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Pitfalls in Predicting Resting Energy Requirements in Critically Ill Children: A Comparison of Predictive Methods to Indirect Calorimetry
Author(s) -
Hardy Christine M.,
Dwyer Johanna,
Snelling Linda K.,
Dallal Gerard E.,
Adelson Joel W.
Publication year - 2002
Publication title -
nutrition in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.725
H-Index - 71
eISSN - 1941-2452
pISSN - 0884-5336
DOI - 10.1177/0115426502017003182
Subject(s) - medicine , resting energy expenditure , critically ill , calorimetry , energy expenditure , limits of agreement , allowance (engineering) , predictive value , energy (signal processing) , kilogram , basal metabolic rate , intensive care unit , intensive care medicine , pediatrics , statistics , body weight , mathematics , nuclear medicine , mechanical engineering , physics , engineering , thermodynamics
Background: Critical illness in children is thought to have profound effects on nutritional status. It is essential to avoid complications associated with inadequate nutrition support and delivery of excess energy. Objective: To compare the results of several commonly used methods for predicting energy requirements in a group of critically ill children indirect calorimetry was used to measure energy expenditure in these children. Design: Resting energy expenditures estimated by different prediction methods for energy were compared with measurements of actual resting energy expenditure obtained by indirect calorimetry in 52 children admitted to a pediatric intensive care unit. Agreement between each predictive method and indirect calorimetry was evaluated by Bland‐Altman limits of agreement and by whether the methods met the predetermined criterion for accuracy of within 10% of the measured value. Results: None of the equations predicted individual values accurately. Each of the predictive equations gave a wide and variable scatter of predicted values around the median. The recommended dietary allowance for energy was the least accurate and differed significantly even from the other predictive methods, overestimating energy expenditure in 50 of 52 patients. None of the remaining methods stood out as being more precise. Conclusions: Predictive methods commonly used to estimate energy expenditure in critically ill children are very imprecise and may lead to overprovision or underprovision of nutrition support. Resting energy expenditure should be measured by indirect calorimetry whenever possible.