Rupinder Dhaliwal, RDClinical Evaluation Research Unit

Kingston General Hospital

Outline

incidence of underfeeding in the ICU

nutritional screening tools available for use in ICU

familiar with the novel approach used to assess the nutritional risk of critically ill patients and implications of this risk assessment for clinical practice

Does underfeeding in ICUs

exist?

Mean intake 56% International Nutrition Survey, n =211 ICUs

Purpose of Nutrition Screening

Predict the probability of a better or worse

outcome due to nutrition

SCREENINGMalnutrition

goes undetected

Guidelines ASPEN/SCCM 2009

Screening leads to Nutritional Care

Hospitals & healthcare organizations should have a policy and a specific set of protocols for identifying patients at nutritional risk. The following process is suggested:

Screening Assessment Monitoring & Outcome Communication Audit

Kondrup et al. Clin Nutr 22(4):415-421;2003.

• Underfeeding does occur in ICUs• Malnutrition: 30% ICU patients (SGA)

• Existing tools for nutrition screening

Malnutrition Universal Screening Tool (MUST)

Nutritional Risk Screening (NRS 2002)Nutritional Risk Screening (NRS 2002)Mini Nutritional Assessment (MNA)

Short Nutritional Assessment Questionnaire (SNAQ)Malnutrition Screening Tool (MST)

Subjective Global Assessment (SGA)Subjective Global Assessment (SGA)

Anthony NCP 2008

All ICU patients treated the same

Subjective Global Assessment

When training provided in advance, SGA can produce reliable estimates of malnutrition

Note rates of missing data

(7-34%)

n = 119, > 65 yrs, mostly medical patients, not all ICU

no difference between well-nourished and malnourished patients with regard to the serum protein values on admission, LOS, and mortality rate

n = 124, mostly surgical patients100% data available for SGASGA predicted mortality

Quantify Lean Muscle Mass: CT Scan

• Body composition tools:– BIA, skin fold: low precision , DEXA: not specific, $$

• CTs becoming common research tool – Measures tissue mass and changes over time

50 geriatric trauma pts

prevalence of sarcopenia (low muscularity) on admission =78%

Despite the majority being overweight!

M. Mourtzakis et al

ICU patients are not all created equal…should we expect the impact of nutrition

therapy to be the same across all patients?

Malnutrition should be diagnosed on the basis of etiology…. inflammation acute vs

chronic

How do we figure out who will benefit the most from Nutrition

Therapy?

In the ICU…..

Caloric debt/underfeedingMalnutrition exists 34% or >Historical nutrition data n/a Not all patients equalConsider

InflammationAcute diseasesChronic diseases

Nutrition Statusmicronutrient levels - immune markers - muscle mass

Starvation

Acute-Reduced po intake

-pre ICU hospital stay

Chronic-Recent weight loss

-BMI?

InflammationAcute

-IL-6-CRP-PCT

Chronic-Comorbid illness

A Conceptual Model for Nutrition Risk Assessment in the Critically ill

Objective

Develop a score using the variables in the model to

Quantify the risk of ICU pts developing adverse events that may be modified by nutrition

The Development of the NUTrition Risk in the Critically ill Score (NUTRIC Score)

• When adjusting for age, APACHE II, and SOFA, what effect of nutritional risk factors on clinical outcomes?

• Multi institutional data base of 598 patients (3 ICUs)

• Historical po intake and weight loss only available in 171 patients

• Outcome: 28 day vent-free days and mortality

What are the nutritional risk factors associated with mortality?

(validation of our candidate variables)Non-survivors by day 28

(n=138) Survivors by day 28

(n=460) p values

Age 71.7 [60.8 to 77.2] 61.7 [49.7 to 71.5] <.001

Baseline APACHE II score 26.0 [21.0 to 31.0] 20.0 [15.0 to 25.0] <.001

Baseline SOFA 9.0 [6.0 to 11.0] 6.0 [4.0 to 8.5] <.001

# of days in hospital prior to ICU admission 0.9 [0.1 to 4.5] 0.3 [0.0 to 2.2] <.001

Baseline Body Mass Index 26.0 [22.6 to 29.9] 26.8 [23.4 to 31.5] 0.13

Body Mass Index 0.66

<20 6 ( 4.3%) 25 ( 5.4%)≥20 122 ( 88.4%) 414 ( 90.0%)

# of co-morbidities at baseline 3.0 [2.0 to 4.0] 3.0 [1.0 to 4.0] <0.001

Co-morbidity <0.001

Patients with 0-1 co-morbidity 20 (14.5%) 140 (30.5%)Patients with 2 or more co-morbidities 118 (85.5%) 319 (69.5%)

C-reactive protein¶ 135.0 [73.0 to 214.0] 108.0 [59.0 to 192.0] 0.07

Procalcitionin¶ 4.1 [1.2 to 21.3] 1.0 [0.3 to 5.1] <.001

Interleukin-6¶ 158.4 [39.2 to 1034.4] 72.0 [30.2 to 189.9] <.001

171 patients had data of recent oral intake and weight loss Non-survivors by day 28

(n=32) Survivors by day 28

(n=139) p values

% Oral intake (food) in the week prior to enrolment 4.0[ 1.0 to 70.0] 50.0[ 1.0 to 100.0] 0.10

