studies from the Lund group [55, 158-166] have advocated the use of ß-

blockers in brain injury. The group has developed a management protocol based on

volume-targeted therapy principles. The basis of the protocol is the optimization of fluid

flow across the blood brain barrier (BBB) to reduce cerebral edema. The Lund group

proposed the following measures to achieve this goal: 1) stress reduction with adequate

sedation and catecholamine blockade; 2) maintenance of euvolemia through the use of

erythrocyte transfusion and maintenance of a normal albumin level; 3) preservation of

cerebral perfusion pressure (60–70 mm Hg for adults and 40–55 mm Hg for children and

adolescents); 4) avoidance of cerebrospinal drainage; 5) use of early nutrition; and 6) use of

mechanical ventilation to promote normal oxygenation and ventilation. In part the protocol

emphasizes the use of metoprolol, a selective ß1-antagonist, and clonidine, a α2-agonist

used to limit the posttraumatic hyperadrenergic stress response. These investigators

advocate the use of these agents to limit the formation of cerebral edema. Clonidine

mediates systemic vasodilation and inhibits the release of central catecholamine [167] and

metoprolol reduces myocardial contractility, lowers cardiac output, and lowers median

arterial blood pressure. Combined, these drugs can be used to hypothetically reduce

capillary hydrostatic pressure to the point where fluid filtration halts and reabsorption can

occur. Although this induced reduction in blood pressure may lower cerebral perfusion

pressure [168], the Lund group has used hemodynamic [158] and microdialysis [167] data

to suggest that this effect is well tolerated by patients with brain injuries. Clinical studies

indicate that the volume-targeted Lund therapy may reduce the mortality rate following

TBI. To date, several studies have been performed indicating improved survival in adults

[158, 162, 163] and children [166] treated with Lund therapy. Eke [159] reported a

reduction of mortality from 47 to 8% (p<0.001) in patients with severe TBI and high ICP.

22

In another study, Naredi [162] reported 13% mortality rate in the analysis of

a standardized therapy focusing on prevention and treatment of vasogenic edema in

patients suffering severe TBI. Of the 33 surviving patients, 27 (71%) were noted to have

had a good recovery or moderate disability. In another study [163], these same authors

reported that only 1 of 31 patients who underwent treatment with Lund therapy died, and

22 experienced a good recovery or only moderate disability. It should be noted that the

significance of these results is controversial due to the nonrandomized nature of the studies

and the use of historical controls. Despite these criticisms this group appears to have shown

that the adrenergic blocking agent clonidine and metoprolol can be applied to a group of

patients with TBI without significant adverse effects.

In an animal study, Liu [71] used a mouse model to analyze the effects of

propranolol. The author performed a weight drop impact in BALB-C mice, followed by an

intraperitoneal injection of 2.5 mg/kg of propranolol. Mice who received propranolol had a

reduction in brain water content and scored higher on the string test (an ordinal scoring

system for the ability of the mouse to hold on to a string) and grip time test at one hour

after injury. In another study [72] performed in mice injured via a 60 minute middle

cerebral artery occlusion followed by 24 hour reperfusion, Han compared the specific β2

inhibitor ICI 118,551 and β2 genetic knockout. They reported that β2 KO animals had a

22% reduction in infarct volume measured by cresyl violet or TTC (2,3,5-

triphenyltetrazolium chloride) when compared to controls. Furthermore, the lesion size was

reduced 25% in mice treated with ICI 118,551. In a study by Kato [69], the reduction of the

acute phase protein IL-6 was reported in CSF after SAH. The author investigated the role

of adrenergic inhibitors on cytokine levels in CSF after SAH. They found that rats treated

with butoxamine or propranolol, which inhibits β2 receptors, had reduced IL-6

concentrations. In contrast, the β1 inhibitor metoprolol was ineffective. In a rat MCAO

model, IV treatment with propranolol (β1/ β2), carvedilol (β1/ β2/a1), esmolol (β1) or

landilol (β1) resulted in improved neurological deficit scores and smaller infarct volumes

[146]. Different types of adrenergic agonists or antagonists have been investigated in

animal studies. Junker [156] demonstrated that in mixed cultures treated with glutamate,

cell death was blocked by the β2 agonist clenbuterol (1uM) and the effect of clenbuterol

was reversed by the nonspecific β1/ β2 antagonist propranol, β2 antagonist ICI 118,551,

23

but not β1 antagonist metoprolol. In the animals, clenbuterol was again protective and this

could be reversed by propranolol. However, when they combined clenbuterol with

metoprolol, they identified a better neuroprotection than clenbuterol alone.

In humans, several retrospective trauma database analyses demonstrated decreased

mortality in TBI patients treated with β-blockers. One study [141] in severe TBI patients

identified that β-blockers were associated with reduced mortality (adjusted odds ratio: 0.54;

95% CI, 0.33 to 0.91; p<0.01). In the same study [141] β-blocker therapy was associated

with a significant survival advantage in TBI patients with elevated cardiac troponins (OR:

0.38; p=0.03). When the type of ß-blockers was compared, lower mortality was observed in

TBI patients who received propranolol. More recently, systematic review and meta-

analysis performed by Alali [169] included one randomized controlled trial (RCT) and

eight retrospective cohort studies. The critical appraisal of the included studies

demonstrated moderate to severe risk of bias. They concluded that the current body of

evidence is suggestive of a benefit of beta blockers following TBI. However,

methodologically sound RCTs are indicated to confirm the efficacy of ß-blockers in

patients with brain injury.

There are several theoretical pros and cons with regard to the preference for either

α- or ß-adrenoreceptor antagonists, or both, although blockade of both α- and ß-

adrenoreceptors with drugs would seem a logical step to try and prevent the complications

caused by sympathetic overactivation in acute brain injury. For instance, many experts

would agree that blocking peripheral ß-adrenoreceptors, with the risk of inducing

hypotension, may endanger cerebral blood supply, as elevation of blood pressure (which is

preferably left untreated) is generally considered a beneficial compensatory reaction to

preserve cerebral blood flow [129].

In an international multicentre RCT (n=114), Cruickshank [170] investigated the

association between increased sympathetic activity and cardiac morbidity, and the effect of

ß-1 selective adrenoreceptor blockade with atenolol. The study was performed in patients

with TBI, with or without extracranial injury admitted to an ICU. Treatment with atenolol

was administered intravenously, 10 mg every 6h for 3 days, followed by 100 mg orally for

4 days, or a matching placebo. Patients had to be hemodinamically stable, and a strict

24

inclusion and exclusion criteria was adopted. The follow up was possible in 104 patients

and baseline characteristics and concomitant drug use was well matched in both groups.

The authors found that NE levels were higher in patients than in controls, but there was no

treatment effect of atenolol on these levels. They also measured CKMB and CK (with a

known cut off for significant myocardial injury) and concluded that the cardiac enzymes

were elevated in 30% of controls and in 7.4% (p<0.05) in the group treated with atenolol.

Supraventricular tachycardias, ST segment and T wave changes occurred less frequently in

the atenolol group. No focal necrotic lesions were detected in 4/4 hearts that were

examined post mortem in the atenolol group, whereas the post mortem analysis of 2

patients in the placebo group, showed necrotic lesions in both.

Several recent observational studies confirmed a robust association between the use

of ß-blockers and improved outcome, presumably by attenuation of the hyperadrenergic

state post-TBI. Cotton [142] found in a retrospective cohort (n=420), based on a large

trauma registry, that ß-blocker exposure for at least two days after admission in patients

with TBI was associated with an adjusted decreased mortality (5.1% vs. 10.8%) when

compared to patients that did not use ß-blockers during the course of their illness. In

another study by Inaba [171], 1156 patients were included in a retrospective cohort, and

18% received ß-blockers (n=203). Patients with severe extracranial injuries and

nonsurvivable head injury were excluded. Stepwise logistic regression was performed to

identify independent prognostic factors for mortality. The main findings were that ß-

blocker use is inversely associated with mortality (adjusted OR 0.5, 95% CI 0.3-0.9). The

three strongest predictors for death were head abbreviated injury severity score (AIS) ≥4

(OR 5.0, 95% CI 2.9-8.6), GCS ≤8 (OR 4.5, 95% CI 2.9-6.9), and age ≥55 (OR 3.7, 95%

CI 2.4-5.8). The stratification of patients with these predictors of mortality in a subgroup

analysis identified that they benefit the most from ß-blocker exposure. No ß-blocker use

was associated with an OR of 2.32 (95% CI 1.02-10.57) for death in these patients. The

above mentioned observational findings were corroborated in a large retrospective single

center cohort study [172] (N=2601) with blunt TBI patients. There were 506 patients (20%)

using ß-blockers with a mean time to first dose of 5 days (0-132 days). ß-blocker use was

considered to be present when more than one dose had been administered according to the

pharmacists’ registry. Patients using ß-blockers were older, had more serious associated

25

injuries, slightly lower GCS on admission, longer ICU length of stay, longer hospital stays,

and more frequently experienced ventilator associated pneumonia. The unadjusted data

showed equal mortality of 15-16% in both the ß-blocker treated and non- ß-blocker treated

patients. However after adjustment for prognostic variables as selected by a regression

model ß-blockers were significantly associated with survival (OR for death 0.347, 95% CI

0.246-0.490).

Finally, in a 2014 large retrospective cohort [173] (n=1,755), Schroeppel studied

patients with brain injury admitted during a 48-month period, who received ß-blocker,

compared with those who did not. The study excluded patients who received pre-injury ß-

blocker, deaths within 48 hours, and head AIS score <3 or >5. In addition, propranolol was

also compared with all other ß-blockers. They found that patients who received ß-blockers

(n=427) were older (49 years vs. 40 years; p<0.0001), had a higher ISS score (30 vs. 24,

p<0.001), and had a higher head AIS score (4.2 vs. 4.0, p<0.001). By univariate analysis,

ß-blocker patients had a higher mortality (13% vs. 6%, p<0.001); after adjusted analysis,

no difference was identified (adjusted OR 0.850, 95% CI 0.536-1.348). Seventy-eight

patients (18%) received propranolol during the study. Propranolol patients were younger

(30 years vs. 53 years; p<0.001) but more severely injured (ISS, 33 vs. 29; p=0.01; head

AIS, 4.5 vs. 4.2; p<0.001), with longer hospital stays (44 days vs. 26 days, p<0.001).

Mortality was less in the propranolol group (3% vs. 15%, p=0.002). Adjusted analysis

confirmed the protective effect of propranolol (adjusted OR 0.19, 95% CI 0.043-0.920).

The authors concluded that propranolol is the best ß-blocker to limit secondary injury and

decrease mortality in patients with traumatic brain injury.

Relevant pharmacological properties with regard to penetrance of specific ß-

blockers into the brain should be taken into account when studying the effects of these

agents on adverse cerebral effects of sympathetic activation. Caution is advised however, in

extrapolating pharmacokinetic properties in this regard from healthy subjects to patients

with acute brain injury because permeability of the blood-brain barrier is probably much

higher in the latter.

In summary, the evidence reports a potential benefit in reducing mortality with the

use of ß-blocker in patients with brain injury and as consequence it may be justifiable to

26

proceed to phase II studies in humans. However, several important choices have to be made

reflecting the uncertainties that still exist on the clinical significance and pathophysiology

of sympathetic overstimulation. Questions to be answered are, for example: 1) the type of

ß-blocker to be tested (selective versus nonselective, penetration of blood-brain barrier or

not); 2) the precise selection criteria for study participation based on the presence or

absence of risk factors for sympathetically mediated complications; 3) the primary outcome

to be chosen (stress cardiomyopathy incidence, functional outcome, mortality); 4) dosing

issues; 5) initiation and duration of treatment; 6) fixed dose treatment or titration to, for

instance, a physiological variable such as heart rate, or even assessment of individual

sympathetic/parasympathetic tone.

1.4. Prediction of Outcome after TBI

“No head injury is so serious that it should be neither despaired or nor so trivial

that it can be ignored” (Hippocrates). The Hippocratic aphorism expresses the uncertainty

that exists about the prediction of outcome after TBI. It still remains difficult to determine

with certainty what the future course of events will be in an individual TBI patient [9, 174-

176]. Some of the features that have been used to predict outcome after TBI include the

patient age, clinical indices of the severity of injury (GCS, AIS), pupillary diameter and

light reflex, hypotension and the results of investigation and imaging studies, particularly

ICP and computed tomography (CT). The previous established tools and the additional

markers of prediction of outcome in TBI are discussed in sequence.

1.4.1. Age

Age is an important prediction tool while evaluating patients with brain injury. It is

well stablished that in patients older than 60 years prognosis is worse with higher incidence

of death, vegetative status or severe disability [171].

Several studies [177-182] have demonstrated that younger individuals do better

than others. Mortality rate was identified as being remarkably low in children as early as

1973 [180]. Subsequent studies [183-188] showed that more children survived and had

better neurologic outcomes than adults. A prospective study [189] (n=372) in TBI patients

with a GCS less than 13 or ISS greater than 16 and age above 14 years showed no

27

prognostic effect of age up to 50 years. After 50 years, age became an independent

predictor of mortality. Sixty appears to be a critical age. Patients older than 60, had

significant worse outcomes according to the Traumatic Coma Data Bank (TCDB) [190]. In

this study, six months after severe head injury, 92% of those older than 60 were dead, in a

vegetative state, or severely disabled. Other studies demonstrated mortality greater than

75% in severely TBI patients older than 60 [182, 186, 191].

Aging is associated with increased number of injuries caused by falls and pedestrian

accidents [180, 191-193]. In a prospective study of the TCDB, motor-vehicle crashes were

the cause of injury in 55% of patients ages 15–25, whereas only about 5% suffered falls.

However, in the age range above 55, 45% suffered falls and only about 15% were in motor-

vehicle crashes. Interestingly, in this study the mechanism of injury did not appear as an

independent predictor of poor outcome. Older patients had worse outcome compared to

younger ones, regardless of the cause of injury. In the same study a marked increase in pre-

existing co morbidities was found with increasing age, which was associated with poor

outcomes (death and vegetative state) in 86% vs. 50% in younger patients. However, this

correlation was not found in younger age groups. In addition, multiple systemic injuries

were less likely in the older age group thus emphasizing the role of the severity of brain

injury in determining outcome.

In the TCDB study there was an age-related trend towards increasing the size of

intracranial hematomas (ICH) with the largest observed in the oldest group. The chances of

survival in patients with ICH decrease with advancing age [191, 193-199]. A significant

correlation was noted in the TCDB study between a poor outcome and those patients who

had intracerebral hematomas (ICH) or extra cerebral hematomas greater than 15ml, SAH,

midline shift, compressed cisterns, which all increased with age. The TCDB group

conducted a multivariate logistic regression analysis to evaluate the independent effect of

age on outcome from severe TBI. Age was an independent predictor after adjusting to all

other factors. One explanation for this is that the brain has a decreased capacity for repair

as it ages (more vulnerable, fragile, at higher risk). This has some support in that the

proportion of survivors with good neurologic recovery (GOSE scores 3-5) all declined with

age [200].

28

In summary, the current literature demonstrates that age is an important predictor of

outcome in brain injury. Currently, most studies have many limitations, including lack of

analysis of age as a continuous variable, and the analysis of the effect of confounding

variables such as pre-existing medical conditions. Furthermore, the biology of the aging

brain and its vulnerability to injury warrants further detailed investigation.

1.4.2. Pupillary Diameter and Light Reflex

The pupillary diameter and light reflex are important tools for the initial assessment

and during subsequent re-evaluations of patients with TBI. An increased diameter and a

fixed pupil are generally consequences of increased ICP. The identification of increased

ICP is of fundamental importance as it impacts outcome and the early management of

patients with moderate and severe TBI [201].

Increased ICP results in uncal herniation and compresses the third cranial nerve.

This causes reduction in the parasympathetic tone to the pupillary constrictor fibers leading

to a dilated pupil. Similarly, destruction of the third nerve parasympathetic brainstem

pathway also causes a dilated and fixed to light pupil. Therefore, the pupillary light reflex

is an indirect measure of herniation and brainstem injury. Usually, a single dilated and

fixed pupil suggests herniation, whereas bilateral dilated and fixed pupils are associated

with irreversible brainstem injury in a fully resuscitated patient [201]. A dilated and

nonreactive pupil may also be caused by direct orbital trauma without brainstem or

intracranial third nerve compression, which should not be associated with death or

neurologic outcome. The “blown pupil” is important in the context of a decreased level of

consciousness (LOC) and must be assessed for outcome with the LOC and presence of

intracranial pathology. Many clinical studies have investigated the prognostic value of the

pupillary light reflex. Few studies have rigorously measured the size and reaction of the

pupil to light [201] but restricted the analysis to dilated vs. non-dilated pupils, without

measuring their size or describing their response to light even though it is implied.

On average 65% of patients with severe TBI have normal reactive pupils after

resuscitation, 12% have one abnormal pupil, and 28% have bilateral non-reactive pupils.

There is a significant association between pupillary reactivity and other early indicators of

outcome; GCS score [178], hypotension [202-204], and compression of basal cisterns on

29

the CT scan [198]. Several studies [178, 205, 206] demonstrated a strong association

between bilateral nonreactive pupils and poor outcome. In two well-designed studies [178,

201], bilateral nonreactive pupils had a greater than 70% positive predictive value (PPV)

for poor outcome. In a prospective study [177] of 133 patients with severe TBI, bilateral

fixed pupils were found in 35% of the patients and 70% of them had poor outcomes. In

another larger study [178] (N=305) on prognostic tools, bilateral nonreactive pupils were

associated with 90% mortality. In a recent prospective study [207] in South Africa, the

authors developed a simple predictive model for severe TBI using clinical variables that

included pupillary reflex. A binary logistic regression model was used, which included:

oxygen saturation, GCS and pupil reactivity. The model correctly predicted the outcome in

74.4% of the events, with the odds ratio of 4.405 for a good outcome when both pupils

were reactive.

The current literature has many limitations. Future work should consider studying

the association between pupil size and light reactivity (appropriately measured) to outcome,

as well as the duration of pupillary dilation or fixation. A standardized method of

measuring pupil size and reactivity to light would decrease inter-observer variability [201].

Definition of size of dilated pupils is lacking, and some have proposed greater than 4 mm

[208] or no constrictor response to bright light. Right or left distinction should be made

when the pupils are asymmetric.

In summary, lack of pupillary response to light is a good prognostic tool used to

predict outcome. However, direct orbital trauma should be excluded as a causative agent,

hypotension should be reversed prior to assessment of pupils, and repeat examination after

evacuation of intracranial hematomas should be performed. Pupillary size and reactivity

still need to be better defined and properly measured.

1.4.3. Hypotension

Hypotension is an important factor associated with secondary brain injury

influencing outcome post TBI as consequence. Many studies have investigated the effect of

major secondary brain insults such as hypotension, hypoxemia and hypothermia on the

outcome after severe TBI. Furthermore, hypotension seems to be the most robust predicting

factor.

30

Several studies [209-212] found a significant relationship between hypotension,

hypoxemia and hypothermia with poorer outcome, which often occur prior to hospital

admission. Despite being purely observational, these results have resulted in resuscitation

strategies to reduce their occurrence and potential deleterious effects [213]. Miller [214,

215], established the importance of these secondary insults as outcome determinants, but

did not study their independence with respect to other predictive factors. In a study [216]

(n=717) of the influence of secondary brain insults on outcome, hypotension was defined

as a single measurement of a systolic blood pressure less than 90 mmHg. The occurrence of

one or more episodes of hypotension during the period from injury through resuscitation or

during the shorter period of resuscitation only, was associated with a doubling of mortality

and a marked increase in morbidity. Hypotension was an independent and statistically

significant predictor of outcome compared to other major predictors, including age,

hypoxemia, and the other severe non-TBI injuries. When the influence of hypotension on

outcome was analyzed separately, the statistical significance of severe non-TBI trauma as a

predictor of outcome was eliminated, suggesting that their effect on the outcome of patients

with severe TBI is primarily mediated through hypotension [216]. The same TCDB study

[216] revealed that the five most powerful early predictors of outcome are age, positive CT

scan for intracranial injury, pupillary reactivity, post-resuscitation GCS score, and

hypotension. Of all 5 predictors identified, hypotension is the only one amenable to

medical intervention, which was demonstrated by a study from Australia [217]. The study

reported that early (within 6 hours) and late (within 48 hours) episodes of hypotension are

independent predictors of outcome including mortality and neurologic outcome,

dichotomized in good/moderate-to-severe deficits or vegetative/death.

The effects of hypotension on outcome are particularly pronounced in the early time

period following TBI. The International Mission for Prognosis and Analysis of Clinical

trials in TBI (IMPACT) study [213] performed a meta-analysis of 7 RCTs (n=6,629) aimed

at establishing an association between hypoxia-hypotension events before or at hospital

admission, and outcome. The study conducted a proportional odds modelling that showed

worse outcomes (OR=2.7). In another study by Chestnut [218] (n=493), conducted in

patients with severe TBI in whom hypotension was eliminated, demonstrated that for

patients without hypotension, 17% died or remained in a vegetative state. For those patients

31

with early hypotension (at admission), 47% died; for late hypotension (in the ICU), 66%

died and for both insults then 77% of the patients died. Both early and late hypotensive

episodes were significant independent predictors of outcome after controlling for

confounders. Pietropaoli [219] demonstrated that severe TBI patients without previous

hypotensive episodes, after had been subjected to surgical procedures, where iatrogenic

hypotensive episodes occurred, had significantly worse neurologic outcomes than those

without. Additionally, outcome was inversely correlated with duration of intraoperative

hypotension.

Other studies [220, 221] further demonstrated strong associations between early

hypotension and outcome. Vassar [221], in a multicenter RCT examined initial

resuscitation with hypertonic saline versus normal saline in hypotensive multisystem

trauma patients. The hypertonic saline group had higher blood pressure, decreased overall

fluid requirements, and trended towards improvement in survival. A subgroup analysis of

patients with severe TBI revealed that the hypertonic saline group had a significant

improvement in survival at the time of discharge. In this study, hypotension appeared to

eliminate the generally more favorable outcome afforded by younger age. Carrel [222] also

addressed the ability of on-site resuscitation in decreasing secondary injures and improve

outcome. Patients whose secondary brain insults were reversed in the field had a 42%

decrease in poor outcomes at three-month follow-up. However, the study did not control

for confounding factors.

Secondary brain insults are also associated with the appearance of other factors,

which in turn are strongly associated with prognosis. In particular, early hypotension

appears to exacerbate the subsequent development of intracranial hypertension in terms of

frequency and magnitude [223-225], which may impact on outcome. Lobato [223] reported

that the high incidence of hypotension and/or hypoxemia at admission (47% of cases) and

the severity of the clinical presentation (82% of patients scored 5 points or less on the GCS,

74% had unilateral or bilateral mydriasis, and 80% had an initial ICP above normal)

correlated with a very poor final outcome (87% mortality). In this study, elevation of ICP

at any stage was associated with a significantly poorer outcome (77%) as compared to

patients with normal ICP courses (43%) (p<0.0001).

32

In summary, hypotension, occurring at any time from injury through resuscitation

phase and ICU admission, has been repeatedly shown to be a strong predictor of outcome

in TBI. Hypotension is arguably the only prognostic indicator amenable to therapeutic

interventions. The recording of a single hypotensive episode doubles mortality and

increases morbidity. The estimated reduction in unfavorable outcome that would result

from the elimination of hypotensive secondary brain insults is profound.

1.4.4. Glasgow Coma Scale

The GCS was developed by Teasdale and Jennett [226] in 1974 for measuring the

level of consciousness and has become has become the most widely used clinical tool to

measure severity of head injury and, despite its limitations, it is also used to predict

outcome.

The initial GCS score, however, may not be reliable due to sedation and intubation

and may lack precision for predicting good outcome when it is initially low. An European

study [227] showed that the motor score could not be tested in 28% of patients on

admission and the full GCS score was not testable in 44%. Additionally, a survey

conducted in major trauma centers in the United States [7] found a substantial variability of

practice when the initial GCS was assigned for patients who had received prehospital

treatment, including neuromuscular blockers. Gale [8] found that the mortality rate for

those with a true GCS score of 3-5 was 88%, while it was 65% for those with the same

GCS score when a verbal score of 1 was used because of endotracheal intubation. Another

study [9] (n=100) described the accuracy of outcome predictions in severe TBI by an

experienced neurosurgeon. Outcomes were predicted based on the best GCS scores within

24 hours after injury. Correct prognosis was estimated in only 56% of the cases, poor

outcomes were overestimated by 32%-52% and good outcomes underestimate by 35%.

Matis [10] suggested that the use of GCS as a sole predictor has a limited predictive value

in patients with mild to moderate injury. Indeed, the same authors who developed the GCS

found that the predictive accuracy of the initial GCS was poor, in particular when

compared to the Glasgow Outcome Scale (GOS), another widely used score to predict

functional neurological outcome in TBI [11].

Reliability of the initial measurement and its lack of precision for predicting good

33

outcome when the initial score is low, are the two most important limitations to using the

initial GCS for prognostication. Approximately 20% of the patients with the worst initial

GCS score will survive and 8%-10% will have a good neurologic recovery (GOS 4-5), if

the initial GCS score is reliably obtained and not tainted by prehospital medications or

intubation [227]. Despite these concerns, the GCS score has been shown to have a

significant correlation with outcome following severe TBI, both as the sum score or as just

the motor component [228-232]. In a prospective study [177] a PPV of 77% for a poor

outcome (GOS 1-4) was measured for patients with a GCS score of 3-5 and 26% poor

predictive value for a GCS score 6-8.

In summary, when considering the use of the initial GCS score for prognosis, the

two most important problems are the reliability of the initial measurement and its lack of

precision for prediction of a good outcome if the initial GCS score is low. Currently, the

issues that need better investigation are the optimal time after injury for determining the

initial GCS, when to assess the GCS score for those who have received paralytic or

sedative medication and the reliability of the prehospital GCS score acquisition.

1.4.5. Computed Tomography (CT) Findings

The widespread availability and the speed of image processing have established CT

as a cornerstone in the evaluation and outcome prediction of patients with TBI. Several

features readily identified on head CT scan have major prognostic significance, including:

shift of midline structures, encroachment of the basal cisterns, cerebral infarction, SAH,

intraventricular hemorrhage (IVH), diffuse injury, and extra-axial hematomas [233-236].

However, CT scans have many limitations, including the lack of resolution to correctly

identify or characterize small white matter lesions as in the setting of diffuse axonal injury

[237], for example. The CT scan findings and their association with outcome will be

analysed in this section.

1.4.5.1. Abnormal CT

The reported incidence of abnormalities on CT scan in patients with severe TBI

varies between 68%-94%. A study in patients with severe TBI [238] showed that any

abnormality on CT has a PPV of 78% with respect to an unfavorable outcome. However,

34

the patients in the study already had an incidence just over 70% of an unfavorable outcome

which makes the predictive value of initial abnormalities on CT scan limited. The negative

predictive value (NPV), that is, the relation between absence of abnormalities and

favorable outcome, is of greater importance and significance [238]. The outcome of

patients without abnormalities on initial CT examination is better than in the overall

population of patients with severe TBI. Other studies [177, 204, 239, 240] have reported

favorable outcomes in 76-83% of patients with a normal CT scan on ED admission.

When determining prognostic significance of lesions on the CT scan, the time

elapsed between injury and CT examination must be taken into account. Various authors

have addressed the issue of changes on CT appearance over time. In a study [241] with 138

patients, 60 (43.4%) developed a new lesion and only 12 (20%) patients had a favorable

outcome, while a favorable outcome was seen in 60 (76.9%) of the 78 patients not

developing a new lesion. We identified four other studies [242-245] that demonstrated

development of later lesions in patients with an initial CT with isolated ICHs. On average,

patients with new lesions evolved with a worse outcome. Lobato [240] demonstrated that

new lesions may develop on subsequent CT scans on 33% of the patients. More recently, in

the literature, a systematic review and meta-analysis [246] reported that repeated CT scan

after TBI results in a change in management for only a minority of patients. However, the

role of repeating CT scans in head injury is yet not well established.

In summary, the initial CT scan demonstrates, on average, abnormalities in

approximately 90% of patients with severe TBI. Prognosis in patients with severe TBI and

demonstrable pathology on initial CT scan is less favorable than when CT is normal. In

patients with a normal CT on admission, outcome appears to be primarily related to

concomitant extracranial injuries. The absence of abnormalities on CT at admission does

not preclude the occurrence of raised ICP, and significant new lesions on repeated CT

scans may develop in up to 40% of patients.

1.4.5.2. Classification of TBI according to CT findings

Computed tomography plays an important role in the rapid assessment of patients

with TBI in that it detects posttraumatic hemorrhagic lesions and allows selection of

patients who require emergency neurosurgery [247]. Several classifications using head CT

35

scan findings have been proposed in the recent decades. According to Gennarelli [248],

conventional classification of CT findings in severely head-injured patients, differentiates

between focal (extradural hematomas [EDH], subdural hematomas [SDH], ICH and space

occupying contusions) and diffuse head injury. Diffuse injuries are defined by the absence

of mass lesions, although small contusions without mass effect may be present. In terms of

outcome, patients with diffuse injuries were found to have an intermediate prognosis when

compared to patients with EDH or SDH. While acute SDH with low GCS scores had a high

mortality, diffuse injuries with higher GCS scores showed a low mortality and a high

incidence of good recovery. In practice, some confusion exists between this category of

patients with diffuse lesions and the more neuropathologically oriented entity of diffuse

axonal injury (DAI). DAI is characterized by wide-spread tearing of axons and/or small

blood vessels. Radiologic criteria for diagnosis of DAI are small hemorrhagic lesions at the

corticomedullary junction, in the corpus callosum, in the midbrain, and in the brain stem,

sometimes in conjunction with some intraventricular bleeding. As demonstrated by Adams

[249] and Zimmerman [250] DAI can sometimes be superimposed by generalized brain

swelling. Another study [251] has expanded the anatomical patterns of the conventional CT

classification, outlining eight categories of injury, mainly subdividing patients with focal

lesions which permitted a stronger predictive value than the conventional categorization.

Outcome was significantly better in EDH without concomitant brain swelling, simple brain

contusion, generalized swelling, and in the absence of lesions.

In 1991, Marshall (Table 7) proposed a new classification in which the category of

diffuse injury is further expanded, taking into account signs of raised ICP [206]. The

Marshall classification is the most frequently used prognostic method that incorporates the

anatomical nature of the injury in the determination of outcome after acute TBI. It uses the

findings from CT scans on the status of the mesencephalic cisterns, the degree of midline

shift and the presence or absence of local lesions to categorize patients into six different

groups [206]. The score allows identification of patients at risk of deterioration from high

ICP, which offers the possibility of early intervention [206]. Since its introduction in 1991,

this classification has been increasingly used for predicting outcome, including overall

survival, GOS, elevated ICP and neuropsychological consequences [252]. There is a very

strong relationship between the Marshall CT classification, mortality and the frequency of

36

elevated ICP [252]. The presence of a midline shift of > 5 mm on the initial brain CT scan

and a high or mixed density lesion > 25 cm3 in volume have both been correlated with

early death [253]. The relative risk of requiring a delayed operation has been shown to be

related to the Marshall CT classification of initial CT scans (diffuse injury IV, 30.7%;

diffuse injury III, 30.5%; non-evacuated mass, 20.0%; evacuated mass, 20.2%; diffuse

injury II, 12.1%; diffuse injury I, 8.6%) [254]. Ono [255] found that all diffuse brain injury

I patients recovered well six months post injury. In the diffuse brain injury II group, age,

the GCS score and the presence of multiple parenchymal lesions on CT scans were

significantly correlated with outcome. For the diffuse brain injury III and IV groups, the

only significant prognostic factor was the GCS score. In patients with a mass lesion, the

GCS score was also the only significant prognostic factor in the EDH, but the GCS score

and the presence of SAH were predictive factors in the acute SDH group. Outcomes were

unfavourable in the majority of patients with ICH. With regard to the frequency of elevated

ICP, Hiler [256] reported that the Marshall CT classification correlated significantly only

with ICP measured within 24 of admission. In contrast, the 6 month GOS score correlated

with the initial CT scan findings. These results all suggest that the Marshall CT scan

classification provides accurate predictions regarding the likelihood of a fatal or non-fatal

outcome. Mataró [257] reported a relationship between the acute intracranial lesion

diagnosis according to the Marshall CT classification and neuropsychological results and

ventricular dilatation indices at 6 months post-injury. Although the Marshall CT

classification is an adjunct to clinical parameters and is easy to use, it does not take into

account all possible prognostic factors visible on CT and clearly has some limitations. An

important limitation is that the classification is partially based on arbitrary assessments and

is dependent on the accuracy of measured volumes of focal mass lesions. Furthermore,

TCDB categories V (mass lesion surgically evacuated) and VI (mass lesion not operated)

are, in part, retrospective in nature as they depend on the decision to operate or not [258].

