1
Implementation of an evidence-based extubation readiness bundle in 499 brain-
injured patients - a before-after evaluation of a quality improvement project
Antoine Roquilly, M.D. (1), Raphaël Cinotti, M.D. (2), Samir Jaber, M.D.,Ph.D. (3), Mickael Vourc’h (2), Florence Pengam (1), Pierre Joachim Mahe, M.D. (1), Karim Lakhal, M.D. (2), Dominique Demeure Dit Latte, M.D. (1), Nelly Rondeau, M.D. (2), Olivier Loutrel, M.D. (1), Jérôme Paulus, M.D. (1), Bertrand Rozec, M.D., Ph.D. (2), Yvonnick Blanloeil, M.D., Ph.D. (2), Marie-Anne Vibet (4,5), Véronique Sebille, Ph.D. (5,6), Fanny Feuillet (5,6), Karim Asehnoune, M.D., Ph.D. (1) Affiliations 1. Intensive Care Unit, Anesthesia and Critical Care Department, Hôtel Dieu - HME, University
Hospital of Nantes, France 2. Intensive Care Unit, Anesthesia and Critical Care Department, Laennec, University Hospital of
Nantes, France 3. Intensive Care Unit, Anesthesia and Critical Care Department Saint Eloi University Hospital of
Montpellier, France 4. INSERM U 657, Paris, France 5. Plateforme de Biométrie, Cellule de promotion de la recherche clinique, University Hospital of
Nantes, France 6. EA 4275 SPHERE "Biostatistics, Pharmacoepidemiology & Human Science Research", UFR
des Sciences Pharmaceutiques, Nantes University, France Corresponding Author
Karim Asehnoune, M.D.,Ph.D., CHU de Nantes, Service d’Anesthésie Réanimation, 1 place Alexis Ricordeau 44093 Nantes Cedex 1. e-mail address [email protected] Tel (+33) 240 08 3005. Fax (+33) 240 08 4682
The work was performed at the Nantes University Hospital 1 place Alexis Ricordeau 44093 Nantes Cedex 1. Authors’ Contributions: AR, RC, SJ, KA contributed to the study design, data analyses, interpretation of results, writing and revision of the manuscript; MAV, FF, VS contributed to the statistical analysis and revised the manuscript; MV, FP, PJM, KL, DDDL, NR, OL, JP, BR, YB contributed to data collection, manuscript writing and revision. All authors have approved the final manuscript for publication. Funding sources: institutional funds Short Running head: Mechanical ventilation in neurological patients
Descriptor: 10.12 ICU Management/Outcome
Word count text only: 2927
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AT A GLANCE COMMENTARY (88 words): Scientific knowledge on the subject: Complications associated with prolonged mechanical
ventilation frequently develop in brain-injured patients. Strategies to decrease ventilator time have
been poorly documented to date in this specific population.
What this study adds to the field: Implementation of an evidence-based extubation readiness bundle
associating protective ventilation, early enteral nutrition, local protocol for the probabilistic treatment
of hospital-acquired pneumonia (HAP) and systematic approach to extubation, was associated with a
reduction in the duration of mechanical ventilation and in the rates of HAP as well as of unplanned
extubation.
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Abstract
Rationale: Mechanical ventilation is associated with morbidity in brain-injured patients. This study
aims to assess the effectiveness of an extubation readiness bundle to decrease ventilator time in brain-
injured patients.
Methods: Before/after design in two intensive care units (ICUs) in one university hospital. Brain-
injured patients ventilated > 24 hours were evaluated during two phases (a 3-year control phase
followed by a 22-month intervention phase). Bundle components were: protective ventilation, early
enteral nutrition, standardization of antibiotherapy for hospital-acquired pneumonia and systematic
approach to extubation. The primary endpoint was the duration of mechanical ventilation.
Results: 299 and 200 patients respectively were analyzed in the control and the intervention phases of
this before/after study. The intervention phase was associated with lower tidal volume (P<0.01), higher
PEEP (P<0.01), and higher enteral intake in the first 7 days (P=0.01). The duration of mechanical
ventilation was 14.9±11.7 days in the control phase and 12.6±10.3 days in the intervention phase
(P=0.02). The hazard ratio (HR) for extubation was 1.28 (95% confidence interval (95%CI) 1.04-1.57;
P=0.02) in the intervention phase. Adjusted HR was 1.40 (95%CI, 1.12-1.76, P<0.01) in multivariate
analysis and 1.34 (95%CI, 1.03-1.74; P=0.02) in propensity score-adjusted analysis. ICU-free days at
day-90 increased from 50±33 in the control phase versus 57±29 in the intervention phase (P<0.01).
Mortality at day 90 was 28.4% in the control phase and 23.5% in the intervention phase (P=0.22).
Conclusion: The implementation of an evidence-based extubation readiness bundle was associated
with a reduction in the duration of ventilation in brain-injured patients.
Key words: Mechanical Ventilation, Brain injury, Weaning, Ventilator-induced lung injury,
extubation.
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Introduction
Weaning from mechanical ventilation is a major issue in the intensive care unit (ICU) (1). Brain-
injury is a major cause of respiratory failure and a frequent cause of prolonged mechanical ventilation
(2). Although primary brain insults are the main determinants of outcomes in critically ill neurologic
patients, mechanical ventilation morbidity has been associated with poor neurological recovery and
death in this specific population (3-5). Reduction of mechanical ventilation duration could improve
health-related quality of life and it reduces the medical costs associated with critically ill patients (6,
7).
