Predicting Resting Energy Expenditure in Critically Ill Patients by Measuring Lean Body Mass by US

The study aims to correlate Lean Body Mass (LBM) Evaluated by Musculoskeletal Ultrasound with Resting Energy Expenditure (REE) measured by Indirect Calorimetry and to generate a predictive equation of REE based on LBM, in addition to identifying other factors that may affect REE such as age, gender, and severity scores.

Caloric needs in critically-ill patients fluctuate significantly over the course of the disease which might expose patients to either malnutrition or overfeeding.Malnutrition is associated with deterioration of lean body mass (LBM), poor wound healing, increased risk of nosocomial infection, and weakened respiratory muscles. On the other hand overfeeding in medically compromised patients can promote lipogenesis, hyperglycemia, and exacerbation of respiratory failure. Many factors may affect the resting energy expenditure (REE) through manipulation of oxygen consumption (VO2). One of the strongest determinants of REE is the LBM. A measurement of muscle mass and changes in muscle mass could thus provide an index of LBM in critically ill patients. At present, computerized tomography, magnetic resonance imaging and dual-energy X-ray absorptiometry (DXA) are widely used as reference methods for evaluating LBM in vivo. However, these methods are impractical in critically ill patients. More practically, ultrasound scanning is a simple, portable, safe, and a low-patient burden technique. Several studies found that the use of ultrasound can be a good estimate to LBM. Indirect calorimetry remains the accepted standard for determining the REE in the critically ill. Indirect calorimetry measures oxygen consumption(VO2) and carbon dioxide excretion (VCO2 ) (both in mL/min), which are used to calculate the respiratory quotient and the resting energy expenditure. Although, the measured LBM has been shown as an important determinant of REE, there was no previous study tested the relationship between estimated LBM by ultrasound-based muscle thickness measurement and REE.