Nilesh M Mehta1, Craig D Smallwood2, Koen F M Joosten3, Jessie M Hulst3, Robert C Tasker2, Christopher P Duggan2. 1. Boston Children's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States. Electronic address: nilesh.mehta@childrens.harvard.edu. 2. Boston Children's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States. 3. Erasmus MC-Sophia Children's Hospital, Rotterdam, Netherlands.
Abstract
BACKGROUND & AIMS: Accurate assessment of resting energy expenditure (REE) and metabolic state is essential to optimize nutrient intake in critically ill patients. We aimed to examine the accuracy of a simplified equation for predicting REE using carbon dioxide elimination (VCO2) values. METHODS: We conducted a two-center study of metabolic data from mechanically ventilated children less than 18 years of age. Mean respiratory quotient (RQ) from the derivation set (n = 72 subjects) was used to modify the Weir equation to obtain a simplified equation based on VCO2 measurements alone. This equation was then applied to subjects at the second institution (validation dataset, n = 94) to predict resting energy expenditure. Bland-Altman analysis was used to assess the agreement between measured REE values, and REE estimated by the new equation as well as the Schofield equation. We also examined the accuracy of the new equation in classifying patients according to their metabolic state. RESULTS: Mean respiratory quotient (± SD) of 0.89 ± 0.09 in the derivation set was used to obtain a simplified equation, REE (kcal/day) = 5.534*VCO2 (L/min)*1440. In relation to the measured REE in the validation set, the mean bias (limits of agreement) for the REE predicted by this equation was -0.65% (-14.4-13.1%); and the overall diagnostic accuracy for classifying subjects as hypometabolic or hypermetabolic was 84%. Mean bias (limits) of agreement between measured and Schofield equation estimated REE was -0.1% (-40.5-40.7%). CONCLUSIONS: A simplified metabolic equation using VCO2 values was superior to the standard equation in estimating REE, and provided a reasonably accurate metabolic classification in mechanically ventilated children. In the absence of indirect calorimetry, bedside VCO2 monitoring could provide valuable continuous metabolic information to guide optimal nutrient intake.
BACKGROUND & AIMS: Accurate assessment of resting energy expenditure (REE) and metabolic state is essential to optimize nutrient intake in critically illpatients. We aimed to examine the accuracy of a simplified equation for predicting REE using carbon dioxide elimination (VCO2) values. METHODS: We conducted a two-center study of metabolic data from mechanically ventilated children less than 18 years of age. Mean respiratory quotient (RQ) from the derivation set (n = 72 subjects) was used to modify the Weir equation to obtain a simplified equation based on VCO2 measurements alone. This equation was then applied to subjects at the second institution (validation dataset, n = 94) to predict resting energy expenditure. Bland-Altman analysis was used to assess the agreement between measured REE values, and REE estimated by the new equation as well as the Schofield equation. We also examined the accuracy of the new equation in classifying patients according to their metabolic state. RESULTS: Mean respiratory quotient (± SD) of 0.89 ± 0.09 in the derivation set was used to obtain a simplified equation, REE (kcal/day) = 5.534*VCO2 (L/min)*1440. In relation to the measured REE in the validation set, the mean bias (limits of agreement) for the REE predicted by this equation was -0.65% (-14.4-13.1%); and the overall diagnostic accuracy for classifying subjects as hypometabolic or hypermetabolic was 84%. Mean bias (limits) of agreement between measured and Schofield equation estimated REE was -0.1% (-40.5-40.7%). CONCLUSIONS: A simplified metabolic equation using VCO2 values was superior to the standard equation in estimating REE, and provided a reasonably accurate metabolic classification in mechanically ventilated children. In the absence of indirect calorimetry, bedside VCO2 monitoring could provide valuable continuous metabolic information to guide optimal nutrient intake.
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