The standardization of medical care has been shown to improve the outcomes of critically ill
patients. We hypothesized that the systematic application of a limited number of specific interventions
could reduce ventilator time in brain-injured patients. In this setting, four main targets appeared
attractive in this population. First, protective ventilation, defined as low tidal volume and positive end-
expiratory pressure (PEEP), is attractive since brain injury potentiates ventilator-induced lung injuries
(8, 9) and since PEEP does not alter brain perfusion (10, 11). Second, early enteral feeding decreases
the rate of infection as well as the duration of mechanical ventilation in surgical and trauma patients
(12, 13). Third, optimal protocols of probabilistic antibiotherapy to treat hospital-acquired pneumonia
(HAP) are mandated since inadequate antibiotherapy is associated with alteration of outcomes in ICU
patients (14). Consideration of local epidemiology is necessary when implementing international
guidelines for antibiotherapy of HAP (15-17). Fourth, extubation of patients without complete
awakeness could be safe (19, 20), reducing the risk of unplanned extubation (18, 19) and decreasing
the duration of ICU stay (20).
We hypothesized that the implementation of an evidence-base care bundle including protective
ventilation, early enteral nutrition, standardization of antibiotherapy and systemic approach to
extubation can accelerate extubation readiness in brain-injured patients (21). We therefore conducted a
before/after study to investigate the implementation of an evidence-based bundle to decrease ventilator
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time in brain-injured patients. Some of the results of this study have been previously reported in the
form of an unpublished abstract (22).
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Materials and methods Ethics statement
The protocol was approved by the local ethics committee of Nantes hospital (Groupe Nantais
d’Ethique dans le Domaine de la Santé, Nantes, France). Consent was waived because the project was
a prospective improvement process within a collaborative institutional quality improvement program
applied to all brain-injured patients hospitalized in our ICUs.
Patients and setting
The present study was performed in two ICUs of a university hospital. Data from all adult brain-
injured patients (traumatic brain-injured, subarachnoid hemorrhage, stroke or other) who required
mechanical ventilation for more than 24 hours were collected and analyzed. Brain injury was
considered when a Glasgow Coma Scale 12 was associated with at least one anomaly related to an
acute process on head tomographic tomodensitometry (extradural hematoma, subarachnoid
hemorrhage, brain contusion, hematoma, brain edema, skull fracture, stroke, abscess). Exclusion
criteria were early decision to withdraw care (taken in the first 24 hours in ICU), death in the first 24
hours or inclusion in a randomized controlled trial.
General Care for brain-injured patients
As previously described (23, 24), all patients were sedated with a continuous intravenous infusion of
fentanyl (2-5 g.kg-1.hr-1) and midazolam (initiated at 0.1 mg.kg-1.hr-1 and increased up to 0.2-0.5
mg.kg-1.hr-1 in case of intracranial hypertension). Intracranial pressure was monitored with an
intraparenchymal probe placed in the most affected side (Codman, Johnson and Johnson Company,
Raynham, Mass., USA.) in patients who were considered at increased risk of intracranial hypertension
(25). When control of intracranial pressure was poor despite osmotherapy or ventricular drainage,
sodium thiopental was used with a loading dose (2-3 mg.kg-1) followed by continuous administration
(2-3 mg.kg-1.hr-1) adapted to intracranial pressure evolution and to serum level monitoring (blood
level of thiopental between 20 and 30 g.ml-1). No daily interruption of sedation was performed during
the period of intracranial hypertension. Sedation was discontinued as soon as the risk of intracranial
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hypertension was considered as low on head tomographic tomodensitometry (no cortical sulcal
effacement, no midline shift and no compressed peri-mesencephalic cisterns).
Study protocol
Study design
A before/after study design was used. The before period (control phase) consisted of all consecutive
patients with severe brain-injury who were admitted to the participating ICUs three years before the
educational program began (January 2007-December 2009). The intervention was introduced over a 12
month period (January-December 2010), during which no patient data were collected. The intervention
phase consisted of all consecutive severe brain-injured patients admitted to the participating ICUs
during a 22 month period (January 2011-October 2012).
Control phase
During a 3 year control phase, ventilatory setting, enteral nutrition, probabilistic antibiotherapy
for HAP and decision for extubation were performed at the discretion of the attending physician. We
performed a retrospective analysis of prospectively recorded data regarding: demographic
characteristics, ventilatory setting, nutritional support, pathogens involved in HAP, duration of
mechanical ventilation, hospital stay and mortality. The ideal body weight was calculated from the
patient’s height (ideal body weight of male patients was calculated as equal to 50+ 0.91(centimeters of
height - 152.4); that of female patients was calculated as equal to 45.5+0.91(centimeters of height-
152.4)).
