Acute and critical care · 2025
Estimating resting energy expenditure in critically ill patients: a retrospective exploratory comparison of predictive equations and Fick-derived Weir estimates in Italy.
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Romanelli Antonio, Calicchio Alessandro, Palmese Salvatore, Pascarella Sabato, Pisapia Bruna, Gammaldi Renato
Аннотация
BACKGROUND: Resting energy expenditure (REE) estimation is crucial in critically ill patients. While indirect calorimetry (IC) is the gold standard, its limited availability often necessitates alternative methods. In this exploratory study, we compared the accuracy of the stress factor-corrected Harris-Benedict (cREEHB) and weight-based (REEWB) equations with the Weir equation (REEW) using oxygen consumption (VO₂) and carbon dioxide production (VCO₂) estimated via the Fick principle.
METHODS: We included patients admitted to the intensive care unit (ICU) between January and August 2024, and computed cREEHB, REEWB (22.5 kcal/kg/day), and REEW. Agreement between methods was assessed through Bland-Altman analysis. Sensitivity and correlation analyses identified bias determinants. Multiple linear regression explored associations of REEW with VO₂, VCO₂, and cardiac output (CO).
RESULTS: The sample size consisted of 30 patients. No correlation was found between REEW and cREEHB (r=0.177, P=0.349) or REEWB (r=-0.006, P=0.975). Compared to REEW, cREEHB underestimated REE (mean bias, -47.9 kcal), while REEWB overestimated it (mean bias, +9.7 kcal). CREEHB bias was associated with sex, height, body surface area (BSA), VO2, and respiratory quotient (RQ); REEWB bias was influenced by actual body weight, body mass index, BSA, VO2, and RQ (all P<0.05). Multiple linear regression analysis showed that REEW was influenced by VO2 (P<0.001) and VCO2 (P<0.001) but not by CO (P=0.164).
CONCLUSIONS: Predictive equations may not be interchangeable in ICU settings, leading to inaccurate metabolic assessments. Studies incorporating IC as a reference are needed to determine the most reliable approach for estimating REE and optimizing nutritional support in critical patients.
METHODS: We included patients admitted to the intensive care unit (ICU) between January and August 2024, and computed cREEHB, REEWB (22.5 kcal/kg/day), and REEW. Agreement between methods was assessed through Bland-Altman analysis. Sensitivity and correlation analyses identified bias determinants. Multiple linear regression explored associations of REEW with VO₂, VCO₂, and cardiac output (CO).
RESULTS: The sample size consisted of 30 patients. No correlation was found between REEW and cREEHB (r=0.177, P=0.349) or REEWB (r=-0.006, P=0.975). Compared to REEW, cREEHB underestimated REE (mean bias, -47.9 kcal), while REEWB overestimated it (mean bias, +9.7 kcal). CREEHB bias was associated with sex, height, body surface area (BSA), VO2, and respiratory quotient (RQ); REEWB bias was influenced by actual body weight, body mass index, BSA, VO2, and RQ (all P<0.05). Multiple linear regression analysis showed that REEW was influenced by VO2 (P<0.001) and VCO2 (P<0.001) but not by CO (P=0.164).
CONCLUSIONS: Predictive equations may not be interchangeable in ICU settings, leading to inaccurate metabolic assessments. Studies incorporating IC as a reference are needed to determine the most reliable approach for estimating REE and optimizing nutritional support in critical patients.