Excess Body Weight Is Not Independently Associated with Outcome in Mechanically Ventilated Patients with Acute Lung Injury

Context Although obesity poses many health risks, clinicians have been uncertain whether excess body weight adversely affects the outcomes of severe illnesses such as acute lung injury requiring mechanical ventilation. Contribution Among patients in a trial of mechanical ventilation strategies, obese patients and lean patients had similar mortality and ventilation outcomes. Implications Physicians should not assume that intubated obese patients fare worse than those who are of normal weight. Whether excess body weight puts patients at risk for poor outcomes in other types of critical illness is a subject for future study. The Editors Sixty-four percent of U.S. adults are overweight or obese, and this trend is accelerating (1, 2). Despite the well-described chronic health consequences of excess weight (3), we know little about the effect of obesity on outcomes from acute illnesses, particularly those requiring admission to the intensive care unit. Obese patients have a greater prevalence of comorbid conditions that may affect outcome (3), and they experience physiologic changes (4, 5) that may impair their ability to compensate for the stresses of critical illness. Because of these findings, conventional wisdom holds that obesity increases mortality and morbidity for patients in the intensive care unit. However, an independent effect of obesity on outcome from critical illness has never been conclusively demonstrated. If, in fact, obese persons are at risk, investigators should determine the mechanism of this increased risk and target interventions to this group. Acute lung injury is an inflammatory pulmonary condition associated with a variety of initiating insults. Acute lung injury is a frequent cause of respiratory failure requiring mechanical ventilation and a common indication for admission to the intensive care unit. The reported mortality rate is 40% to 60% (6). We performed a secondary analysis of a randomized trial of ventilator management in patients with acute lung injury (7) to better describe the influence of excess body weight on the outcome of critical illness. In that trial, patients randomly assigned to low tidal volume had better outcomes than patients assigned to high tidal volume. The experimental protocols for this trial required measurement of height to determine assigned tidal volume. This measurement also allowed calculation of body mass index (BMI) for each patient, a variable not often recorded for critically ill patients. Some argue that larger tidal volumes are beneficial for obese patients requiring mechanical ventilation (8). This raises concern that patients with different BMIs may require different ventilator strategies. By evaluating the interaction between the assigned ventilator protocol and BMI, we were able to determine whether the beneficial effect of lower tidal volume extends to obese patients with acute lung injury. Methods Setting and Sample We examined data on patients who participated in the National Heart, Lung, and Blood Institute's multicenter, randomized trials of the Acute Respiratory Distress Syndrome Network (7, 9, 10). Of the 902 patients in these studies, the first 861 participated in a randomized trial of mechanical ventilation that compared lower tidal volume with higher tidal volume (6 mL/kg of predicted body weight vs. 12 mL/kg, respectively). In a factorial design, 2 other trials evaluated ketoconazole versus placebo (234 patients) or lisofylline versus placebo (194 patients). After the ventilator trial ended because it showed a significant benefit associated with lower tidal volumes, an additional 41 patients received lisofylline or placebo plus the lower tidal volume strategy. Neither lisofylline (9) nor ketoconazole (10) affected outcomes of acute lung injury. Details of these studies and inclusion and exclusion criteria are described elsewhere (7, 9, 10). In brief, patients were eligible if they required mechanical ventilation and met diagnostic criteria for acute lung injury. Patients with a weight-to-height ratio (kilograms divided by centimeters) of 1.0 or greater were excluded. Analysis was done on an intention-to-treat basis. Measures of Excess Body Weight We used BMI as a measure of the degree of excess body weight. We calculated BMI from data in enrollment documents by dividing the patient's body weight in kilograms by the square of his or her height in meters. Ventilator and Weaning Protocols The protocol for mechanical ventilator management is described elsewhere (7). The major difference between the two study groups was the selected tidal volume. Investigators calculated predicted body weight from the patient's height and sex and used this predicted weight to determine the initial tidal volume for each patient. In the group assigned to higher tidal volumes, the initial tidal volume was 12 mL/kg of predicted body weight. In the group treated with lower tidal volumes, the initial