Interphase
During a 12 month period, we developed a 4 point bundle to decrease ventilator time based on a
review of the literature and on analysis of the pathogens involved in HAP in our ICUs. Four targets
were defined: protective ventilation, early enteral nutrition, optimization of the probabilistic
antibiotherapy for HAP and a systematic approach to extubation (Table 1). During this phase, all
physicians, residents, physiotherapists and nurses received formal training for the processes and
procedures related to the 4 point bundle. Based on the prospective follow-up of the pathogens involved
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in HAP during the control phase in our ICUs, two criteria have been defined for prescription of
probabilistic antibiotherapy against multiple-drug-resistant bacteria (previous 48-hour antibiotherapy
and/or hospitalization lasting more than 9 days). We also considered that cephalosporinase is the main
mechanism of resistance for Enterobacteriacae in our ICUs, and we therefore recommend the use of
cefepime, which is not affected by these enzymes. Moreover, methicillin-resistant Staphylococcus
aureus (S. aureus) was infrequent in our ICUs and this bacterium was not considered in probabilistic
antibiotherapy. This protocol is reassessed annually. During the control phase, sedation was already
standardized according to international guidelines (26, 27) and the management of sedation was
therefore not included in the bundle interventions.
Intervention phase
During a 22-month period, the recommended procedure was to conform to the extubation
readiness bundle (Table 1) and patients were followed up until day 90.
Outcomes
The primary outcome was the duration of mechanical ventilation. Secondary outcomes were the
compliance with bundle elements, the number of ventilator-free days at days 28 and 90, the rates of
extubation failure, of unplanned extubation, of tracheotomy, of HAP; ICU length of stay, the number
of ICU-free days at day 90 and the mortality at day 90.
Compliance with antibiotherapy for HAP was not applicable in the control phase. Compliance
with the systematic approach to extubation (undelayed extubation) was considered in the two phases
when tube removal was performed within 48 hours after all of the requirements for extubation were
met (inspiratory support < 10 cm H2O, Glasgow Coma Scale 10 and cough) (20).
The number of ventilator-free days was defined as the number of days from day 1 to day 28 (or
day 90 as stated) on which a patient breathed spontaneously and was alive.
Pneumonia was considered when two signs (among body temperature > 38°C; leukocytosis > 12
000/mL or leukopenia < 4000/mL and purulent pulmonary secretions) were associated with the
appearance of a new infiltrate or changes in an existing infiltrate on chest x-ray (28). Diagnosis was
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confirmed by a respiratory tract sample using a quantitative culture with a predefined positive
threshold of 104 colony-forming units per milliliter (CFU/mL) for a bronchoalveolar lavage or non-
bronchoscopic sample, 106 CFU/mL for an endotracheal aspirate. Hospital-acquired pneumonia was
defined as pneumonia that occurred 48 hours after admission that had not been incubating at the time
of admission.
Statistical analysis
In a previous study by Mascia et al. (8), brain-injured patients who developed VILI had a 25%
decrease in the number of ventilator-free days. Our study was designed to detect a 25% relative
reduction in the duration of mechanical ventilation, which was estimated at 13 ± 10 days in the control
phase (29) with a power of 90% and a type I error of 5%. Considering this power analysis, 398 patients
are needed. The control phase has been a priori set to a 3-year duration and 299 patients were included
in this phase. Finally, the preintervention to postintervention ratio was set as 3:2, and a total of 500
patients were included in the two phases.
The primary analysis consisted in comparing the duration of mechanical ventilation between the
two phases by means of a Student’s t-test. A stratified log-rank test was then applied. To consider
death as a competing event, individuals presenting this event were censored at this time-point
(mechanical ventilation equal to the duration of survival).
A sensitivity analysis with a Fine and Gray model was a posteriori applied in order to consider
the potential bias associated with the treatment of death. Extubation was defined as the principal event
and death before extubation was defined as a competing risk (30). Proportional risk assumption was
not verified for the treatment phase, so a time-dependent variable was included in the model. A cut-off
was observed in the graphics and an optimal cut-off was obtained by minimizing the AIC criterion.
In order to consider potential bias associated with the before/after study design, we decided a
posteriori to perform two complementary sensitivity analyses with an adjustment for demographic
characteristics: 1/ A multivariate analysis was performed using a Cox regression model including
variables differing between the two phases in bivariate analyses (with a p value <0.10). Variables used
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for adjustment were : cardiac failure, simplified acute physiology score-II, Glasgow Coma Scale,
initial pathology, extra-ventricular drainage for hydrocephalus and decompressive craniectomy; 2/ A
propensity score method was applied to balance covariates in the two phases and to reduce bias.
Propensity score is defined as the conditional probability of being in the intervention phase given the
covariates. It was estimated using logistic regression, including variables recorded on ICU admission.
A propensity score method was applied to balance covariates in the two phases and to reduce bias.
Propensity score was defined as the conditional probability of being in the intervention phase given the
covariates. It was estimated using logistic regression, including variables recorded on ICU admission.
At each step of the algorithm an intervention subject i was randomly selected and the difference
between his propensity score and the propensity score of all control subjects was calculated (ic,
i=1,…,m where m was the number of intervention subjects; c=1,...,n where n was the number of
control subjects). In order to select the lowest distance between propensity scores for all intervention
subjects (Di1, Di2,…, Din for subject i, i=1,…,m), a distance caliper was used whose size is a quarter
of a standard deviation of the logit of the propensity score. All control subjects with a distance ic
lower than the caliper size were retained for each intervention subject (control subjects for which ic
is higher than the caliper size are not retained). Finally, Mahalanobis distances were calculated
between each previously retained control subject and the intervention subject. The closest control and
intervention subject, regarding Mahalanobis distance, was then removed from the pool, and the process
was repeated for all intervention subjects (31). This caliper matching method was used to match 153
(76.5%) patients in the intervention phase and 153 patients in the control phase. A stratified log-rank
test and a Cox regression model were performed on this matched sample.
