Energy expenditure in children with severe head injury: lack of agreement between measured and estimated energy expenditure

Nutr Clin Pract. 2006 Apr;21(2):175-81. doi: 10.1177/0115426506021002175.

Abstract

Background: The purpose of this study was to test the hypotheses that estimates of resting energy expenditure (REE) vary significantly from measured energy expenditure in a population of head-injured children and are not accurate for use in determining nutrition needs in this population.

Methods: This is a retrospective study of 30 children with severe head injury, with Glasgow Coma Scale (GCS) score of <8 and needing mechanical ventilation. Measured REE was obtained using indirect calorimetry. Estimated REEs were calculated using Harris-Benedict, World Health Organization (WHO), Schofield, and White formulas. Severity of illness was calculated using Pediatric Risk of Mortality (PRISM) score. Agreement between measured REE and estimated REE was tested using the Bland-Altman method. Correlation coefficient between PRISM score and measured REE was calculated using Spearman test.

Results: More than half of the estimates of REE differed from measured REE by >10%. Significant disagreement between estimated REE and measured REE was demonstrated using the Bland-Altman method. There was no correlation between severity of illness and measured REE to explain the inaccuracies of REE estimates.

Conclusion: Energy expenditure in critically ill children cannot be estimated accurately; hence, nutrition for critically ill children with head injury should be provided according to measurement of REE to avoid the consequences of overfeeding or malnutrition.

Publication types

  • Comparative Study

MeSH terms

  • Adolescent
  • Basal Metabolism / physiology*
  • Calorimetry, Indirect
  • Child
  • Child, Preschool
  • Craniocerebral Trauma / metabolism*
  • Craniocerebral Trauma / physiopathology
  • Energy Metabolism / physiology*
  • Female
  • Humans
  • Intensive Care Units, Pediatric
  • Male
  • Nutritional Requirements
  • Nutritional Status
  • Predictive Value of Tests
  • Retrospective Studies
  • Severity of Illness Index
  • Statistics, Nonparametric