tidal volume was 6 mL/kg. Investigators performed a daily weaning screen on every patient in an attempt to standardize the process of liberation from mechanical ventilation. Outcome Measures The primary outcome measure was survival to 28 days after study enrollment. Secondary dependent variables included achievement of unassisted ventilation by day 28, survival to discharge to home or to 180 days (the duration of follow-up in the primary studies), and the number of ventilator-free days. Unassisted ventilation was defined as liberation from mechanical ventilation for 48 or more consecutive hours. The number of ventilator-free days is the number of days of unassisted ventilation from day 1 to day 28. Statistical Analysis We performed unadjusted analyses by comparing values for patients across the 3 BMI categories (normal vs. overweight vs. obese) for outcome variables of interest and for other predictors. Unadjusted associations between other predictors and the outcomes were also explored. We used a 2-sided Fisher exact test for dichotomous variables; a 2-sided likelihood ratio chi-square test for nondichotomous categorical variables; and a KruskalWallis test, analysis of variance, or Wilcoxon rank-sum test for continuous variables, as appropriate. We constructed correlation matrices to guide regression estimation. We used logistic regression for the dichotomous outcome variables and linear regression for the continuous outcome variables. To estimate the base regressions, we selected variables for inclusion on the basis of several considerations, including significant differences in unadjusted analyses and clinical relevance. Among variables with a correlation greater than 0.50, only 1 was considered for inclusion to minimize multicollinearity. Variables that were thought to be strongly clinically relevant to the outcome and those found to have a statistically significant unadjusted effect (P < 0.05) were ultimately included in the base model. Variables in addition to those in Table 1 that were evaluated for inclusion were study site, ethnicity, diagnosis of diabetes, peak glucose level within 24 hours of enrollment, nonpulmonary organ failures, use of vasopressors, fluid balance in the 24 hours before study entry, and pneumonia as primary cause of lung injury. Unless otherwise stated, variables reflected the patient's clinical state at the time of study enrollment. Table 1. Characteristics of the Sample After estimation of the base regressions, we forced the indicators of excess body weight into the model and determined their predictive values. We performed analyses in several different ways. We used the National Heart, Lung, and Blood Institute divisions of BMI to categorize patients as normal weight (BMI of 18.5 to 24.9 kg/m2), overweight (BMI of 25.0 to 29.9 kg/m2), or obese (BMI 30 kg/m2). To test any effect across BMI category, we used a categorical variable with 2 degrees of freedom in the regression. Because of concern that we would not be able to detect an effect that was nonincremental, we compared the overweight BMI group with the normal BMI group and the obese BMI group with the normal BMI group. To examine whether the efficacy of lower tidal volume ventilation varied by degree of excess body weight, we estimated the interaction effects between BMI group and assignment to the higher tidal volume protocol. Because the interaction effects between BMI category and treatment assignment were not significant (as tested by using a likelihood ratio test with 2 degrees of freedom), a main effects model was fit. This likelihood-ratio test was also used to test the significance of the 3-category BMI variable. To examine the patients with extreme excess body weight, patients were divided into 4 BMI categories (normal, overweight, obese [BMI of 30 to 39.9 kg/m2], and severely obese [BMI 40 kg/m2]). This categorical variable with 3 degrees of freedom was also tested in the regression. In addition to these analyses, we also used BMI as a continuous variable. Because critically ill patients often receive fluid resuscitation or diuresis, we recalculated BMI as adjusted for the net fluid balance for each patient over the 24 hours before study entry (fluid-adjusted BMI). Negative fluid balances were added to the patient's body weight and positive fluid balances were subtracted from his or her weight to calculate BMI. We substituted the median fluid balance for the patient's study site if the individual fluid balance was unavailable (51 records). We used a MantelHaenszel chi-square test for the ordinally categorical variables and a Wilcoxon rank-sum test for continuous variables. Pearson chi-square test produced results similar (P > 0.2) to those of the MantelHaenszel test. We used SAS software, version 8.02 (SAS Institute, Inc., Cary, North Carolina), for all analyses. A P value less than 0.05 was considered statistically significant. Protection of Human Subjects The institutional review boards of each participating center approved the primary studies. Patients or their sur