Prediction of resting metabolic rate in critically ill adult patients: results of a systematic review of the evidence

J Am Diet Assoc. 2007 Sep;107(9):1552-61. doi: 10.1016/j.jada.2007.06.010.

Abstract

Metabolic rate is generally assessed by use of equations in critically ill patients, but evidence pertaining to the validity of these equations in this population has not been systematically evaluated. This paper represents the first such systematic analysis in adult patients. A work group created by the American Dietetic Association identified pertinent peer-reviewed articles. The work group systematically evaluated these articles and formulated conclusion statements and grades based on the available evidence. Seven equations plus the Fick method were found to have validation work that met criteria for inclusion in this analysis. The Harris-Benedict equation with and without modifiers had the most validation work behind it (n=13), followed by Ireton-Jones (1992 and 1997) (n=9), Penn State (1998, 2003) (n=2), and Swinamer (n=1). Five studies pertaining to the Fick method met acceptance criteria. Based on these validation studies, the Harris-Benedict, Ireton-Jones 1997, and Fick methods can be confidently eliminated from use in assessment of energy expenditure in critically ill patients. The Penn State 2003, Swinamer, and Ireton-Jones 1992 equations may be useful in critically ill nonobese patients, whereas the Ireton-Jones 1992 and Penn State 1998 equations seem to be useful in obese patients. The strength of these conclusions is moderated because of limited and sometimes inconsistent data. More validation work is needed to confirm and increase the strength of these conclusions.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't
  • Review
  • Systematic Review

MeSH terms

  • Basal Metabolism / physiology*
  • Critical Illness*
  • Evidence-Based Medicine
  • Humans
  • Mathematics*
  • Nutritional Requirements*
  • Obesity / metabolism
  • Predictive Value of Tests
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Severity of Illness Index