% of weight loss in the last 3 month 0.0[ 0.0 to 2.5] 0.0[ 0.0 to 0.0] 0.06

Variable

Spearman correlation with VFD within 28

days

p valuesNumber of

observations

Age -0.1891 <.0001 598

Baseline APACHE II score -0.3914 <.0001 598

Baseline SOFA -0.3857 <.0001 594

% Oral intake (food) in the week prior to enrollment 0.1676 0.0234 183

number of days in hospital prior to ICU admission -0.1387 0.0007 598

% of weight loss in the last 3 month -0.1828 0.0130 184

Baseline BMI 0.0581 0.1671 567

# of co-morbidities at baseline -0.0832 0.0420 598

Baseline CRP -0.1539 0.0002 589

Baseline Procalcitionin -0.3189 <.0001 582

Baseline IL-6 -0.2908 <.0001 581

What are the nutritional risk factors associated with Vent Free days?

(validation of our candidate variables)

BMI: no effect on Vent free days

The Development of the NUTrition Risk in the Critically ill Score (NUTRIC Score)

• % oral intake in the week prior dichotomized into

– patients who reported less than 100%

– all other patients

• Weight loss was dichotomized as

– patients who reported any weight loss

– all other patients

• BMI was dichotomized as

– <20

– all others

• Comorbidities was left as integer values range 0-5

The Development of the NUTrition Risk in the Critically ill Score (NUTRIC Score)

All other variables (Age, APACHE 2, SOFA, Comorbidities, LOS pre ICU, IL 6)

were categorized into five equal sized groups (quintiles)

Exact quintiles and logistic parameters for age

Exact Quintile Parameter Points

19.3-48.8 referent 0

48.9-59.7 0.780 1

59.7-67.4 0.949 1

67.5-75.3 1.272 1

75.4-89.4 1.907 2

Logistic regression analyses

Each quintile compared to lowest risk category

Rounded off to the nearest whole # to provide points for the scoring system

The Development of the NUTrition Risk in the Critically ill Score (NUTRIC Score)

Variable Range PointsAge <50 0

50-<75 1>=75 2

APACHE II <15 015-<20 120-28 2>=28 3

SOFA <6 06-<10 1>=10 2

# Comorbidities 0-1 02+ 1

Days from hospital to ICU admit 0-<1 01+ 1

IL6 0-<400 0400+ 1

AUC 0.783Gen R-Squared 0.169Gen Max-rescaled R-Squared  0.256

BMI, CRP, PCT, weight loss, and oral intake were excluded because they were not significantly associated with mortality or their inclusion did not improve the fit of the final model.

The Validation of the NUTrition Risk in the Critically ill Score (NUTRIC Score)

0 1 2 3 4 5 6 7 8 9 10

Nutrition Risk Score

Mo

rta

lity

Ra

te (

%)

02

04

06

08

0

ObservedModel-based

n=12 n=33 n=55 n=75 n=90 n=114 n=82 n=72 n=46 n=17 n=2

Statistical modeling

higher score = higher

mortality

The Validation of the NUTrition Risk in the Critically ill Score (NUTRIC Score)

0 1 2 3 4 5 6 7 8 9 10

Nutrition Risk Score

Da

ys o

n M

ech

an

ica

l Ve

ntil

ato

r

02

46

81

01

21

4 ObservedModel-based

n=12 n=33 n=55 n=75 n=90 n=114 n=82 n=72 n=46 n=17 n=2

high score = longer

ventilation

The Validation of the NUTrition Risk in the Critically ill Score (NUTRIC Score)

Can NUTRIC score modify the association between nutritional adequacy and mortality? (n=211)

P value for the interaction=0.01

0 50 100 150

0.0

0.2

0.4

0.6

0.8

1.0

Nutrition Adequacy Levles (%)

28

Da

y M

ort

alit

y

NUTRIC 0-3NUTRIC 4-6NUTRIC 7-8NUTRIC 9-10

P value for the interaction=0.01

Highest score pts, low nutrition is associated with higher mortality!!

Lowest score pts, more nutrition

may be associated with

higher mortality ?

Summarize: NUTRIC Score• NUTRIC Score (0-10) based on

– Age– APACHE II– SOFA– # comorbidities– Days in hospital pre ICU– IL 6

• High NUTRIC Score associated worse outcomes (mortality, ventilation)

• High NUTRIC Score benefit the most from nutrition• Low NUTRIC Score : harmful?

Applications of NUTRIC Score

• Help determine which patients will benefit more from nutrition– Supplemental PN– Aggressive feeding– Small bowel feeding

• Design & interpretation of future studies– Negative studies, non high risk, heterogenous patients

Limitations

• Applies only to macronutrients• Does not apply to pharmaconutrients• Nutritional history is suboptimal• Requires IL-6

Conclusion

• Iatrogenic underfeeding in ICUs exist• Nutrition Screening/audits* detect underfeeding• Existing Screening tools not helpful in ICU• Not all ICU patients are the same in terms of ‘risk’• NUTRIC Score is one way to quantify that risk and can

be used in your ICU• Further refinement of this tool will ensure that the right

patient gets nutrition

Bedside nutrition tool

Thanks

Dr. Daren HeylandXuran JiangAndrew Day