In addition, the Marshall CT classification does not take the presence of tSAH into account.

The incidence of CT documented tSAH in patients with severe TBI is 23 – 63% [259]. It is

most common in patients with SDH or haemorrhage contusion and is associated with a

worse prognosis [259-261]. Adding SAH to any CT classification system may enhance its

37

predictive power for outcome and may have consequences for treatment and outcome

issues, and in clinical trials [259, 260].

Another classification widely used is the head Abbreviated Injury Score (AIS)

[262], (Table 6). The Head AIS is used to classify patients with severe head injury. In this

injury scoring system, the severity of injury is rated from minor (AIS=1) to unsalvageable

(AIS=6).

Based on this rating system, severe head injury is considered to be Head AIS>3

[263-266]. The AIS is the most widely used anatomic injury severity rating system in the

world [267]. Walder [268], have compared the predictive value of the Marshall`s

Classification to the worst applicable severity code from the AIS. A high correlation was

found between AIS and outcome at six months, the Marshall’s Classification and outcome

as well as between GCS score and outcome. The PPV for favorable outcome was shown to

be greater for the AIS score than for the Marshall’s classification (95% vs. 71%), when

considering outcome categories dead or vegetative.

In summary, a strong correlation exists between the different types of intracranial

lesions post TBI and outcome. As consequence, the Marshall Classification yields

important prognostic information in TBI. The AIS score shows a strong correlation

between the worst intracranial AIS severity code of the initial CT in severe head injury and

outcome at six months. Future work should address the complicated issue of how optimally

to combine CT characteristics for prognostic purposes and how to improve on currently

used CT classifications to predict outcome more accurately.

1.4.6. Additional Strategies to Determine Outcome

1.4.6.1. Clinical Assessment

Other recently proposed prognostic models have used the motor sub-score of GCS:

the Corticosteroid Randomization after Significant Head Injury trial collaborators

(CRASH) trial [269] and the International Mission on Prognosis and Clinical Trial Design

in TBI (IMPACT) [270]. The CRASH model (Figure 2) is used as an aid to estimate

mortality at 14 days and death/severe disability at 6 months. The predictions are based on

the average outcome of adult patients with GCS of 14 or less, within 8 hours of injury and

38

can only support (not replace) clinical judgment. The estimations are based on alternative

sets that consider low and middle, or high income countries. The CRASH model has been

extensively validated and a calculator is available online at no cost.

Figure 2 – Screenshot of web based calculator.

Available at http://www.crash2.lshtm.ac.uk/

The IMPACT model (Figure 3) predicts 6 month outcome in adult patients with

moderate and severe TBI (GCS ≤12) on admission. By entering the characteristics into the

calculator, which is available online or by an app, the models will provide an estimate of

the expected outcome at 6 months. The model discriminates well, and is particularly suited

for purposes of classification and characterization of large cohort of patients and caution

should be used when applying the estimated prognosis to individual patients.

39

Figure 3 – Screenshot of web based calculator.

Available at http://www.tbi-impact.org/?p=impact/calc

Another score, the Full Outline of UnResponsiveness (FOUR) score [271] (Table 1)

attempts to address some of the limitations of the GCS score by removing any verbal

assessment and integrating brainstem responses and breathing patterns.

40

Table 1 – Full Outline of UnResponsiveness (FOUR).

Score Eye response

4 Eyelids open and tracking, or blinking on command

3 Eyelids open but not tracking

2 Eyelids closed but open to loud voice

1 Eyelids closed but open to pain

0 Eyelids closed with pain

Score Motor response

4 Makes sign (thumbs-up, fist, other)

3 Localizing to pain

2 Flexion response to pain

1 Extension response to pain

0 No response to pain

0 Generalized myoclonus status

Brainstem Score Pupil reflexes Corneal reflexes Cough

4 Present Present Present

3 One pupil wide and fixed Present Present

2 Absent Present NA

2 Present Absent NA

1 Absent Absent Present

0 Absent Absent Absent

Respiratory Score Intubation Breathing

4 Not intubated Regular

3 Not intubated Cheyne-Stockes

2 Not intubated Irregular

0 Not intubated Apnea

1 Intubated Above ventilator rate

0 Intubated Breathes at ventilator rate

0 – 16 Total score

In a recent prospective study (n=51), the AUC of the FOUR score in predicting

poor functional outcome (GOS score 1, 2 and 3) at 6 months was 0.85, equivalent to the

AUC of 0.83 observed with the GCS [272]. The FOUR scale allows testing of eye

41

movements or blinking that facilitates the detection of locked-in state or the transition from

vegetative to minimal conscious state. However, the usefulness of a scale that excludes

verbal assessment could be debated especially in the TBI population, the majority of who

have moderate or mild injury in which a critical distinguishing feature is verbal

performance. Furthermore, respiratory patterns can be difficult to interpret in patients

undergoing mechanical ventilation. These characteristics suggest that the clinical utility of

the FOUR score may be more relevant in the post-acute phase of TBI.

In summary, the three mentioned prediction models are robust in providing an

estimate of the expected outcome at 6 months. They discriminate well and attempt to

address some of the limitations of the GCS score. However, those models have limitations

that still need to be addressed.

1.4.6.2. Neuroimaging

Many different and novel imaging resources have been explored for prognostication

of patients with TBI. As mentioned, the most widely used is the CT scan. Abnormalities

such as midline shift, encroachment of the basal cisterns, cerebral infarction, SAH, IVH,

DAI, and extra-axial hematomas [233-236] are of robust prognostication significance.

Computed tomography has been established as fundamental in the evaluation and outcome

prediction in TBI. However, CT has significant limitations particularly when characterizing

DAI [237]. The use of Xenon CT is a method used to measure quantitatively the cerebral

blood flow (CBF) in 22 cortical mantle regions within 6–12h after severe TBI. The method

has been studied prospectively in 120 patients [273] and the study was able to differentiate

patients with poor outcome (GOS 1–2) from those with good outcome (p<0.001).

Magnetic resonance as a predictor of outcome tool in TBI has been also

investigated [274]. MRI sequences such as diffusion weighted imaging and susceptibility

weighted imaging are potentially more sensitive to DAI and have been shown to increase

the accuracy of outcome prediction [275-277]. Recent studies [278-280] indicate that

diffusion tensor imaging (DTI) in MRI is highly sensitive to traumatic white matter

damage and is predictive of long-term functional outcome. Galanaud [281] evaluated 105

comatose patients (≥7 days post TBI) with MRI scans including DTI and constructed a

composite DTI score. Prediction of unfavorable outcome (GOS 1, 2 and 3 minus) in this

42

study, demonstrated a sensitivity of 64% and a specificity of 95%. This small study found

that the DTI 1-year prediction model (based on white matter tracts) was found to be more

accurate than the IMPACT score. The conventional morphological MRI sequences are not

able to identify axonal loss (reduced N-acetyl aspartate-to-creatine ratio) and increased

myelin turnover (increased choline-to-creatine ratio) in the cerebral tissue, what is

permitted with the early proton magnetic resonance spectroscopy [282]. These changes

have been linked to worse long-term outcome [279, 282, 283].

Hilario [284] demonstrated that bilateral brainstem injuries, detected on MRI in the

first 30 days after severe TBI, were strongly associated with unfavorable outcome (GOSE

1–3; p<0.05) at 6 months, with a sensitivity of 38%, a specificity of 100%, and a PPV of

100%. Posterior brainstem lesions predicted outcome better (OR 6.8, p<0.05) and disability

(OR 4.8, p<0.01), with a sensitivity and specificity of 68 and 76%, respectively. In another

study [285], MRI was performed in 106 patients with severe TBI within 4 weeks post

trauma. The authors looked at the depth of lesions as a potential predictor of outcome at 1

year. Bilateral brain stem injury was strongly associated with poor outcome in severe

compared with moderate TBI (p<0.001) with PPV and NPV of 0.86 and 0.88, respectively.

Betz [286] retrospectively assessed the capability of prediction of outcome using DTI in 59

patients with severe TBI. Unfavorable prognosis (death or severe disability) at hospital

discharge was associated with lower average apparent diffusion coefficient (ADC) values,

axial diffusivity in the genu, and lower fractional anisotropy values in the splenium of the

corpus callosum. The body of corpus callosum also had lower fractional anisotropy, ADC,

and axial diffusivity values in patients with unfavorable outcome.

In summary, there is an ongoing increase of the importance of MRI sequences such

as diffusion weighted imaging and susceptibility weighted imaging which may be more

sensitive to DAI and increase the accuracy of outcome prediction, however, CT scan

remains the most widely used tool.

1.4.6.3. Brain Physiology/Metabolism

A few novel physiologic measurements and neuro metabolites have been identified

and appear to have an effect in outcome after TBI. ICP is commonly monitored in patients

with severe TBI. Studies [236, 287] demonstrate that constant elevations of ICP to greater

43

than 20 mmHg or decreases in cerebral perfusion pressure (CPP) to less than 50–60 mmHg

can cause cerebral infarction, herniation, and death following TBI. Other studies [256, 288-

290] indicate that changes in ICP elevations cannot be predicted in a reliable or timely

manner with either clinical assessment or imaging and the efficacy of treating elevated ICP

has been challenged [291-293]. Direct measurements of the brain tissue oxygenation

indicates that even when ICP and CPP are within normal limits, significant reductions in

brain tissue oxygen pressure may occur, which has been associated with worse outcomes

[294, 295]. Consistent with these observations, a few studies suggest that clinical

algorithms that target normalization of brain tissue oxygen pressure may have a beneficial

effect on outcome [296-298].

The use of cerebral microdialysis probes has identified neurometabolites in the

brain interstitium that are associated with outcome in TBI [299, 300]. Timofeev [301], in a

large cohort of 223 patients with severe TBI, demonstrated low levels of brain extracellular

glucose and elevated levels of lactate to pyruvate ratio (L/P) to be independent predictors

of mortality at 6 months. In another study [302], microdialytic assessment identified

irreversible neuronal loss and subsequent volume loss in the frontal lobes due to elevations

in L/P in the acute setting. Additionally, preliminary microdialysis studies in patients with

severe TBI suggest that brain extracellular concentrations of amyloid fragments, tau

protein, and neurofilament heavy chain protein may also have prognostic significance [303-

305].

In summary, measurement of ICP and brain tissue oxygen pressure may have a

beneficial effect on outcome. Furthermore, some interstitial neurometabolites measured in

the microdialysis fluid of an injured brain, may have an association with outcome. Further

research in this field is still warranted.

1.4.6.4. Electrophysiology

More recently, electroencephalography (EEG) has been used for detection of

seizure activity since seizure has been associated with outcome in brain injury [300, 301].

The use of continuous EEG suggests that seizure activity and status epilepticus, often

clinically undetected, occur in a significant number of patients with severe TBI, and such

perturbations have been linked to outcome [306, 307]. In one prospective, observational,

44

multicenter study, 109 patients who required neurosurgery for TBI (at median of 9.9h after

injury) had cortical spreading depolarization monitoring, which participates in the

extension of secondary insults after brain injury [308]. Presence of spreading

depolarization was associated with an increased risk of unfavorable outcome (GOSE 1–4)

and an OR of 7.58, p=0.0002). In a study [309] of 94 patients with moderate to severe TBI

who underwent continuous EEG monitoring, seizures occurred in 21 patients, and mortality

was 100% in the patients with status epilepticus. Vespa [310, 311] reported that seizures

following TBI are associated with increased cerebral metabolic rate, cerebral blood flow

and volume, and increased ICP in susceptible patients. Interestingly it has been suggested

that seizures cause injury that compounds the primary trauma-induced damage.

Hippocampal atrophy was more pronounced in TBI patients with seizures than in those

without seizures, and atrophy was most prevalent on the hippocampus ipsilateral to the

seizure focus [305]. Currently, the guidelines recommend 7 days of seizure prophylaxis

following moderate to severe TBI [312].

The use of somatosensory evoked potentials (SSEPs) in predicting outcome of

severe TBI was evaluated in a meta-analysis of 44 studies [313]. The bilateral absence of

cortical signals on SSEP had a PPV of 98.7% in predicting adverse outcome 2 months to 3

years after head injury. However, the accuracy of prediction is significantly lower when

patients have focal lesions, SDH, and recent decompressive surgery [313]. Houlden [314],

in a more recent report, demonstrated that bilaterally absent cortical SSEP responses

assessed on the third day after severe TBI were correlated with functional outcomes at 1

year. Furthermore, SSEP helped predict performance on tests of information-processing

speed, working memory, and attention 1 year after injury.

In summary, the current evidence concerning the effects of seizures on outcome in

TBI patients lacks robustness. Seizure activity may increase cerebral blood flow and

consequently ICP. Additional research is needed to determine if early and intensive

suppression of seizure activity or periodic discharges may improve outcome after TBI.

Additionally, SSEPs on the third day post injury may correlate with outcomes at 1 year.

1.4.6.5. Serum Biomarkers

45

The prospect of using peripheral blood-based markers synergistically with current

clinical diagnostic and prognostic assessments of TBI is favorable for a variety of reasons:

(1) it is more clinically accepted compared to other invasive procedures; (2) it is cost

effective; (3) it may quickly and accurately provide specific information about the

underlying pathophysiology of TBI, which clinicians can then use in the diagnosis and

formulation of treatment strategies [315]. Many different biomarkers identified in patients

with brain injury, such as S100 beta (S100ß) protein, neuron-specific enolase (NSE), glial

fibrillary acidic protein (GFAP), pentraxin 3 (PTX3), interleukin-2 (IL-2), interleukin-6

(IL-6), Ubiquitin C-terminal hydrolase (UCH-L1), brain-derived neurotrophic factor

(BDNF), monocyte chemoattractant protein (MCP)-1, intercellular adhesion molecule

(ICAM)-5, and peroxiredoxin (PRDX)-6, have been demonstrated more recently and are

associated with severity of brain injury and neurological outcome [110, 316-328].

Serum levels of S100ß protein and NSE, markers of glial and neuronal damage,

respectively, have been extensively studied in patients with hypoxic-ischemic

encephalopathy. In some studies, these markers correlated with findings on neuroimaging

but were not independently predictive of specific outcomes [316-318]. Other investigations

have indicated that S100ß and NSE have value not only in determining the severity of TBI

but also in classifying their outcomes [319-326, 329]. In a study by Di Battista [329],

where peripheral blood was collected from 85 patients with isolated moderate and severe

TBI, unfavorable neurological outcome was associated with elevations in S100B, GFAP,

and MCP-1. Mortality was related to differences in six of the seven markers analyzed.

Combined admission concentrations of s100B, GFAP, and MCP-1 was able to discriminate

favorable versus unfavorable outcome (AUC=0.83), and survival versus death

(AUC=0.87), although not significantly better than S100B alone (AUC=0.82 and 0.86,

respectively).

In another study, S100ß levels at 24 h were a useful tool for predicting mortality at

1 month after TBI [327]. Best cut-offs for S100ß were 0.461 and 0.025mg/l (serum and

urine, respectively) with a sensitivity of 90%. In one small study [327] (n=28) in patients

with DAI secondary to severe TBI, median levels of S100ßß (monomer of S100ß) at 72 h

(49.3 ng/l) were found to have 88% sensitivity and 100% specificity to predict unfavorable

46

outcome after 3 months (p<0.0001). S100ß is being extensively studied as a prognosticator

in severe TBI, but data in mild and moderate TBI are sparse.

GFAP is specific to glial cells in the CNS, and increased levels are detectable in the

serum of patients with acquired brain injury. Studies suggest that serum GFAP levels

correlate with clinical and neuroradiologic injury severity and are significantly higher in

patients who die or have unfavorable outcome [323, 326, 330, 331]. The predictive value of

other serum biomarkers, in particular tau protein, is still under investigation [332, 333].

Gullo [334], studying patients with severe TBI (n=84), reported that PTX3, a

component of innate immunity) was observed to be predictive of hospital mortality.

Patients who died showed a mean serum PTX3 level (mean of 18 h) of 9.95 mg/ml (±6.42)

in comparison to 5.46 mg/ml (±4.87) in the survivor group (p=0.007). In patients with

isolated TBI, elevated serum PTX3 levels remained significantly associated with mortality

(p=0.04). An association between TBI and inflammatory cytokines has also been

investigated. Elevated IL-2 levels (>90 pg/ml) at 10 hours after severe TBI were found to

be six times more frequently associated with in-hospital mortality compared to levels less

than 50 pg/ml (OR=6.2, 95%, CI 1.2–25.1, p=0.03) in an observational study (n=93) by

Schneider [335]. UCH-L1 is a novel gene product specific to neurons. Papa [336] reported

that CSF UCH-L1 levels were elevated in patients (n=41 and 25 controls) with severe TBI

who had intraventricular pressure monitoring. Mean UCH-L1 levels of 44.2 ng/ml (±7.9) at

6–18h after TBI were higher in patients with 6-week mortality and in those with an

unfavorable 6-month outcome (GOS 1–4) compared with controls (p<0.001).

In summary, new serum biomarkers that represent cerebral tissue damage have been

described. The current evidence demonstrates that there is an association of these

biomarkers with the severity of brain injury and with outcome. Furthermore, these

biomarkers may have the potential to improve prediction, but more research in this field is

warranted.

1.4.6.6. Laboratory Parameters

Several routinely measured laboratory parameters have been linked to severity and

adverse outcomes post brain injury and their association with outcome in TBI have been

47

investigated in several studies [211, 270, 337-341]. Coagulation disturbances, low platelet

counts, anemia, hypoalbuminemia, elevated serum creatinine, and high serum glucose

concentrations are the parameters mostly associated with adverse outcomes in both

univariate and multivariate models. Given the adverse association of high glucose

concentrations with outcome [342-345], recent RCTs have evaluated intensive insulin

therapy to maintain normoglycemia in TBI patients. The question of whether

hyperglycemia is simply a marker of more severe disease or actually causes worse outcome

has not been definitively answered. However, the impact of interventions such as more

aggressive control of blood sugar with intensive insulin therapy is being studied [346]. In

surgical ICU patients, intensive insulin therapy to keep blood glucose between 80 and

110mg/dl compared to a blood glucose level of 180 to 215 mg/dl have shown to reduce

mortality, morbidity, and ICU stay [347]. Overall in-hospital mortality rates were lower in

the intensive insulin therapy group at 7.2% compared with 10.9% (p<0.01). Other studies

using cerebral microdialysis have found that intensive insulin therapy may result in

unfavorable trends in brain extracellular glucose and L/P ratios [348-350]. In a randomized

crossover trial of intensive (80–110 mg/dL) vs. less intensive (120–150 mg/dL) glycemic

control in 13 patients with severe TBI, critical reductions in brain interstitial glucose and

elevations of L/P ratio were more frequent in patients allocated to intensive glycemic

control and were associated with increased [18F]-deoxy-d-glucose uptake on PET [351].

Finally, a study by Green [346] demonstrated no benefit to intensive insulin therapy in

patients with stroke and TBI, regarding their functional neurologic outcome. The authors

concluded that intensive insulin therapy is not advantageous over the conventional control.

Given data linking poor glycemic control and adverse head injury outcome [230, 341],

additional studies are needed to evaluate whether increased brain glucose delivery via

carefully titrated moderate hyperglycemia represents a viable strategy in severe TBI.

In summary, most tests are not specific to TBI, but they offer an overall idea of the

global clinical situation of the patient. Determining blood sugar seems to be more

important, as it seems that glucose level correlates with outcome more importantly.

1.4.6.7. Therapeutic Interventions

48

Evidence and good sense suggests that rigorous supportive management and

enhancements of the process of care favourably influence outcome. Aggressive

normalization of oxygenation, volume status, and blood pressure in the early stages of

injury have been associated with improved outcome [352-354], as used in high-volume

trauma centers with implemented clinical practice guidelines [355, 356]. However, studies

favoring these interventions are associative in nature, and direct evidence of their causal

effect on the biology and natural history of TBI still lacks. Hypothermia may have greater

value in the management of high ICP. In a systematic review of hypothermia trials in TBI,

four of five studies targeting ICP elevation reported a decrease in mortality or in the

percentage of patients having a poor recovery, whereas none of the three studies in which

hypothermia was assessed as a neuroprotectant showed any benefit [357].

In summary, although the evidence is not robust, it is instinctive that the care

offered to the TBI patient, since the initial assessment and management in the trauma room

and subsequently in the ICU, is of fundamental importance in determining outcome.

1.4.7. The Role of Catecholamines as Outcome Predictors after TBI

Many studies performed in animals and in humans have demonstrated an

association between circulating catecholamine levels and severity of injury and with

neurological outcome TBI [358]. The early hyperadrenergic response post TBI causes a

rapid increase in the circulating E and NE levels in the blood and it appears that levels are

directly linked to the severity of TBI [358]. Since catecholamine levels rise exponentially

as a function of injury severity, they have been evaluated as prognostic biomarkers after

TBI. Clinical studies show a significant association between high levels of admission E and

NE in TBI patients and their GCS score, duration of mechanical ventilation, myocardial

damage, endocrine abnormalities, length of hospital stay and neurological outcome [39, 42,

358-360].

Hamill [39] studied plasma catecholamines in 33 patients with TBI. A

catecholamine gradient that reflected the extent of brain injury was demonstrated within 48

hours of the injury. In patients with a GCS of 3 to 4, NE and E levels increased four to

fivefold and the DA level increased threefold above normal (NE, 1686+/-416 pg/mL; E,

430+/-172 pg/mL; DA, 236+/-110 pg/mL), while patients with mild brain injury (GCS

49

>11) had either slightly elevated or normal levels. Patients with marked (GCS 5 to 7) and

moderate (GCS 8 to 10) TBI had intermediate levels. Patients with severe and unchanging

neurological impairment one week after injury had markedly elevated initial NE levels

(2,176+/-531pg/mL), whereas initial NE levels (544+/-89 pg/mL) were only mildly

elevated in patients who improved to a GCS of greater than 11. These authors concluded

that markedly elevated NE levels predict outcome in patients with comparable neurological

deficits.

Woolf [42] studied the catecholamine response in patients with multisystem trauma

with and without TBI (n=124 and 82, respectively) and found that catecholamine

concentrations, particularly NE levels, significantly correlated with severity of injury only

in patients with TBI. The same authors [360] evaluated the catecholamine levels within 48

hours after TBI in 61 patients to determine whether their levels would provide reliable

prognostic markers of outcome assessed by the GCS score. Those patients with NE less

than 900pg/mL improved GCS while those with values greater than 900pg/mL remained

with low GCS scores or died. It was also found that the catecholamine concentration

correlated with the time of mechanical ventilation and length of stay. Woolf [361] also

studied in 66 patients the relationship between changes in thyroid function tests and

catecholamine concentrations measured on admission and after four days of TBI. They

observed that T3 and T4 levels fell significantly within 24 hours of injury. They found

highly significant correlations between day four T3 and T4 levels and admission and day

four NE and E concentrations. The study concludes that patients with TBI exhibit a

gradient of thyroid dysfunction that occurs promptly, is dependent on the degree of

neurologic impairment, and reflects ultimate outcome. The significant association with

catecholamine levels suggests a role for SNS activation in its causation, independent of a

generalized stress response, since there is no correlation of thyroid test abnormality with

the degree of adrenocortical secretion [362].

Rizoli [363] demonstrated that resuscitation with hypertonic saline plus dextran

(HSD) significantly reduces catecholamine secretion in resuscitated hemorrhagic shock

patients. In a prospective randomized controlled trial to evaluate prehospital hypertonic

fluid resuscitation after severe TBI [104] it was demonstrated in a subgroup of 65 patients

that mean admission levels of E (665.3±188.2) and NE (671.6±85.2) were elevated up to

50

18x in all patients compared to healthy volunteers (E 36.8±2.6; NE 311.8±21.0). These

findings confirm the intense sympathetic surge after TBI and substantiate catecholamine

levels as potential biomarkers for severity of TBI and consequently outcome. In this study,

patients resuscitated with normal saline massively released E (1082.7±291.3) and NE

(823.7±124.8) with levels up to 30x that of controls; whereas, HSD-resuscitated patients

exhibited only modestly elevated E (195.8±60.1, 5x) and NE (500.5±85.9, 1.6x) levels,

which normalized by 12h. Moreover, peak levels of E, NE and DA were significantly

higher in patients with poor neurological outcome (GOS score of 1–3).

The catecholamine response in TBI patients seems to present a unique profile,

being more robust and sustained compared to other neurologic insults. Woolf [43]

investigated catecholamine response in four groups of patients: TBI (n=24), vascular brain

injury (n=l0), multi system trauma (n=7) and medical/surgical patients in an intensive care

unit (ICU) (n=29). Despite significant 3 to 7-fold elevations in both free and total NE and

E, the ratio of free to total NE:E remained constant over a very broad range of values. The

proportion of free E was twice normal (30.1-33.5 vs. 16.2%) in all but patients with

polytrauma, whereas the percentage of free NE was unchanged in all patients (43.0%). In

the patients with traumatic or vascular brain injury, significant inverse correlations were

present between free NE, E, and DA and total NE and DA levels and the degree of

neurological dysfunction, as indicated by the concomitant GCS score. Thus, during

conditions of intense and prolonged catecholamine release, the proportion of free

catecholamine remains constant and the total as well as free catecholamine concentration is

proportional to the GCS. The authors concluded that total as well as free NE and E may

correlate only with the severity of brain injury.

In summary, the presented literature has important insights about the potential role

of catecholamines in predicting outcome post brain injury. However, we found many

limitations of the available studies, including small number of patients, lack of power to

evaluate outcome, lack of adjustments for the main confounders, no clear determination of

a cut-off value associated to outcome, variability in the population studied, and variability

in the time that catecholamines were measured post injury.

51

CHAPTER 2 – The COMA-TBI Study

2.1. Rationale

Traumatic brain injury leads to an intense sympathetic nervous system discharge,

where the catecholamine levels rise exponentially as a function of injury severity. Previous

studies demonstrate that levels of catecholamines increase early in TBI, are associated with

poor neurological outcome, and as consequence, could be used as predictors of outcome.

Furthermore, recent evidence demonstrates that the suppression of catecholamine release,

using beta blockers early post TBI may improve outcome, suggesting that high levels of

catecholamines may have deleterious effects to the brain and systemically. However, the

existing evidence is originated in studies with methodological limitations such as: (1) small

sample sizes, (2) lack of adjustment for confounders, (3) delayed time to measure plasma

catecholamine levels post injury, (4) heterogeneous population included in the studies.

2.2. Hypothesis and Aims

2.2.1. Hypothesis

We hypothesize that: Elevated admission catecholamine levels are independently

associated with unfavorable outcome in moderate to severe isolated TBI patients and thus

are useful biomarkers for prediction of outcome. To validate the hypothesis that there is an

independent association between circulating plasma catecholamine levels on admission

with neurological outcome in patients with TBI, we studied a cohort of 181 patients with

isolated moderate to severe TBI in a prospective blinded fashion. We determined the

association between elevated catecholamine levels on admission with the Glasgow

Outcome Scale Extended (GOSE) score at 6 months. All analyses were adjusted for

clinically important factors that can be associated with the outcome such as age, admission

GCS, admission AIS, hypotension on admission, coagulopathy and the use of vasopressors.

2.2.2. Specific Aims

2.2.2.1. Specific Aims for the Initial Analysis (SAIA)

SAIA 1 – To describe patient enrollment flow in the study

52

SAIA 2 – To describe blood samples flow in the study

SAIA 3 – To describe and compare the association between demographic variables

and patients with an unfavorable (GOSE 1-4) outcome

SAIA 4 – To describe and compare the association between the classification of

severity of injury and patients with an unfavorable (GOSE 1-4) outcome

SAIA 5 – To describe and compare the association between clinical variables and

patients with an unfavorable (GOSE 1-4) outcome

SAIA 6 – To describe and compare the association between laboratory variables

and patients with an unfavorable (GOSE 1-4) outcome

SAIA 7 – To describe and compare the association between radiological variables

and patients with an unfavorable (GOSE 1-4) outcome

SAIA 8 – To describe the distribution of patients across categories of moderate

(GCS 9-12) and severe (GCS 3-8) head injury in the Glasgow Coma Scale (GCS)

SAIA 9 – To describe the distribution of patients across categories of 1 to 5 of the

Abbreviated Injury Score (AIS)

SAIA 10 – To describe the distribution of patients across categories of I to VI of the

Marshall Classification

SAIA 11 – To describe the distribution of patients across categories of 1 to 8 of the

Glasgow Outcome Scale Extended (GOSE) at discharge

SAIA 12 – To describe the distribution of patients across categories of 1 to 8 of the

Glasgow Outcome Scale Extended (GOSE) at 6 months

2.2.2.3. Specific Aims for the Primary Outcome Analysis (SAPOA)

SAPOA 1 – To describe the plasma catecholamine levels according to the Glasgow

Outcome Scale Extended (GOSE) at 6 months in patients with favorable (GOSE 5-8) and

unfavorable (GOSE 1-4) outcomes

SAPOA 2 – To estimate the unadjusted odds ratio of an unfavorable outcome at the

6-month follow up (GOSE1-4) for both E and NE

53

SAPOA 3 – To estimate the adjusted odds ratio of an unfavorable outcome at the 6-

month follow up (GOSE 1-4) for both E and NE

SAPOA 4 – To estimate the adjusted odds ratio of an unfavorable outcome at the 6-

month follow up (GOSE 1-4) using the median tertile levels of both E and NE

2.2.2.3. Specific Aims for the Secondary Outcome Analysis (SASOA)

SASOA 1 – To estimate and compare the hospital and ICU length of stay in both

groups of patients with a favorable and an unfavorable outcome

SASOA 2 – To estimate and compare the ventilation days in both groups of patients

with a favorable and an unfavorable outcome

SASOA 3 – To estimate the in-hospital and the 6-month mortality in patients with

an unfavorable outcome

SASOA 4 – To estimate and compare the ventilator free days and ICU free days in

both groups of patients with a favorable and an unfavorable outcome

2.2.2.1. Specific Aims for the Catecholamine Analysis (SACA)

SACA 1 – To describe the plasma catecholamine profile in pooled patients across

all 4 time points and the baseline plasma catecholamine levels in healthy volunteers

SACA 2 – To describe the plasma catecholamine levels according to the Glasgow

Coma Scale (GCS) in moderate (GCS 9-12) and severe (GCS 3-8) TBI patients

SACA 3 – To describe the plasma catecholamine levels according to the

Abbreviated Injury Score (AIS) in patients with severe (AIS 4, 5) and non-severe (AIS 1, 2,

3) TBI

SACA 4 – To describe the plasma catecholamine profile across all 4 time points in

all categories of the Marshall Classification

SACA 5 – To describe the plasma catecholamine profile across categories of 1 to 8

of the Glasgow Outcome Scale Extended (GOSE) at 6 months

SACA 6 – To analyse and compare the plasma catecholamine profile across all 4

time points in patients with favorable outcome (GOSE 1-4)

54

SACA 7 – To analyse and compare the plasma catecholamine profile across all 4

time points in patients with unfavorable outcome (GOSE 5-8)

SACA 8 – To describe the plasma catecholamine levels in patients with and without

high ICP and compare both groups

SACA 9 – To describe the plasma catecholamine levels in patients with and without

sepsis and compare both groups

SACA 10 – To describe the plasma catecholamine levels in patients with and

without MODS and compare both groups

SACA 11 – To describe the plasma catecholamine levels in patients who died or

survived and compare both groups

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CHAPTER 3 – Methods

3.1. Setting

The COMA-TBI study was conducted in 3 Level I Trauma Centers in North

America. Two centers are located in Toronto and affiliated with the University of Toronto

(Sunnybrook Health Sciences Centre – SHSC and Saint Michael`s Hospital – SMH) and

the third center is located in Los Angeles (LA), California (Los Angeles County Medical

Center – LA County) affiliated with the University of South California (USC). The 2

Trauma Centers from Toronto capture all adult trauma cases in the Greater Toronto Area

(over 5 million inhabitants) and surroundings. The LA County Hospital provides healthcare

services for the region's medically underserved areas serving around 4 million inhabitants

and treats over 28 percent of the region`s trauma victims.

