The Novel Use of Point-of-Care Ultrasound to Predict Resting Energy Expenditure in Critically Ill Patients.

Mukhtar, A., M. AbdelGhany, A. Hasanin, W. Hamimy, A. Abougabal, H. Nasser, A. Elsayed, and E. Ayman, "The Novel Use of Point-of-Care Ultrasound to Predict Resting Energy Expenditure in Critically Ill Patients.", Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine, vol. 40, issue 8, pp. 1581-1589, 2021.


OBJECTIVES: Accurate estimation of a critically ill patient's caloric requirements is essential for a proper nutritional plan. This study aimed to evaluate the use of point-of-care ultrasound (US) to predict the resting energy expenditure (REE) in critically ill patients.

METHODS: In 69 critically ill patients, we measured the REE using indirect calorimetry (REE_IC), muscle layer thicknesses (MLTs), and cardiac output (CO). Muscle thickness was measured at the biceps and the quadriceps muscles. Patients were randomly split into a model development group (n = 46) and a cross-validation group (n = 23). In the model development group, a multiple regression analysis was applied to generate REE using US (REE_US) values. In the cross-validation group, REE was calculated by the REE_US and the resting energy expenditure using the Harris-Benedict equation (REE_HB), and both were compared to the REE_IC.

RESULTS: In the model development group, the REE_US was predicted by the following formula: predicted REE_US (kcal/d) = 206 + 173.5 × CO (L/min) + 137 × MLT (cm) - 230 × (women = 1; men = 0) (R  = 0.8; P < .0001). In the cross-validated group, the REE_IC and REE_US values were comparable (mean difference, -66 [-3.3%] kcal/d; P = .14). However, the difference between the mean REE_IC and the mean REE_HB was 455.8 (26%) kcal/d (P < .001). According to a Bland-Altman analysis, the REE_US agreed well with the REE_IC, whereas the REE_HB did not.

CONCLUSIONS: Resting energy expenditure could be estimated from US measurements of MLTs and CO. Our point-of-care US model explains 80% of the change in the REE in critically ill patients.