Predictive versus measured energy expenditure using limits-of-agreement analysis in hospitalized, obese patients

Background: Accuracy of predictive formulae is crucial for therapeutic plan ning because indirect calorimetry measurement is not always possible or cos t effective. Energy requirements are more difficult to predict in the acute ly ill obese patient compared with lean patients because of an increased re sting energy expenditure per lean body mass and a variable stress response to illness. Methods: A retrospective review of 726 patients identified 57 p atients (32 spontaneous breathing, S; 25 ventilator dependent, V) with body mass indexes of 30-50 kg/m(2). Limits-of-agreement analysis determined bia s (the mean difference between measured and predicted values) and precision (the standard deviation of the bias) to evaluate the accuracy of predictiv e formulae compared with measured resting energy expenditure (MREE) by a De ltatrac Metabolic Monitor. Predictive accuracy was determined within +/-10% MREE. The predictive formulae examined were: variations of the Harris-Bene dict equations using ideal, adjusted weights of 25% and 50% and actual weig hts with stress factors ranging from 1.0 to 1.5; the Ireton-Jones equation for obesity; the Ireton-Jones equations for hospitalized patients (S and V) ; and the ratio of 21 kcalories per kilogram actual weight. Results: The me an MREE was 21 kcal/kg actual weight. The adjusted Harris-Benedict average weight equation was optimal for predicting MREE for the combined S and V se ts (bias = 182 +/- 123; 67% +/- 10% MREE), as well as the S subset (bias = 159 +/- 112; 69% +/- 10% MREE). Conclusions: The Harris-Benedict equations using the average of actual and ideal weight and a stress factor of 1.3 mos t accurately predicted MREE in acutely ill, obese patients with BMIs of 30- 50 kg/m(2). Predictive formulae were least accurate for obese, ventilator-d ependent patients.