SHSC houses the Tory Regional Trauma Centre, which was the first designated

Trauma Centre in Canada and remains the largest one. It receives approximately 1,200

adult severely injured patients annually. Sixty per cent of the patients arrive at Sunnybrook

directly from the scene and most (80%) suffer blunt trauma. Sixty per cent have a head

injury. Half of all trauma patients are admitted to the Intensive Care Unit (ICU) and 25%

undergo surgery in the first 48 hours of admission. St. Michael’s Hospital serves over 800

trauma patients annually, 80% blunt and 20% penetrating. Seventy per cent have a head

injury, 55% are admitted to the ICU and 35% undergo a surgical procedure. It has the Allen

T. Lambert Trauma and Neurosurgery Intensive Care Unit (TNICU) which is one of only

two of its kind in Canada, specializing in TBI, providing a unique environment to study the

acute care of brain injury. Both centers have well stablished Research Institutes that

function to create collaborations beyond divisions and departments reflecting the wide

range of disciplines involved in trauma-related care and research. They support a range of

activities from laboratory, clinical and broader team-based research activity. The LA

County Hospital is a 600-bed public teaching hospital. It is jointly operated by Los Angeles

County Department of Health Services and the USC and treats an average of 7000 trauma

patients per year (86% blunt mechanism). It has a 18-bed Neuroscience ICU which is a

state-of-the art unit allowing for the most advanced monitoring equipment. Trauma ICU

56

admissions reach 77% and 33% go under a surgical procedure.

In the trauma room of the three institutions, patients are assessed and treated by a

trauma team led by a trauma team leader who can be a trauma surgeon, emergency

physician, anesthesiologist or orthopedist. Acutely, care may also be provided by attending

staff from Critical Care Medicine, Anesthesia, Vascular Surgery and Neurosurgery. For

massively bleeding trauma patients, transfusion medicine specialists may also be contacted,

and are available for assistance with transfusion decisions.

3.2. Study design

This is a multi-site prospective blinded cohort study of all consecutive adult trauma

patients with isolated moderate to severe TBI. The core laboratories at each hospital

centrifuged, froze, and stored the samples which were sent in batches every three months to

the laboratory facility at Defense Research and Development Canada (DRDC) for analyses.

The clinical and research teams did not have access to the data until the end of the study,

thereby ensuring that all those involved with the trial remained blinded to the results until

after the 6-month follow-up assessments were completed.

3.3. Study Definitions

The Injury Severity score (ISS) (Table 2). Patients included in the study were

classified according to their severity of injury using the ISS. The score is an anatomic

trauma scoring system which takes into account the squared values of the three mostly

injured body areas based on the AIS and correlates strongly with mortality [364-367]. It

varies from minor traumas with practically no significant injuries (score point = 1) to

unsalvageable injuries (score point = 75). Mortality increases significantly for scores of 15

or higher, which is commonly used to define severe trauma [364-367].

57

Table 2 – The Injury Severity Score.

Regions AIS AIS meaning

Head, neck and C-spine

1

Minor

Face including nose, mouth, eyes, ears 2 Moderate

Thorax, thoracic spine, diaphragm 3 Serious

Abdomen and lumbar spine

4

Severe

Extremities including pelvis

5

Critical

External soft tissue injury

6

Maximal (untreatable)

Calculate AIS for most severely injured body part in each region. ISS is calculated as sum of

square of AIS for the 3 most injured body regions. Maximum score is 75. If any body region

is assigned a 6, the overall ISS is automatically 75.

Legend: AIS – abbreviated injury scale

The Glasgow Coma Scale – GCS (Table 3): mild, moderate and severe head

injury. Since 1974, the Glasgow coma scale has been providing a practical method for

bedside assessment of the level of consciousness, the clinical hallmark of acute brain injury

[220]. The GCS score has been validated in the literature and is widely used for

classification of the severity of the brain injury and the association with outcome [228-

232]. We used the GCS score to classify study patients on admission. Patients are classified

in three different groups, according to the score: severe head injury includes patients with a

score from 3 to 8, moderate head injury includes patients with a score from 9 to 12 and

mild head injury includes patients with a score from 13 to 15. The score is determined by

the trauma team leader during the primary assessment of patients with isolated TBI, and is

subsequently recalculated as needed for continuous follow-up.

58

Table 3 – The Glasgow Coma Scale.

Eye opening

4 Spontaneous 3 To speech 2 To pain 1 None Verbal response

5 Orientated 4 Confused 3 Inappropriate words 2 Incomprehensible sounds 1 None Best motor response

6 Obeys commands 5 Localizes pain 4 Flexion, withdrawals to pain 3 Flexion, abnormal to pain 2 Extension to pain 1 No response

3 – 15 Total score

The Glasgow Outcome Scale Extended – GOSE (Table 4): favorable and

unfavorable neurological outcome. The GOS was created in 1975 by Jennett [368] and

has become the most widely used scale for assessing functional outcome after head injury

and non-traumatic acute brain insults [8, 9]. The initial GOS was increasingly recognized

to have important limitations. Shortcomings of GOS were addressed by adopting a standard

format for the interview used to assign outcome. A structured interview (Table 5) was

created for both the 5-point GOS and an extended eight-point GOS (GOSE), which yielded

a high inter-rater reliability, turning the scale to a more practical and reliable tool [10, 11].

In our study the patients were evaluated at hospital discharge and at 6 months post TBI by

59

an experienced physician unaware of any catecholamine values. At 6 months the patients

were evaluated via a telephone call with the structured interview questionnaire, with the

patients themselves, a family member and/or a caregiver. Patients were classified according

to the GOSE categories to assess primary outcome where 1 = dead and 8 = totally

recovered. We dichotomized the scale to unfavorable outcome (GOSE 1 to 4) and

favorable outcome (GOSE 5 to 8), as this is frequently used in the brain injury [369-371]

literature. Dead patients, patients in vegetative state or with severe disability were

considered as having unfavorable outcome and patients with moderate disability and good

recovery were considered as having favorable outcome.

Table 4 – The Glasgow Outcome Scale Extended (GOSE).

Score Item Description

1 (D) Death

2 (VS)

Persistent vegetative state

Condition of unawareness with only reflex responses

but with periods of spontaneous eye opening

3 (SD-)

4 (SD+)

Lower severe disability

Upper severe disability

Patient who is dependent for daily support for mental or

physical disability, usually a combination of both. If the

patient can be left alone for more than 8 hours at home

it is upper level of SD, if not then it is lower level of SD

5 (MD-)

6 (MD+)

Lower moderate disability

Upper moderate disability

Patients have some disabilities such as aphasia,

hemiparesis or epilepsy and/or deficits of memory or

personality but are able to look after themselves. They

are independent at home but dependent outside. If they

are able to return to work even with special

arrangements it is upper level of MD, if not then it is

lower level of MD

7 (GR-)

8 (GR+)

Lower good recovery

Upper good recovery

Resumption of normal life with the capacity to work

even if pre-injury status has not been achieved. Some

patients have minor neurological or psychological

deficits. If these deficits are not disabling then it is

upper GR, if disabling then it is lower level of GR

Legend: GR- – lower good recovery, GR+ – upper good recovery, MD- – lower moderate

disability, MD+ – upper moderate disability, SD- – lower severe disability, SD+ – upper

severe disability.

60

The structured interview used post discharge for assessment of outcome in the

GOSE scale is represented below in Table 5.

Table 5 – The Post Discharge Structured Interview for GOSE.

POST DISCHARGE STRUCTURED INTERVIEW FOR GOSE

(Glasgow Outcome Scale Extended)

Counsciousness:

1 – Is the head-injured person able to obey simple commands or say any words?

Yes No (VS)

Note: anyone who shows the ability to obey even simple commands or utter any word or communicate

specifically in any other way is no longer considered to be in vegetative state. Eye movements are not

reliable evidence of meaningful responsiveness. Corroborate with nursing staff and/or other

caretakers. Confirmation of VS requires full assessment.

Independence at home:

2a – Is the assistance of another person at home essential every day for some activities of daily living?

Yes No (VS) If no, go to 3

Note: for a NO answer they should be able to look after themselves at home for 24 hours if necessary,

though they need not actually look after themselves. Independence includes the ability to plan for and

carry out the following activities: getting washed, putting on clean clothes without prompting,

preparing food for themselves, dealing with callers and handling minor domestic crises. The person

should be able to carry out activities without needing prompting or reminding and should be capable

of being left alone overnight.

2b – Do they need frequent help of someone to be around at home most of the time?

Yes (lower SD) No (upper SD)

Note: for a NO answer they should be able to look after themselves at home up to eight hours during

the day if necessary, though they need not actually look after themselves.

2c – Was the patient independent at home before the injury?

Yes No

Independence outside home:

3a – Are they able to shop without assistance?

Yes No (upper SD)

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Note: this includes being able to plan what to buy, take care of money themselves and behave

appropriately in public. They need not normally shop, but must be able to do so.

3b – Were they able to shop without assistance before?

Yes No

4a – Are they able to travel locally without assistance?

Yes No (upper SD)

Note: they may drive or use public transport to get around. Ability to use a taxi is sufficient, provided

the person can phone for it themselves and instructs the driver.

4b – Were they able to travel locally without assistance before the injury?

Yes No

Work:

5a – Are they currently able to work (or look after others at home) to their previous capacity?

Yes If yes, go to 6 No

5b – How restricted are they?

a – Reduced work capacity?

b – Able to work only in a sheltered workshop or non-competitive job or currently unable to work?

a. (Upper MD) b. (Lower MD)

5c – Does the level of restriction represent a change in respect to the pre-trauma situation?

Yes No

Social and Leisure activities:

6a – Are they able to resume regular social and leisure activities outside home?

Yes If yes, go to 7 No

Note: they need not have resumed all their previous leisure activities, but should not be prevented by

physical or mental impairment. If they have stopped the majority of activities because of loss of

interest or motivation, then this is also considered a disability.

6b – What is the extent of restriction on their social and leisure activities?

a – Participate a bit less: at least half as often as before

b – Participate much less: less than half as often

c – Unable to participate: rarely, if ever, take part

a. (lower GR) b. (upper MD) c. (lower MD)

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6c – Does the extent of restriction in regular social and leisure activities outside home represent

a change in respect or pre-trauma

Yes No

Family and friendships:

7a – Has there been family or friendship disruption due to psychological problems?

Yes No If no, go to 8

Note: typical post-traumatic personality changes are: quick temper, irritability, anxiety, insensitivity to

others, mood swings, depression and unreasonable or childish behaviour.

7b – What has been the extent of disruption or strain?

a – Occasional - less than weekly

b – Frequent - once a week or more, but not tolerable

c – Constant - daily and intolerable

a. (lower GR) b. (upper MD) c. (lower MD)

7c. Does the level of disruption or strain represent a change in respect to pre-trauma situation?

Yes No

Note: if there were some problems before injury, but these have become markedly worse since the

injury then answer yes to question

Return to normal life:

8a – Are there any other current problems relating to the injury which affect daily life?

Yes (Lower GR) No (Upper GR)

Note: other typical problems reported after head injury: headaches, dizziness, sensitivity to noise or

light, slowness, memory failures and concentration problems.

8b – If similar problems were present before the injury, have these become markedly worse?

Yes No

9 – What is the most important factor in outcome?

a – Effects of head injury

b – Effects of illness or injury to another part of the body

c – A mixture of these

Note: extended GOS grades are shown beside responses on the CRF. The overall rating is based on

the lowest outcome category indicated. Areas in which there has been no change with respect to the

pre-trauma situation are ignored when the overall rating is made

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The Head Abbreviated Injury Scale – AIS (Table 6): severe and non-severe

head injury. The AIS is the most widely used anatomic injury severity rating system in the

world [267]. It was developed in 1971 by the American Medical Association Committee on

Medical Aspects of Automotive Safety to provide researchers with an accurate method for

rating and comparing injuries from automotive crashes, as well as to establish a common

language when describing injuries (Committee on Medical Aspects of Automotive Safety,

1971, 1972) [372, 373]. A subsequent number of revisions followed its original version: (1)

1981, several non-anatomic components were included (Committee on Injury Scaling,

1981) [374]; (2) 1985, the scale body regions were expanded from five to nine and

expanded sections on thoracic, abdominal and pelvic regions were added [375]. New

entries for penetrating, vascular and skin injuries were incorporated (Committee on Injury

Scaling, 1985) [375]; (3) 1990, more descriptors of penetrating injuries, specific codes for

pediatric trauma and a different classification for the body regions were included

(Association for the Advancement of Automotive Medicine, 1990) [376]. The head AIS

was used to classify the severity of the brain injury, which was rated from minor (AIS=1)

to unsalvageable (AIS=6). Severe head injury was considered a Head AIS >3 as previously

defined in the literature [364-367].

Table 6 – The Abbreviated Injury Scale (AIS).

Score Severity of injury

AIS 1

Minor

AIS 2

AIS 3

Moderate

Serious but not life threatening

AIS 4

Severe, life threatening, survival probable

AIS 5

Critical, survival uncertain

AIS 6

Unsurvivable

The Marshall Classification (Table 7): diffuse injury, diffuse injury with

intracranial hypertension, mass lesions. The Marshall classification uses the findings

from CT scans on the status of the mesencephalic cisterns, the degree of midline shift and

the presence or absence of local lesions to categorize patients into six different groups

64

[206]. It was used in our study for the correlation of catecholamine levels with severity of

tomographic injury as demonstrated by the classification. Please refer to the item 1.4.5.2.:

"Classification of TBI According to CT Findings" for detailed information about origin,

validation and utilization of the Marshall Classification. The Classification is summarized

on Table 7.

Table 7 – The Marshall Classification.

Score CT scan

Diffuse injury I (no visible pathology)

No visible intracranial pathology seen on CT scan

Diffuse injury II

Cisterns are present with midline shift of 0-5 mm and/or lesions densities present; no high or mixed density lesion >25cm

3; may

include bone fragments or foreign bodies Diffuse injury III (swelling)

Cisterns compressed or absent with midline shift 0-5 mm; no high or mixed density lesion >25cm

3

Diffuse injury IV (shift)

Midline shift >5mm; no high or mixed density lesion >25cm

3

Evacuated mass lesion

Any lesion surgically evacuated

Non evacuated mass lesion

High or mixed density lesion >25cm

3; not

surgically evacuated

Inclusion Criteria

Patients were included if they had isolated moderate to severe TBI. Isolated TBI was

defined by any head AIS plus a non-head AIS < 2. Moderate and severe TBI were defined by a

GCS 9-12 and GCS 3-8, respectively. To be included in the trial the patient had to meet both

definitions of suffering an isolated TBI that was moderate or severe.

Exclusion Criteria

Patients were excluded if they had any of the following: elapsed time between the

trauma and admission to hospital exceeding 3 hours; age less than 16 years; pregnancy;

65

absence of vital signs on admission or clinical evidence of brain death on hospital admission.

Sample Size Calculation

The sample size was determined based on previous data [1] of moderate/severe TBI

patients showing that 25% had an unfavorable outcome (GOSE=1-4). To detect a

statistically significant difference of 300ng/ml in E between patients with favorable

(GOS=5-8) versus unfavorable outcome (GOSE 1-4), the study required 113 patients with

favorable and 39 patients with unfavorable outcome, for 80% power at 5% significance

level. Assuming losses in follow-up from 20% to 30%, we initially estimated that 200

patients were needed.

Informed Consent

Trauma team was responsible to enroll the patients who meet the criteria above

after obtaining an informed consent from substitute decision makers for participation and

continuation in the study. For patients without a substitute decision maker, the informed

consent was delayed in accordance with the Tri-Council Policy Agreement for Research in

Emergency Health Situations (Article 2.8). A delayed written consent for participation in

the study was subsequently obtained from the next-of-kin. If the patient recovered

sufficiently to provide written informed consent for continuation in the study, then the

patient’s consent was also obtained (Appendix 1).

3.4. Data Acquisition

Each Trauma Center had a dedicated full-time team of research coordinators on-site

during regular working hours Mon-Fri 9am-5pm who were available to respond to trauma

pages and ensure that the blood samples were collected and processed, to obtain informed

consent from the substitution decision makers or patients, fill out the Case Report Forms

(Appendix 2) while the patient was still in-hospital, and complete the hospital discharge

and 6-month follow-up assessments. In addition, given the unpredictable and 24/7 nature of

trauma patient arrival to the trauma centers, the participating sites have implemented on-

call programs for trauma clinical research assistants for off-hours. Once paged, the research

coordinators were directed to the trauma room to confirm eligibility and collect the blood

samples. The coordinators also arranged for the subsequent blood sample collections.

66

Clinical and laboratory data were retrieved from the hospital chart and electronic patient

records.

Clinical Data Collected Upon Hospital Admission (Appendix 2)

Demographics: age and gender.

Trauma: mechanism of injury, elapsed time from the scene to the

Emergency Room, injury.

Injury Severity Scores: ISS, head Abbreviated Injury Score (head AIS).

Neurological status: level of consciousness as categorized by the GCS,

pupil size and reactivity, lateralization signs, seizures, alcohol level.

Clinical status: blood pressure, heart rate, respiratory rate, tracheal

intubation, spontaneous vs. mechanical ventilation, oxygen saturation,

temperature, sedation, paralysis.

Past medical history and present medications: including beta-blockers

and anticoagulants.

Routine Laboratory and Imaging on Admission

Complete blood count, potassium (K), glucose, arterial blood gas analysis,

INR, aPTT, lactate and troponin, sodium (Na), chest radiography,

eletrocardiogram and head CT scan classified as Marshall CT score.

Blood samples for the study of catecholamines, neuro biomarkers and

inflammatory biomarkers were collected on admission and at 6, 12 and 24

hours post trauma. Neuro and inflammatory biomarkers were used for

another arm of the COMA-TBI study that will study the association of these

inflammatory biomarkers with outcome.

Blood samples for routine laboratory exams and imaging studies were

subsequently performed when clinically indicated as per standard of care.

Na, K, pH, BD, glucose, troponin, lactate, platelet count, hemoglobin, aPTT

and INR were measured each time point: admission and 6h, 12h, 24h post

admission (Appendix 2).

67

First 24 Hours Events

All significant clinical/surgical events during the first 24 hours were recorded,

including any treatment with vasoactive drugs, neurosurgical procedures, hypotension

episodes, respiratory failure, high ICP (determined in the ED by the trauma team leader or

neurosurgeon according to clinical signs, head CT scan (Marshall Classification) or in the

intensive care unit/operating room by clinical signs, a subsequent CT scan or ICP

monitoring). In case the patient had an ICP monitor, we considered the measurement to

determine whether there was intracranial hypertension or not, instead of relying on clinical

signs or the Marshall Classification. As per hospital protocol, high ICP was defined as one

episode greater than 25mmHg persisting for at least 5 minutes. We also documented

changes in head CT scan, chest radiography or electrocardiogram. Any treatment with

vasoactive drug, doses and timing were recorded as we anticipate that the use of

vasopressors likely would be given to a number of patients to help optimize cerebral

perfusion pressure and could interfere with the catecholamine levels.

Follow up During Hospitalization

In addition to clinical, laboratory, and image data collected on admission and during

the first 24 hours after admission, patients were followed during the course of their hospital

stay, recording any new surgical procedure, including tracheostomy, duration of

mechanical ventilation, development of infection, sepsis or a new organ failure, length of

ICU and hospital stay. For those who died, the cause of death was recorded and classified

as directly related to the TBI or not. Sepsis was defined following current guidelines from

the Surviving Sepsis Campaign [377]: presence (probable or documented) of infection

together with systemic manifestations of infection. Severe sepsis was defined as sepsis plus

sepsis-induced organ dysfunction or tissue hypoperfusion [377].

Follow up Post Discharge (GOSE at 6 months)

Using previous experience with studies of long-term outcome in patients with acute

lung injury, we took the following steps to ensure high follow-up rates: (a) Prior to hospital

discharge we obtained multiple contact numbers from family members; (b) We sent a study

reminder card at 3 months post-enrollment to maintain contact with the participant; (c) We

68

sent a reminder card in advance of the 6-month follow-up; (d) We checked survival status

of any participants lost to follow up from public provincial registries.

GOSE was recorded at discharge and at 6 months post trauma, by an expert

physician, through a telephone structured interview with the patient and/or with their

caregiver, as defined before (Table 5). The GOSE categories are from 1 = dead to 8 = good

recovery (Table 4). We dichotomized the scale to unfavorable outcome (GOSE 1 to 4) and

favorable outcome (GOSE 5 to 8), as this is being consistently used in the brain injury

literature [369-371]. As for this dichotomization, patients who died, were in vegetative

state or with severe disability were considered to have an unfavorable outcome and patients

with moderate disability and good recovery, a favorable outcome.

The COMA-TBI study flow is highlighted in Figure 4.

69

Legend: CT – computed tomography, CXR – chest x-ray, E – epinephrine, ECG – eletrocardiogram, GOSE – Glasgow outcome scale extended, ICP – intra cranial pressure, ICU – intensive care unit, MODS – multi organ dysfunction syndrome, NE – norepinephrine, TBI – traumatic brain injury.

Blood Sample Collection and Preservation

For the measurement of plasma circulating catecholamines, the blood samples were

drawn into either 10-mL K2EDTA (with 4 mM sodium metabisulfite [Na2S2O5]) or 10mL

sodium heparin vacutainers (Vacutainer, Becton Dickinson, Rutherford, NJ). Specimens

were immediately centrifuged at 1600 x g for 15 minutes the plasma was separated into six

70

(1-2 mL) aliquots and frozen at -70°C until the analyses at DRDC.

Measurement of Circulating Catecholamines

Quantification of plasma catecholamines concentrations (pmol/L) was performed

using commercially available solid-phase competitive enzyme immunoassay (EIA) kits

(Rocky Mountains Diagnostics, Colorado Springs, CO), as per the manufacturer’s protocol.

Briefly, plasma samples were extracted, derivitized and diluted with assay buffer;

standards, samples, controls, and the solid-phase bound analytes compete for a fixed

number of antiserum binding sites, which are incubated in precoated 96well microtiter

plates. Optical density with wavelength correction, were read using an automated Synergy

2 microplate photometer (BioTek, Winooski, VT). The reference values for E were

50pmol/L and for NE were 380pmol/L as per manufacturer information.

3.5. Study Outcomes

3.5.1. Primary Study Outcome

PSO 1 – Neurological function determined by GOSE score at 6 months.

PSO 2 – Independent association between admission catecholamine levels and

unfavorable outcome

PSO 3 – Independent association between the tertiles of levels of both E and NE

and an unfavorable outcome

3.5.2. Secondary Study Outcomes

SSO 1 – Length of ICU and hospital stay in both groups of patients with a favorable

and an unfavorable outcome

SSO 2 – Ventilation days in both groups of patients with a favorable and an

unfavorable outcome

SSO 3 – In-hospital and the 6-month mortality in patients with an unfavorable

outcome

SSO 4 – Ventilator free days and ICU free days in both groups of patients with a

favorable and an unfavorable outcome

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SSO 5 – Plasma catecholamine profile across all 4 time points in pooled patients

SSO 6 – Plasma catecholamine levels in healthy volunteers

SSO 7 – Plasma catecholamine levels according to the Glasgow Coma Scale (GCS)

in moderate (GCS 9-12) and severe (GCS 3-8) TBI patients

SSO 8 – Plasma catecholamine levels according to the Abbreviated Injury Score

(AIS) in patients with severe (AIS 4, 5) and non-severe (AIS 1, 2, 3) TBI

SSO 9 – Plasma catecholamine profile across all 4 time points in all categories of

the Marshall Classification

SSO 10 – Plasma catecholamine profile in pooled patients across categories of 1 to

8 of the Glasgow Outcome Scale Extended (GOSE) at 6 months

SSO 11 – Plasma catecholamine profile across all 4 time points in patients with

favorable outcome (GOSE 1-4)

SSO 12 – Plasma catecholamine profile across all 4 time points in patients with

unfavorable outcome (GOSE 5-8)

SSO 13 – Plasma catecholamine levels in patients with and without high ICP

SSO 14 – Plasma catecholamine levels in patients with and without sepsis

SSO 15 – Plasma catecholamine levels in patients with and without MODS

SSO 16 – Plasma catecholamine levels in patients who died or survived

3.6. Statistical Analysis

Descriptive statistics are presented as proportions, medians and interquartile ranges,

Univariate associations between characteristics at time of hospital admission and

unfavorable outcome were determined using the Wilcoxon two-sample test for continuous

measures, and the chi-square or Fisher’s exact test for categorical variables. To test for the

independent association of catecholamine levels at time of hospital admission and

unfavorable outcome at 6 months (GOSE at 180 days =1 [dead], or 2 [vegetative state] or 3

[low severe disability] or 4 [upper severe disability]), we estimated unadjusted and adjusted

odds ratios and 95% CI from two multivariate logistic regression models: Model 1 included

72

NE in units of 380pmol/L (mean basal levels among healthy individuals) and Model 2

included E in units of 50pmol/L (mean basal levels among healthy individuals). The

clinical prognostic factors on admission used for the adjustment in the 2 models were: age

(in decades), presence of hypotension (SBP<100mmHg), severe TBI (GCS 3-8), severe

head injury (AIS 4-5), INR (<1.2), and the use of vasopressors. To facilitate interpretation

we also reported the final model using admission tertiles of NE (≤6,540.5 [reference],

6,540.5-17,708.7, >17,708.7) and admission tertiles of E (≤1,368.7 [reference], 1,368.7-

4,019.9, >4,019.9).

In addition to the independent association, the C-Statistic was estimated to provide

the descriptive measure of discrimination between unfavourable and favourable outcome

groups, with the estimation of AUC.

The Hosmer-Lemeshow goodness of fit assessed adequacy of the final model.

We estimated the association of both E and NE levels in categories III/IV of the

Marshall Classification (brain edema with intracranial hypertension), with the other

categories in the Classification, across all 4 time points (admission, 6, 12 and 24 hours).

We hypothesized that patients with scores of III or IV have consistently higher levels of

both E and NE over the 24-hour period, what was initially inferred in Figure 15. We

compared categories III/IV with V/VI (edema/high ICP vs. collections), III/IV with II

(edema with high ICP vs. just edema), I with II (normal vs. edema), and I with V/VI

(normal vs. mass lesions). Therefore, we had 4 comparisons by time point resulting in a

total of 16 comparisons, overall. To test the 16 comparisons and because of the

catecholamines are measured at multiple time points, we performed a model that could

accommodate the correlations among the repeated measurements. As we already noted, the

distribution of catecholamines is skewed, although this aspect did not matter for the

univariate analysis (using Wilcoxon or Kruskall-Wallis, non-parametric tests), or the

multivariate analyses (using the logistic regression model). However, to analyze the

longitudinal catecholamine data, we used repeated measures analyses using the mixed

model framework. This technique requires that the model residuals, adjusting for the

Marshall categories, follow a normal distribution, which is not possible if catecholamines

are analyzed on their original scale. Therefore, we applied a log base-10 transformation to

73

E and NE before fitting the model, which included Marshall categories and time as factors,

as well as their interaction. The correlation among repeated measures was assumed to have

a compound symmetry structure. As we were interested in 16 comparisons, we used the

Bonferroni approach to adjust the significance level for multiple comparisons, that is, for

each catecholamine, a comparison was considered statistically significant if p <0.05/16

=0.003125.

74

CHAPTER 4 – Results

4.1. Initial Analysis

4.1.1. Centers and Study Participants Enrollment

Figure 5 illustrates the study enrollment process and follow-up. From September

2011 to June 2013, 3,264 patients were screened in the 2 trauma centers in Toronto (2,216

at SHSC, 1,048 at SMH) and from January 2013 to March 2013, 1750 patients were

screened at the LA County). Two thousands and ninety five patients did not meet the

inclusion criteria at SHSC, 978 at SMH and 1737 at LA County. The final cohort was of

189 patients with isolated moderate to severe TBI enrolled in the study (121 patients from

SHSC, 55 patients from SMH and 13 patients from LA County). One patient was excluded

later after enrollment at SHSC as it was noticed that the age was less than 15 years old.

Three patients at SHSC and four patients at LA County were removed from the cohort due

to withdrawal of consent post enrollment, by the patient`s power of attorney. During the

post hospital follow up period, we lost only 2 patients from SHSC, who unfortunately were

not located using previous contact information and within the provincial registries.

75

Figure 5 – Flow diagram of the screening process.

Legend: LA – Los Angeles, SHSC – Sunnybrook Health Sciences Centre, SMH – Saint

Michael`s Hospital, WC – withdrawal of consent.

4.1.2. Blood Samples Flow in the Study

Figure 6 illustrates the blood samples flow in the study. For each time point

(admission, 6, 12 and 24 hours post injury), 181 blood samples should have been collected,

totalizing 724 samples. Unfortunately, due to technical problems during the specimen

acquisition, laboratory manipulation and preservation, we lost 101 vials (16 at the

admission time point, 8.8% of the total number of admission samples). For the subsequent

time points, samples were not collected or were discarded due to patients being discharged

(n=9), dead (n=11) and the consent being withdrew post inclusion in the study (n=7). We

Patients screened SHSC – 2216 SMH – 1048

LA – 1750

Did not meet criteria/excluded SHSC – 2095

SMH – 993 LA – 1737

Final Enrolled SHSC – 121

SMH – 55 LA – 13

Excluded Post Enrollment < 15yo – 1 patient WC – 3 at SHSC

WC – 4 at LA

Final Included

N=181

76

had a total of 596 samples sent to the laboratory at DRDC for circulating plasma

catecholamine analysis.

Figure 6 – Flow diagram of blood samples collection and manipulation.

Legend: WC – withdrawal of consent.

4.1.3. Association between Demographics, Clinical, Laboratory and

Radiological Characteristics with Unfavorable Outcome

We summarized all demographics, clinical, laboratory, and radiological variables,

and checked whether there was significant difference in both groups of favorable (n=66

patients) and unfavorable outcome (n=113 patients) at 6 months (Table 8), using

appropriate univariate statistical analysis as described previously.

Demographic Variables

724 samples

Samples lost (n=101)

(n=16 at admission)

Subsequent losses Discharged (n=9)

Dead (n=11)

WC (n=7)

Final number of Blood Samples sent to DRDC n=596

77

The median/IQR age across all patients was 47 (29-64) years. Male gender was

predominant (137 patients, 75.6%). Patients with an unfavorable outcome were older (51

[36-72]) years, compared to patients with a favorable outcome (33.5 [21-51]), p<0.0001).

Most patients had a blunt mechanism as the cause of injury (176 patients, 97.2%).

Classification of Injury Severity

The scores of injury severity (GCS, AIS, ISS and Marshall) and the APACHE score

were measured in all patients included in the study. The median/IQR ISS score was 25 (17-

30) and the median/IQR APACHE score was 21 (17-26), across all patients. Patients with

an unfavorable outcome had higher scores compared to patients with a favorable outcome

(p<0.0001 for all scores: GCS, AIS, ISS and APACHE). Patients with an unfavorable

outcome had worse Marshall classification, with 105 patients (92.9%) distributed in

categories II to VI and only 5 patients (4.4%) in category I. Conversely, 55 patients

(83.8%) with a favorable outcome were distributed in categories I and II and only 11

patients (16.6%) in the other categories (p<0.0001).

