Energy expenditure measurement in critical care: Implications for personalized nutrition support

Abstract

BACKGROUND

Accurate measurement of energy expenditure (EE) is critical for optimizing nutritional support in critically ill patients. Indirect calorimetry (IC) is the reference method used, but its availability at the bedside is limited. As a result, numerous predictive equations have been devised to estimate EE in critically ill patients, along with other more novel methods recently proposed.

AIM

To evaluate current methods of measuring EE in critical care, focusing on practical challenges, accuracy, feasibility, and limitations. We will also discuss how these methods contribute to improving nutrition support strategies for intensive care unit patients for a more personalised and effective solution.

METHODS

A comprehensive search was conducted in PubMed and EMBASE for studies published from December 2014 to December 2024. Eligible studies compared EE measurement methods in critically ill populations. Data extraction and quality assessment followed PRISMA guidelines. Adherence to reporting standards was assessed using the TRIPOD questionnaire and risk of bias was evaluated using the PROBAST tool.

RESULTS

Twenty five original studies met the inclusion criteria and were analysed.

CONCLUSION

Each method has unique strengths and limitations. We found that while IC remains the reference standard, less accurate predictive equations have greater accessibility and ease of implementation. Emerging technologies show promise for bedside applicability. Future research should address practical barriers and validate newer approaches.

Keywords: Energy expenditure; Nutrition in critical care; Indirect calorimetry; Predictive equations; Emerging technologies; Feeding in critical care

Core Tip: This systematic review evaluates current methods of measuring energy expenditure in critical care, focusing on practical challenges, accuracy, feasibility, and limitations of each one. We find that indirect calorimetry (IC) remains the gold standard with the most accurate measurements, but there remains significant difficulty in widespread use. Predictive equations are more accessible but lack accuracy. However, there are new ways of using IC and predictive equations that bring promise, and new alternative methods also show potential for application in the clinical context.