In order to assess treatment effect heterogeneity across initial pathology, a subgroup analysis was
performed using a Cox regression model (traumatic brain injury, subarachnoid hemorrhage, stroke and
other conditions). Interaction between phase and initial pathology subgroups was tested. To estimate
time trends effect, a time series analysis on aggregated data was performed. Segmented linear
regression was used. In order to determine the effect of adherence to best practices, the factors
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associated with the duration of mechanical ventilation were investigated through a multivariate Cox
regression model.
The normality of the variables was tested with a Kolmogorov-Smirnoff test. Continuous
parametric data were expressed as the mean (SD), and non-parametric data were expressed as the
median and interquartile range (IQR). Categorical data were expressed as numbers and percentage, as
well as the absolute difference (95% confidence interval, 95%CI). For demographic characteristics and
secondary endpoint 2 test, Student’s t-test or Wilcoxon rank-sum test were used as appropriate. All
statistical tests were two-sided. A two-sided p value less than 0.05 was considered statistically
significant. An independent statistician performed the analyses with SAS statistical software (SAS 9.3
Institute, Cary, NC) and R statistical software (R 3.0).
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Results
Population
Demographic characteristics at baseline are reported in Table 2. Of 7,590 patients admitted in the
participating ICUs, 299 brain-injured patients (49.3% traumatic brain-injured, 30.9% subarachnoid
hemorrhage, 18.8% stroke, 1% cancer or meningitis) were included in the control phase, and 200 in the
intervention phase (39% traumatic brain-injured, 36.5% subarachnoid hemorrhage, 16% stroke, 8.5%
cancer or meningitis) P<0.01) (see flow chart, Figure 1). In the intervention phase, extra-ventricular
drainage (P<0.01) and decompressive craniectomy (P=0.03) were performed more frequently than in
the control phase.
Compliance with bundle elements
Intervention adherence is reported in Table 3. The rates of adherence to tidal volume and PEEP
recommendations were 33.6% and 37.8% in the control phase respectively, and 42.6% and 62.6% in
the intervention phase (P=0.09 and P<0.01). When considering tidal volume and PEEP as continuous
values, the mean tidal volume was significantly lower and the mean PEEP was significantly higher in
the intervention phase than in the control phase (P=0.02 and P<0.01 respectively, Figures 2A-B).
These differences lasted during the first 5 days of mechanical ventilation (data not recorded afterward).
The rates of enteral nutrition on day-1 and of input target reached on day-3 were significantly higher in
the intervention phase than in the control phase (P<0.01 for both comparisons). Probabilistic
antibiotherapy was conformed to the protocol in 79 (83.2%) episodes of HAP. The percentage of
patients extubated within the first 48 hours after all requirements were met (ventilatory weaning,
Glasgow Coma Scale 10 and cough) increased from 57.5% patients in the control phase to 68.9% in
the intervention phase (P=0.03). The percentage of patients in whom care complied with the whole set
of best practices increased from 6.0% in the control phase to 21.1% in the intervention phase (P<0.01).
Primary outcome: Duration of mechanical ventilation
The mean duration of mechanical ventilation was 14.9 ± 11.7 days in the control phase and 12.6 ±
10.3 days in the intervention phase (P=0.02). No secular time trends unrelated to the intervention
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under study was highlighted (see supplemental analysis). When considering death as a competitive
event (stratified log-rank test), the median duration of mechanical ventilation was 17 (9-25) days in the
control phase and 12 (7-19) days in the protocol-guided phase (P=0.02), with an hazard ratio (HR) for
weaning from the mechanical ventilation in the intervention phase of 1.28 (95% confidence interval
(95%CI), 1.04-1.57; P=0.02; Figure 3.A). In sub-group analysis, the benefit was consistent under all
conditions, and the test for interaction between phase and initial pathology subgroups was not
significant (P for interaction = 0.55; Figure 3.B). Using the Fine and Gray model with a time-
dependent effect, a cut-off was defined at 10 days. Before 10 days of mechanical ventilation, the HR
was 1.04 (95%CI, 0.89-1.21, P=0.64). After 10 days of mechanical ventilation, the HR was 1.28
(95%CI, 1.01-1.62, P=0.04). In order to account for potential confounding factors associated with a
before/after design, three sensitivity analyses were performed to assess the robustness of this result.
Using a cox multivariate proportional hazards model adjusted on variables unbalanced between the 2
phases (P<0.10, Table 1), the adjusted HR for being alive and free of mechanical ventilation was 1.40
(95%CI, 1.12-1.76, P<0.01) in the intervention phase. After propensity matching based on variables
potentially associated with the intervention phase (see Table 2), the HR was 1.34 (95%CI, 1.03-1.74,
P=0.02).
We then estimated the contribution of best practices to the probability of extubation (Table 4).
Only tidal volume 8 ml.kg-1 (HR 1.38, 95%CI 1.08-1.76; P<0.01) and PEEP > 3 cmH2O (HR 1.30,
95%CI 1.00-1.69; P=0.05) were associated with a reduction in the duration of mechanical ventilation.