Clinical Variables

At least one episode of hypotension occurred in 26 patients (14.3%), mostly in

patients with unfavorable outcome (22 patients, 84.6%, p=0.01). At least one episode of

desaturation occurred in 4 patients (2.2%), mostly in patients with an unfavorable outcome

(3 patients, 75%) but with a non-statistically significant difference due to the number of

desaturations (p=1.00). The median temperature/IQR across all patients was 360C (35.1-

370C), and no statistical difference was found between both groups (p=0.35). Vasopressors

were administered to 54 patients (29.8%) and more frequently (48 patients, 88.8%) in

patients with unfavorable outcome (p<0.0001). No patients received a drip of vasopressors

before the admission blood sample was collected. We unfortunately did not collect

information about boluses of vasopressors received before admission to our ED. Most

subjects (135 patients, 74.5%) were intubated on admission. Ninety six patients (84.9%) in

the unfavorable outcome group were intubated on admission, compared to 39 patients

(59.1%) in the favorable outcome group (p<0.0001). Patients with an unfavorable outcome

had more frequently unequal and unreactive pupils (p=0.0005 and p<0.0001, respectively)

78

and underwent more neurosurgical procedures (42 patients, 79.2%, p=0.003). ICP was

measured in 42 patients (23.2%) and of these, 20 patients (47.6%) had a high ICP (at least

one episode of ICP≥25mmHg persistently for 5 minutes or more). Patients with an

unfavorable outcome had measured high ICP more commonly (27 patients, 64.3%,

compared to patients with a favorable outcome [p=0.004]). Patients with high ICP were

mostly from the group with an unfavorable outcome (16 patients, 80%, p=0.02). Signs of

high ICP on CT scan (Marshall Classification) was seen in 46 patients (25.4%), the

majority in the unfavorable outcome group (41 patients, 89.1%, p=0.001). Sepsis occurred

in 48 patients (26.5%), more commonly in the unfavorable outcome group (38 patients,

79.1%, p=0.007). Multi organ dysfunction syndrome was diagnosed in 20 patients (11%),

all from the unfavorable outcome group (p=0.0003). No patients with a favorable outcome

at 6 months had MODS during their hospitalization period. Only 10 patients (5.5%) were

using beta blockers prior to hospital admission, 3 in the favorable and 7 in the unfavorable

outcome groups, respectively, but without statistical significance (p=0.26). Fifty seven

patients (31.5%) had known comorbidities, which were similarly distributed between both

groups (18/66, 27.3% and 39/113, 34.5%) in the favourable and unfavourable outcome

groups, respectively (p=0.44).

Laboratory Variables

Laboratory parameters that reached statistical difference between those patients

with unfavourable and favourable 6-month outcome were INR (p=0.002), platelet counts

(p=0.001), hemoglobin (p=0.0001), glucose (p=0.0008), troponin (p=0.02) and K (p=0.02).

However, a meaningful clinical difference was not observed in none of the parameters, as

their values were mostly within normal ranges or mildly abnormal. The eletrocardiogram

was performed in 116 patients and was abnormal in 69 (59.5%), mostly in patients with an

unfavorable outcome (47 patients, 68.1%, p=0.014).

Radiological Variables

A subsequent head CT scan was performed in 135 patients and was worse

compared to the admission CT in 56 patients (41.5%). Patients with an unfavorable

outcome had a worse subsequent CT scan in 41.6%, while the CT was worse in favorable

79

outcome patients in only 13.6% (p=0.0002). Pulmonary edema was diagnosed in only 7

patients (3.8%), mostly in the unfavorable outcome group (6 patients, 85.7%), which was

not statistically significant (p=0.26). Only 22 patients (16.6%) had evidence of a worse

chest X-ray during hospital admission, and no statistical difference was found between

both groups (p=0.95).

Table 8 – Association between demographics, clinical, laboratory and radiological

characteristics with unfavorable outcome

Variable (median, IQR)

All trauma patients (n=181)

Favourable outcome (n=66)

Unfavourable outcome (n=113)

p

Demographics

Age 47 (29-64) 33.5 (21-51) 51 (36-72) <0.0001

Male gender 137 (75.7%) 54 (81.8%) 81 (71.7%) 0.12

Clinical Variables

Mechanism of injury Blunt Penetrating

176 (97.2%) 5 (2.7%)

65 (98.5%) 1 (1.5%)

109 (96.5%) 4 (3.5%)

0.65

Time to ED 60 (34-105) 60 (34-120) 50 (33-90) 0.13

ISS (1-75) 25 (17-30) 18 (10-25) 26 (25-33) <0.0001

GCS (3-15) 5 (3-8) 7.5 (50-10) 4 (3-7) <0.0001

AIS severe head (>3) 136 (75.1%) 40 (60.6%) 96 (84.9%) <0.0001

APACHE (0-71) 21 (17-26) 18 (12.5-22) 24 (19-29) <0.0001

Marshall Score I II III IV V VI

29 (16.0%) 83 (45.8%) 15 (8.3%) 31 (17.1%) 22 (12.1%) 1 (0.5%)

19 (28.7%) 36 (54.5%) 3 (4.5%) 2 (3.0%) 6 (9.0%) 0

8 (7.1%) 47 (41.6%) 12 (10.6%) 29 (25.6%) 16 (14.1%) 1 (0.9%)

<0.0001

HR (60-80bpm) 88 (72-108) 88 (73-102) 88 (70-110) 0.91

SBP (90-119mmHg) 135 (120-159) 135 (120-156) 136 (120-160) 0.91

RR (12-20breaths/min) 18 (16-20.5) 18 (16-20) 18 (16-22) 0.61

Hypotension (≤100mmHg)

26 (14.4%) 4 (6.1%) 22 (19.5%) 0.01

Desaturation (<90%) 4 (2.2%) 1 (1.5%) 3 (2.6%) 1.00

O2 Sat (90-100%) 99 (97-100) 100 (97-100) 99 (97-100) 0.66

Temperature (36.5-

37.5◦C)

36.0 (35.1-37.0) 36 (35.3-37) 36 (35-36.65) 0.35

80

Variable (median, IQR)

All trauma patients (n=181)

Favourable outcome (n=66)

Unfavourable outcome (n=113)

p

Vasopressors 54 (29.8%) 6 (9.1%) 48 (42.5%) <0.0001

Pulmonary edema 7 (3.9%) 1 (1.5%) 6 (5.3%) 0.26

Intubation 135 (74.6%) 39 (59.1%) 96 (84.9%) <0.0001

Sedation 141 (77.9%) 47 (71.2%) 94 (83.2%) 0.08

Paralysis 86 (47.5%) 28 (42.4%) 58 (51.3%) 0.35

Ventilation 135 (74.6%) 43 (65.1%) 92 (81.4%) 0.0002

ICP Measured High ICP High ICP on CT

42 (23.2%) 20 (47.6%) 46 (25.4%)

15 (35.7%) 4 (20.0%) 5 (10.9%)

27 (64.3%) 16 (80.0%) 41 (89.1%)

0.004 0.02 0.001

Seizures 18 (9.9%) 10 (15.1%) 8 (7.1%) 0.08

Pupils unequal Pupils unreactive

46 (25.4%) 72 (39.8%)

7 (10.6%) 14 (21.2%)

39 (34.5%) 58 (51.3%)

0.0005 0.0001

Sepsis/infection 48 (26.5%) 10 (15.1%) 38 (33.6%) 0.007

MODS 20 (11.0%) 0 20 (17.7%) 0.0003

Neurosurgery 53 (29.3%) 11 (16.7%) 42 (37.2%) 0.003

Beta blockers 10 (5.52%) 3 (4.54%) 7 (6.2%) 0.26

ETOH Yes No

64 (35.3%) 117 (64.6%)

32 (48.5%) 34 (51.5%)

32 (28.3%) 83 (73.4%)

0.004

Comorbidities present 57 (31.5%) 18 (27.3%) 39 (34.5%) 0.44

Laboratory variables

INR (0.90-1.10) 1.05 (0.98-1.1) 1.02 (0.97-1.1) 1.08 (1-1.2) 0.002

aPTT (24-36sec) 27.9 (25.6-30.7) 27.7 (25.2-28.7) 28.2 (25.9-34.5) 0.08

PLT (150-400.000/mm3) 219 (170-269) 240 (191-284) 199 (164-244) 0.001

HGB (130-180g/L) 134.5 (121.5-149) 143 (131-151) 130 (115-142) 0.0001

BD (0-4mmol/L) 4.15 (2-7) 4.2 (2.8-6.4) 4.2 (2-8) 0.79

Lactate (0.5-2.0mmol/L) 2.75 (1.9-4) 2.6 (1.5-3.6) 2.9 (1.9-4.2) 0.35

pH (7.35-7.45) 7.33 (7.28-7.4) 7.31 (7.28-7.4) 7.33 (7.27-7.4) 0.75

Glucose (4.0-8.0mmol/L) 7.8 (6.4-9.8) 7.15 (5.9-8.1) 8.4 (6.8-10.4) 0.0008

Troponin (<15ng/L) 7 (5-16) 5 (5-9) 8 (5-23) 0.02

ETOH level (<2mmol/L) 43 (15.4-59.5) 43.95 (14.5-68) 42 (15.4-57.7) 0.47

K (3.5-5.0mmol/L) 3.7 (3.2-4) 3.8 (3.4-4.2) 3.6 (3.10-3.9) 0.02

Na (135-147mmol/L) 139 (136.5-141.5) 139 (137-141) 139 (136-142) 0.86

ECG abnormal * 69 (59.5%) 22 (33.3%) 47 (41.6%) 0.01

81

Variable (median, IQR)

All trauma patients (n=181)

Favourable outcome (n=66)

Unfavourable outcome (n=113)

p

Worse ECG** 4 (3.4%) 0 4 (3.53%) 0.28

Radiological variables

Worse chest X-ray § 22 (16.7%) 7 (10.6%) 15 (13.3%) 0.95

Worse CT head † 56 (41.5%) 9 (13.6%) 47 (41.6%) 0.0002

Data presented as numbers, percentage and median (interquartile ranges) when appropriate; p values generated by Wilcoxon rank sum or Fisher`s exact/Chi square tests when appropriate. Two-sided test performed and p<0.05 considered significant. Legend: APACHE – acute and physiology and chronic health evaluation, aPTT – activated partial thromboplastin time, BD – base deficit, CT – computerized tomography, ECG – eletrocardiogram, ED – emergency department, ETOH – ethanol, GCS – Glasgow coma scale, GOSE – Glasgow outcome scale extended, HGB – hemoglobin, ICP – intra cerebral pressure, ICU – intensive care unit, ISS – injury severity score, INR – international normalized ratio, MI – myocardial infarction, MODS – multi organ dysfunction syndrome, O2 – oxygen, pH – potential hydrogen, PLT – platelet count, RR respiratory rate, SBP – systolic blood pressure, WLS – withdrawal of life support.. * ECG was performed in 116 patients. ** A subsequent ECG was performed in 116 patients. § A subsequent chest X-ray was performed in 132 patients. † A subsequent head CT scan was performed in 135 patients.

4.1.4. Distribution of Patients According to Injury Severity Scores (GCS, AIS,

Marshall) and GOSE.

Figure 7 illustrates the distribution of patients according to GCS score. Severe head

injury (GCS 3-8) was diagnosed in 143 patients (79%), with 71 (49.6%) having a score of 3

and 72 (50.3%) distributed across scores 4 to 8. Within the severe head injury score range,

91 patients (63.6%) had scores 3 to 5 and 52 (36.4%) had 6 to 8. Only 38 patients (21%)

were diagnosed with moderate TBI using GCS score. The median/IQR GCS across all

patients was 5 (3-8), highlighting that the majority of patients had a very low score.

82

Figure 8 illustrates the distribution of patients according to the AIS score. The

majority of subjects (141 patients, 77.9%) had a severe head injury (AIS 4-5) and only 40

patients (22.1%) had a non-severe injury (AIS 1-3). More than half of the subjects had an

AIS 5 (92 patients, 55.7%). Patients with an AIS 4 were 49 (29.7%) and with an AIS 3

were 24 (14.5%).

83

Figure 9 illustrates the distribution of patients according to the Marshall

classification. Only 29 patients (16%) had a normal initial head CT. Eighty three patients

(45.8%) had an injury class II (brain edema with midline shift less than 5mm). In the more

severe categories, with brain edema and compressed cisterns (class III) and a midline shift

larger than 5mm (class IV), there were 15 (8.3%) and 31 (17.1%), respectively. In

categories V (evacuated mass lesions) and VI (non-evacuated mass lesions), there were 22

patients (12.1%) and 1 patient (0.5%), respectively. Most subjects (129 patients, 71.3%)

were distributed in the category with edema (category II) and in categories with edema and

signs of intracranial hypertension (categories III and IV). Only 23 patients (12.7%) had

mass lesions (categories V and VI).

Figure 10 illustrates the distribution of patients across the GOSE categories. Note

that the in-hospital mortality was 28.7% (52 patients). At 6 months, 2 other patients died,

resulting in 54 patients dead (30.2% mortality). There were no patients in vegetative state

(GOSE 2) at discharge or at the 6-month follow-up. At discharge, patients with an

unfavorable outcome were 145 (80.1%) and at 6 months they were 113 (63.1%). This

reduction is represented by 30 patients (16.6%) from the severe disability category that

84

improved neurologically and moved to the categories of moderate disability and good

recovery. The number of patients with a favorable outcome (moderate disability and good

recovery, GOSE 5-8) at hospital discharge was 36 (19.9%) and increased to 66 (36.9%) at

the 6-month follow up. Patients with a moderate disability at discharge were 14 (7.7%) and

at 6 months they were 25 (14%). Patients with a good recovery at discharge were 22

(12.3%) and at 6 months they were 41 (22.9%).

4.2. Primary Study Outcome

The GOSE was dichotomized into favorable (GOSE 5-8), and unfavorable (GOSE

1-4) outcomes (Figure 11), and both E and NE levels were judged on their ability to

distinguish between these two groups. Sixty-six patients were classified as a having a

“favorable” outcome at 6-month GOSE, and 113 patients were characterized as having an

“unfavorable” outcome. The admission median levels of both E and NE were elevated in

both groups of patients with favorable and unfavorable outcomes, compared to the levels of

healthy volunteers. In patients with an unfavorable outcome, levels were substantially more

elevated when compared to the levels in patients with a favorable outcome. Baseline

85

median levels of E/NE were 3,357.5pmol/L/17,210.7pmol/L in unfavorable outcome and

1,159.4pmol/L/6,276.6pmol/L in favorable outcome patients, respectively (p<0.0001 for

both E and NE). Healthy volunteers had substantially lower median levels for both E and

NE (E = 223.4pmol/L and NE = 2,000.4pmol/L).

After analysing the levels of catecholamines on admission in both groups of

favorable and unfavorable outcomes, we conducted a logistic regression to estimate the

unadjusted OR/CI of an unfavorable outcome at 6-month follow up (GOSE 1-4). In all

models that used E and NE, we used the median admission level among healthy individuals

for E (50pmol/L) and for NE (380pmol/L). The unadjusted OR/CI for E was 1.01 (CI 1.0-

1.02) and a ROC/AUC = 0.73. This means that for every increase in 50 units of E, the odds

of an unfavorable outcome increases by 1.1%. For NE, the unadjusted OR/CI was 1.03

(1.01-1.04) and a ROC/AUC = 0.76, meaning that for every increase in 380 units of NE,

the odds of an unfavorable outcome increases by 3.0%.

Subsequently, to test for the independent association of catecholamine levels on

admission with an unfavorable outcome at 6 months (GOSE 1- 4) we estimated adjusted

odds ratios and 95% CI from five multivariate logistic regression models (Table 9). We

86

included in these 5 models several predictors extracted from the univariate analysis which

were associated with an unfavorable outcome and are known to be clinically relevant. The

variables included were: severe TBI (GCS 3-8), severe head injury (AIS 4-5), age (in

decades), hypotension (SBP<100mmHg), INR (>1.2) and the use of vasopressors. Model 1

included only the described variables without E or NE, and all patients (including patients

who had missing values [n=16)] of admission catecholamines). The discriminatory power

of predicting an unfavorable outcome in model 1 was high (ROC AUC 0.84). In model 2

we performed a sensitivity analysis, excluding the 16 patients without admission values of

E and NE. The model estimated a ROC/AUC = 0.85. Model 3 included the 6 variables and

E, which generated an OR = 1.01 (CI 1.0-1.01) and a ROC/AUC = 0.86. This means that

for every increase in 50 pmol/L of E, the adjusted odds of an unfavorable outcome

increases by 1%. The fourth model, including NE and the 6 variables, estimated an

adjusted OR of 1.02 (CI 1.01-1.04) and an AUC of 0.8. This means that for every increase

in 380 units of NE, the adjusted odds of an unfavorable outcome increases by 2.4%.

Finally, in model 5 we included the 6 variables, E and NE what estimated an OR = 1.01 (CI

1.0-1.01) for E and an OR = 1.02 (CI 1.01-1.04) for NE. The model estimated a ROC/AUC

= 0.87. We tested the calibration of the 5 models with the Hosmer-Lemeshow goodness-of-

fit test, and a very good calibration was found, demonstrating that the models fit well the

data.

87

Table 9 – Multivariate logistic regression models for predicting unfavorable outcome

(GOSE 1-4) at 6 months.

Models Units (pmol/L)

Odds ratio 95% Wald confidence intervals

ROC AUC

Model 1 (variables only)

___

___

___

0.84

Model 2 (- missing values)

___

___

___

0.85

Model 3 (+ Epinephrine)

50

1.01

1.0 – 1.01

0.86

Model 4 (+ Norepinephrine)

380

1.02

1.01 – 1.04

0.88

Model 5 (+ Epinephrine) (+ Norepinephrine)

50 380

1.01 1.02

1.0 – 1.01 1.0 – 1.04

0.87

Model 1 – Included age (in decades), hypotension (<100mmHg), severe TBI (GCS 3-8),

severe head injury (AIS 4-5), coagulopathy (INR >1.2) and use of (*) vasopressors;

model 2 – All 6 variables included in model 1 excluding patients with missing admission

catecholamine levels; model 3 – Model 1 added median E admission level; model 4 –

all 6 variables included in model 1 added to median NE admission level; model 5 – All 6

variables added E and NE.

(*) When a drip of vasopressors were used, they were administered after the determination

of admission catecholamines

Hosmer and Lemeshow goodness-of-fit test demonstrated adequacy of the models

(p=0.84)

Legend: AIS – abbreviated injury scale, AUC – area under the curve, E – epinephrine,

GCS – Glasgow coma scale, GOSE – Glasgow outcome scale extended, INR –

international normalized ratio, NE – norepinephrine, pmol/L – picomoles per liter

ROC – receiving operator curve, TBI – traumatic brain injury.

We conducted another multivariate logistic regression analysis (Table 10) to

facilitate interpretation, where we also reported the adjusted OR/CI in a model using

median tertiles of E on admission (≤1,368.7pmol/L [used as reference], 1,368.7-

4,019.9pmol/L, >4,019.9pmol/L) and NE on admission (≤6,540.5pmol/L [used as

reference], 6,540.5-17,708.8pmol/L, >17,708.8pmol/L). For E, the third tertile

(>4,019.9pmol/L) demonstrated an adjusted OR of 3.5 (CI 1.03-12.2). This means that

88

patients with admission median E level >4,019.9pmol/L have an odds of an unfavorable

outcome of 3.546 times higher compared to level in the first tertile. For NE, the third tertile

(>17,708.8pmol/L) demonstrated an adjusted OR of 4.61 (CI 1.12-18.8), what means that

patients with an admission median NE level >17,708.8pmol/L have an odds of an

unfavorable outcome of 4.6 times higher compared to the level of the first tertile. We also

conducted the Hosmer-Lemeshow goodness-of-fit test which showed a good calibration,

demonstrating that the models fit well the data.

Table 10 – Multivariate logistic regression for tertiles of E and NE admission levels,

including age (in decades), hypotension (<100mmHg), severe TBI (GCS 3-8), severe

head injury (AIS 4-5), coagulopathy (INR >1.2) and vasopressors (*) for predicting

unfavorable outcome (GOSE 1-4) at 6 months.

Tertiles (pmol/L) Odds ratio

95% Wald confidence intervals

ROC AUC

Epinephrine 2nd

T (1,368.7 – 4,019.9)

Epinephrine 3rd

T (>4.019.9)

1.77

3.55

0.6 – 4.9

1.0 – 12.1

0.86

Norepinephrine 2nd

T (6,540.5 – 17,708.8)

Norepinephrine 3rd

T (>17,708.8)

1.43

4.61

0.5 – 3.8

1.1 – 18.8

0.87

(*) When vasopressors were used, they were administered after the determination

of admission catecholamines.

Hosmer and Lemeshow goodness-of-fit test demonstrated adequacy of the model

(p=0.29)

Legend: AIS – abbreviated injury scale, AUC – area under the curve, E – epinephrine,

GCS – Glasgow coma scale, GOSE – Glasgow outcome scale extended, INR –

international normalized ratio, NE – norepinephrine, pmol/L – picomoles per liter, ROC –

receiving operator curve, TBI – traumatic brain injury.

4.3. Secondary Study Outcomes

4.3.1. Hospital/ICU Length of Stay, Ventilation and Mortality

Table 11 illustrates some of the secondary outcomes. Patients with unfavorable

outcome had a median/IQR ICU stay of 7 (3-20) days, which was significantly longer

compared to patients with a favorable outcome, who had a median/IQR of 3.5 (2-10) days,

p=0.001. Length of hospital stay did not reach a statistical significance (p=0.08) between

the two groups of favorable and unfavorable outcomes. Survivors had a longer hospital stay

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(median/IQR 18 [7-37] days) compared to patients who died (median/IQR 3 [1-8.2] days).

As expected, patients with an unfavorable outcome required longer period of mechanical

ventilation, with a median/IQR of 5 (2-16) days, compared to patients with a favorable

outcome with 2 (1-6) days (p<0.0001). The median/IQR ICU free days and ventilator free

days across all patients was 3 (0-14.2) and 1 (0-4), respectively.

Fifty two patients died in hospital (29%). Head injury was the cause of death in 47

patients (90.4%), followed by MODS in 4 patients (7.7%) and myocardial infarction in 1

patient (1.9%). Of the 47 patients who died of TBI, 18 (38.3%) had brain death declared

and 8 (17%) had their life support removed after discussion with family. Post discharge, 2

additional patients died, totalizing 54 patients (30.2%), both due to pneumonia and

respiratory failure.

Table 11 – Association between secondary outcome variables and unfavorable

outcome.

Variable (median, IQR)

All trauma patients (n=181)

Favourable outcome (n=66)

Unfavourable outcome (n=113)

p

Hospital stay

Survivors

Dead

13 (4-30)

18 (7-37)

3 (1-8.25)

10.5 (4-22) 16 (3-37) 0.08

ICU stay 6 (2-17) 3.5 (2-10) 7 (3-20) 0.001

Ventilation days 3 (1-12) 2 (1-6) 5 (2-16) <0.0001

Mortality in-hospital:

Brain injury

Brain death

WLS

MODS

MI

52 (28.7%)

47 (90.4%)

18 (38.3%)

8 (17%)

4 (7.7%)

1 (1.9%)

NA NA NA

Mortality at 6 months

Pneumonia

54 (30.2%)

2 (100%)

NA NA NA

Data presented as numbers, percentage and median (interquartile ranges) when

appropriate; p values generated by Wilcoxon rank sum or Fisher`s exact/Chi square

tests when appropriate. Two-sided test performed and p<0.05 considered significant.

Legend: ICU – intensive care unit, IQR – interquartile range, MI – myocardial infarction,

MODS – multiple organ dysfunction syndrome, WLS – withdrawal of life support.

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4.3.2. Catecholamine Levels in Pooled TBI Patients

Figure 12 illustrates that the hospital admission median levels of catecholamines

were significantly higher in TBI patients compared to healthy controls. Epinephrine levels

were over 11 times higher (median/IQR=2,593.7pmol/L [986.9-5,753.6]) than healthy

individuals (median/IQR=223.4pmol/L [145.2-299.7], p<0.0001), while NE levels were

over 5 times higher (median/IQR=10,274.9pmol/L [5,256.5-28,959.8]) than their healthy

counterparts (median/IQR=2,005.4pmol/L [477.7-2,561.5]), p<0.0001). Although the

circulating catecholamine levels for both E and NE demonstrated a decrescendo across all

4 times points, they remained significantly higher compared to the healthy control levels,

across all-time points. As illustrated in Figure 12, NE median levels are substantially more

elevated and the decrescendo is more pronounced across all 4 time points, differently from

the E, whose initial median levels are smaller tending to a plateau in the last 2 time points

(12 and 24 hours).

4.3.3. Catecholamine Levels According to Severity of Injury (GCS, AIS and

Marshall)

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Another step in the analysis was to study the association between the levels of

catecholamines and the severity of head injury (GCS, AIS and Marshall Classification),

and demonstrate whether there was an association between high levels with a worse injury.

As illustrated in Figure 13, in patients with a severe head injury (GCS3-8) or a

moderate head injury (GCS 8-12), the median levels of both E and NE on hospital

admission were significantly higher in those patients with severe injuries (p<0.0001 for NE

and p=0.001 for E, respectively). Admission median/IQR levels for E were 3 times higher

in severe TBI patients compared to moderate TBI (3,119.5pmol/L vs. 908.6pmol/L,

p=0.001). For NE, the levels were almost 2 times higher (12,559.9pmol/L vs.

6,967.9pmol/L, p<0.0001) for severe and moderate TBI, respectively.

Figure 14 illustrates a similar association of admission median catecholamine levels

when head AIS was used. Patients with a severe head injury (AIS 4-5) had baseline

median/IQR levels for E also 3 times higher (3,141.8pmol/L vs. 988.5pmol/L, p=0.005) for

severe injury compared to patients with non-severe injury (AIS 1-3). For NE, the levels

were almost 2 times higher for severe head injury compared to non-severe head injury

(13,092.4pmol/L vs. 6,850.9pmol/L, p<0.0001).

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Patterns and severity of injury were also assessed according to the Marshall

classification. The only patient in category VI was removed and considered in category V

for analytical reasons. Differently from the previous analysis, we used the median levels of

both E and NE in each time point to study the profile of both E and NE across all

Marshall`s categories in each time point (Figure 15). Both E and NE had median levels

increasing progressively from categories I to V/VI in all 4 time points, but more

pronounced in the first 2 time points (first 6 hours post admission) with a median/IQR E

2,869.2pmol/L (2,063.5-4,084.1) on admission and 1,456.6pmol/L (878.8-3,026.7) at 6

hours, and a median/IQR NE 13,071.6mol/L (9,618.1-19,925.4) on admission and

14,005.9pmol/L (5,041.1-24,350.7) at 6 hours. The median E level was smaller than the

median NE level in each time point, across all categories of the Marshall classification. For

E, the median/IQR was 878.80pmol/L (632.7-2,264.9) and for NE it was 9,976.2pmol.L

(4,939.5-13,394.1), and both median values were statistically different when compared to

the median values of healthy volunteers (p<0.0001).

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As illustrated in Figure 15, median levels of both E and NE seem to be more

elevated across all time points in the categories with tomographic signs of high ICP

(Marshall III and IV). However, the levels are even more elevated in the first 2 time points

(admission and 6 hours) when compared to the subsequent time points. Interestingly, the

median NE level at the first time point (hospital admission) has a noticeable high peak

associated with the category III. Smaller median peaks of NE at the 6-hour time point are

also noticed in categories III and IV generating a small plateau. This denotes a visible

association between high catecholamine levels and brain edema, especially when there are

signs of high ICP (categories III and IV), compared to categories without high ICP

(category II) or focal mass lesions (categories V and VI).

We conducted a subsequent step in the analysis of the profiles of both E and NE

across all 4 time points in association with the Marshall Classification. Our hypothesis was

that patients with scores III and IV had consistently higher levels of both E and NE vs.

others over the 24-hour period (across all 4 time points). Categories III & IV (cerebral

edema with signs of high ICP) and V & VI (focal mass lesions) were paired together for

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the analyses. We compared categories III/IV with V/VI (cerebral edema and high ICP with

focal mass lesions), III/IV with II (cerebral edema and high ICP with just cerebral edema),

I with II (normal CT with just cerebral edema), and I with V/VI (normal CT with focal

mass lesions). We conducted repeated measures with a mixed model framework using a log

base-10 transformation to E and NE before fitting the model.

For E (Table 12), the comparisons between categories III/IV vs. V/VI did not show

a statistical significance over the 4 time points, highlighting that the median E levels were

not significantly different between those 2 categories. On admission, the comparisons of

the median levels in categories II vs. I, V/VI vs. I and III/IV vs. II were all statistically

significant (p=0.0009, p<0.0001, p<0.0001, respectively) (Table 12). At 6 hours, the

comparisons between the median levels in categories V/VI vs. I and III/IV vs. II were also

statistically significant (p<0.0001 for both comparisons). Finally, at 12 hours the

statistically significant comparisons were in categories V/VI vs. I (p<0.0001) and in III/IV

vs. II (p=0.0009). In conclusion, we found that patients with edema and signs of high ICP

have higher levels of E consistently over the 4 time points.

Table 12 – Statistically significant comparisons of the log base-10 scale of median E levels

according with each time point in the Marshall Classification.

Time point Result p

Admission I < II

I < V/VI

II < III/IV

0.0009

<0.0001

<0.0001

6 hours I < V/VI

II < III/IV

<0.0001

<0.0001

12 hours I < V/VI

II < III/IV

<0.0001

0.0009

24 hours (*) ___ ___

Mixed model framework with application of a log base-10 transformation to E and NE,

including Marshall categories and time as factors, as well as their interaction. Bonferroni

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approach was used to adjust the significance level for multiple comparisons (for each

catecholamine, a comparison was considered statistically significant if p <0.05/16

=0.003125).

(*) – At the 24-hour time point no comparison was statistically significant.

Legend: I – diffuse injury (no visible pathology), II – diffuse injury (midline shift 0-5mm), III –

diffuse injury (swelling), IV – diffuse injury (midline shift), V – evacuated mass lesion, VI –

non evacuated mass lesion.

For NE (Table 13), the comparisons between categories III/IV vs. V/VI did not

show a statistical significance in time points 6, 12, 24 hours. However, on admission there

was a marginal significance (p=0.03). In all 4 time points, the comparisons between

categories III/IV vs. II were statistically significant (p<0.0001 for all comparisons). The

comparisons between categories V/VI vs. I were statistically significant in the 6, 12 and 24-

hour time points (p<0.0001, p=0.0002 and p=0.0006, respectively), but not significant on

admission. Corroborating with the findings for E, the levels of NE in patients with signs of

edema and high ICP were consistently more elevated compared to the levels in patients

without signs of high ICP.

Table 13 – Statistically significant comparisons of the log base-10 scale of median NE levels

according with each time point in the Marshall Classification.

Time point Result p

Admission II < III/IV <0.0001

6 hours I < V/VI

II < III/IV

<0.0001

<0.0001

12 hours I < V/VI

II < III/IV

0.0002

0.0010

24 hours I < V/VI

II < III/IV

0.0006

<0.0001

Mixed model framework with application of a log base-10 transformation to E and NE,

including Marshall categories and time as factors, as well as their interaction. Bonferroni

approach was used to adjust the significance level for multiple comparisons (for each

catecholamine, a comparison was considered statistically significant if p <0.05/16

=0.003125).

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Legend: I – diffuse injury (no visible pathology), II – diffuse injury (midline shift 0-5mm), III –

diffuse injury (swelling), IV – diffuse injury (midline shift), V – evacuated mass lesion, VI –

non evacuated mass lesion.

