The effect of age and body mass index on energy expenditure of critically ill medical patients

Abstract

Background Data on the influence of age and body mass index (BMI) on energy metabolism of the critically ill are heterogeneous. Due to the increasingly aging critically ill population, investigation on age-and BMI-specific energy metabolism is relevant. Methods A total of 394 indirect calorimetry measurements were conducted on 348 critically ill adult medical patients, including 46 repeat measurements after 3.6 ± 4.3 days. Measured resting energy expenditure (MREE) was compared for age groups, BMI, and gender. Predicted energy expenditure (PEE) using the Penn State, Swinamer, and Ireton-Jones equations and the ACCP recommendations was also compared with MREE. Results The patients were 65.6 ± 14.5 years old. Their mean Acute Physiology and Chronic Health Evaluation II score was 27.6 ± 7.8. Mean BMI was 27.8 ± 8.4 kg/m 2 , and 25.6% were obese. MREE adjusted for ideal body weight decreased with increasing age, while it increased with increasing BMI. Age, BMI, and gender are independent determinants of MREE after adjusting for clinical factors (R 2 = 0.34). All four prediction equations showed a proportional bias, with the Penn State equation performing acceptably. In 46 patients with repeat indirect calorimetry, there was no significant difference between the first and second MREE (p = 0.62). Conclusions Age, BMI, and gender are independent determinants of resting energy expenditure in critically ill adults. Variations between measured and predicted energy expenditure are considerable. Should prediction equations be used, their performance in the specific population should be taken into consideration. Repeat indirect calorimetry may not always be necessary. However, this may depend on the length of stay and the extent of stress.

Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements

“…In the present study, weight and age were the ‘static’ variables selected for use in the prediction models of both the acute and late phases. Older patients may have lower REEs partly because of age-associated changes in body composition and the relative size of fat-free mass (FFM) components [ 27 , 34 , 35 ]. Many studies have shown that body weight and FFM (the metabolizing mass of the body) correlate with REE [ 35 – 37 ].…”

“…Older patients may have lower REEs partly because of age-associated changes in body composition and the relative size of fat-free mass (FFM) components [ 27 , 34 , 35 ]. Many studies have shown that body weight and FFM (the metabolizing mass of the body) correlate with REE [ 35 – 37 ]. However, the relationship between REE and body weight is nonlinear at the extremes of body weight [ 22 , 27 , 38 ].…”

Resting Energy Expenditure in the Critically Ill and Healthy Elderly—A Retrospective Matched Cohort Study

“…Another study of 348 critically ill adult medical patients (mean age 65 years), comparing mREE to cREE with the Penn State, Swinamer, Ireton-Jones and ACCP equations, showed that age, BMI and gender were independent determinants of REE, with considerable variations between mREE and cREE [ 43 ]. Comparing interindividual mREE critically ill patients to healthy persons matched for age, gender and BMI, as identified in the study by Hölzel and coworkers, we further identified predictors that may be causally linked to the higher disease severity, i.e., maximum body temperature, respiratory rate and FiO 2 .…”

Indirect calorimetry: should it be part of routine care or only used in specific situations?

“…Over the course of ICU admission, this can result in substantial underfeeding or overfeeding. Data describing the accuracy and/or bias of predictive equations continues to be published in various ICU populations including surgical [ 9 , 10 ], trauma [ 11 , 12 ], medical [ 13 ] and mixed [ 14 , 15 ] critically ill patients, reinforcing the poor predictive value of equations. Unsurprisingly, the last few years have also seen an increase in the number of publications describing mREE in patients with SARS-CoV-2 infection [ 16 ▪ , 17 , 18 ▪ ].…”