Measured resting energy expenditure via indirect calorimetry of critically ill patients: A comparison with predictive equations.

BACKGROUND AND OBJECTIVES: Assessing the resting energy expenditure (REE) of critically ill patients is essential for individual nutritional programs. We hypothesized that different evaluated ways for REE can be compared, and REE may be associated with disease severity and clinical prognosis. This study aimed to compare the differences between measured resting energy expenditure (m-REE) by indirect calorimetry and values estimated by predictive equations in critically ill patients, and to explore the correlations between REE and inflammatory status or clinical prognosis. METHODS: The patients in intensive care unit (ICU) were categorized based on APACHE II scores. REE was assessed using indirect calorimetry (m-REE) and compared with estimates from multiple equations including Harris-Benedict (H-B), adjusted H-B, Mifflin-St Jeor, WHO/FAO/UNU, Owen, Henry, and Weight-kilogram. Serum procalcitonin (PCT) and high-sensitivity C-reactive protein (hsCRP) were measured, and ICU staying days were recorded for correlation analysis. RESULTS: Results showed that m-REE was significantly higher than most equation-predicted values (p <0.01) when APACHE II ≥15, while no significant differences were found with adjusted H-B, Owen, and Weight-kilogram equation. Additionally, m-REE was positively correlated with hsCRP, PCT, ICU staying days and hospital length (all p <0.05). When APACHE II <15, m-REE was generally lower than predicted values. CONCLUSION: The findings suggest that in the absence of indirect calorimetry, the adjusted H-B, Owen, and Weight-kilogram equations may be applicable for patients with APACHE II ≥15. Furthermore, m-REE may serve as a potential predictor of inflammatory status and clinical prognosis in critically ill patients.