After demonstrating that the levels of both E and NE progressively increase

according to the severity of TBI (associating with GCS, AIS and Marshall), we studied

whether there was an association between catecholamine levels and functional outcome

(including mortality), using the GOSE at 6 months. Figure 16 illustrates the baseline

median levels on admission of both E and NE according to the categories of GOSE at 6

months. Notably, median plasma levels increase progressively from severe disability to

death (categories of unfavorable outcome, GOSE 1-4). There were no patients in vegetative

state. We found a statistical difference for both E and NE in at least one category

(p<0.0001) and a statistical difference when comparing severe disability with death

(p<0.0001) for both E and NE. Median levels of both E and NE reach a plateau within the

categories of moderate disability and good recovery, with a mild NE elevation in moderate

disability + (MD+) category and a mild E elevation in good recovery - (GR-) category.

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In Figures 17 and 18 we plotted the median values in all 4 time points (admission,

6, 12 and 24 hours) to demonstrate the profile of both E and NE within the 24 hours post

injury. The E profile (Figure 17) shows an important difference between the median levels

on admission (p<0.0001) and at 6 hours (p=0.001), with levels, much higher in patients

with an unfavorable outcome. The subsequent time points did not show a statistical

difference. Conversely, the NE profile (Figure 18) demonstrates a much higher level across

all time points with a statistical significance (p<0.0001) in each admission, 6, 12 and 24 h

time points post admission.

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4.3.4. Catecholamine Levels According to Death, MODS, Sepsis and ICP

We analysed plasma levels of both E and NE according to death, survival, presence

or absence of sepsis, MODS and high ICP and checked whether there was a statistical

difference in each group. As stated previously, diagnosis of high ICP was conducted in the

ED by the trauma team leader and the neurosurgeon according to clinical (unilateral or

bilateral pupils non reactivity or Cushing response, for example) and/or CT scan findings

(Marshall Classification). In the ICU the diagnosis was conducted by the intensive care

attending, according to clinical signs, ICP monitoring, CT scan or MRI. Sepsis and MODS

were confirmed by the ICU physician during ICU stay according to current guidelines

mentioned previously. ICP was measured in 42 patients and 20 (47.6%) had high pressures.

Forty eight patients (26.5%) were diagnosed with sepsis and 4 patients (11%) diagnosed

with MODS.

In Figure 19, patients who had a diagnosis of elevated ICP, had higher median

plasma levels of both E and NE with statistical significance (median E level =

3,956.6pmol/L vs. 2,317pmol/L [p=0.04]) and median NE level = 33,837.7pmol/L vs.

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10,084.5pmol/L, p=0.02. Patients with evidence of MODS had higher E levels when

compared to patients without MODS (median E level = 4,027.1pmol/L vs. 2,115.3pmol/L,

p=0.03). For NE, although patients with MODS had a higher median level, statistical

significance was not achieved (median NE level = 17,352.9pmol/L vs. 10,003.3pmol/L

[p=0.19]). For patients who died, the levels of both E and NE were markedly increased

when compared to survivors (median E level = 6997.3pmol/L vs. 1,769.4pmol/L,

p<0.0001) and median NE level = 22,269.7pmol/L vs. 7,798.5pmol/L, p<0.0001). A

statistical significance was not found for patients with and without sepsis (p=0.17 for E and

p=0.15 for NE).

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CHAPTER 5 – Discussion and Future Directions

5.1. Discussion

5.1.1. Summary of Key Findings

The growing interest in modulating the adrenergic response initiated post brain

injury, with the use of adrenergic medications, has increased the body of literature on this

subject recently. Several studies have demonstrated that adrenergic agonists and

antagonists administered to animals and patients with brain injury may blunt catecholamine

release and the inflammatory response to injury. It appears that modulation of

catecholamine release and the inflammatory response to brain injury improve cerebral

edema, ischemia, and functional neurological outcome. Several studies in animals and in

humans [70-71, 147-156] have addressed the administration of different types of ß-blockers

and alpha agonists or alpha antagonists and have demonstrated that they may offer a

protective effect. Furthermore, several studies have demonstrated that high levels of

catecholamines released after brain injury may be associated with a poor neurological

outcome [39, 45] highlighting that catecholamines may take part in the pathophysiology of

brain injury. However, molecular and cellular processes involved in this pathophysiology

are still to be elucidated.

The COMA-TBI study was designed to replicate and extend the findings of those

previous studies that demonstrated an association between high levels of circulating plasma

catecholamines with severity of brain injury, and poor neurological outcome. No robust

conclusions from these previous studies can be drawn proving that the association is

independent due to lack of a better prospective design, power and adjustment for

confounders, among other methodological problems. The primary objective of the COMA-

TBI study was to determine whether patients with isolated moderate to severe TBI have

high circulating plasma levels on admission, compared to basal catecholamines levels of

healthy volunteers, and that the levels are independently associated with neurological

outcome as determined by the GOSE scale at 6 months post injury. The approach was to

conduct a powered prospective observational blinded cohort study examining the levels

and their independent association with neurological outcome. We looked for factors that

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were associated with an unfavorable outcome in the univariate analysis, and conducted a

multivariate logistic regression model, generating adjusted ORs and Cis for an unfavorable

outcome. Other secondary exploratory objectives of the COMA-TBI study were to: (1)

Examine ICU and hospital length of stays in both groups of patients with unfavorable and

favorable outcomes; (2) Examine ventilation days in both groups; (3) Estimate in-hospital

and 6 months post discharge mortality; (4) Examine the profile of median circulating

plasma catecholamine levels within 24 hours post admission (across 4 time points

[admission, 6, 12 and 24 hours]), in pooled patients, and in both groups; (5) Describe the

association of median catecholamine levels with severity of injury, using several scores,

such as GCS, AIS, Marshall Classification, and the functional outcome scale GOSE; and

lastly (6) Describe the levels in patients who had or did not have MODS, sepsis or high

ICP, and in patients who died or survived.

Consistent with the hypothesis, patients with isolated moderate to severe TBI

demonstrated a significant elevation of both E and NE on admission, compared to the basal

levels in healthy volunteers. The COMA-TBI study is the first powered observational study

to demonstrate the natural history of both E and NE release in the peripheral circulation

early post moderate and severe isolated TBI. Furthermore, we found an independent

association between admission levels and an unfavorable outcome at 6 months, after

adjusting for age, severity of TBI (GCS, AIS), hypotension, use of vasopressors, and

coagulopathy. Patients exhibit high levels early post injury, have a stepwise pattern, and a

decrescendo profile over the first 24 hours post trauma. Patients who have worse indices of

severity of injury (GCS, AIS and Marshall Classification), and worse neurological recovery

by GOSE, have higher levels of both E and NE. Patients with severe head injury classified

by GCS and AIS had higher median levels of both E and NE which were statistically

different when compared with the median levels in patients with moderate TBI and non-

severe head injury, respectively. As for the association with the categories of Marshall

Classification, it became evident that the levels raise progressively across categories I to

VI. There is also a substantial elevation of both E and NE across all 4 time points post

trauma in the categories associated with brain edema and signs of intracranial hypertension

(Marshall III and IV). As for GOSE, the levels progressively decrease across categories 1

to 8, with levels substantially increased in patients with unfavorable outcome compared to

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patients with a favorable outcome. Finally, the association of median plasma catecholamine

levels with death, MODS and high ICP is statistically significant compared to patients

without those complications. A statistically significant median level was not found when

analysing patients with and without sepsis.

5.1.2. Primary Study Outcome and Previous Data

Our study indicates that E and NE, two of the major components of the

sympathoadrenomedullary axis, are biomarkers of the stress response to brain trauma and

may be part of its pathophysiology. Within 24 hours of brain injury, the admission median

plasma levels of E and NE increased eleven-fold and five-fold respectively, compared to

the basal levels of both E and NE in healthy individuals. Since we enrolled patients directly

from the scene and our median time to the first assessment and catecholamine

determination (time to ED) was 60 minutes, we were able to measure E and NE levels early

post injury. We have shown that the admission levels are the highest levels within the 24

hours post injury and that these levels are independently associated with an unfavorable

outcome as measured by GOSE at 6 months, after adjusting for the main factors associated

with unfavorable outcome (age, hypotension, GCS score, AIS score, coagulopathy and use

of vasopressors).

The sympathoadrenomedullary activation in multisystem trauma and in cerebral

injury, whether traumatic or nontraumatic, is well known [37, 38, 359, 378-381]. During

the first week after TBI, about 25 to 30% of patients with severe brain injury exhibit

periodic symptoms of the hyperadrenergic state, such as tachypnea, tachycardia, systolic

hypertension, and hyperpyrexia [37]. A hyperdynamic state is present and characterized by

an increased cardiac output, cardiac work, pulmonary shunting, and oxygen delivery and

consumption [48]. The association between these responses and the severity of brain injury

and outcome is not entirely explained. Furthermore, the harm that this exacerbated

sympathetic response cause to the already injured brain is not completely understood. The

non-neurological consequences of this exaggerated catecholamine surge, such as the

cardiovascular dysfunction and the neurogenic pulmonary edema are substantially better

described but still underdiagnosed and undertreated. However, the pathophysiology of the

tissue damage to the already injured brain needs a more robust comprehension.

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Earlier studies have reported that the degree of sympathoadrenomedullary

activation correlates with the extent of brain injury and ICP [38, 358]. Although elevated

NE levels may correlate with severity of brain injury [358] and elevated circulating

catecholamine levels may underlie such cardiovascular dysfunction [378], as well as

mediate the myocardial infarction and necrosis observed after head trauma [378, 382],

there is not a proved association between prognosis and presence of autonomic

abnormalities [379]. Animal and human studies demonstrate that a local accumulation of

catecholamines causes vasoconstriction in the microcirculation, with low perfusion leading

to ischemia, further edema, high intracranial pressure and worse outcomes. Damage of the

BBB following brain injury was demonstrated by Schoultz [66] who found that trauma to

the spinal cord possibly leads to the accumulation of catecholamines in the CNS from the

circulation affecting local microcirculation and cellular function [67]. It appears that

persistent elevated levels of NE promotes a leaky barrier and may worsen cerebral edema

and ischemia [68]. Furthermore, with the injury to the BBB, circulating catecholamines

produced peripherally may reach the already injured brain and promote even more damage.

Studies with small numbers of patients and without adjustment for confounders

have demonstrated the association of the SNS activation and neurological outcome. Hamil

[39] reported a better functional recovery after TBI in patients with lower circulating

catecholamine levels. The study concluded that the elevated levels appear to reflect the

extent of brain injury and may predict the recovery. In our study, patients with the highest

levels had the worst neurological outcomes (GOSE 1-4), demonstrating a dose-effect

association. We also identified an association of high levels with other severity scores, such

as GCS, AIS and the Marshall Classification, what corroborates with the findings in the

current literature that associate levels with the extent of brain injury. We could not identify

a clear cut-off value of E or NE with high sensitivity/specificity that would predict an

unfavorable outcome. Conversely, we demonstrated that the highest the E/NE levels, the

highest is the adjusted odds of an unfavorable outcome (dose-effect response). In the

current literature, the only study that found a cut-off value was conducted by Woolf [45]

who evaluated catecholamine levels within 48 hours after TBI to determine whether their

levels would provide reliable prognostic markers of outcome assessed by the GCS score.

Those patients with NE less than 900 pg/mL improved GCS while those with values

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greater than 900 pg/mL remained with low GCS scores or died. However, this study was

not powered and included patients with multisystem trauma with or without brain injury

and did not include patients with isolated TBI, and the catecholamine measurement was not

early post trauma, as performed in our study.

Although current literature lacks robustness to definitively conclude, it is suggested

that catecholamines may participate in the pathophysiology of brain injury. The normal and

fundamental stress response post trauma may be exacerbated in some cases, leading to

deleterious consequences. Due to the association with severity of injury and the outcome,

plasma catecholamine levels may help to predict clinical outcome and may represent useful

prognostic markers in patients with TBI. Catecholamine levels on admission may predict

patients who will have a worse outcome or die and may be added to the current panel of

biomarkers of brain injury severity. The feasibility, predictive value in relation to other

indices, and the costs of measuring E and NE on admission are still to be addressed,

though.

Outcome is influenced by many other factors in patients with severe TBI, such as

age, GCS, pupillary response to light, abnormal computed tomography, and evoked

potentials [177, 178, 251, 379, 383]. Our data indicate that high catecholamine levels are

important biochemical variables that may be added to the existing panel of predictors of

unfavorable outcome in severe TBI. In the future, it will be important to compare the

predictive value of catecholamines with the traditional predictors, such as pupillary

responses and brainstem reflexes. In addition, it will be important to investigate whether

the exaggerated catecholaminergic storm is directly responsible for the cardiovascular

collapse that appears to be a terminal event in many patients with severe TBI. Regardless

of the final answers to these questions, it appears that sympathetic activation as reflected by

plasma levels of E and NE is associated with the level of coma and may predict outcome.

Another important question that needs to be addressed is whether the augmented

catecholamine response is maladaptive or is simply a reflection of injury severity.

Currently the body of evidence lacks studies with a good methodological quality

addressing these issues. However, the existing data suggests that, in addition to reflecting

the severity of injury, the enhanced sympathetic response is deleterious. For example,

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studies show that a hypermetabolic and hyperdynamic state is apparent early in trauma

patients [384, 385]. High plasma glucose and lactate levels are directly associated with the

concentrations of circulating catecholamines [386]. Increased cardiac output and cardiac

work, hypertension, tachycardia, decreased or normal systemic and pulmonary vascular

resistance, and increased oxygen delivery have been found after injury to the brain [387].

Finally, subendocardial infarction [378] and arrhythmias [388] are thought to be directly

caused by excessive catecholamine discharge.

In brief, our results show that the exaggerated catecholamine surge that occurs early

post moderate and severe isolated brain injury is associated with the severity of injury,

mostly with the severity of TBI, in a dose response pattern. Patients with a worse initial

severity of injury have higher levels and the levels decrease as the severity of injury

decreases. We demonstrated that high levels are independently associated with

neurological outcome at 6 months. Our findings are corroborated by previous animal and

human studies. However, these previous studies have methodological limitations, such as

small sample sizes and lack of adjustment for confounders. Catecholamine storm has

systemic effects and is possibly harmful to cardiovascular, respiratory, metabolic, immune

and coagulation systems, what may contribute to a worse outcome in patients with TBI. It

is also demonstrated that the release of catecholamines in the injured brain activates local

and systemic inflammatory pathways, with further cell damage, SIRS, infection and

MODS. In general, animal and human studies report that the initial exaggerated

catecholamine response in the brain may increase vasoconstriction of the microcirculation,

leading to more edema, ischemia, higher intracranial pressures and worse outcomes. It is

proposed that there is damage to the BBB, with further increase of catecholamine levels in

the brain due to the circulating catecholamines in the blood, what promotes a vicious cycle

of ongoing cell damage. However, a more robust knowledge of the pathophysiology related

to this processes is still to be demonstrated. Finally, another critical question that needs to

be addressed is whether the augmented catecholamine response is maladaptive or is simply

a reflection of injury severity. Currently, the evidence demonstrates that the catecholamine

surge related to moderate and severe TBI is not only a stress response geared towards re-

establishing homeostasis, but is a harmful response that has local and systemic deleterious

effects.

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5.1.3. Secondary Outcomes and Previous Data

The profile of catecholamine response across all 4 time points in pooled patients

demonstrated a stepwise pattern for both E and NE, with admission levels substantially

elevated for both catecholamines and a subsequent decrescendo across the 6, 12 and 24h

time points, especially for NE. On admission, E levels increased five-fold and NE levels

increased eleven-fold, compared to the basal levels of healthy volunteers. Hamil [39] has

reported in 33 patients with severe TBI that for both E and NE the levels increased four- to

five-fold on admission. The stepwise pattern was not identified in other studies found in the

literature. However, these studies did not measure catecholamine levels sequentially in the

first hours post admission to the ED as performed in our study, and most patients in those

studies had multisystem trauma, including or not TBI. Clifton [358] measured

catecholamines on admission and daily at 8am and 8pm, for 1 week. The levels remained

elevated over the entire week, without a specific trend, but the strongest association

between the levels with neurological outcome occurred within the first 48 hours post

admission. According to our findings, a substantial catecholamine surge is initiated early

post injury and this is crucial information to be considered when studies addressing the

modulation of the sympathetic activity post TBI are conducted. We believe that if the

administration of adrenergic antagonists/agonists is conducted for modulation of the

hyperadrenergic state, it should begin soon after injury.

Corroborating with our findings, Hamil [39] demonstrated an association between

low GCS scores with the highest levels of catecholamines. High AIS scores, as

demonstrated in our data, had a substantial association with high levels of both E and NE.

Patients with a non-severe head injury, had lower E and NE levels compared to patients

with a severe head injury as classified per AIS. We did not find information in the current

literature addressing the association with AIS specifically. However, in the study by Clifton

[358] a strong association between a high ISS score (that uses AIS for its determination)

with higher levels of both E and NE was found.

Catecholamines are released by the sympathetic tissue in the brain. Sympathetic

neurons secrete only NE, and not E, and NE is produced by noradrenergic neurons in the

locus coeruleus in the brain stem. It appears that NE is produced in larger amounts

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compared to E, which has been demonstrated by our results. However, even with smaller

levels, E is consistently elevated and is also associated with the severity of brain tissue

damage. Abercrombie [24] reported that NE levels measured in the microdialysate from the

hippocampus remain normal until >50% of the neurons are destroyed. When simulation of

excitotoxicity was induced, even when <50% of the cells were depleted, higher release of

NE was achieved. This implicates the locus coeruleus as the primary source for NE

elevation after TBI. Currently it is unclear whether a specific type of lesion influences the

release of catecholamines within the CNS, such as DAI, that is associated with the

autonomic storm, or whether certain critical diencephalic and/or brainstem lesions are

present. We did not find the association between the location of cerebral injury with

catecholamine levels. However, we were able to demonstrate an association between the

profile response of both E and NE with the Marshall Classification. We noted that the

highest levels of catecholamines were associated with increased edema and signs of high

ICP (Marshall categories III and IV). Norepinephrine was substantially more elevated in

the first 2 time points (admission and 6 hours) than in the 2 other time points. Epinephrine

followed the same pattern. However, the E median levels were less elevated across all 4

time points. Furthermore, we found that patients who had their ICP measured by an ICP

monitor and had at least one episode of ICP ≥25mmHg in the first 24 hours, had higher

median E and NE levels. Our data emphasizes that there is an association between cerebral

edema and intracranial hypertension with high levels of both E and NE within 24 hours

post hospital admission. We believe that a vicious cycle may happen, involving: (1) Brain

injury and damage to the BBB; (2) Production and release of central and peripheral

catecholamines; (3) Activation of local and systemic inflammatory responses; (4) Local

vasoconstriction of the microcirculation; (5) Subsequent necrosis; (6) Further edema; (7)

Higher intracranial pressures, with further tissue damage, leading to worse clinical

outcomes.

A stepwise pattern was observed when analysing the response profile of both E and

NE according to the GOSE at 6 months. Patients in the categories of unfavorable outcome

(GOSE 1-4) had higher levels with a decrescendo pattern and the highest levels in patients

who died demonstrating and dose response pattern. The levels in patients with a favorable

outcome were less elevated and there was a trend to a plateau. Clifton [358] described the

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response profile of catecholamines in patients with multisystem trauma with brain injury,

but not in patients with isolated brain injury. In his study, the levels were substantially

higher in patients who died and showed a decrescendo pattern, but less pronounced than

what was found in our study. We believe that this difference is due to the fact that we

included isolated brain injury patients and there appears to be a stronger association

between the levels of both E and NE in this population compared to patients with

multisystem trauma without TBI.

In the analysis of the response profile of E and NE median levels according to the

outcome (favorable or unfavorable), our data shows that for NE, the median plasma levels

are significantly different across all time points. Patients with an unfavorable outcome have

higher median NE levels in all measures, demonstrating a good ability to discriminate

between both groups within the first 24 hours post injury. The response profile for E is less

discriminatory as the median plasma levels are statistically different only in the first 2 time

points (admission and 6 hours). Currently there is no data in the literature estimating the

differences in the profiles for both E and NE according to the outcome as measured by

GOSE. In general the ability of NE to discriminate between the 2 groups seems to more

robust, compared to E, as demonstrated in our study.

We identified that levels of both E and NE in patients with MODS were

substantially higher compared to patients who did not develop this complication. The

current literature on inflammation demonstrates that the exacerbated catecholamine release

triggers the local inflammatory response and SIRS [124]. SIRS causes the disruption or

dysfunction of one or more organ systems [124]. For example, in patients with severe TBI,

the presence of at least one organ system dysfunction occurred in 89% of subjects [125].

SIRS results from the release of inflammatory mediators that cause early and delayed

systemic effects, including subsequent complement deficit and coagulopathy and can

detrimentally self-propagate [124]. SIRS causes tissue damage, further inflammation and

more damage, leaving the body in a vicious cycle of hyperinflammation. Therefore,

important inflammatory mediators such as IL-1 beta, IL-6 and TNF alpha, are targeted in a

compensatory anti-inflammatory response syndrome, in an attempt to control the

development of SIRS. However, the activation of this anti-inflammatory response

syndrome often leads to immunosuppression and subsequent sepsis and MODS [124].

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In our data, we noticed higher levels of both E and NE in patients with sepsis, but it

did not reach statistical significance, possibly due to the small number of patients that

developed the complication. Studies [124, 126-129] have shown that after brain injury, the

catecholamine surge can render the immune system anergic, and lead to an inability to fight

sepsis, possibly culminating in MODS. As mentioned previously, the exaggerated release

of catecholamines can alter the production of multiple inflammatory mediators in

peripheral blood immune cells and in various organs (spleen, pancreas, lungs and the

diaphragm). These immunomodulatory effects have increasingly received attention,

especially due to the potential for pharmacological intervention. For example, patients with

sympathetic storm post TBI have higher levels of IL-10 and severely depressed monocytic

HLA-DR expression, 62% of whom develop severe infections [128]. Another example is

shown in a study using isolation of splenic macrophages of a polymicrobial sepsis model,

in which further adrenergic stimulation inhibits TNF and IL-6 production by the

macrophages [129].

In brief, the COMA-TBI study demonstrates that both E and NE are substantially

elevated early post isolated brain injury, and have a stepwise pattern with a progressive

decrescendo within the first 24 hours post hospital admission, demonstrating a dose-

response pattern. This pattern corroborates partially with the current literature, but previous

studies have methodological limitations. Elevated median plasma catecholamine levels are

consistently associated with indices of severity of injury, such as GCS and AIS, which also

is documented in the current literature. Brain edema with signs of intracranial hypertension

(Marshall Categories III and IV) is the pattern of injury that is markedly associated with the

highest levels of both E and NE. We believe that the high circulating median

catecholamine levels found specially in this pattern of injury, is part of a vicious cycle of

brain injury, production and release of central and peripheral catecholamines, activation of

local and systemic inflammatory responses, local vasoconstriction of the microcirculation

and subsequent necrosis, further edema, and higher intracranial pressures, with further

tissue damage, leading to worse clinical outcomes. Norepinephrine is the amine that has

the best power to discriminate between groups of unfavorable and favorable outcome. The

profiles of median NE levels within the first 24 hours in patients with unfavorable and

favorable outcomes are consistently different, showing a discriminatory power of NE in

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distinguishing both groups. High median levels of both E and NE seem to be associated

with SIRS, sepsis and MODS. We believe that large production and release of

catecholamines may lead to these complications due to the temporal relationship. SIRS,

sepsis and MODS occur later post brain injury and are associated with the initial (on

admission) high levels of both E and NE. High levels of catecholamines trigger local

inflammation, with subsequent SIRS/MODS and the anti-inflammatory syndrome CARS.

CARS leads to immunodepression and subsequent sepsis, with worse outcomes.

5.2. Future Directions

The COMA-TBI study enabled us to identify several areas that deserve further

investigations:

5.2.1. Pathophysiology

(i) The pathophysiology of the hyperadrenergic storm in the CNS of patients with

brain injury is not completely understood. We were able to demonstrate that there is an

independent association between the production and release of catecholamines in the

peripheral blood stream, with the severity of brain injury and with an unfavorable

neurological outcome 6 months post injury. These elevated levels of both E and NE may be

harmful to the brain itself, causing further tissue damage due to vasoconstriction, ischemia,

necrosis and subsequent further edema leading to an increased ICP, and

initiation/perpetuation of a local inflammatory process what contributes to more injury. The

stress response post traumatic brain injury geared towards re-establishing homeostasis

seems to be exaggerated in patients with a higher severity of TBI. Large amounts of E and

NE seem to be deleterious systemically and have the potential to initiate non-neurological

effects such as the activation of systemic inflammatory/anti-inflammatory systems, and

effects on the neuroendocrine, immune, coagulation and metabolic systems. A fuller

understanding of the pathophysiological processes at molecular and cellular level will

undoubtedly help in developing strategies for early diagnosis and therapy, contributing to a

decrease in morbidity and in mortality of patients with brain injury. A fundamental aspect

that still needs to be elucidated is whether the catecholamine response is maladaptive or is

simply a consequence of the severity of injury. In addition, it will be important to

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investigate whether, in fact, the sympathetic storm is directly responsible for the peripheral

cardiovascular and pulmonary collapses that appear to be a terminal event in many patients

with severe brain injury.

5.2.2. Tools for Prediction of Outcome

(i) Age is one of the most important predictors of outcome in brain injury as

described previously. However, some questions still need to be addressed. Future studies

should use age as a continuous variable in their designs. Furthermore, analysis of the

effects of confounding variables such as pre-existing medical conditions should be

considered. Additionally, the biology of the aging brain and its vulnerability to injury still

warrants further detailed investigation.

(ii) Although the impact on outcome of hypotension as a secondary brain insult is

well established, future investigations must prospectively collect accurate and frequent

physiologic data on the occurrence of hypotension as well as the actual blood pressure

values throughout resuscitation. Critical physiologic threshold values and the efficacy of

various therapeutic manipulations in decreasing secondary brain insults and improving

outcome must be derived from such data after controlling for factor-factor interactions.

Investigation into the prevention or elimination of secondary brain insult might well

represent the area of early brain injury treatment with the greatest potential for improving

outcome.

(iii) Currently, the measurement of pupil size and reactivity has many limitations.

Future work should consider studying the association between those 2 parameters

(appropriately measured) to outcome, as well as the duration of pupillary dilation or

fixation. A standardized method of measuring pupil size and reactivity to light would

decrease inter-observer variability. Additionally, a definition of the size of dilated pupils is

lacking. Causative agents should be considered when assessing pupils in trauma patients,

such as orbital trauma, hypotension, and repeat evaluation after evacuation of intracranial

hematomas.

(iv) When considering the use of the GCS score for prognosis, the two most

important problems are the reliability of the initial measurement and its lack of precision

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for prediction of a good outcome if the initial GCS score is low. Future work should

address are the optimal time after injury for determining the initial GCS, when to assess the

GCS score for those who have received paralytic or sedative medication and the reliability

of the prehospital GCS score acquisition.

(v) A strong correlation exists between the different types of intracranial lesions

post TBI and outcome. However, there are still questions to be assessed. Future work

should address the complicated issue of how optimally to combine CT characteristics for

prognostic purposes and how to improve on currently used CT classifications to predict

outcome more accurately. There is a need for improved definition for intraparenchymal

lesions. A more detailed recording of surgical indications is required in future studies.

Standardized reporting of indications for surgery (clinical deterioration, CT, results of ICP

monitoring), time to operation and involving lesions are a prerequisite for comparison of

different series and determination of prognostic value. Also reasons for not operating, such

as poor prognosis or local “conservative” policy, should be explicitly stated.

(vi) The serum biomarkers and interstitial neurometabolites that represent cerebral

tissue damage are associated with severity of brain injury and/or with neurological

outcome. Further work for defining their specific role in predicting outcome in TBI is still

warranted, though.

(vii) The strong and independent association between the levels of both E and NE

with severity of brain injury and with neurological outcome may add important information

to other pre exiting tools during the primary assessment/management of patients with

moderate to severe TBI, and facilitate diagnosis, early and late management, prediction of

outcome and family counselling. In the future, it will be important to compare the

predictive value of the activation of the sympathoadrenomedullary axis with more

traditional indices of brain injury, such as pupillary responses and brainstem reflexes.

5.2.3. Modulation of the Hyperadrenergic State

Modulation of the hyperadrenergic state is a new field in the management of brain

injury. However, the evidence is growing substantially in the past years. Questions still to

be solved in the near future are:

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(i) Relevant pharmacological properties with regard to penetrance of specific ß-

blockers into the brain should be taken into account. Caution is advised in extrapolating

pharmacokinetic properties in this regard from healthy subjects to patients with acute brain

injury because permeability of the BBB is probably much higher in the latter.

(ii) As the evidence reports a potential benefit in reducing mortality with the use of

ß-blockers in patients with brain injury, it may be justifiable to proceed to phase II studies

in humans.

(iii) Several important choices have to be made reflecting the uncertainties that still

exist on the clinical significance and pathophysiology of sympathetic overstimulation. For

example: 1) the type of ß-blocker to be tested (selective versus nonselective, penetration of

blood-brain barrier or not); 2) the precise selection criteria for study participation based on

the presence or absence of risk factors for sympathetically mediated complications; 3) the

primary outcome to be chosen (stress cardiomyopathy incidence, functional outcome,

mortality); 4) dosing issues; 5) initiation and duration of treatment; 6) fixed dose treatment

or titration to, for instance, a physiological variable such as heart rate, or even assessment

of individual sympathetic/parasympathetic tone.

5.3. Limitations

Our study has several limitations as follows:

5.3.1. Risk of Information Biases

(i) Sixteen patients had no catecholamine measure available on admission due to

technical problems during specimen acquisition. This represents 8.83% of the total

admission samples obtained (181 samples). In further analysis of the 16 patients, we did

not find a trend or pattern of association with patient`s characteristics. Patients who had

their samples lost had their characteristics distributed randomly across all patients. We

don’t expect introduction of bias due to this random loss. Imputation of data was not

required due to the small number of admission samples lost.

(ii) Misclassification of the GCS on admission could possibly have happened in

some cases. We did not retrieve information about when GCS was captured in patients who

114

arrived intubated, sedated and paralysed on admission. Misclassification of GCS may have

caused an overestimation of coma and consequently misclassification bias. A factor that

possibly minimized this problem was that the trauma team leader always tries to retrieve

information from EMS personnel about the GCS before the patient`s sedation, intubation

and paralysis. The research personnel were oriented to register GCS before sedation and

paralysis (in case the patient was intubated at the scene or in route), or during the primary

assessment in the trauma room, in case the patient was not sedated, intubated and paralysed

pre admission.

(iii) Troponin and ECG were performed in a small number of patients. Both tests

are not considered standard of care and are requested depending on the clinical indication.

Although both tests were in our study protocol and were expected to be performed in all

patients, the concerning about delaying care was the reason why they were performed only

when necessary. Further analysis of both troponin and ECG could not be conducted due to

the small number of measures.

5.3.2. Risk of Confounding

(i) We did not account for the administration of drugs that could have affected

levels of catecholamines, before the acquisition of the admission blood sample, such as E

or NE boluses for example. Other drugs such as Ketamine, Ephedrine and Cocaine are

known to release catecholamines in the circulation. These drugs may act as confounders, as

they are related to the independent and dependent variables, but not part of the causal

pathway. Higher levels of catecholamines caused by these drugs may have caused bias to

both directions, depending on what patient`s characteristics these higher levels were

associated with. If the patient has a higher level caused by these confounders and had an

unfavorable outcome, there will be an overestimation of the effect of catecholamine in

patients with unfavorable outcome. Conversely, if a patient with a favorable outcome has

higher levels due to these confounders, the effect of catecholamine levels in unfavorable

outcome patients will be underestimated.

(ii) We did not account for patients who were receiving anticoagulants before

hospital admission. However, we measured INR and platelets in all patients and a

meaningful clinical difference was not observed, as their median values were mostly within

115

normal ranges or mildly abnormal. However, as coagulopathy is known as a factor that

worsens outcome in trauma and in TBI, and as on univariate analysis we found INR

associated with unfavorable outcome, we adjusted in the multivariate analysis for INR >

1.2.

