Objectives: Accurate assessments of energy expenditure are vital for determining optimal nutritional support, especially in critically ill children. We evaluated current methods for energy expenditure prediction, in comparison with indirect calorimetry, and developed a new estimation equation for mechanically ventilated, critically ill Korean children.
Design: Single-center retrospective study.
Setting: Fourteen-bed pediatric medical ICU in a tertiary care children's hospital.
Patients: Pediatric patients admitted to the PICU between October 2017 and September 2019 with a measured energy expenditure by indirect calorimetry.
Interventions: None.
Measurements And Main Results: A total 95 pediatric patients (70 in derivation cohort for development of a new predictive equation and 25 in validation cohort) were included. Mean measured energy expenditure of group A was 66.20 ± 15.35 kcal/kg/d. All previously established predictive equations underestimated the predicted energy expenditure, compared with the measured energy expenditure, except the Food and Agriculture/World Health Organization/United Nations University equation. The Schofield-Height and Weight equation showed the best performance among the tested predictive equations for the entire cohort (least bias, -68.58 kcal/d; best percentage, 108.46% ± 33.60%) compared with the measured energy expenditure. It was also the best performing predictive equation in subgroup analysis by age, sex, nutritional status, and organ failure. Because some discrepancies remained between the measured energy expenditure and predicted energy expenditures, we developed a new estimation equation using multiple regression analysis and those variables significantly associated with our current measured energy expenditures: Energy expenditure = -321.264 + 72.152 × (body weight, kg)-1.396 × (body weight) + 5.668 × height (cm) + organ dysfunction* (*hematologic, 76.699; neurologic, -87.984). This new estimation equation showed the least bias and best percentage compared with previous predictive equations (least bias, 15.51 kcal/d; best percentage, 102.30% ± 28.10%).
Conclusions: There are significant disparities between measured and calculated energy expenditures. We developed a new estimation equation based on measured energy expenditure data that shows better performance in mechanically ventilated Korean children than other equations. This new estimation equation requires further prospective validation in pediatric series with a range in body habitus.
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