title: Resting energy expenditure in children in a pediatric intensive care unit: comparison of Harris-Benedict and Talbot predictions with indirect calorimetry values.
abstract: The use of prediction equations has been recommended for calculating energy expenditure. We evaluated two equations that predict energy expenditure, each of which were corrected for two different stress factors, and compared the values obtained with those calculated by indirect calorimetry. The subjects were 55 critically ill children on mechanical ventilation. Basal metabolic rates were calculated with the Harris-Benedict and Talbot methods. Measured resting energy expenditure was 4.72 +/- 2.53 MJ/d. The average difference between measured resting energy expenditure and the Harris-Benedict prediction with a stress factor of 1.5 was -0.98 MJ/d, with an SD delta of 1.56 MJ/d and limits of agreement from -4.12 to 2.15; for a stress factor of 1.3 the average difference was -0.22 MJ/d, with an SD delta of 1.57 MJ/d and limits of agreement from -3.37 to 2.93. The average difference between measured resting energy expenditure and the Talbot prediction with a stress factor of 1.5 was -0.23 MJ/d, with an SD delta of 1.36 MJ/d and limits of agreement from -2.95 to 2.48; for a stress factor of 1.3, it was 0.42 MJ/d, with an SD delta of 1.24 MJ/d and limits of agreement from -2.04 to 2.92. These limits of agreement indicate large differences in energy expenditure between the measured value and the prediction estimated for some patients. Therefore, neither the Harris-Benedict nor the Talbot method will predict resting energy expenditure with acceptable precision for clinical use. Indirect calorimetry appears to be the only useful way of determining resting energy expenditure in these patients.
authors.affiliation: Department of Pediatrics, Baylor College of Medicine, Houston, USA.
authors.forename: J A
authors.initials: JA
authors.lastname: Coss-Bu
authors.forename: L S
authors.initials: LS
authors.lastname: Jefferson
authors.forename: D
authors.initials: D
authors.lastname: Walding
authors.forename: Y
authors.initials: Y
authors.lastname: David
authors.forename: E O
authors.initials: EO
authors.lastname: Smith
authors.forename: W J
authors.initials: WJ
authors.lastname: Klish
mesh_terms: D000328:Adult; D001481:Basal Metabolism / Q000502:physiology; D002153:Calorimetry, Indirect / Q000379:methods*; D002648:Child; D002675:Child, Preschool; D016638:Critical Illness; D003627:Data Interpretation, Statistical; D004734:Energy Metabolism / Q000502:physiology*; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D015278:Intensive Care Units, Pediatric; D008297:Male; D010101:Oxygen Consumption / Q000502:physiology*; D011237:Predictive Value of Tests; D012121:Respiration, Artificial