5.3.3. Dichotomization of Variables

(i) We dichotomized some continuous variables to add them to the multivariate

logistic regression model. We understand that dichotomization of continuous variables may

create methodological problems such as loss of power and residual confounding [389], but

we argue that these cut-off values used are clinically relevant and have been used in the

previous and current literature. They have a strong association with unfavorable outcome in

brain injury. Age was stratified according to decades and we understand that stratification

was a better choice. Hypotension is one of the most important predictors of unfavorable

outcome in brain injury. We used the cut-off of <100mmHg, which is widely used in the

literature for general and brain trauma. Coagulopathy is also known as a predictor of

unfavorable outcome in trauma. The cut-off of INR>1.2 was previously demonstrated as a

clinically relevant factor for this population. Dichotomization of vasopressors could

possibly have caused bias as we did not capture doses and types of vasopressors and they

are known to have a dose-response pattern. Patients with severe TBI (GCS 3-8) and severe

head (AIS 4-5) have an unfavorable outcome in their majority. Patients with a GCS 3 to 8

and with AIS 4 to 5 are classified in the same diagnostic category, are managed equally in

their majority, and mostly have the same neurological outcome. We believe that these

factors have minimized possibility of bias in our study.

5.3.4. Practice Variability

(i) The 3 sites followed the Brain Trauma Foundation guidelines [390] for the

insertion of ICP monitors in moderate and severe brain injury patients. However, we

noticed some variability in practice based on the attending neurosurgeon. In order to

overcome this variability, we used the criteria previously described. In patients who did not

have an ICP monitor high ICP was captured with clinical or tomographic signs. These

criteria may have introduced bias to our analysis. If ICP is not being measured through a

116

monitor, a delay in capturing an elevated ICP or a mild elevated ICP is possible. If patients

are considered to have a normal ICP, and in fact they have a high ICP, bias against

showing a difference may have happen. Conversely, if the classification includes patients

in the high ICP group, but in fact these patients have a normal ICP, bias favouring a

difference may have happened.

(ii) LA County Hospital captured patients only in the end of the period of

enrollment (13 patients). The number of patients was small and no large variability in the

management of patients with TBI is expected to occur in the LA County Hospital

compared to the 2 Canadian centers. We believe that introduction of bias have unlikely

happened due to this reason.

5.4. Conclusions

The COMA-TBI study demonstrates that catecholamines are substantially elevated

early post isolated brain injury and, furthermore, that there is a strong independent

association between high levels of both E and NE with the severity of brain damage and

with an unfavorable neurological outcome at 6 months post injury. Both E and NE are

biomarkers of unfavorable outcome patients with isolated moderate to severe TBI and may

be added to the panel of tools used to predict outcome in brain injury. They may help

facilitating future research, improving quality of care and assisting with goals of care, and

end-of-life decisions.

Our data demonstrates that there is a hyperadrenergic state in patients with isolated

moderate to severe brain injury, and that this state is initiated early post injury, with high

levels initially and a decrescendo stepwise profile thereafter. We were able to demonstrate

the natural history of catecholamine release early post TBI. This early exaggerated storm is

associated with the severity of injury in a dose-response fashion and may be part of the

pathophysiology of TBI. It may be harmful to the brain itself, and possibly contribute to a

vicious cycle of injury. High levels of central and peripheral catecholamines may cause

vasoconstriction of the microcirculation, ischemia and further tissue damage, leading to

subsequent worse edema and increased ICP. However, this hypothesis still needs to be

further delineated as the molecular and cellular processes related to the hyperadrenergic

117

surge are still to be elucidated. Among other factors, future studies should address whether

the catecholamine response is maladaptive or is simply a consequence of the severity of

injury.

We believe that an important step in this field is to further address the modulation

of the hyperadrenergic state in patients with brain injury, even before a better

understanding of the pathophysiology of the hyperadrenergic state. As demonstrated in the

current literature, the use of adrenergic antagonists to blunt catecholamine release may

improve the injury itself by ameliorating inflammation, coagulopathy, ischemia, tissue

damage, edema and ICP, with subsequent improvement in neurological outcome and

mortality. However, current literature lacks studies with better methodological quality in

this field.

8. Disclaimer

The Coma study was funded by the Physicians1 Services Incorporation Foundation

and the Defense Research and Development Canada.

9. Conflicts of Interest

Sandro Rizoli received honorarium and speaker’s fees (as a member of the

Scientific Advisory Board) from NovoNordisk S/A, manufacturer of NovoSeven

(recombinant factor VII). The other authors have no conflict of interest relevant to the

subject matter of this publication.

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10. Reference List

1. Zygun DA, Laupland KB, Hader WJ et al.: Severe traumatic brain injury in a

large Canadian health region. Can J Neurological Sci 2005, 32(1): 87-92.

2. Campbell CG, Kuehn SM, Richards PM et al.: Medical and cognitive outcome

in children with traumatic brain injury. Can J Neurological Sci 2004, 31(2): 213-

19.

3. Rose JM: Continuum of care model for managing mild traumatic brain

injury in workers. Compensation context: a description of the model and its

development. Brain Injury 2005, 19(1): 29-39.

4. Head injuries in Canada: a decade of change (1994-1995 to 2003-2004):

Canadian Institute for Health Information 2006. [www.cihi.ca].

5. Faul M, Xu L, Wald MM, Coronado VG: Traumatic brain injury in the United

States: emergency department visits, hospitalizations, and deaths. Atlanta Ga

Centers Dis Control Prev Natl Cent Inj Prev Control 2010.

6. Head injury: triage, assessment, investigation and early management of

head injury in children, young people and adults. National Clinical Guideline

Centre 2014. [www.nice.org.uk/guidance/CG56].

7. Marion DW, Carlier PM: Problems with initial Glasgow Coma Score

assessment caused by the prehospital treatment of head-injured patients:

results of a national survey. J Trauma 1994, 36: 89-95.

8. Gale JL, Dikmen S, Wyler A, et al.: Head injury in the Pacific Northwest.

Neurosurg 1983, 12: 487-491.

9. Kaufmann MA, Buchmann B, Scheidegger D, et al.: Severe head injury:

should expected outcome influence resuscitation and first-day decisions.

Resuscitation 1992, 23: 199-206.

10. Matis GK, Birbilis TA: Poor relation between Glasgow coma scale and

survival after head injury. Med Sci Monit 2009, 15(2): 62-65.

11. Jennett B, Teasdale G, Braakman R, et al.: Predicting outcome in individual

patients after severe head injury. Lancet 1976, 1: 1031-1034.

119

12. Henderson J: “Ernest Starling and 'Hormones': an historical

commentary". J Endocrinol 2005, 184(1): 5-10.

13. Nagatsu, T: Genes for human catecholamine-synthesizing enzymes.

Neurosci Res 1991, 12: 315-345.

14. Zigmond RE, Schwarzschild MA, Rittenhouse AR: Acute regulation of

tyrosine hydroxylase by nerve activity and by neurotransmitters via

phosphorylation. Annu. Rev Neurosci 1989, 12: 415-461.

15. Daubner SC, Lauriano C, Haycock JW, et al.: Site-directed mutagenesis of

serine 40 of rat tyrosine hydroxylase: Effects of dopamine and cAMP-

dependent phosphorylation on enzyme activity. J Biol Chem 1992, 267: 12639-

12646.

16. Kumer SC, Vrana KE: Intricate regulation of tyrosine hydroxylase activity

and gene expression. J Neurochem 1996, 67: 443-462.

17. Brownstein MJ, Hoffman BJ: Neurotransmitter transporters. Recent Prog

Horm Res 1994, 49: 27-42.

18. Schuldiner S: A molecular glimpse of vesicular monoamine transporters. J

Neurochem 1994, 62: 2067-2078.

19. Eisenhofer G: The role of neuronal and extraneuronal plasma membrane

transporters in the inactivation of peripheral catecholamines. Pharmacol Ther

2001, 91: 35-62.

20. Aunis D: Exocytosis in chromaffin cells of the adrenal medulla. Int Rev

Cytol 1998, 181:213-320.

21. Dooley TP: Cloning of the human phenol sulfotransferase gene family:

Three genes implicated in the metabolism of catecholamines, thyroid

hormones and drugs. Chem Biol Interact 1998, 109: 29-41.

22. Ahlquist R P: A study of the adrenotropic receptors. Am J Physiol 1948,

153: 586-600.

23. Himms-Hagen J: Sympathetic regulation of metabolism. Pharmacol Rev

1967, 367-461.

120

24. Abercrombie ED, Zigmond MJ: Partial injury to central noradrenergic

neurons: reduction of tissue norepinephrine content is greater than

reduction of extracellular norepinephrine measured by microdialysis. J

Neurosci 1989, 9: 4062-4067.

25. Xiao RP: Beta-adrenergic signaling in the heart: dual coupling of the

beta2-adrenergic receptor to G(s) and G(i) proteins. Sci Stke 2001, 104: re 15.

26. Dolphin A C: A short history of voltage-gated calcium channels. Br J

Pharmacol 2006, 147: Suppl 1, S56-62.

27. Duman RS, Nestler EJ: in Psychopharmacol Fourth Gener Prog (Lippincott

Williams & Wilkins, 2000). [http://www.acnp.org/g4/GN401000028/CH.html].

28. Rankovic V, et al.: Modulation of calcium-dependent inactivation of L-type

Ca2+ channels via beta-adrenergic signaling in thalamocortical relay

neurons. Plos One 2011, 6(12): e27474.

29. Murphy GJ, Holder JC: PPAR-[gamma] agonists: therapeutic role in

diabetes, inflammation and cancer. Trends Pharmacol Sci 2000, 21(12): 469-

474.

30. Hudmon A, Schulman H: Neuronal Ca2+/calmodulin-dependent protein

kinase II: the role of structure and auto regulation in cellular function. Annu

Rev Biochem 2002, 71: 473-510.

31. Colbran RJ: Targeting of calcium/calmodulin-dependent protein kinase II.

Biochem J 2004, 378: 1-16.

32. Coultrap SJ, Vest RS, Ashpole NM, et al.: CaMKII in cerebral ischemia. Acta

Pharmacol Sin 2011, 32(7): 861-872.

33. Dvoriantchikova G, et al.: Inactivation of astroglial NF‐κB promotes survival

of retinal neurons following ischemic injury. Eur J Neurosci 2009, 30(2): 175-

185.

34. Pippig S, Andexinger S, Lohse MJ: Sequestration and recycling of beta 2-

adrenergic receptors permit receptor resensitization. Mol Pharmacol 1995,

47(4): 666 -676.

121

35. Elenkov IJ, Wilder RL, Chrousos GP, et al: The sympathetic nerve – an

integrative interface between two super systems: the brain and the immune

system. Pharmacol Rev 2000, 5(2): 595-638.

36. Molina PE: Neurobiology of the stress response: contribution of the

sympathetic nervous system to the neuroimmune axis in traumatic injury.

Shock 2005, 24: 3-10.

37. Johnston IH, Johnston JA, Jennett B: Intracranial pressure changes

following head injury. Lancet 1970, 2: 433-436.

38. Miller JD, Becker DP, Ward JD, et al.: Significance of intracranial

hypertension in severe head injury. J Neurosurg 1977, 47: 503-516.

39. Hamill RW, Woolf PD, McDonald JV, et al.: Catecholamines predict outcome

in traumatic brain injury. Ann Neurol 1987, 21: 438-443.

40. Mautes AEM, Muller M, Cortbus F, et al.: Alterations of norepinephrine

levels in plasma and CSF of patients after traumatic brain injury in relation to

disruption of the blood-brain barrier. Acta Neurochir 2001, 143: 51-58.

41. Woolf PD, Akowauah ES, Lee L, et al.: Evaluation of the dopamine

response to stress in man. J Clin Endocrinol Metab 1983, 56: 246-250.

42. Woolf PD, Hamill RW, Lee LA, et al.: The predictive value of

catecholamines in assessing outcome in traumatic brain injury. J Neurosurg

1987, 66: 875-882.

43. Woolf PD, Hamill RW, Lee LA, et al.: Free and total catecholamines in

critical illness. Am J Physiol 1988, 254: E287-E291.

44. Naredi S, Lambert G, Eden E, et al.: Increased sympathetic nervous activity

in patients with nontraumatic subrachnoid hemorrhage. Stroke 2000, 31: 901-

906.

45. Woolf P, McDonald J, Feliciano D, et al.: The catecholamine response to

multisystem trauma. Arch Surg 1992, 127: 899-903.

46. Timothy Y, Tran BA, Irie E, et al.: Beta blockers exposure and traumatic

brain injury: a literature review. Neurosurg Focus 2008, 25(4): E8.

122

47. Arbabi S, Ahrns KS, Wahl WL, et al.: Beta-blocker use is associated with

improved outcomes in adult burn patients. J Trauma 2004, 56(2): 265-269.

48. Clifton GL, Robertson CS, Kyper K, et al.: Cardiovascular response to

severe head injury. J Neurosurg 1983, 59: 447-454.

49. Friese RS, Barber R, McBride D, et al.: Could beta blockade improve

outcome after injury by modulating inflammatory profiles? J Trauma 2008,

64: 1061-1068.

50. Gebhard F, Pfetsch H, Steinbach G, et al.: Is interleukin 6 an early marker of

injury severity following major trauma in humans? Arch Surg 2000, 135(3):

291-295.

51. Kraus J, Conroy C, Cox P, et al.: Survival times and case fatality rates of

brain-injured persons. J Neurosurg 1985, 63: 537-543.

52. Maier B, Lefering R, Lehnert M, et al.: Early versus late onset of multiple

organ failure is associated with differing patterns of plasma cytokine

biomarker expression and outcome after severe trauma. Shock 2007, 28: 668-

674.

53. Morganti-Kossmann MC, Satgunaseelan L, Bye N, et al.: Modulation of

immune response by head injury. Injury 2007, 38: 1392-1400.

54. Morel DR, Forster A, Suter PM: Evaluation of IV labetalol for treatment of

posttraumatic hyperdynamic state. Intensive Care Med 1984, 10: 133-137.

55. Nordstrom CH, Messeter K, Sundbarg G, et al.: Cerebral blood flow,

vasoreactivity, and oxygen consumption during barbiturate therapy in

severe traumatic brain lesions. J Neurosurg 1988, 68: 424-431.

56. Seekamp A, Jochum M, Ziegler M, et al.: Cytokines and adhesion molecules

in elective and accidental trauma-related ischemia/reperfusion. J Trauma

1998, 44: 874-882.

57. Walter P, Neil-Dwyer G, Cruickshank JM: Beneficial effects of adrenergic

blockade in patients with subarachnoid haemorrhage. BMJ 1982, 284: 1661-

1664.

123

58. Woiciechowsky C, Schoning B, Cobanov J, et al.: Early IL-6 plasma

concentrations correlate with severity of brain injury and pneumonia in brain

injured patients. J Trauma 2002, 52: 339-345.

59. Zygun DA, Kortbeek JB, Fick GH, et al.: Non-neurologic organ dysfunction

in severe traumatic brain injury. Crit Care Med 2005, 33: 654-660.

60. Alexander RW, Davis JN, Lefkowitz RJ: Direct identification and

characterization of beta-adrenergic receptors in rat brain. Nature 1975, 258:

437-440.

61. Joyce JN, Lexow N, Kim SJ, et al.: Distribution of beta-adrenergic receptor

subtypes in human post-mortem brain: alterations in limbic regions of

schizophrenics. Synapse 1992, 10: 228-246.

62. Bryan RM: Cerebral blood flow and energy metabolism during stress. Am

J Physiol 1990, 259: H269-H280.

63. Rosenberg PA: Catecholamine toxicity in cerebral cortex in dissociated cell culture. J Neurosci 1988, 8(8): 2887-2894.

64. Weil-Malherbe H, Axerold J, Tomchick R: Blood-brain barrier for adrenaline.

Science 1959, 129: 1226-1227

65. Ziegler MG, Lake CR, Wood JH, et al.: Relationship between

norepinephrine in blood and cerebrospinal fluid in the presence of a blood-

cerebrospinal fluid barrier for norepinephrine. J Neurochem 1977, 28: 677-

679.

66. Schoultz TW, De Luca DC, Reding DL: Norepinephrine levels in traumatized

spinal cord of catecholamine-depleted cats. Brain Res 1976, 109: 367-374.

67. MacKenzie ET, McCulloch J, Harper AM: Influence of endogenous

norepinephrine on cerebral blood flow and metabolism. Am J Physiol 1976,

231: 489-494.

68. Sasaki M, Dunn L: A model of acute subdural hematoma in the mouse. J

Neurotrauma 2001, 18: 1241-1246.

124

69. Ley EJ, Park R, Dagliyan G, et al.: In vivo effect of propranolol dose and

timing on cerebral perfusion after traumatic brain injury. J Trauma 2010,

68(2): 353-356.

70. Wang J, Li J, Sheng X, et al.: Adrenoceptor mediated surgery-induced

production of proinflammatory cytokines in rat microglia cells. J

Neuroimmunol 2010, 223(1-2): 77-83.

71. Kato H, Kawaguchi M, Inoue S, et al.: The effects of beta-adrenoceptor

antagonists on proinflammatory cytokine concentrations after subarachnoid

hemorrhage in rats. Anesth Analg 2009, 108(1): 288-95.

72. Liu MY: Protective effects of propranolol on experimentally head injured

mouse brains. J Formos Med Assoc 1995, 94(7): 386-390.

73. Han RQ, Ouyang YB, Xu L, et al.: Post-ischemic brain injury is attenuated

in mice lacking the beta-2-adrenergic receptor. Anesth Analg 2009, 108(1):

280-287.

74. Ueyama T: Emotional stress-induced Tako-tsubo cardiomyopathy: animal

model and molecular mechanism. Ann N Y Acad Sci 2004,1018: 437-444.

75. Iwata M, Inoue S, Kawaguchi M, et al.: Post-treatment but not pre-treatment

with selective beta-adrenoreceptor 1 antagonists provides neuroprotection

in the hippocampus in rats subjected to transient forebrain ischemia. Anesth

Analg 2010, 110(4): 1126-1132.

76. Ley E, Scehnet J, Park R, et al.: The in vivo effect of propranolol on

cerebral perfusion and hypoxia after traumatic brain injury. J Trauma 2009,

66:154-161.

77. Herndon DN, Hart DW, Wolf SE, et al.: Reversal of catabolism by beta-

blockade after severe burns. N Engl J Med 2001, 345: 1223-1229.

78. Bunc G, Kovacic S, Strnad S: The influence of noradrenergic blockade on

vasospasm and the quantity of cerebral dopamine beta-hydroxylase

following subarachnoid haemorrhage in rabbits. Wien Klin Wochenschr 2003,

115(17-18): 652-659.

125

79. Svendgaard NA, Brismar J, Delgado TJ, et al.: Subarachnoid haemorrhage

in the rat: effect on the development of vasospasm of selective lesions of the

catecholamine systems in the lower brain stem. Stroke 1985, 16(4): 602-608.

80. Dilraj A, Botha JH, Rambiritch V, et al.: Levels of catecholamine in plasma

and cerebrospinal fluid in aneurysmal subarachnoid hemorrhage.

Neurosurgery 1992, 31(1): 42-50.

81. Crompton M: Hypothalamic lesions following closed head injury. Brain

1971, 94: 165-172.

82. Bullard D: Diencephalic seizures: responsiveness to bromocriptine and

morphine. Ann Neurol 1987, 21: 609-611.

83. Boeve B, Wijdicks E, Benarroch E, et al.: Paroxysmal sympathetic storms

(“diencephalic seizures”) after sever diffuse axonal head injury. Mayo Clin

Proc 1998, 73: 148-152.

84. Nosuka S: Hypertension induced by extensive medial anteromedian

hypothalamic destruction in the rat. Jpn Circ J 1966, 30: 509-523.

85. Reis D, Gauthier P, Nathan M: Hypertension, adrenal catecholamine

release, pulmonary edema, and behavioral excitement elicited from the

anterior hypothalamus in rat. Elmsford NY 1976: Pergamon Press.

86. Kemp C, Johnson J, Riordan W, et al.: How we die: the impact of non-

neurological organ dysfunction after severe traumatic brain injury. Am Surg

2008, 74: 866-872.

87. Piek J, Chesnut R, Marshall L, et al.: Extracranial complications of severe

head injury. J Neurosurg 1992, 77: 901-907.

88. Penfield W: Diencephalic autonomic epilepsy. Arch Neurol 1929, 22: 358–

374.

89. Rossitch E, Bullard D: The autonomic dysfunction syndrome: aetiology

and treatment. Br J Neurosurg 1988, 2: 471-478.

126

90. Baguley I, Heriseanu R, Cameron I, et al.: Critical review of the

pathophysiology of Dysautonomia following traumatic brain injury. Neurocrit

Care 2008, 8: 293-300.

91. Pranzatelli M, Pavlakis S, Gould R, et al.: Hypothalamic midbrain

dysregulation syndrome: hypertension, hyperthermia, hyperventilation, and

decerebration. J Child Neurol 1991, 6: 115-122.

92. Blackman J, Patrick P, Buck M, et al.: Paroxysmal autonomic instability

with dystonia after brain injury. Arch Neurol 2004, 61: 321-328.

93. Baguley I: The excitatory:inhibitory ratio model (EIR model): An

integrative explanation of acute autonomic overactivity syndromes. Med

Hypotheses 2008, 70: 26-35.

94. Baguley I, Heriseanu R, Felmingham K, et al.: Dysautonia and heart rate

variability following severe traumatic brain injury. Brain Inj 2006, 20: 437-444.

95. Kupferman I: Hypothalamus and limbic system, II: motivation. New York

NY. Elsevier Science Publishers 1985.

96. Roe S, Rothwell N: Whole body metabolic responses to brain trauma in

the rat. J Neurotrauma 1997, 14: 399-408.

97. Chiolero R, Breitenstein E, Thorin D, et al.: Effects of propranolol on resting

metabolic rate after severe head injury. Crit Care Med 1989, 17: 328-334.

98. Foley N, Marshall S, Pikul J, et al.: Hypermetabolism following moderate to

severe traumatic acute brain injury: a systemic review. J Neurotrauma 2008,

25: 1415-1431.

99. Wilmore DW, Long JM, Mason AD, et al.: Catecholamines: mediator of the

hypermetabolic response to thermal injury. Ann Surg 1974, 180: 653-669.

100. Jachuck S, Ramani P, Clark F, et al.: Electrocardiographic abnormalities

associated with raised intracranial pressure. Br Med J 1975, 1: 242-244.

101. Randell T, Tanskanen P, Scheinin M, et al.: QT depression after

subarachnoid hemorrhage. J Neurosurg Anesthesiol 1999, 11: 163-166.

127

102. Samuels MA: Neurogenic heart disease: a unifying hypothesis. Am J

Cardiol 1987, 60: 15-19.

103. Di Angelantonio E, Fiorelli M, et al.: Prognostic significance of admission

levels of troponin I in patients with acute ischaemic stroke. J Neurol

Neurosurg Psychiatry 2005, 76: 76-81.

104. Rhind SG, Capone AN, Baker AJ, et al.: Hypertonic resuscitation reduces

sympathetic nervous system activation after severe traumatic brain injury.

Submission to Critical Care Medicine, February 2010.

105. Singhal A, Baker AJ, Hare GM, et al.: Association between cerebrospinal

fluid interleukin-6 concentrations and outcome after severe human traumatic

brain injury. J Neurotrauma 2002, 19(8): 929-937.

106. Minambres E, Cemborain A, et al.: Correlation between transcranial IL-6

gradient and outcome in patients with acute brain injury. Crit Care Med 2003,

31(3): 933-938.

107. Harari A, Rapin M, Regnier B, et al.: Normal pulmonary capillary pressures

in the late phase of neurogenic pulmonary oedema. Lancet 1976, 1: 494.

108. Smith W, Matthay M: Evidence for a hydrostatic mechanism in human

neurogenic pulmonary edema. Chest 1997, 111: 1326-1333.

109. Cruickshank J, Neil-Dwyer G, Stott A: Possible role of catecholamines,

corticosteroids, and potassium in production of electrocardiographic

abnormalities associated with subarachnoid haemorrhage. Br Heart J 1974,

36: 697-703.

110. Greenhoot J, Reichenbach D: Cardiac injury and subarachnoid

hemorrhage. A clinical, pathological and physiological correlation. J

Neurosurg 1969, 30: 521-531.

111. Neil-Dwyer G, Cruickshank J, Stratton C: Beta-blockers, plasma total

creatine kinase and creatine kinase myocardial isoenzyme, and the

prognosis of subarachnoid hemorrhage. Surg Neurol 1986, 25: 163-168.

128

112. Sparks H, Hollenberg M, Carriere S, et al.: Sympathomimetic drugs and

repolarization of ventricular myocardium of the dog. Cardiovasc Res 1970, 4: 363-

370.

113. Maling H, Highman B: Exaggerated ventricular arrhythmias and

myocardia fatty changes after large doses of norepinephrine and

epinephrine in unanesthetized dogs. Am J Physiol 1958, 194: 590-596.

114. Bratton SL, Davis RL: Acute lung injury in isolated traumatic brain injury.

Neurosurgery 1997, 40: 707-712.

115. Rogers FB, Shackford SR, Trevisani GT, et al.: Neurogenic pulmonary

edema in fatal and nonfatal head injuries. J Trauma 1995, 39: 860-866.

116. Simon RP: Neurogenic pulmonary edema. Neurol Clin 1993, 11: 309-323.

117. Novitzky D, Wicomb WN, Rose AG, et al.: Pathophysiology of pulmonary

edema following experimental brain death in the chacma baboon. Ann Thorac

Surg 1987, 43: 288-94.

118. Beckman DL, Ginty DD, Gaither AC: Neurogenic pulmonary edema in a

pulmonary normotensive model. Proc Soc Exp Biol Med 1987, 186: 170-173.

119. Mertes PM, Beck B, Jaboin Y et al.: Microdialysis in the estimation of

interstitial myocardial neuropeptide Y release. Regul Pept 1993, 49: 81-90.

120. Mertes PM, Carteaux JP, Jaboin Y et al.: Estimation of myocardial

interstitial norepinephrine release after brain death using cardiac

microdialysis. Transplantation 1994, 57: 371-377.

121. Hamdy O, Nishiwaki K, Yajima M et al.: Presence and quantification of

neuropeptide Y in pulmonary edema fluids in rats. Exp Lung Res 2000, 26:

137-147.

122. Hirabayashi A, Nishiwaki K, Shimada Y, et al.: Role of neuropeptide Y and

its receptor subtypes in neurogenic pulmonary edema. Eur J Pharmacol 1996,

296: 297-305.

123. Baumann A, Audibert G, Mcdonnell J, et al.: Neurogenic pulmonary edema.

Acta Anaesthesiol Scand 2007, 51: 447-455.

129

124. Lu J, Goh SJ, Tng PYL, et al.: Systemic inflammatory response following

acute traumatic brain injury. Frontiers in Bioscience 2009, 14: 3795-3813.

125. Clond M: Therapeutic advances in traumatic brain injury and

traumatology. A thesis submitted to the faculty in conformity with the

requirements for the degree of doctor of philosophy in biomedical science and

translational medicine. Cedars-Sinai Medical Center 2013. Los Angeles, California.

126. Woiciechowsky C, Volk HD: Increased intracranial pressure induces a

rapid systemic interleukin-10 release through activation of the sympathetic

nervous system. Acta Neurochir Suppl 2005, 95: 373-376.

127. Flierl MA, Rittirsch D, Nadeau BA, et al.: Upregulation of phagocyte-

derived catecholamines augments the acute inflammatory response. PLoS

One 2009, 4(2): e4414.

128. Woiciechowsky C, Asadullah K, Nestler D, et al.: Sympathetic activation

triggers systemic interleukin-10 release in immunodepression induced by

brain injury. Nat Med 1998, 4: 808-813.

129. Deng J, Muthu K, Gamelli R, et al.: Adrenergic modulation of splenic

macrophage cytokine release in polymicrobial sepsis. Am J Physiol Cell

Physiol 2004, 287: C730-C736.

130. Meisel C, Schwab JM, Prass K, et al.: Central nervous system injury-

induced immune deficiency syndrome. Nat Rev Neurosci 2005, 6(10): 775-786.

131. Strand T, Alling C, Karlsson B, et al.: Brain and plasma proteins in spinal

fluid as markers for brain damage and severity of stroke. Stroke 1984, 15:

138–144.

132. Becker K, Kindrick D, McCarron R, et al.: Adoptive transfer of myelin basic

protein-tolerized splenocytes to naive animals reduces infarct size: a role for

lymphocytes in ischemic brain injury? Stroke 2003, 34: 1809-1815.

133. Schwab JM, Nguyen TD, Meyermann R et al.: Human focal cerebral

infarctions induce differential lesional interleukin-16 (IL-16) expression

confined to infiltrating granulocytes, CD8+ T-lymphocytes and activated

microglia/macrophages. J Neuroimmunol 2001, 114: 232-241.

130

134. Schwartz, M: Harnessing the immune system for neuroprotection:

therapeutic vaccines for acute and chronic neurodegenerative disorders. Cell

Mol Neurobiol 2001, 21: 617-627.

135. Connor TJ, Brewer C, Kelly JP, et al.: Acute stress suppresses pro-

inflammatory cytokines TNF-alpha and IL-1 beta independent of a

catecholamine-driven increase in IL-10 production. J Neuroimmunol 2005,

159: 119-128.

136. Rontgen P, Sablotzki A, Simm A, et al.: Effect of catecholamines on

intracellular cytokine synthesis in human monocytes. Eur Cytokine Netw

2004, 15: 14-23.

137. Guirao X, Kumar A, et al.: Catecholamines increase monocyte TNF

receptors and inhibit TNF through beta 2-adrenoreceptor activation. Am J

Physiol 1997, 273: E1203-1208.

138. Bergmann M, Sautner T: Immunomodulatory effects of vasoactive

catecholamines. Wien Klin Wochenschr 2002, 114: 752-761.

139. Van Poll T: Effects of catecholamines on the inflammatory response.

Sepsis 2000, 4: 159-167.

140. Ker K, Blackhall K: Beta-2 receptor antagonists for acute traumatic brain

injury. Cochrane Database Syst Rev 2008, 23(1): CD006686.

141. Tran TY, Dunne IE, German JW: Beta blockers exposure and traumatic

brain injury: a literature review. Neurosurg Focus 2008, 25(4): E8.

142. Cotton BA, Snodgrass KB, Fleming SB, et al.: Beta-blocker exposure is

associated with improved survival after severe traumatic brain injury. J

Trauma 2007, 62: 26-33.

143. Tien HC, Tremblay LN, Rizoli SB, et al.: Association between alcohol and

mortality in patients with severe traumatic head injury. Arch Surg 2006, 141: 1185-

1191.

144. Salim A, Ley EJ, Cryer HG, et al.: Positive serum ethanol level and

mortality in moderate to severe traumatic brain injury. Arch Surg 2009, 144:

865-871.

131

145. Woolf PD, Cox C, McDonald JV, et al.: Alcohol intoxication blunts

sympatho-adrenal activation following brain injury. Alcoholism 1990, 14(2):

205-209.

146. Woolf PD, Cox C, McDonald JV, et al.: Effects of intoxication on the

catecholamine response to multisystem injury. J Trauma 1991, 31: 1271-1275.

147. Markus T, Hansson SR, Cronberg T, et al.: β-Adrenoceptor activation

depresses brain inflammation and is neuroprotective in lipopolysaccharide-

induced sensitization to oxygen-glucose deprivation in organotypic

hippocampal slices. J Neuroinflammation 2010, 20(7): 94.

148. Pedrinelli R, Tarazi RC: Interference of calcium entry blockade in vivo

with pressor responses to alpha-adrenergic stimulation: effects of two

unrelated blockers on responses to both exogenous and endogenously

released norepinephrine. Circulation 1984, 69(6): 1171-1176.

149. Gleeson LC, Ryan KJ, Griffin EW, et al.: The β2-adrenoceptor agonist

clenbuterol elicits neuroprotective, anti-inflammatory and neurotrophic

actions in the kainic acid model of excitotoxicity. Brain Behav Immun 2010,

24(8): 1354-1361.