Secondary outcomes
Secondary outcomes are provided in Table 5. The percentage of patients with HAP decreased
after bundle implementation. At day-90, both ventilator-free days and ICU-free days increased in the
intervention phase compared with the control phase. No significant difference in the mortality rate at
day-90 was apparent between the two phases.
Extubation-related complications
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In the control phase, 27 (9%) reintubations were required compared with 22 (13.8%) in the
intervention phase (P=0.11, Table 5). The rate of unplanned extubation decreased from 9.4%, to 4.5%
(P<0.01). The rate of tracheostomy was 10% in the control phase and 8.7% in the intervention phase
(P=0.62).
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Discussion
The present study shows for the first time that implementation of an evidence-based extubation
readiness bundle in brain-injured patients can reduce the duration of ventilator support. This bundle
can be mainly effective in patients with a duration of mechanical ventilation exceeding 10 days ,
corresponding to patients with a difficult or prolonged weaning (32). The rates of HAP and of
unplanned extubation were also lower in the intervention phase as compared with the control phase.
The reduction in mechanical ventilation support was well tolerated regarding mortality.
When caring for critically ill patients, standardized protocols have been shown to improve
outcomes in several conditions such as sedation (33), sepsis management (34) or surgical procedures
(35). In acute stroke units, the implementation of an evidence-based protocol to prevent extra-cerebral
complications has been shown to improve patient outcomes after discharge (36). We reported the
effectiveness of a bundle developed to reduce the duration of mechanical ventilation in brain-injured
patients.
Protective ventilation relies on the association of a low tidal volume with a positive end-
expiratory pressure. Lung protective ventilation was initially shown to reduce the duration of
mechanical ventilation in patients with acute respiratory distress syndrome (37). Few data are available
in brain-injured patients because they are most likely excluded from randomized clinical trials
evaluating such strategies. Thus, no consensus has been reached regarding protective ventilation in
neurologic critically ill patients (38). As a result, protective ventilation was poorly applied in
neurological patients in a recent large observational study (2) and the application of high tidal volume
is still recommended as a means to induce moderate hypocapnia (39). In the experimental setting,
brain injuries were shown to potentiate ventilator-induced lung injury (9) and a tidal volume higher
than 9 ml.kg-1 was associated with the subsequent development of acute lung injury and with brain
hypoxemia in patients with subarachnoid hemorrhage (8, 40). In a recent meta-analysis pooling studies
with relatively short durations of mechanical ventilation (mean duration: 6.9 hours) in patients without
ARDS, protective ventilation was associated with a decreased of ARDS/ALI rate and of mortality risk
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(41). In this meta-analysis, protective ventilation was associated with a low increase in capnia (from 38
to 41 mmHg) which could be damaging in brain-injured patients. However, the lung compliance of
these patients is frequently not altered and we assume that the prevention of hypercapnia could easily
be achieved in brain-injured patients by increasing the respiratory rate instead of increasing the tidal
volume. In the current study, low tidal volume and PEEP were the only interventions independently
associated with the probability of successful extubation. Since tidal volumes (> 10 ml/kg) were
associated with ARDS and death in stroke patients (42), interventions aiming to reduce the use of such
tidal volumes could be particularly relevant in brain-injured patients. Interestingly, the favorable
effects of protective ventilation on the duration of mechanical ventilation were consistent for all of the
neurological conditions studied, but the effects could have been more pronounced in stroke patients.
Critically ill patients frequently experience episodes of enteral feeding interruption, and
nutritional goals are frequently not reached, thereby requiring early nutritional support. Early enteral
nutrition remains a controversial issue mainly because of potential problems regarding tolerance and
risk of HAP. Nutrition guidelines recommend achieving only 65% of calorie goals in the first week
(43). Early enteral nutrition provided within the first 48 hours after ICU admission has not been shown
prospectively to alter mortality (44). However, we have previously reported that early enteral nutrition
was a protective factor regarding the risk of HAP in traumatic brain-injured patients (29). For these
reasons, we chose early initiation of enteral nutrition and to reach the targeted input in the first 5 days.
Consistent with two meta-analyses on early enteral nutrition in ICU (13, 45), the current management
bundle was associated with a decrease in HAP that may have contributed to the reduction in the
duration of ventilatory support.
Trauma and central nervous system diseases are recognized as major independent risk
factors for pneumonia in critically ill patients (46). In several randomized studies, HAP reached
up to 40-50% of brain-injured patients (47-49). This high percentage of infection can partially
be explained by the prolonged duration of mechanical ventilation in this population (1).
Moreover, a central nervous system injury-induced immune deficiency alters host response to
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pathogens and increases the rate of pneumonia in a neuro-ICU (50). Given the frequency and the
morbidity of HAP, optimization of antibiotherapy is a major objective when caring for brain-
injured patients. Indeed, delay in the administration of appropriate antibiotic therapy for HAP is
associated with worse outcomes in the ICU (14). Optimization of empirical antibiotic therapy
decreases the duration of mechanical ventilation in septic critically ill patients (51) and may
therefore reduce ventilator time for brain-injured patients. However, implementation of
international guidelines for antibiotherapy of HAP is controversial (16, 17), probably because it
is essential to consider local epidemiology (15) and patient conditions when choosing
probabilistic antibiotherapy (52). In the current study, adaptation of international guidelines to
local epidemiology was associated with a non-significant trend toward a decrease in
probabilistic antibiotherapy failure.
