Predicting energy expenditure in sepsis: Harris-Benedict and Schofield equations versus the Weir derivation.

BACKGROUND Given the difficulties of using indirect calorimetry in many intensive care units, clinicians routinely employ predictive equations (the Harris-Benedict equation [HBE] and Schofield equation are commonly used) to estimate energy expenditure in critically ill patients. Some extrapolate CO(2) production (V CO(2)) and O(2) consumption (V O(2)) by the Weir derivation to estimate energy expenditure. These derivative methods have not been compared with predictive equations. OBJECTIVE To compare prediction of energy expenditure by the HBE and Schofield equation with energy expenditure as estimated by the Weir derivation in a cohort of critically ill patients. METHODS Between June 2009 and May 2010, we conducted a prospective single-centre study of 60 mechanically ventilated patients with sepsis of varying severity in the ICU of a metropolitan hospital. Three groups of patients were compared: those with systemic inflammatory response syndrome (SIRS), severe sepsis and septic shock. The HBE and Schofield equation are age-based, weight-determined, sex-specific derivations that may incorporate stress and/or activity factors. Total energy expenditure (TEE) values calculated from these equations (TEE(HBE) and TEE(SCH), respectively) were compared with the measured energy expenditure (MEE) calculated by the Weir derivation. We derived V CO(2) from end-tidal CO(2) and deduced V O2 assuming a respiratory quotient of 0.8381. RESULTS Mean (± SD) APACHE II score for the 60 patients was 25.7 ± 8.4. All patients received nutrition (51 enteral, eight parenteral and one combined) in addition to standard management for sepsis and multiorgan supportive therapy. Overall, 45 patients required inotropes and four received continuous renal replacement therapy. TEE derived from both predictive equations correlated well with MEE derived from the Weir equation (mean TEE(HBE), 7810.7 ± 1669.2 kJ/day; mean TEE(SCH), 8029.1 ± 1418.6 kJ/day; mean MEE, 7660.8 ± 2092.2 kJ/day), being within 8% of each other. Better correlations between TEE and MEE were observed in patients with APACHE II scores < 25 (vs those with scores ≥25) and patients with SIRS or severe sepsis (vs those with septic shock). CONCLUSION In a cohort of patients with sepsis, TEE values calculated by the HBE and Schofield equation matched reasonably well with MEE values derived from the Weir equation. Correlation was better in patients with less severe sepsis (SIRS and severe sepsis and APACHE II score < 25). Our results suggest that predictive equations have sufficient validity for ongoing regular use in clinical practice.