CI: Body Weight and Outcomes: Mixed ICU Patients (2007)

Citation:

Garrouste-Orgeas M, Troche G, Azoulay E, Caubel A, de Lassence A, Cheval C, Montesino L, Thuong M, Vincent F, Cohen Y, Timsit JF. Body mass index. An additional prognostic factor in ICU patients. Intensive Care Med. 2004 Mar;30(3):437-43.

PubMed ID: 14767583
 
Study Design:
Prospective Cohort Study
Class:
B - Click here for explanation of classification scheme.
Quality Rating:
Positive POSITIVE: See Quality Criteria Checklist below.
Research Purpose:
Authors conducted a prospective multicenter study to examine the association between BMI and mortality in a large prospective cohort of patients from six ICUs in France. They hypothesized that BMI may add prognostic informaiton for use in predicting mortality.
Inclusion Criteria:
All patients who were older than 18 years of age and had an ICU stay of at least 48 h were included. Patients were studied over a 2 year period in 6 ICUs in France. 
Exclusion Criteria:

Subjects excluded were those < 18 yeard of age and/or those with less than a 48 hour stay in the ICU.

Description of Study Protocol:

Recruitment Over a 2 year period in 6 ICUs in France all patients who were older than 18 yeard of age and had an ICU stay of at least 48 h were recruited.

 

Design Prospective multicenter cohort study

 

Blinding used (not applicable)

Intervention (not applicable)

Statistical Analysis Categorical variables were compared using the Fisher exact test and continuous variables using the Wilcoxon rank sum test for unpaired data or the Kruskal-Wallis test. Multivariate analysis was performed using stepwise forward logistic regression. Variables significantly associated with hospital mortality in the univariate analysis and variables that were not balanced among BMI categories were first introduced into the model.  Odds ratio and confidence intervals were calculated.

 

Data Collection Summary:

Timing of Measurements Measurements were recorded prospectively beginning with admission to ICU. Data were collected on each calendar day. Day 1 defined as the interval from the time of admission to 8 am on the next day, all other days were calendar from 8 am to 8 am. 

Dependent Variables

  • Duration of ICU stay
  • Acute care hospital stay
  • Vital status at ICU
  • hospital discharge
  • Organ sysfunction & severity scores using the Simplified Acute Physiologic Score (SAPS II)
  • Logistic organ dysfunction score (LOD Score)
  • Sepsis-related organ failure assessment (SOFA Score)
  • Intensity of care provided in ICU using Omega score- comprises 47 diagnostic and therapeutic items weighted from 0 to 10 points according to corresponding work load.  The total omega score is the sum of the points accumulated during the ICU stay.
  • Hospital Mortality
  • Standardized Mortality ratio

Independent Variables

Body Mass Index (BMI) weight in kilograms divided by the square of the height in meters, categorized using World Health Organization cut-off points, as follows: normal 18.5-24.9,; grade 1 overweight, 25-29.9; grade 2 overweight, 30-39.9; grade 3 overweight > 40; grades 2 & 3 were combined because of few subjects in grade 3; authors added fifth category with BMI values lower than 18.5.

Control Variables

 

Description of Actual Data Sample:

Initial N: 1,698 (1067 male, 631 female)

Attrition (final N): 1,698

Age: mean age by BMI category <18.5, 62, 18.5-29.9, 65; 25-29.9, 69; >30, 65

Ethnicity: not given

Other relevant demographics: none given

Anthropometrics weights were significantly different for four BMI groups (p=0.0001); height was significantly different for BMI groups (p=0.0002

Location: 6 ICUs in France, all situated in the Paris metropolis in university hosptials, two were medical, two surgical, two were medical-surgical ICUs.

 

Summary of Results:

Univariate Analysis of Variables

Variables

BMI < 18.5

n=189

BMI 18.5-24.9

n=806

BMI 25-29.9

n=476)

BMI > 30

n=227

p value
SAPS II at admission, mean (range) 41 (29-59) 38 (28-51) 39 (29-53) 39 (29-53) 0.32
ICU Mortality, n (%) 54 (28.5%) 181 (22.4%) 92 (19.3%) 41 (18%) 0.03
Hospital Mortality, n (%) 83 (43.9% 257 (31.8%) 135 (29.9%) 57 (25.1%) 0.03

Independent Predictors of Mortality by Logistic Regression Analysis

Independent Variable OR (95% CI) P Value
BMI 18.5-24.9 1  
BMI < 18.5 1.63 (1.11-2.39) 0.01
BMI 25-29.9 0.75 (0.56-1.004) 0.053
BMI > 30 0.60 (0.40-0.88) 0.01

 

Author Conclusion:
A low BMI (< 18.5) is associated with higher mortality. A BMI > 25 is associated with lower mortality. Studies should be done to determine whether or not BMI should be added to scores for predicting mortality.
Funding Source:
Reviewer Comments:
This prospective multicenter cohort study supplied information on BMI as a prognostic factor in ICU patients.  Authors reported that weight and height were measured at admission in sedated patients and estimated in others.  Also in sedated patients the body length was measured with a tape measure on admission.  Accuracy was not tested.  The number of subjects whose weight was estimated was not given.
Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) Yes
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) Yes
 
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? Yes
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? Yes
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? Yes
3. Were study groups comparable? Yes
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) Yes
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? Yes
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) N/A
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? Yes
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) N/A
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? N/A
4. Was method of handling withdrawals described? N/A
  4.1. Were follow-up methods described and the same for all groups? N/A
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) N/A
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? N/A
  4.4. Were reasons for withdrawals similar across groups? N/A
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? N/A
5. Was blinding used to prevent introduction of bias? Yes
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? N/A
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) Yes
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? Yes
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? N/A
  5.5. In diagnostic study, were test results blinded to patient history and other test results? N/A
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? Yes
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? N/A
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? Yes
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? Yes
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? N/A
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? N/A
  6.6. Were extra or unplanned treatments described? N/A
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? Yes
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? Yes
  7.1. Were primary and secondary endpoints described and relevant to the question? Yes
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? Yes
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? Yes
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? Yes
  7.7. Were the measurements conducted consistently across groups? Yes
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? N/A
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? Yes
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? Yes
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? Yes
10. Is bias due to study's funding or sponsorship unlikely? Yes
  10.1. Were sources of funding and investigators' affiliations described? Yes
  10.2. Was the study free from apparent conflict of interest? Yes