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

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Abstract
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) (R2 = 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.

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