150. Rough J, Endahl R, Opperman K, et al.: Beta-2-adrenoreceptor blockade

attenuates the hyperinflammatory response induced by traumatic injury.

Surgery 2009, 145: 235-242.

151. Savitz SI, Erhardt JA, Anthony JV, et al.: The novel beta-blocker,

carvedilol, provides neuroprotection in transient focal stroke. J Cereb Blood

Flow Metab 2000, 20: 1197-1204.

152. Goyagi T, Kimura T, Nishikawa T, et al.: Beta-adrenoreceptor antagonists

attenuate brain injury after transient focal ischemia in rats. Anesth Analg

2006, 103: 658-663.

153. Nikolaeva MA, Richard S, Mouihate A, et al.: Effects of the noradrenergic

system in rat white matter exposed to oxygen-glucose deprivation in vitro. J

Neurosci 2009, 29: 1796-1804.

154. Noh JS, Kim EY, Kang JS, et al.: Neurotoxic and neuroprotective actions

of catecholamines in cortical neurons. Exp Neurol 1999, 159: 217-224.

132

155. Culmsee C: Targeting β2-adrenoceptors for neuroprotection after

cerebral ischemia: is inhibition or stimulation best? Anesth Analg 2009, 108:

3-5.

156. Junker V, Becker A, Huhne R, et al.: Stimulation of beta-adrenoceptors

activates astrocytes and provides neuroprotection. Eur J Pharmacol 2002,

446: 25-36.

157. Mantyh PW, Rogers SD, Allen CJ, et al.: Beta 2-adrenergic receptors are

expressed by glia in vivo in the normal and injured central nervous system in

the rat, rabbit, and human. J Neurosci 1995, 15: 152–164.

158. Asgeirsson B, Grände PO, Nordström CH, et al.: Effects of hypotensive

treatment with alpha 2-agonist and beta 1-antagonist on cerebral

haemodynamics in severely head injured patients. Acta Anaesthesiol Scand

1995, 39: 347-351.

159. Eker C, Asgeirsson B, Grande PO, et al.: Improved outcome after severe

head injury with a new therapy based on principles for brain volume

regulation and preserved microcirculation. Crit Care Med 1998, 26: 1881-1886.

160. Gisvold SE: The Lund concept for treatment of head injuries– faith or

science? Acta Anaesthesiol Scand 2001, 45: 399-401.

161. Grande PO, Asgeirsson B, Nordstrom CH: Volume-targeted therapy of

increased intracranial pressure: the Lund concept unifies surgical and non-

surgical treatments. Acta Anaesthesiol Scand 2002, 46: 929-941.

162. Naredi S, Eden E, Zall S, et al.: A standardized neurosurgical

neurointensive therapy directed toward vasogenic edema after severe

traumatic brain injury: clinical results. Intensive Care Med 1998, 24: 446-451.

163. Naredi S, Olivecrona M, Lindgren C, et al.: An outcome study of severe

traumatic head injury using the “Lund therapy” with low-dose prostacyclin.

Acta Anaesthesiol Scand 2001, 45: 402-406.

164. Nilsson F, Nilsson T, Edvinsson L, et al.: Effects of dihydroergotamine and

sumatriptan on isolated human cerebral and peripheral arteries and veins.

Acta Anaesthesiol Scand 1997, 41: 1257-1262.

133

165. Stahl N, Ungerstedt U, Nordstrom CH: Brain energy metabolism during

controlled reduction of cerebral perfusion pressure in severe head injuries.

Intensive Care Med 2001, 27: 1215-1223.

166. Wahlstrom MR, Olivecrona M, Koskinen LO, et al.: Severe traumatic brain

injury in pediatric patients: treatment and outcome using an intracranial

pressure targeted therapy–the Lund concept. Intensive Care Med 2005, 31:

832-839.

167. Payen D, Quintin L, Plaisance P, Chiron B, Lhoste F: Head injury: clonidine

decreases plasma catecholamines. Crit Care Med 1990, 18: 392-395.

168. Moss E: Cerebral blood flow during induced hypotension. Br J Anaesth

1995, 74: 635-637.

169. Alali AS, McCredie VA, Golan E, et al.: Beta blockers for acute traumatic

brain injury: a systematic review and meta-analysis. Neurocrit Care 2014,

20(3): 514-523.

170. Cruickshank JM, Neil-Dwyer G, Degaute JP, et al.: Reduction of

stress/catecholamine-induced cardiac necrosis by beta-1-selective blockade.

Lancet 1987, 2(8559): 585-589.

171. [50] Inaba K, Teixeira PG, David JS, et al.: Beta-blockers in isolated blunt

head injury. J Am Coll Surg 2008, 206(3): 432-438.

172. [51] Schroeppel TJ, Fischer PE, Zarzaur BL, et al.: Beta-adrenergic

blockade and traumatic brain injury: protective? J Trauma 2010, 69(4): 776-

782.

173. Schroeppel TJ, Sharpe JP, Magnotti LJ, et al.: Traumatic brain injury and β-

blockers: not all drugs are created equal. J Trauma Acute Care Surg 2014,

76(2): 504-509.

174. Barlow P, Teasdale G: Prediction of outcome and the management of

severe head injuries: the attitudes of neurosurgeons. Neurosurg 1986, 19:

989-991.

134

175. Chang RWS, Lee B, Jacobs S: Accuracy of decisions to withdraw therapy

in critically ill patients: clinical judgment versus a computer model. Crit Care

Med 1989, 17: 1091-1097.

176. Dawes RM, Faust D, Meehl RE: Clinical versus acturial judgment. Science

1989, 243: 1668-21674.

177. Narayan RK, Greenberg RP, Miller JD, et al.: Improved confidence of

outcome prediction in severe head injury in the clinical examination,

multimodality evoked potentials, CT scanning, and intracranial pressure. J

Neurosurg 1981, 54: 751-762.

178. Braakman R, Glepke GJ, Habberna JDF, et al.: Systematic selection of

prognostic features in patients with severe head injury. Neurosurg 1980, 6:

362-370.

179. Edna TH: Risk factors in traumatic head injury. Acta Neurochir 1983, 69:

15-21.

180. Hernesniemi J: Outcome following head injuries in the aged. Neurochir

1979, 49: 67-79.

181. Jennett B, Teasdale G: Prognosis after severe head injury. In:

Management of Head Injuries. Davis: Philadelphia 1981, 317.

182. Teasdale G, Skene A, Spiegelhalter D, et al.: Age, severity, and outcome of

head injury. In: Grossman RG, Gildenberg PL (ed.): Head Injury: Basic and

Clinical Aspects. New York: Raven Press 1982, 213-220.

183. Alberico AM, Ward JD, Choi SC, et al.: Outcome after severe head injury.

Relationship to mass lesions, diffuse injury, and ICP course in pediatric and

adult patients. J Neurosurg 1987, 67: 648-656.

184. Andrews B, Pitts LH: Functional recovery after traumatic transtentorial

herniation. Neurosurg 1991, 2: 227-231.

185. Berger MS, Pitts LH, Lovely M, et al.: Outcome from a severe head injury

in children and adolescents. J Neurosurg 1985, 62: 194-199.

135

186. Bruce DA, Schut L, Bruno LA, et al.: Outcome following severe head

injuries in children. J Neurosurg 1978, 48: 679-688.

187. Gruszkiewicz J, Doron Y, Peyser E: Recovery from severe craniocerebral

injury with brainstem lesions in childhood. Surg Neurol 1973, 1: 197-201.

188. Leurssen TG, Klauber MR, Marshall LF: Outcome from head injury related

to patient’s age. A longitudinal prospective study of adult and pediatric head

injury. J Neurosurg 1988, 68: 409-416.

189. Signorini DF, Andrews PJ, Jones PA, et al.: Predicting survival using

simple clinical variables; a case study in traumatic brain injury. J Neurol

Neurosurg Psychiatry 1999, 60: 20-25.

190. Lavati A, Farina ML, Vecchi G, et al.: Prognosis of severe head injuries. J

Neurosurg 1982, 57: 779-783.

191. Amacher A, Bybee DE: Toleration of head injury by the elderly. Neurosurg

1987, 20: 954-958.

192. Klauber MR, Barrett-Connor E, Marshall LF, et al.: The epidemiology of

head injury. Am J Epidemiol 1981, 113: 500-509.

193. Pentland B, Jones PA, Roy CW, et al.: Head injury in the elderly. Age and

Ageing 1986, 15: 193-202.

194. Becker DP, Miller JD, Ward JD, et al.: The outcome from severe head

injury with early diagnosis and intensive management. J Neurosurg 1977, 47:

491-502.

195. Carlsson CA, von Essen C, Löfgren J: Factors affecting the clinical course

of patients with severe head injuries. Part 1: Influence of biological factors.

Part 2: Significance of posttraumatic coma. J Neurosurg 1968, 29: 242-251.

196. Fell DA, Fitzgerald S, Hoiel R, et al.: Acute subdural hematomas. Review

of 144 cases. J Neurosurg 1975, 42: 37-42.

197. McKissock W, Richardson A, Bloom WH: Subdural hematoma: a review of

389 cases. Lancet 1960, 1: 1365-1369.

136

198. Talalla A, Morin MA: Acute traumatic subdural hematoma: a review of one

hundred consecutive cases. J Trauma 1971, 11: 771-776.

199. Wilberger J, Harris M, Diamond D: Acute subdural hematoma: morbidity,

mortality, and operative timing. J Neurosurg 1991, 74: 212-218.

200. Chesnut RM: Early indicators of prognosis in severe traumatic brain

injury. Brain Trauma Foundation. Chapter: age, pp 174-185.

[https://www.braintrauma.org/pdf/protected/prognosis_guidelines.pdf]. Assessed

26 January 2015.

201. Chesnut RM: Early indicators of prognosis in severe traumatic brain

injury. Brain Trauma Foundation. Chapter: pupillary diameter and light reflex, pp

186-198.[https://www.braintrauma.org/pdf/protected/prognosis_guidelines.pdf].

Assessed 26 January 2015.

202. Sakas DE, Bullock R, Teasdale G: One-year outcome following

craniotomy for traumatic hematoma in patients with fixed dilated pupils. J

Neurosurg 1995, 82: 961-965.

203. Andrews BT, Levy ML, Pitts LH: Implications of systemic hypotension for

the neurological examination in patients with severe head injury. Surg Neurol

1987, 28: 419-22.

204. Van Dongen KJ, Braakman R: The prognostic value of computerized

tomography in comatose head injured patients. J Neurosurg 1983, 59: 951-

957.

205. Heiden JS, Small R, Caton W, et al.: Severe head injury clinical

assessment and outcome. Physical Therapy 1983, 63: 1946-1951.

206. Marshall LF, Gautille T, Klauber M, et al.: The outcome of severe closed

head injury. J Neurosurg 1991, 75: 28-36.

207. Sobuwa S, Hartzenberg HB, Geduld H, et al.: Predicting outcome in

severe traumatic brain injury using a simple prognostic model. S Afr Med J

2014, 104(7): 492-494.

208. Rivas J, Lobato R, Sarabia R, et al.: Extradural hematoma: analysis of

factors influencing the courses of 161 patients. Neurosurg 1988, 23: 44-51.

137

209. Bahloul M, Chelly H, Ben Hmida M, et al.: Prognosis of traumatic head

injury in South Tunisia: a multivariate analysis of 437 cases. J Trauma 2004,

57: 255-261.

210. Fabbri A, Servadei F, Marchesini G, et al.: Early predictors of unfavourable

outcome in subjects with moderate head injury in the emergency

department. J Neurology, Neurosurg & Psych 2008, 79: 567-573.

211. Van Beek JG, Mushkudiani NA, Steyerberg EW, et al.: Prognostic value of

admission laboratory parameters in traumatic brain injury: results from the

IMPACT study. J Neurotrauma 2007, 24: 315-328.

212. Stassen W, Welzel T: The prevalence of hypotension and hypoxaemia in

blunt traumatic brain injury in the prehospital setting of Johannesburg,

South Africa: a retrospective chart review. S Afr Med J 2014, 104(6): 424-427.

213. McHugh GS, Engel DC, Butcher I, et al.: Prognostic value of secondary

insults in traumatic brain injury: results from the IMPACT study. J

Neurotrauma 2007, 24: 287-293.

214. Miller JD, Becker DP: Secondary insults to the injured brain. J Royal Coll

Surg 1982, 27: 292-298.

215. Miller JD, Sweet RC, Narayan R, et al.: Early insults to the injured brain.

JAMA 1978, 240: 439-42.

216. Chesnut RM, Marshall LF, Klauber MR, et al.: The role of secondary brain

injury in determining outcome from severe head injury. J Trauma 1993, 34:

216-222.

217. Fearnside MR, Cook RJ, McDougall P, et al.: The Westmead Head Injury

Project outcome in severe head injury. A comparative analysis of

prehospital, clinical and CT variables. BJ Neurosurg 1993, 7: 267-79.

218. Chesnut RM, Marshall SB, Piek J, et al.: Early and late systemic

hypotension as a frequent and fundamental source of cerebral ischemia

following severe brain injury in the Traumatic Coma Data Bank. Acta

Neurochirurgica 1993, 59: 121-125.

138

219. Pietropaoli JA, Rogers FB, Shackford SR, et al.: The deleterious effects of

intraoperative hypotension on outcome in patients with severe head injuries.

J Trauma 1992, 33: 403-407.

220. Pigula FA, Wald SL, Shackford SR, et al.: The effect of hypotension and

hypoxia on children with severe head injuries. J Pediatr Surg 1993, 28: 310-

314.

221. Vassar MJ, Fischer RP, O’Brien PE, et al.: A multicenter trial for

resuscitation of injured patients with 7.5% sodium chloride. The effect of

added dextran 70. The multicenter group for the study of hypertonic saline in

trauma patients. Arch Surg 1993, 128: 1003-1011.

222. Carrel M, Moeschler O, Ravussin P, et al.: Medicalisation prehospitaliere

heliportee et agressions cerebrales secondaires d’origine systemique chez

les traumatises craniocerebraux graves. Annales Francaises d Anesthesie et

de Reanimation 1994, 13: 326-35.

223. Lobato RD, Sarabia R, Cordobes F, et al.: Post-traumatic cerebral

hemispheric swelling. Analysis of 55 cases studied with computerized

tomography. J Neurosurg 1988, 68: 417-423.

224. Narayan RK, Kishore PR, Becker DP, et al.: Intracranial pressure: to

monitor or not to monitor? A review of our experience with severe head

injury. J Neurosurg 1982, 56: 650-659.

225. Seelig JM, Klauber MR, Toole BM, et al.: Increased ICP and systemic

hypotension during the first 72 hours following severe head injury: In: Miller

JD, Teasdale GM, Rowan JO, et al. (eds): Intracranial Pressure VI. Springer-

Verlag: Berlin 1986, 675-679.

226. Teasdale G, Jennett B: Assessment of coma and impaired

consciousness. A practical scale. Lancet 1974, 2: 81-84.

227. Chesnut RM: Early indicators of prognosis in severe traumatic brain

injury. Brain Trauma Foundation. Chapter: GCS, pp 163-173.

[https://www.braintrauma.org/pdf/protected/prognosis_guidelines.pdf]. Assessed

26 January 2015.

139

228. Beca J, Cox PN, Taylor MJ, et al.: Somatosensory evoked potentials for

prediction of outcome in acute severe brain injury. J Pediat 1995, 126: 44-49.

229. Bhatty GB, Kapoor N: The Glasgow Coma Scale: a mathematical critique.

Acta Neurochir 1993, 120: 132-135.

230. Choi SC, Barnes TY, Bullock R, et al.: Temporal profile of outcomes in

severe head injury. J Neurosurg 1994, 81: 169-173.

231. Choi SC, Narayan RK, Anderson RL, et al.: Enhanced specificity of

prognosis in severe head injury. J Neurosurg 1988, 69: 381-385.

232. Michaud LJ, Rivara FP, Grady MS, et al.: Predictors of survival and

severity of disability after severe brain injury in children. Neurosurg 1992, 31:

254-264.

233. Maas AI, Steyerberg EW, Butcher I, et al.: Prognostic value of

computerized tomography scan characteristics in traumatic brain injury:

Results from the IMPACT study. J Neurotrauma 2007, 24: 303-314.

234. Maas AI, Hukkelhoven CW, Marshall LF, et al.: Prediction of outcome in

traumatic brain injury with computed tomographic characteristics: A

comparison between the computed tomographic classification and

combinations of computed tomographic predictors. Neurosurgery 2005, 57:

1173-1182.

235. Marshall LF, Toole BM, Bowers SA: The National Traumatic Coma Data

Bank. Part 2: Patients who talk and deteriorate: Implications for treatment. J

Neurosurg 1983, 59: 285-288.

236. Marino R, Gasparotti R, Pinelli L, et al.: Posttraumatic cerebral infarction in

patients with moderate or severe head trauma. Neurology 2006, 67: 1165-

1171.

237. Mittl RL, Grossman RI, Hiehle JF, et al.: Prevalence of MR evidence of

diffuse axonal injury in patients with mild head injury and normal head CT

findings. Am J Neuroradiol 1994, 15: 1583-1589.

238. Chesnut RM: Early indicators of prognosis in severe traumatic brain

injury. Brain Trauma Foundation. Chapter: CT scan features, pp 207-255.

140

[https://www.braintrauma.org/pdf/protected/prognosis_guidelines.pdf]. Assessed

26 January 2015.

239. Holliday PO, Kelly DL Jr, Ball M: Normal computed tomograms in acute

head injury: correlation of intracranial pressure, ventricular size, and

outcome. Neurosurg 1982, 10: 25-28.

240. Lobato RD, Sarabia R, Rivas JJ, et al.: Normal computerized tomography

scans in severe head injury. Prognostic and clinical management

implications. J Neurosurg 1986, 65: 784-789.

241. Kobayashi S, Nakazawa S, Otsuka T: Clinical value of serial computed

tomography with severe head injury. Surg Neurology 1983, 20: 25-29.

242. Servadei F, Piazza G, Serrachioli A, et al.: Extradural haematomas: an

analysis of the changing characteristics of patients admitted from 1980 to

1986: diagnostic and therapeutic implications in 158 cases. Brain Injury 1988,

2: 87-100.

243. Sweet RC, Miller JD, Lipper M, et al.: Significance of bilateral

abnormalities on the CT scan in patients with severe head injury. Neurosurg

1978, 3: 16-21.

244. Soloniuk D, Pitts LH, Lovely M, et al.: Traumatic intracerebral hematomas:

timing of appearance and indications for operative removal. J Trauma 1986,

26: 787-794.

245. Tseng SH: Delayed traumatic intracerebral hemorrhage: a study of

prognostic factors. J Formosan Med Assoc 1992, 91: 585-589.

246. Reljic T, Mahony H, Djulbegovic B, et al.: Value of repeat head computed

tomography after traumatic brain injury: systematic review and meta-

analysis. J Neurotrauma 2014, 31: 78-98.

247. Mata-Mbemba D, Mugikura S, Nakagawa A et al.: Early CT findings to

predict early death in patients with traumatic brain injury: Marshall and

Rotterdam CTscoring systems compared inthe major academic tertiary care

hospital in northeastern Japan. Acad Radiol 2014, 21(5): 605-611.

141

248. Gennarelli TA, Spielman GM, Langfitt TW, et al.: Influence of the type of

intracranial lesion on outcome from severe head injury. J Neurosurg 1982, 56:

26-32.

249. Adams JH, Graham DI, Murray S, et al.: Diffuse axonal injury due to

nonmissile head injury in humans. An analysis of 45 cases. Annals of

Neurology 1982, 12: 557-563.

250. Zimmerman RA, Bilaniuk LT, Genneralli T: Computerized tomography of

shear injury of the cerebral white matter. Radiology 1978, 127: 393-396.

251. Lobato RD, Cordobes F, Rivas JJ, et al.: Outcome from severe head injury

related to the type of intracranial lesion: a computerized tomography study. J

Neurosurg 1983, 59: 762-774.

252. Marshall LF, Marshall SB, Klauber MR, et al.: A new classification of head

injury based on computerized tomography. J Neurosurg 1991; 75: S14-S20.

253. Rapenne T, Lenfant F, N’Guyen KL, et al.: Predictive factors of short-term

mortality in patients with severe head injury. Presse Med 1997; 26: 1661-1665.

254. Lobato RD, Gomez PA, Alday R, et al.: Sequential computerized

tomography changes and related final outcome in severe head injury

patients. Acta Neurochir (Wien) 1997; 139: 385-391.

255. Ono J, Yamaura A, Kubota M, et al.: Outcome prediction in severe head

injury: analyses of clinical prognostic factors. J Clin Neurosci 2001; 8: 120-

123.

256. Hiler M, Czosnyka M, Hutchinson P, et al.: Predictive value of initial

computerized tomography scan, intracranial pressure, and state of

autoregulation in patients with traumatic brain injury. J Neurosurg 2006; 104:

731-737.

257. Mataró M, Poca MA, Sahuquillo J, et al.: Neuropsychological outcome in

relation to the Traumatic Coma Data Bank classification of computed

tomography imaging. J Neurotrauma 2001; 18: 869-879.

142

258. Vos PE, van Voskuilen AC, Beems T, et al.: Evaluation of the traumatic

coma data bank computed tomography classification for severe head injury.

J Neurotrauma 2001; 18: 649-655.

259. Kakarieka A: Review on traumatic subarachnoid hemorrhage. Neurol Res

1997; 19: 230-232.

260. Greene KA, Marciano FF, Johnson BA, et al.: Impact of traumatic

subarachnoid hemorrhage on outcome in nonpenetrating head injury. Part I:

a proposed computerized tomography grading scale. J Neurosurg 1995; 83:

445-452.

261. Okten AI, Gezercan Y, Ergün R: Traumatic subarachnoid hemorrhage: a

prospective study of 58 cases. Ulus Travma Acil Cerrahi Derg 2006; 12: 107-

114.

262. Anonymous: Rating the severity of tissue damage. The abbreviated

scale. JAMA 1971, 215(2): 277-280.

263. Baker SP, O'Neill B: The injury severity score: an update. J.Trauma, 1976,

16: 882-885.

264. Baker SP, O'Neill B, Haddon W Jr, et al.: The injury severity score: a

method for describing patients with multiple injuries and evaluating

emergency care. J Trauma 1974, 14: 187-196.

265. Copes WS, Champion HR, Sacco WJ, et al.: The Injury Severity Score

revisited. J Trauma 1988, 28: 69-77.

266. Senkowski CK, McKenney MG: Trauma scoring systems: a review. J Am

Coll Surg, 189: 491-503.

267. Garthe E, States JD, Mango NK: Abbreviated injury scale unification: the

case for a unified injury system for global use. J Trauma 1999, 47: 309-323.

268. Walder AD, Yeoman PM, Turnbull A: The abbreviated injury scale as a

predictor of outcome of severe head injury. Int Care Med 1995, 21: 606-609.

143

269. Perel P, Arango M, Clayton T, et al.: Predicting outcome after traumatic

brain injury: Practical prognostic models based on large cohort of

international patients. BMJ 2008, 336(7641): 425-429.

270. Steyerberg EW, Mushkudiani N, Perel P, et al.: Predicting outcome after

traumatic brain injury: development and international validation of

prognostic scores based on admission characteristics. PLoS Med 2008, 5(8):

e165.

271. Wijdicks EF, Bamlet WR, Maramattom BV, et al.: Validation of a new coma

scale: The FOUR score. Ann Neurol 2005, 58: 585-593.

272. Sadaka F, Patel D, Lakshmanan R: The FOUR score predicts outcome

in patients after traumatic brain injury. Neurocrit Care 2012, 16: 95-101.

273. Kaloostian P, Robertson C, Gopinath SP, et al.: Outcome prediction within

twelve hours after severe traumatic brain injury by quantitative cerebral

blood flow. J Neurotrauma 2012, 29: 727-734.

274. Duckworth JL, Stevens RD: Imaging brain trauma. Curr Opin Crit Care

2010, 16: 92-97. PAREI AQUI

275. Huisman TA, Schwamm LH, Schaefer PW, et al.: Diffusion tensor imaging

as potential biomarker of white matter injury in diffuse axonal injury. AJNR

Am J Neuroradiol 2004, 25: 370-376.

276. Tong KA, Ashwal S, Holshouser BA, et al.: Diffuse axonal injury in

children: Clinical correlation with hemorrhagic lesions. Ann Neurol 2004, 56:

36-50.

277. Schaefer PW, Huisman TA, Sorensen AG, et al.: Diffusion-weighted MR

imaging in closed head injury: High correlation with initial Glasgow coma

scale score and score on modified Rankin scale at discharge. Radiology

2004, 233: 58-66.

278. Newcombe VF, Williams GB, Nortje J, et al.: Analysis of acute traumatic

axonal injury using diffusion tensor imaging. Br J Neurosurg 2007, 21: 340-

348.

144

279. Tollard E, Galanaud D, Perlbarg V, et al.: Experience of diffusion tensor

imaging and 1H spectroscopy for outcome prediction in severe traumatic

brain injury: Preliminary results. Crit Care Med 2009, 37: 1448-1455.

280. Sidaros A, Engberg AW, Sidaros K, et al.: Diffusion tensor imaging during

recovery from severe traumatic brain injury and relation to clinical outcome:

A longitudinal study. Brain 2008, 131(Pt 2): 559-572.

281. Galanaud D, Perlbarg V, Gupta R, et al.: Assessment of white matter injury

and outcome in severe brain trauma. Anesthesiology 2012, 117: 1300-1310.

282. Garnett MR, Blamire AM, Corkill RG, et al.: Early proton magnetic

resonance spectroscopy in normal-appearing brain correlates with outcome

in patients following traumatic brain injury. Brain 2000, 123(Pt10): 2046-2054.

283. Marino S, Zei E, Battaglini M, et al.: Acute metabolic brain changes

following traumatic brain injury and their relevance to clinical severity and

outcome. J Neurol Neurosurg Psychiatry 2007, 78: 501-507.

284. Hilario A, Ramos A, Millan JM, et al.: Severe traumatic head injury:

prognostic value of brain stem injuries detected at MRI. AJNR 2012, 33: 1925-

1931.

285. Skandsen T, Kvistad KA, Solheim O, et al.: Prognostic value of magnetic

resonance imaging in moderate and severe head injury: a prospective study

of early MRI findings and one-year outcome. J Neurotrauma 2011, 28: 691-699.

286. Betz J, Zhuo J, Roy A, et al.: Prognostic value of diffusion tensor imaging

parameters in severe traumatic brain injury. J Neurotrauma 2012, 29: 1292-

1305.

287. Vik A, Nag T, Fredriksli OA, et al.: Relationship of “dose” of intracranial

hypertension to outcome in severe traumatic brain injury. J Neurosurg 2008,

109: 678-684.

288. O’Sullivan MG, Statham PF, Jones PA, et al.: Role of intracranial pressure

monitoring in severely head-injured patients without signs of intracranial

hypertension on initial computerized tomography. J Neurosurg 1994, 80: 46-

50.

145

289. Juul N, Morris GF, Marshall SB, et al.: Intracranial hypertension and

cerebral perfusion pressure: Influence on neurological deterioration and

outcome in severe head injury. The Executive Committee of the International

Selfotel Trial. J Neurosurg 2000, 92: 1-6.

290. Brain Trauma Foundation: Guidelines for the management of severe

traumatic brain injury. J Neurotrauma 2007, 24(Suppl 1): S1-106.

291. Cremer OL, van Dijk GW, van Wensen E, et al.: Effect of intracranial

pressure monitoring and targeted intensive care on functional outcome after

severe head injury. Crit Care Med 2005, 33: 2207-2213.

292. Shafi S, Diaz-Arrastia R, Madden C, et al.: Intracranial pressure monitoring

in brain-injured patients is associated with worsening of survival. J Trauma

2008, 64: 335-340.

293. Chesnut RM, Temkin N, Carney N, et al.: A trial of intracranial pressure

monitoring in traumatic brain injury. N Engl J Med 2012, 367: 2471-2481.

294. Stiefel MF, Udoetuk JD, Spiotta AM, et al.: Conventional neurocritical care

and cerebral oxygenation after traumatic brain injury. J Neurosurg 2006, 105:

568-575.

295. Chang JJ, Youn TS, Benson D, et al.: Physiologic and functional outcome

correlates of brain tissue hypoxia in traumatic brain injury. Crit Care Med

2009, 37: 283-290.

296. Spiotta AM, Stiefel MF, Gracias VH, et al.: Brain tissue oxygen directed

management and outcome in patients with severe traumatic brain injury. J

Neurosurg 2010, 113: 571-580.

297. Stiefel MF, Spiotta A, Gracias VH, et al.: Reduced mortality rate in patients

with severe traumatic brain injury treated with brain tissue oxygen

monitoring. J Neurosurg 2005, 103: 805-811.

298. Narotam PK, Morrison JF, Nathoo N: Brain tissue oxygen monitoring in

traumatic brain injury and major trauma: Outcome analysis of a brain tissue

oxygen-directed therapy. J Neurosurg 2009, 111: 672-682.

146

299. Vespa P, Bergsneider M, Hattori N, et al.: Metabolic crisis without brain

ischemia is common after traumatic brain injury: A combined microdialysis

and positron emission tomography study. J Cereb Blood Flow Metab 2005, 25:

763-774.

300. Engström M, Polito A, Reinstrup P, et al.: Intracerebral microdialysis in

severe brain trauma: The importance of catheter location. J Neurosurg 2005,

102: 460-469.

301. Timofeev I, Carpenter KL, Nortje J, et al.: Cerebral extracellular chemistry

and outcome following traumatic brain injury: A microdialysis study of 223

patients. Brain 2011, 134(Pt 2): 484-494.

302. Marcoux J, McArthur DA, Miller C, et al.: Persistent metabolic crisis as

measured by elevated cerebral microdialysis lactate-pyruvate ratio predicts

chronic frontal lobe brain atrophy after traumatic brain injury. Crit Care Med

2008, 36: 2871-2877.

303. Petzold A, Tisdall MM, Girbes AR, et al.: In vivo monitoring of neuronal

loss in traumatic brain injury: A microdialysis study. Brain 2011, 134(Pt 2):

464-483.

304. Magnoni S, Esparza TJ, Conte V, et al.: Tau elevations in the brain

extracellular space correlate with reduced amyloid-beta levels and predict

adverse clinical outcomes after severe traumatic brain injury. Brain 2011,

135(Pt 4): 1268-1280.

305. Brody DL, Magnoni S, Schwetye KE, et al.: Amyloid-beta dynamics

correlate with neurological status in the injured human brain. Science 2008,

321: 1221-1224.

306. Ronne-Engstrom E, Winkler T: Continuous EEG monitoring in patients

with traumatic brain injury reveals a high incidence of epileptiform activity.

Acta Neurol Scand 2006, 114: 47-53.

307. Wiedemayer H, Triesch K, Schäfer H, et al.: Early seizures following non-

penetrating traumatic brain injury in adults: risk factors and clinical

significance. Brain Inj 2002, 16: 323-330.

147

308. Hartings JA, Bullock MR, Okonkwo DO, et al.: Spreading depolarisations

and outcome after traumatic brain injury: a prospective observational study.

Lancet Neurol 2011, 10: 1058-1064.

309. Vespa PM, Nuwer MR, Nenov V, et al.: Increased incidence and impact of

nonconvulsive and convulsive seizures after traumatic brain injury as

detected by continuous electroencephalographic monitoring. J Neurosurg

1999, 91: 750-760.

310. Vespa PM, Miller C, McArthur D, et al.: Nonconvulsive electrographic

seizures after traumatic brain injury result in a delayed, prolonged increase

in intracranial pressure and metabolic crisis. Crit Care Med 2007, 35: 2830-

2836.

311. Vespa PM, McArthur DL, Xu Y, et al.: Nonconvulsive seizures after

traumatic brain injury are associated with hippocampal atrophy. Neurology

2010, 75: 792-798.