The decision to extubate is particularly challenging in comatose patients (53). On one hand,
extubation failure increases hospitalization duration and mortality in general ICU patients (54)
and on the other hand, delayed extubation is associated with unplanned extubation and with
altered outcomes of brain-injured patients (20). Thus, the prediction of successful extubation is
particularly important since up to 10% of neurological patients require re-intubation (55).
Interestingly, Coplin et al. suggested that prolonged intubation should be avoided when the only
concern is an impaired neurological status (20). Several studies have reported a low risk for
extubation failure in patients with a Glasgow Coma Scale between 8 and 10 provided that
patients are able to cough (19, 56). In a large interventional study, the rate of re-intubation
decreased when extubation was mandated as soon as the Glasgow Coma Scale was above 8 and
associated with cough (18). Using more liberal criteria, we currently report a decrease in the rate
of unplanned extubation. Since unplanned extubations are associated with duration of
hospitalization and death (57), this result may partially explain the beneficial effects of our
bundle. However, the decrease in unplanned extubation was approximately equal to the increase
in extubation failure, suggesting that the Glasgow Coma Scale could be a poor criterion for the
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18
prediction of extubation success. Finally, the overall rate of extubation-related complications
was not altered in the intervention phase compared with the control phase. This result argues for
the development of scores for early detection of brain-injured patients at risk of extubation
failure. Such a score should allow the early extubation of patients with a low risk of extubation
failure, without exposing some high-risk patients to post-extubation respiratory failure.
Several limitations should be noted here. First, this two-phased intervention study did not
make it possible to demonstrate causality. This design was chosen because it was not possible to
randomly assign the bundle in the same ICU without significant cross-contamination. Moreover,
before/after studies provide a good level of evidence (58), with an acceptable estimation of
intervention effect compared with randomized control trials (59, 60). However, a before/after
design may be confounded by secular trends and we cannot exclude that some care
improvements other than the bundles elements (such as management of sedation) participated in
the reduction in morbidity. We therefore performed a time series analysis that did not
demonstrate a secular time trends and did not conclude to a difference in the mean duration of
mechanical ventilation between the two periods. This result did not contradict our conclusion
based on individual analysis. Indeed, interrupted time-series methods lose power because data
are aggregated at the monthly level and moreover, the autoregressive error model cannot control
all of the variability in the number of patients per month. Second, even if the rate of
antibiotherapy failure was low in the intervention phase, the adaption of antibiotherapy to the
local epidemiology observed in the preceding years limits the generalizability of this specific
element. However, ATS/IDSA guidelines state that the initial empiric therapy for HAP is more
likely to be appropriate if a protocol for antibiotic selection is adapted to local patterns of
antibiotic resistance, with each ICU collecting this information and updating it on a regular basis
(28). Third, no intervention targeted an improvement in the management of sedation, though it is
a major determinant of the duration of mechanical ventilation. Moreover, the reported doses of
sedative drugs exceeded those frequently reported in studies evaluating scale-based sedation (61,
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19
62). However, in most trials evaluating sedation, hypnotics are titrated to achieve light sedation
(RASS scores between -2 and +1), when a heavy sedation is recommended for the prevention of
intracranial hypertension in brain-injured patients (27). Finally, similar doses of sedative drugs
were described in a recent meta-analysis reporting the sedation of brain-injured patients (63).
Fourth, overall bundle compliance ranged from 42.6% to 83.2% according the process-of-care
variables, which is similar to other before/after studies which reported ranges from 5% to 87%
(64). Some low rates of compliance have demonstrated that barriers for implementing bundles
remain important. However, these interventions were selected because they implied
multidisciplinary teamwork (nurses, clinicians, physiotherapists) which has been shown to
synergistically improve patient outcomes and health-care processes (65). Moreover, a group of
evidence-based treatments, instituted rapidly and together over a specific timeframe, is
frequently associated with better outcomes than when they are executed individually.
In conclusion, the implementation of a four-point extubation readiness bundle in brain-injured
patients, including a strategy for protective ventilation, early enteral nutrition, adaptation of
antibiotherapy to local epidemiology of HAP and a systematic approach to extubation was associated
with a reduction in the duration of mechanical ventilation and in the rate of associated complications.
The non-significant decrease in hospital mortality pleads for a large multi-center trial investigating the
effects of such a strategy.
Page 19 of 44 AJRCCM Articles in Press. Published on 08-August-2013 as 10.1164/rccm.201301-0116OC
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20
Acknowledgement Delphine Flattres Duchaussoy, Magali Aziza and nurses of participating ICUs for technical support. Conflict of interest
Authors have no related conflict of interest to disclose.
Previous presentation
Some of the results of this study have been previously reported in the form of an unpublished abstract (Société Française d’Anesthésie Réanimation annual meeting, Paris, France, Septembre 19-22, 2012).
