ArticleAcute and critical care2025
Estimating resting energy expenditure in critically ill patients: a retrospective exploratory comparison of predictive equations and Fick-derived Weir estimates in Italy.
Article in Acute and critical care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Interpreting Resting Energy Expenditure in Critically Ill Patients with Obesity: Clinical Impact of Weight Adjustment.Journal of clinical medicine · 2026Article
- Phase-Related Resting Energy Expenditure in Critically Ill Adults: Metabolic Phenotypes and Determinants of Weight-Normalized Indices-A Retrospective Study.Journal of clinical medicine · 2025Article
- Correction and clarification on reported percentage error of estimated continuous cardiac output.Acute and critical care · 2025Article
- Response to "Correction and clarification on reported percentage error of estimated continuous cardiac output".Acute and critical care · 2025Article
- Correction: Estimating resting energy expenditure in critically ill patients: a retrospective exploratory comparison of predictive equations and Fick-derived Weir estimates in Italy.Acute and critical care · 2025Article
- Nutritional support in critical care: estimating resting energy expenditure in the intensive care unit when indirect calorimetry is limited.Acute and critical care · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundResting 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.
methodsWe 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).
resultsThe 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).
conclusionsPredictive 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.
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