A comparison of predictive equations of energy expenditure and measured energy expenditure in critically ill patients

Abstract

Purpose: Multiple equations exist for predicting resting energy expenditure (REE). The accuracy of these for estimating energy requirements of critically ill patients is not clear, especially for obese patients. We sought to compare REE, calculated with published formulas, with measured REE in a cohort of mechanically ventilated subjects.

Materials and methods: We retrospectively identified all mechanically ventilated patients with measured body mass index who underwent indirect calorimetry in the intensive care unit. Limits of agreement and Pitman's test of difference in variance were performed to compare REE by equations with REE measured by indirect calorimetry.

Results: A total of 927 patients were identified, including 401 obese patients. There were bias and poor agreement between measured REE and REE predicted by the Harris-Benedict, Owen, American College of Chest Physicians, and Mifflin equations (P > .05). There was poor agreement between measured and predicted REE by the Ireton-Jones equation, stratifying by sex. Ireton-Jones was the only equation that was unbiased for men and those in weight categories 1 and 2. In all cases except Ireton-Jones, predictive equations underestimated measured REE.

Conclusion: None of these equations accurately estimated measured REE in this group of mechanically ventilated patients, most underestimating energy needs. Development of improved predictive equations for adequate assessment of energy needs is needed.

Conflict of interest statement

CONFLICT OF INTEREST

None of the authors have any person or financial support or involvement with organizations with financial interest in the subject matter. This work was funded by a COBRE grant (5P20RR01557), but this organization was not involved in study design, data analysis, manuscript preparation or submission.

Copyright © 2012 Elsevier Inc. All rights reserved.

Figures

Figure 1

Bland-Altman plot for all patients using Ireton-Jones equation compared to measured energy expenditure by indirect calorimetry. The x-axis shows the average REE by the two methods (kcal/day). The y-axis shows the difference in REE between the two methods (kcal/day). If the two methods of measurement had good agreement, the points should be centered on the “0” y-axis, regardless of the average REE. In this example, the lower the average REE, the more likely the predictive equation is to overestimate REE (negative difference), and the higher the average REE, the more likely the predictive equation is to underestimate the REE (positive difference on y-axis). The appearance of two distinct cohorts displays differences for men and women.