Page 20 of 44 AJRCCM Articles in Press. Published on 08-August-2013 as 10.1164/rccm.201301-0116OC
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Table 1 – Evidence based weaning bundle Intervention
Lung protective ventilation 1. Tidal volume 2. PEEP 3. Respiratory rate
1. 6-8 ml.kg-1 of ideal body weight 2. > 3 cmH2O 3. Set to achieve normocapnia or optional moderate hypocapnia
Nutrition support 1. Day of initiation 2. Input target
1. Day-1 2. 25 kCal.kg-1.day-1 before Day-3
Probabilistic antibiotherapy for hospital acquired pneumonia*
1. Low risk of MDR bacteria 2. High risk of MDR bacteria
1. Amoxicillin - clavulanic acid (2 g x 3/day iv.) 2. Cefepime (2 g x 3/day iv.) + tobramycin (5-6 mg/kg/day iv. once a day)
Systematic approach to extubation 1. Ventilatory weaning
2. Tube removal
1. Early spontaneous breathing: tolerance of inspiratory support < 10 cm H2O or spontaneous breathing and Fi0240% for 30 min. 2. Glasgow Coma Scale 10 and cough (spontaneous or caused)
* Adapted to local epidemiology of pathogen involved in hospital-acquired pneumonia: low risk of
MDR was defined as pneumonia before day-10 and previous antibiotherapy shorter than 48 hours; High risk of MDR bacteria was considered until day-10 or after previous antibiotherapy longer than 48 hours.
MDR: Multiple Drug Resistant, PEEP= positive end expiratory pressure. The management of the sedation was standardized and no formal modification was performed between the two periods of the study.
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Table 2 - Population characteristics
Whole cohort Propensity-matched population
Control phase
Intervention phase
P-value Control phase
Intervention phase
P-value
Number of patients 299 200 153 153 Age, years, mean (SD) 50 (19) 52 (17) 0.15 52 (17) 52 (18) 0.92
Male, N (%) 188 (62.9) 124 (62.0) 0.84 91 (59.5) 96 (62.8) 0.56
Weight, kg, mean (SD) 72.2 (15.2) 73.8 (17.4) 0.30 71 (15) 73.10 (17) 0.27
Height, cm, mean (SD) 168 (9) 168 (10) 0.54 167 (7) 168 (10) 0.24
Medical history, N (%) Cardiac failure Respiratory failure Diabetes mellitus Smoking
100 (33.4) 36 (12.0) 23 (7.7)
74 (24.8)
30 (15.0) 25 (12.5) 24 (12.0) 47 (23.5)
<0.01 0.88 0.11 0.73
35 (22.9) 20 (13.1)
9 (5.9) 38 (24.8)
25 (16.3) 14 (9.2)
16 (10.5) 37 (24.2)
0.15 0.28 0.14 0.89
Severity Scores, mean (SD) SAPS II Glasgow coma scale
38 (13)
8 (4)
41 (13) 9 (4)
0.06 0.05
40.1 (13.9)
7 (3)
39.7 (11.9)
7 (4)
0.78
0.07
Initial pathology, N (%) Traumatic brain injury Sub-arachnoid hemorrhage Stroke Other (cancer, meningitis)
147 (49.3) 92 (30.9) 56 (18.8)
3 (1.0)
78 (39.0) 73 (36.5) 32 (16.0) 17 (8.5)
<0.01
67 (43.8) 61 (39.9) 23 (15.0)
2 (1.3)
72 (47.1) 56 (36.6) 23 (15.0)
2 (1.3)
0.71
Neurological status on ICU admission, N (%) Cerebellum injury Extra-ventricular drainage for hydrocephalus Decompressive craniectomy
33 (11.0) 72 (24.2)
14 (4.7)
18 (9.0)
70 (35.0)
19 (9.5)
0.46 0.01
0.04
17 (11.1) 53 (34.6)
10 (6.5)
13 (8.5)
50 (32.7)
10 (6.5)
0.44 0.71
1
ICU: intensive care unit, SAPS II: simplified acute physiology score.
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Table 3 - Measures of compliance
Control phase Intervention phase P value
Number of patients 299 200 Lung protective ventilation on day 1
1. Tidal volume, N (%) 0.02
<6 ml.kg-1 of ideal body weight 7 (2.5) 7 (3.9) 6-8 ml.kg-1 of ideal body weight 87 (30.9) 70 (38.7) 8-10 ml.kg-1 of ideal body weight 136 (48.2) 88 (48.6) > 10 ml.kg-1 of ideal body weight 52 (18.4) 16 (8.8)
Tidal volume, mean (SD) 8.9 (1.9) 8.1 (1.4) <0.01
2. PEEP, N (%) <0.01
0 cmH2O 90 (30.6) 11 (5.6) 1-3 cmH2O 93 (31.6) 56 (28.3) > 3 cmH2O 111 (37.8) 131 (66.2)
PEEP, mean (SD) 2.7 (2.1) 4.2 (1.6) <0.01
Nutrition support
1. Initiation <0.01
Day 1, N (%) 80 (33.2) 88 (56.1) Day 2, N (%) 161 (66.8) 65 (43.9) Day of initiation, mean (SD) 2.6 (1.8) 1.5 (1.2) <0.01
2. Time to achieve an input of 25 kCal.kg-1.day-1 <0.01
Day 3 49 (25.1) 88 (65.7) Days 4-5 64 (32.8) 17 (12.7) Day 6 82 (42.1) 29 (21.6) Mean time (SD) 6.1 (3.9) 3.7 (3.2) <0.01
3. Total enteral intake in the first 7 days (kCal), mean (SD) 4300 (2650) 8300 (12300) 0.01
Glasgow coma scale on extubation day /
Mean (SD) 11 (2) 11 (3) 0.39
Glasgow 10, N (%) 38 (17.9) 58 (39.2) <0.01
Glasgow 11-12, N (%) 129 (60.9) 48 (32.4)
Glasgow 13-15, N (%) 45 (21.2) 42 (28.4)
Compliance with bundle elements, N (%)
1) Ventilatory setting Tidal volume 8 ml.kg-1 on day 1 PEEP > 3 cm H2O in day 1