312. Brain Trauma Foundation: Guidelines for the management of severe

traumatic brain injury. XIII. Antiseizure prophylaxis. J Neurotrauma 2007,

24(Suppl 1): S83-S86

313. Carter BG, Butt W: Review of the use of somatosensory evoked

potentials in the prediction of outcome after severe brain injury. Crit Care

Med 2001, 29: 178-186.

314. Houlden DA, Taylor AB, Feinstein A, et al.: Early somatosensory evoked

potential grades in comatose traumatic brain injury patients predict

cognitive and functional outcome. Crit Care Med 2010, 38: 167-174.

315. Di Battista AP, Rhind SG, Baker AJ: Application of blood-based

biomarkers in human mild traumatic brain injury. Front Neurol 2013, 4:44.

316. Naeimi ZS, Weinhofer A, Sarahrudi K, et al.: Predictive value of S-100B

protein and neuron specific-enolase as markers of traumatic brain damage in

clinical use. Brain Inj 2006, 20: 463-468.

317. Romner B, Ingebrigtsen T, Kongstad P, et al.: Traumatic brain damage:

serum S-100 protein measurements related to neuroradiological findings. J

Neurotrauma 2000, 17: 641-647.

148

318. Olivecrona M, Rodling-Wahlström M, Naredi S, et al.: S-100B and neuron

specific enolase are poor outcome predictors in severe traumatic brain

injury treated by an intracranial pressure targeted therapy. J Neurol

Neurosurg Psychiatry 2009, 80: 1241-1247.

319. Vos PE, Jacobs B, Andriessen TM, et al.: GFAP and S100B are biomarkers

of traumatic brain injury: An observational cohort study. Neurology 2010, 75:

1786-1793.

320. Rainey T, Lesko M, Sacho R, et al.: Predicting outcome after severe

traumatic brain injury using the serum S100B biomarker: results using a

single (24h) time-point. Resuscitation 2009, 80: 341-345.

321. Korfias S, Stranjalis G, Boviatsis E, et al.: Serum S-100B protein

monitoring in patients with severe traumatic brain injury. Intensive Care Med

2007, 33: 255-260.

322. Nylén K, Ost M, Csajbok LZ, et al.: Serum levels of S100B, S100A1B and

S100BB are all related to outcome after severe traumatic brain injury. Acta

Neurochir (Wien) 2008, 150: 221-227.

323. Wiesmann M, Steinmeier E, Magerkurth O, et al.: Outcome prediction in

traumatic brain injury: comparison of neurological status, CT findings, and

blood levels of S100B and GFAP. Acta Neurol Scand 2010, 121: 178-185.

324. Böhmer AE, Oses JP, Schmidt AP, et al.: Neuron-specific enolase, S100B,

and glial fibrillary acidic protein levels as outcome predictors in patients with

severe traumatic brain injury. Neurosurgery 2011, 68: 1624-1630.

325. Topolovec-Vranic J, Pollmann-Mudryj MA, Ouchterlony D, et al.: The value of

serum biomarkers in prediction models of outcome after mild traumatic brain

injury. J Trauma 2011, 71(5 Suppl 1): S478-S486.

326. Vos PE, Lamers KJ, Hendriks JC, et al.: Glial and neuronal proteins in

serum predict outcome after severe traumatic brain injury. Neurology 2004,

62: 1303-1310.

327. Rodrıguez-Rodrıguez A, Egea-Guerrero JJ, Leon-Justel A, et al.: Role of

S100B protein in urine and serum as an early predictor of mortality after

severe traumatic brain injury in adults. Clin Chim Acta 2012, 414C: 228-233.

149

328. Chabok SY, Moghadam AD, Saneei Z, et al.: Neuron-specific enolase and

S100BB as outcome predictors in severe diffuse axonal injury. J Trauma

Acute Care Surg 2012, 72: 1654-1657.

329. Di Battista AP, Buonora JE, Rhind SG, et al.: Blood biomarkers in moderate-to-severe traumatic brain injury: potential utility of a multi-marker approach in characterizing outcome. Front Neurol 2015, 6:110.

330. Pelinka LE, Kroepfl A, Leixnering M, et al.: GFAP versus S100B in serum

after traumatic brain injury: Relationship to brain damage and outcome. J

Neurotrauma 2004, 21: 1553-1561.

331, Nylén K, Ost M, Csajbok LZ, et al.: Increased serum-GFAP in patients with

severe traumatic brain injury is related to outcome. J Neurol Sci 2006, 240: 85-

91.

332. Liliang PC, Liang CL, Lu K, et al.: Relationship between injury severity and

serum tau protein levels in traumatic brain injured rats. Resuscitation 2010,

81: 1205-1208.

333. Liliang PC, Liang CL, Weng HC, et al.: Tau proteins in serum predict

outcome after severe traumatic brain injury. J Surg Res 2010, 160: 302-307.

334. Gullo JDS, Bertotti MM, Silva CCP, et al.: Hospital mortality of patients

with severe traumatic brain injury is associated with serum PTX3 levels.

Neurocrit Care 2011, 14: 194-199.

335. Schneider SFM, Menezes de Souza N, Liborio SM. Interleukin-10 is an

independent biomarker of severe traumatic brain injury.

Neuroimmunomodulation 2012, 19: 377-385.

336. Papa L, Akinyi L, Liu MC, et al.: Ubiquitin C-terminal hydrolase is a novel

biomarker in humans for severe traumatic brain injury. Crit Care Med 2010,

38: 138-144.

337. Saggar V, Mittal RS, Vyas MC: Hemostatic abnormalities in patients with

closed head injury and their role in predicting early mortality. J Neurotrauma

2009, 26: 1665-1668.

150

338. Oddo M, Levine JM, Kumar M, et al.: Anemia and brain oxygen after

severe traumatic brain injury. Intensive Care Med 2012, 38: 1497-1504.

339. Nelson DW, Rudehill A, MacCallum RM, et al.: Multivariate outcome

prediction in traumatic brain injury with focus on laboratory values. J

Neurotrauma 2012, 29: 2613-2624.

340. Greuters S, van den Berg A, Franschman G, et al.: Acute and delayed mild

coagulopathy are related to outcome in patients with isolated traumatic brain

injury. Crit Care 2011, 15: R2.

341. Jeremitsky E, Omert LA, Dunham CM, et al.: The impact of hyperglycemia

on patients with severe brain injury. J Trauma 2005, 58: 47-50.

342. Rovlias A, Kotsou S. The influence of hyperglycemia on neurological

outcome in patients with severe head injury. Neurosurgery 2000, 46: 335-342.

343. Lam AM, Winn HR, Cullen BF, et al.: Hyperglycemia and neurological

outcome in patients with head injury. J Neurosurg 1991, 7: 545-551.

344. Diaz-Parejo P, Stahl N, Xu W, et al.: Cerebral energy metabolism during

transient hyperglycemia in patients with severe brain trauma. Intensive Care

Med 2003, 29: 544-550.

345. Liu-DeRyke X, Collingridge DS, Orme J, et al.: Clinical impact of

hyperglycemia during acute phase of traumatic brain injury. Neurocrit Care

2009, 11: 151-157.

346. Green DM, O’Phelan KH, Bassin SL, et al.: Intensive versus conventional

insulin therapy in critically ill neurologic patients. Neurocrit Care 2010, 13:

299-306.

347. Van Den Berghe G, Wouters P, Weekers F, et al.: Intensive insulin therapy

in critically ill patients. NEJM 2001, 345: 1359-1367.

348. Vespa P, Boonyaputthikul R, McArthur DL, et al.: Intensive insulin therapy

reduces microdialysis glucose values without altering glucose utilization or

improving the lactate/pyruvate ratio after traumatic brain injury. Crit Care Med

2006, 34: 850-856.

151

349. Meierhans R, Béchir M, Ludwig S, et al.: Brain metabolism is significantly

impaired at blood glucose below 6 mM and brain glucose below 1 mM in

patients with severe traumatic brain injury. Crit Care 2010, 14: R13.

350. Béchir M, Meierhans R, Brandi G, et al.: Insulin differentially influences

brain glucose and lactate in traumatic brain injured patients. Minerva

Anestesiol 2010, 76: 896-904.

351. Vespa P, McArthur DL, Stein N, et al: Tight glycemic control increases

metabolic distress in traumatic brain injury: A randomized controlled within-

subjects trial. Crit Care Med 2012, 40: 1923-1929.

352. Andrews PJ, Sleeman DH, Statham PF, et al.: Predicting recovery in

patients suffering from traumatic brain injury by using admission variables

and physiological data: A comparison between decision tree analysis and

logistic regression. J Neurosurg 2002, 97: 326-336.

353. Clifton GL, Miller ER, Choi SC, et al.: Fluid thresholds and outcome from

severe brain injury. Crit Care Med 2002, 30: 739-745.

354. Davis DP, Peay J, Sise MJ, et al.: Prehospital airway and ventilation

management: A trauma score and injury severity score-based analysis. J

Trauma 2010, 69: 294-301.

355. Bulger EM, Nathens AB, Rivara FP, et al.: Management of severe head

injury: Institutional variations in care and effect on outcome. Crit Care Med

2002, 30: 1870-1876.

356. Patel HC, Menon DK, Tebbs S, et al.: Specialist neurocritical care and

outcome from head injury. Intensive Care Med 2002, 28: 547-553.

357. Sydenham E, Roberts I, Alderson P: Hypothermia for traumatic head

injury. Cochr Database Syst Rev 2009, 1: CD001048.

358. Clifton GL, Ziegler MG, Grossman RG: Circulating catecholamines and

sympathetic activity after head injury. Neurosurgery 1981, 8: 10-14.

359. Rosner MJ, Newsome HH, Becker DP: Mechanical brain injury: the

sympathoadrenal response. J Neurosurg 1984, 61: 76-86.

152

360. Woolf PD, McDonald JV, Feliciano DV, et al.: The catecholamine response

to multisystem trauma. Arch Surg 1992, 127: 899-903.

361. Woolf PD, Lee LA, Hamill RW, et al.: Thyroid test abnormalities in

traumatic brain injury: correlation with neurologic impairment and

sympathetic nervous system activation. Am J Med 1988, 84: 201-208.

362. Cross JS, Gruber DP, Gann DS et al.: Hypertonic saline attenuates the

hormonal response to injury. Ann Surg 1989, 209(6): 684-691.

363. Rizoli SB, Rhind SG, Shek PN et al.: The immunomodulatory effects of

hypertonic saline resuscitation in patients sustaining traumatic hemorrhagic

shock: a randomized, controlled, double-blinded trial. Ann Surg 2006, 243(1):

47-57.

364. Baker SP, O'Neill B: The injury severity score: an update. J Trauma 1976, 16: 882-885. 365. Baker SP, O'Neill B, Haddon W Jr, et al.: The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J.Trauma 1974, 14: 187-196. 366. Copes WS, Champion HR, Sacco WJ, et al.: The Injury Severity Score revisited. J Trauma 1988, 28: 69-77.

367. Senkowski CK, McKenney MG: Trauma scoring systems: a review. J Am Coll Surg 1999, 189: 491-503.

368. Jennett B, Bond M: Assessment of outcome after severe brain damage. Lancet 1975, 1(7905):480-484 369. Levin HS, Boake C, Song J, et al.: Validity and sensitivity to change of the extended Glasgow Outcome Scale in mild to moderate traumatic brain injury. J. Neurotrauma 2001, 18: 575-584. 370. Beers SR, Wisniewski SR, Garcia-Filion P, et al.: Validity of a pediatric version of the Glasgow Outcome Scale-Extended. J Neurotrauma 2012, 29: 1126–1139. 371. Bagiella E, Novack TA, Ansel B, et al.: Measuring outcome in traumatic brain injury treatment trials: recommendations from the traumatic brain injury clinical trials network. J Head Trauma Rehabil 2010, 25: 375-382.

153

372. Committee on medical aspects of automotive safety: Rating the severity of

tissue damage: I. The abbreviated scale. JAMA 1971, 215: 277-280.

373. Committee on medical aspects of automotive safety. Rating the severity of

tissue damage: II. The comprehensive scale. JAMA 1972, 220: 717-720.

374. Petrucelli E, States JD, Hames LN: The abbreviated injury scale:

Evolution, usage and future adaptability. Acid Anal Prev 1981, 13(1): 29-35.

375. American Association for Automotive Medicine. Committee on Injury Scaling

1985: Abbreviated Injury Scale. Revision. Arlington Heights, IL, United States. 376. Association for the Advancement of Automotive Medicine (1990): Abbreviated Injury Scale. Revision. Des Plaines, IL, United States. 377. Dellinger RP: The Surviving Sepsis Campaign: Where have we been and where are we going? CCJM 2015, 82(4): 237-244. 378. Connor RCR: Myocardial damage secondary to brain lesions. Am Heart J 1969, 78: 145-148. 379. Jennett B, Teasdale G: Management of Head Injuries. Contemporary Neurology Series 1981, Philadelphia, Davis. 380. Neil-Dwyer G, Cruickshank J, Stott A, et al.: The urinary catecholamine and plasma cortisol levels in patients with subarachnoid haemorrhage. J Neurol Sci 1974, 22: 375-382. 381. Robertson CS, Clifton GL, Addison AT, et al.: Treatment of hypertension associated with head injury. Neurosurgery 1983, 59: 455-460. 382. Hackenberry LE, Miner ME, Rea GL, et al.: Biochemical evidence of myocardial injury after severe head trauma. Crit Care Med 1982, 10: 641-644. 383. Choi SC, Ward JD, Becker DP: Chart for outcome prediction in severe

head injury. J Neurosurg 1983, 59: 294-297.

384. Askanazi J, Carpentier YA, Jeevanandam M, et al: Energy expenditure,

nitrogen balance, and norepinephrine excretion after injury. Surgery 1981, 89:

478-484.

385. Postel J, Schloerb PR: Metabolic effects of experimental bacteremia. Ann

Surg 1977, 185: 475-480.

154

386. Stoner HB, Frayn KN, Barton RN, et al.: The relationships between plasma

substrates and hormones and the severity of injury in 277 recently injured

patients. Clin Sci 1979, 56: 563-573.

387. Clifton GL, Robertson CS, Grossman RG: Management of the

cardiovascular and metabolic responses to severe head injury. In: Becker

DP, Povlishock JT, eds. Central Nervous System Trauma Status Report.

Bethesda, Md: National Institute of Neurological and Communicative Disorders

and Stroke 1985:139-159.

388. Jachuck SJ, Ramani PS, Clark F, et al.: Electrocardiographic

abnormalities associated with raised intracranial pressure. BMJ 1975, 1: 242-

244.

389. Royston P, Altman DG, Sauerbrei W: Dichotomizing continuous predictors

in multiple regression: a bad idea. Stat Med 2006, 25(1): 127-141.

390. Brain Trauma Foundation, American Association of Neurological Surgeons,

Congress of Neurological Surgeons: Guidelines for the management of severe

traumatic brain injury. J Neurotrauma 2007, 24: S1-S106.

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11. Appendices

Appendix 1 – INFORMED CONSENT TO PARTICIPATE IN A RESEARCH STUDY –

CATECHOLAMINES AS OUTCOME MARKERS IN TRAUMATIC BRAIN INJURY STUDY

INVESTIGATORS

Sandro Rizoli, MD, PhD

Trauma and Critical Care Medicine

St. Michael’s Hospital3-074 Donnelly Wing

30 Bond Street

Toronto, ON • M5B 1W8

Telephone: 416-864-5284

Leo Dante da Costa, MD

Neurosurgery

Sunnybrook Health Sciences Centre, Room A137

Toronto, ON • M4N 3M5

Telephone: 416-480-6100, ext. 6819

Gordon Rubenfeld, MD, MSc

Critical Care Medicine

Sunnybrook Health Sciences Centre, Room D503

Toronto, ON • M4N 3M5

Telephone: 416-480-6100, ext. 89657

INFORMED CONSENT

You are being asked to consider participating in a research study. A research study is a

way of gathering information on a treatment, procedure or medical device or to answer a question

about something that is not well understood.

This form explains the purpose of this research study, provides information about the study,

the tests and procedures involved, possible risks and benefits and the rights of participants.

Please read this form carefully and ask any questions you may have. You may have this

form and all information concerning the study explained to you. If you wish, someone may be

available to verbally translate this form to you in your preferred language.

Please ask the study staff or one of the investigators to clarify anything you do not

understand or would like to know more about. Make sure all your questions are answered to your

satisfaction before deciding whether to participate in this research study.

Participating in this study is your choice (voluntary). You have the right to choose not to

participate or to stop participating in this study at any time.

This research study is being conducted by Dr. Leo Da Costa, Dr. Sandro Rizoli, Dr. Martin

Chapman, and Dr. Gordon Rubenfeld, conducted by the Departments of Critical Care, and

Neurosurgery Teams at Sunnybrook Health Sciences Centre. Before you decide whether you will

participate, it is important for you to understand why the research study is being done and what it

will involve.

156

INTRODUCTION

You are being asked to consider participating in this study to serve as a comparison to the

traumatic brain injured patients and because you will be undergoing a neurological surgical

procedure. In patients who undergo these procedures there is some suggestion from other

research that there may be catecholamines (stress hormones) released, which may have some

relationship to other neurological scales that are routinely used to measure state of consciousness,

and recovery outcome.

WHY IS THIS STUDY BEING DONE?

The purpose of this study is to help us understand the levels of these with TBI severity and

outcome from the injury. If we find a relationship between these, then measuring catecholamine’s

on a routine basis could help doctors better treat these TBI patients and possibly improve their

outcome.

The two scales that will be used in this study are the Glasgow Coma Scale (GCS) and the

Extended Glasgow Outcome Scale (GOS-E). The GCS is a neurological scale that is used to

evaluate the conscious state of a person, for initial and follow-up assessment. A patient is assessed

against criteria on the scale, and the resulting points give a patient a score between 3 (indicating

deep unconsciousness) and 15 (indicating normal consciousness). The first goal of our study is to

prove that there is a relationship between the amount of stress hormones in the blood and the

relationship that it has with the Glasgow Coma Scale.

The outcome of a patient is evaluated using another similar scale to the GCS, called the

Extended Glasgow Outcome Scale (GOS-E), which also a neurological scale, but it is an 8-point

score used to assess the recovery of a patient after a traumatic brain injury (TBI). It is a general

assessment that can be done over the telephone. For this study, a member of the study team will

call you or a member of your family if you do not feel well, and ask some general questions about

how recovery is going 6-months after surgery. This telephone call will take 5-10-minutes, and

doesn’t require a special trip to the hospital.

WHAT WILL HAPPEN DURING THIS STUDY

If you consent to partake in the study, blood samples will be collected for special research

tests that will measured the amount of stress hormones, brain injury markers, and inflammation and

immune system markers that are present in your body. The blood collection will be done at

admission, at 6-hours, 12-hours and 24-hours after your surgery. These blood samples are taken at

the same time that other routine blood work will be done, so no additional punctures will be

necessary. Each research blood test will require an additional 20-mL of blood (equals about 1-

tablespoon). The total amount of blood required for the entire study is 60-mL (or approx. 4

tablespoons). This amount of blood is considered small, and should cause no adverse effects to

you.

Other information about your stay in hospital will be recorded, such as vital signs (blood

pressure, heart rate, breathing rate, and body temperature) and whether or not you were on a

breathing machine will be recorded. Information about you surgery, treatment, and any other

procedures will be recorded. Your condition during participation will be followed very closely by the

study investigators and research coordinators. On discharge the Extended Glasgow Outcome

Scale will be assessed, and also will be repeated by telephone at 6-months post-surgery. The 6-

month follow-up assessment can be done in 5-10-min by telephone, and doesn’t require an extra

trip to hospital.

157

HOW MANY PEOPLE WILL TAKE PART IN THIS STUDY

Approximately 200 trauma patients will be enrolled from Sunnybrook Health Sciences

Centre and St. Michael’s Hospital, and 20 neurosurgical patients will be enrolled in this research

study at Sunnybrook Health Sciences Centre. We will try and show a relationship between

catecholamine levels on admission and over the first 24-hours after trauma or surgery, with the

Extended Glasgow Outcome Score being performed at discharge from hospital, and again at 6-

months. We expect this study to take 24-months to complete the enrollment period.

WHAT ARE THE RESPONSIBILITIES OF STUDY PARTICIPANTS?

If you decide to participate in this study, you will be asked to do the following:

Sign and date the consent form for the study. You will be given a copy to keep for your records.

- Blood samples will be taken at admission, at 6-hours, at 12-hours and at 24-hours after

your surgery at the same time as other routine blood work.

- On discharge, the Extended Glasgow Outcome Score will be assessed.

- Six months post-surgery, the Extended Glasgow Outcome Score will again be assessed by

telephone.

WHAT ARE THE RISKS OR HARMS OF PARTICIPATING IN THIS STUDY?

The risks of participating in this study are the same as those that might occur when

standard routine blood sampling is performed. Since the research blood samples are collected

during routine blood sampling times, there is no additional risk to participating in this research

study.

You will be told about any new information that might reasonably affect your willingness to

continue to participate in this study as soon as the information becomes available to the study staff.

This may include new information about the risks and benefits of being a participant in this study.

WHAT ARE THE BENEFITS OF PARTICIPATING IN THIS STUDY?

There is no known direct benefit for you to participating in this study at this time. The

information obtained during this study may help future trauma patients with traumatic brain injury,

and future patients undergoing neurosurgical procedures.

WHAT OTHER CHOICES ARE THERE?

If you decide not to participate in this study, you will receive standard medical treatment for

your neurosurgical procedure. You do not have to participate in this research study to receive

treatment for you condition.

CAN PARTICIPATION IN THIS STUDY END EARLY?

The investigator(s) may decide to remove you from this study without your consent for any of

the following reasons:

- If you are unable or unwilling to follow the study procedures.

- If there is evidence that the study should be stopped due to safety reasons or lack of

treatment effect.

If you are removed from this study, the investigator(s) will discuss the reasons with you.

You can also choose to end your participation at any time without having to provide a reason.

If you choose to withdraw, your choice will not have any effect on your current or future medical

158

treatment or health care. If you withdraw from the study, you are encouraged to contact Sandy

Trpcic, Trauma Research Manager at (416) 480-6100 x 7322 immediately.

If you leave the study, the information about you and your blood work that was collected before

you left the study will still be used. No new information about you will be collected and no further

testing of your samples will be done without your permission.

WHAT ARE THE COSTS OF PARTICIPATING IN THIS STUDY?

Participation in this study will not involve any additional costs to you.

ARE STUDY PARTICIPANTS PAID TO PARTICIPATE IN THIS STUDY

You will not be paid to participate in this study.

HOW WILL MY INFORMATION BE KEPT CONFIDENTIAL?

You have the right to have any information about you and your health that is collected,

used or disclosed for this study to be handled in a confidential manner.

If you decide to participate in this study, the investigators and study staff will look at your

personal health information and collect only the information they need for this study.

You have the right to access, review and request changes to your personal health

information.

The following people may come to the hospital to look at your personal health information to

check that the information collected for the study is correct and to make sure the study followed the

required laws and guidelines:

- Representatives of the Sunnybrook Research Ethics Board

Access to your personal health information will take place under the supervision of the Principal

Investigator.

Study data is health information about you that is collected for the study, but that does not

directly identify you. Any study data about you that is sent outside of the hospital will have a code

and will not contain your name or address or any other information that directly identifies you.

Study that is sent outside of the hospital will be used for the research purposes explained in

this consent form.

The investigator, study staff and the other people listed above will keep the information they

see or receive about you confidential, to the extent permitted by applicable laws. Even though the

risk of identifying you from the study data is very small, it can never be completely eliminated.

The Principal Investigator will keep any personal health information about you in a secure and

confidential location for five years and then destroy it according to Sunnybrook policy.

When the results of this study are published, your identity will not be disclosed.

You have the right to be informed of the results of the study once the entire study is complete.

If you would like to be informed of the results of this study, please contact Sandy Trpcic, Trauma

Research Manager at (416) 480-6100 x 7322.

DO THE INVESTIGATORS HAVE ANY CONFLICTS OF INTEREST?

159

The investigators have no conflict of interest to disclose. Neither your physician, nor the

investigator will be paid a fee for enrolling you in this study.

WHAT ARE THE RIGHTS OF PARTICIPANTS IN A RESEARCH STUDY?

You have the right to receive all significant information that could help you make a decision

about participating in this study. You also have the right to ask questions about this study and your

rights as a research participant, and to have them answered to your satisfaction, before you make

any decision. You also have the right to ask questions and to receive answers throughout the

study.

If you have any questions about this study, you may contact the person in charge of this

study, Dr. Sandro Rizoli at (416).864-5284

The Sunnybrook Research Ethics Board has reviewed this study. If you have questions

about your rights as a research participant or any ethical issues related to this study that you wish

to discuss with someone not directly involved with the study, you may call Dr. Philip C. Hébert,

Chair of the Sunnybrook Research Ethics Board at (416) 480-4276.

PATIENT DOCUMENTATION OF INFORMED CONSENT

You will be given a copy of this informed consent form after it has been signed and dated by you

and the study staff.

Catecholamines as Outcome Markers in Traumatic Brain Injury Study

Name of Participant: _____________________________________________________________

Participant/Substitute decision-maker:

By signing this form, I confirm that:

This study has been fully explained to me and all of my questions answered to my satisfaction

I understand the requirements of participating in this research study

I have been informed of the risks and benefits, if any, of participating in this research study

I have been informed of any alternatives to participating in this research study

I have been informed of the rights of research participants

I have read each page of this form

I authorize access to my personal health information (medical record) and research study data

as explained in this form

I have agreed, or agree to allow the person I am responsible for, to participate in this research

study.

_________________________ ___________________________ __________________

Name of participant/Substitute Signature Date

Decision-maker (print)

Person Obtaining Consent:

By signing this form, I confirm that:

This study and its purpose has been explained to the participant named above

160

All questions asked by the participant have been answered

I will give a copy of this signed and dated document to the participant

___________________________ ___________________________ __________________

Name of Person obtaining Signature Date

Consent (print)

ASSISTANCE DECLARATION

Was the participant/substitute decision-maker assisted during the consent process? Yes No

The consent form was read to the participant/substitute decision-maker, and the person

signing below attests that the study was accurately explained to, and apparently

understood by, the participant/substitute decision-maker.

The person signing below acted as a translator for the participant/substitute decision-

maker during the consent process. He/she attests that they have accurately translated

the information for the participant/substitute decision-maker, and believe that that

participant/substitute decision-maker has understood the information translated.

__________________________ ___________________________ __________________

Name of Person Assisting (print) Signature Date

Statement of Investigator:

I acknowledge my responsibility for the care and wellbeing of the above participant, to

respect the rights and wishes of the participant as described in this informed consent document,

and to conduct this study according to all applicable laws, regulations and guidelines relating to the

ethical and legal conduct of research.

___________________________ ___________________________ __________________

Name of Investigator (print) Signature Date

Further Contact Information

Sandy Trpcic

Trauma Research Manager

Sunnybrook Health Sciences Centre

2075 Bayview Avenue, Rm H113

Toronto, Ontario M4S 3M5

Telephone: 416-480-6100 ext. 7322

Appendix 2 – CASE REPORT FORM – CATECHOLAMINES AS OUTCOME MARKERS IN TBI

STUDY (REB PIN: 068-2011)

STUDY NUMBER: ___________________________

Hosp. File Number: ________________________ Arrival Date: __________________________

Time: _______________________Elapsed Time (trauma to ER): __________________________

Age: _______________ Sex: M F Weight (kg): _________ Height (cm) _____________

Trauma: Blunt Penetrating Combined

161

Fall from level Fall from stairs MVA Pedestrian hit by car Bike Assault

Elective OR patient Type of OR __________________________________________________

Other __________________________________________________________________________

AIS non-Head, Assessed at Admission: _______________________________________________

Past Medical History: DM COPD CAD PVD CRF CHF HTN

PVD CVA Cancer Other: ___________________________________________________

Concomitant Medications: B-Blocker ______ ASA _______ Plavix ________ Coumadin _________

Steroids ____________

Other Meds: ____________________________________________________________________

ISS: ___________ AIS Head: __________ AIS non-Head: ______________________________

Neurological Status: GCS (E___ M___ V___) Intubated: Y N Sedated: Y N

Pupils: Equal: Y N Reactive: Y N Seizures: Y N U

Alcohol: Y N U Dosage: _______________ Other Intoxication: ____________________

Neuromuscular Blockers: N Y __________________________________________________

Clinical Status: BP: _______________ HR: _________ RR: _________ Temp: ________________

SatO2: _________ Mech. Ventilation: Y N

Chest Radiography: Pulmonary Edema: Y N ______________________________________

Head CT Scan: Marshall Classification _________ Description: ____________________________

ECG: Normal Abnormal ________________________________________________________

First 24 hours

Neurosurgery: N Y ____________________________________________________________

Use of vasopressors: Y N If yes, please write all doses with dates and times

Dose: ___________________ Date: ______________ Time: _____________________________

Dose: ___________________ Date: ______________ Time: _____________________________

Dose: ___________________ Date: ______________ Time: _____________________________

Dose: ___________________ Date: ______________ Time: _____________________________

Episodes of: Hypotension (Max ≤90 mm Hg) Y N ___________________________________

Desaturation < 90% Y N _______________________________________________________

Intracranial Hypertension > 20 mmHg: Y N U ____________________________________

Changes in Head CT Scan: ________________________________________________________

Changes in CXR: ________________________________________________________________

Changes in ECG: ________________________________________________________________

APACHE Score: _______ Other: ____________________________________________________

Follow up

Surgical Procedures: ______________________________________________________________

Duration of Mechanical Ventilation: __________________________________________________

Sepsis / Infections Y N ________________________________________________________

Organ / System Failure: Y N ___________________________________________________

Length of ICU Stay: CrCU: ______________ B5 ICU: _______________ Other: _______________

Length of Hospital Stay: ___________________________________________________________

GOS-E: At Hospital Discharge: __________________At 6 Months: _________________________

Patient Died: Y N

Cause of Death: Non-Brain Injury Y N Brain Injury: Y N

On Admission

162

Notes: _________________________________________________________________________

Research Coordinator/Assistant

Name: ___________________________Signature: _________________Date: _______________

Laboratory Results

Test Admission 6h 12 h 24h

Time

Epinephrine

Norepinephrine

Dopamine

Vasopressin

S-100B

IFN-γ

IL-1β

IL-10

IL-12

IL-6

IL-8

TNF-α

Adenosine

c-TnT

INR

aPTT

pH

BD

HB

Platelets

Lactate

Troponin

Other:__________________________________________________________________________

Marshalls Class Midline shift + Cisterns Status Mass lesions

Diffuse Injury I No visible intracranial pathology

Diffuse Injury II Midline shift < 5 mm

Diffuse Injury III Midline shift > 5 mm/cisterns compressed

Diffuse Injury IV Midline shift > 5 mm

Evacuated Mass Lesion Any evacuated mass

Non Evacuated Lesion Mass lesion > 25 mL

163

12. Copyright Acknowledgements

I would also like to say thanks to BMJ Publishing Group Ltd. for the permission

(license number: 3714931502577) to the use of the screenshot available at

http://www.trialscoordinatingcentre.lshtm.ac.uk/Risk%20calculator/index.html of the of

the CRASH web based calculator, and published at: Perel P, Arango M, Clayton T, et

al.: Predicting outcome after traumatic brain injury: Practical prognostic

models based on large cohort of international patients. BMJ 2008, 336(7641):

425-429 [reference 269 of this dissertation].

I also would like to say thanks to Dr. Ewout Steyerberg for the permission

(reference number: 0108SaR15ES) to use representations of the screenshot of the risk

calculator obtained at http://www.tbi-impact.org/?p=impact/calc and published at:

Steyerberg EW, Mushkudiani N, Perel P, Butcher I, Lu J, McHugh GS, Murray GD,

Marmarou A, Roberts I, Habbema JD, Maas AI: Predicting outcome after

traumatic brain injury: development and international validation of

prognostic scores based on admission characteristics. PLoS Med 2008, 5(8):

e165 [reference 270 of this dissertation].