94 (33.6) 111 (37.8)
77 (42.6)
131 (66.2)
0.09
< 0.01
2) Nutrition support Enteral nutrition initiated on Day-1 Target of enteral support reached Day-3
80 (33.2) 49 (25.1)
88 (56.1) 88 (65.7)
< 0.01 < 0.01
3) Antibiotic therapy for HAP NA 79 (83.2) NA
4) Systematic approach to extubation (undelayed extubation) (&)
122 (57.5) 102 (68.9) 0.03
Overall bundle compliance 18 (6.0) 42 (21.1) <0.01
Assessed in 95 HAP Assessed in 212 patients in the control phase and 148 patients in the intervention phase (not applicable for death prior to extubation or tracheotomy); (&) The compliance with the systematic approach to extubation (undelayed extubation) was considered when tube removal was performed within 48 hours after all requirements are met (ventilatory weaning, Glasgow coma scale 10 and cough); (&&) The compliance was considered when bundle interventions were not applicable: in patients without HAP (for the antibiotherapy protocol); in dead or tracheotomized patients (for the systematic approach to extubation). HAP: hospital acquired pneumonia, PEEP: positive end-expiratory pressure, NA: not applicable
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Table 4 – Association of best practice with probability of weaning from mechanical ventilation
Risk factors Hazard Ratio [95 % CI] P value
Tidal volume 8 ml.kg-1 1.38 [ 1.08; 1.76] <0.01
PEEP > 3 cm H2O 1.30 [1.00; 1.69] 0.05
Early enteral nutrition 1.18 [0.92; 1.51] 0.19
Undelayed extubation (&) 1.07 [0.82; 1.40] 0.63
Compliance with all bundle elements 1.49 [0.97 ; 2.27] 0.07
PEEP: positive end-expiratory pressure. The association of the bundle elements with the duration of mechanical was assessed with an univariate analysis. (&) Undelayed extubation was considered when tube removal was performed within 48 hours after all requirements were met (inspiratory support < 10 cm H2O, Glasgow Coma Scale 10 and cough)
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Table 5 - Outcomes
Control phase Intervention phase p-value
Number of patients 299 200
Duration of mechanical ventilation, days, mean (SD)* Duration of mechanical ventilation, days, median (IQR)** Ventilator-free days at day 28, mean (SD) Ventilator-free days at day 90, mean (SD)
14.9 (11.7) 17 (9-25) 3.7 (5.3) 54 (33)
12.6 (10.3) 12 (8-19) 5.5 (6.5) 64 (29)
0.02 0.02 0.01 0.01
Extubation management, N (%) Overall extubation-related complication (&) Extubation failure Unplanned extubation
Tracheotomy
55 (18.4) 27 (9.0) 28 (9.4)
29 (10.0)
36 (18)
27 (13.5) 9 (4.5)
17 (8.7)
0.91 0.11
<0.01 0.62
Hospital acquired pneumonia, N (%) Probabilistic antibiotherapy failure, N (%)
172 (57.5) 14 (27.5)
95 (47.5) 8 (8.4)
0.03 0.15
Acute respiratory distress syndrome, N (%) 19 (6) 7 (3.5) 0.16
ICU length of stay, days, median (IQR)* ICU-free days at day 90, mean (SD)
20 (11-32) 50 (33)
18 (12-29) 57 (29)
0.48 0.01
Death, N (%) in ICU at day 90
75 (25.1) 85 (28.4)
45 (22.5) 47 (23.5)
0.51 0.22
ICU: intensive care unit * gross analysis (Student’s t-test), ** calculated from stratified log-rank test with consideration of death, (&) defined as extubation failure and/or unplanned extubation.
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Figure 1 - Flow chart MV: mechanical ventilation, RCT: randomized clinical trial
Figure 2 - Evolution of tidal volume and of positive end-expiratory pressure during the first 5
days of mechanical ventilation
Tidal volume and positive end-expiratory pressure (PEEP) were recorded at 8:00 am from days 1 to 5.
IBW: ideal body weight. Data represent mean ± SD. ** p<0.01 versus control phase
Figure 3 - Kaplan-Meier curves for mechanical ventilation
(A) The hazard ratio for weaning from the mechanical ventilation was 1.28 (95%CI, 1.04-1.57;
p=0.02) using a stratified log-rank analysis, 1.40 (95%CI, 1.12-1.76; p<0.01) using a multivariate cox
model and 1.34 (95%CI, 1.03-1.74, p=0.02) after matching with a propensity analysis. Multivariate
cox model was adjusted on cardiac failure, simplified acute physiology score II, Glasgow Coma Scale,
initial pathology, extra-ventricular drainage for hydrocephalus and decompressive craniectomy.
(B) Hazard ratio for weaning from mechanical ventilation in traumatic brain injured patients,
subarachnoid hemorrhage patients, stroke patients and other conditions.
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