title: Predicting resting energy expenditure in underweight, normal weight, overweight, and obese adult hospital patients.
abstract: BACKGROUND
  When indirect calorimetry is not available, predictive equations are used to estimate resing energy expenditure (REE). There is no consensus about which equation to use in hospitalized patients. The objective of this study is to examine the validity of REE predictive equations for underweight, normal weight, overweight, and obese inpatients and outpatients by comparison with indirect calorimetry.
  
  
  METHODS
  Equations were included when based on weight, height, age, and/or gender. REE was measured with indirect calorimetry. A prediction between 90 and 110% of the measured REE was considered accurate. The bias and root-mean-square error (RMSE) were used to evaluate how well the equations fitted the REE measurement. Subgroup analysis was performed for BMI. A new equation was developed based on regression analysis and tested.
  
  
  RESULTS
  513 general hospital patients were included, (253 F, 260 M), 237 inpatients and 276 outpatients. Fifteen predictive equations were used. The most used fixed factors (25 kcal/kg/day, 30 kcal/kg/day and 2000 kcal for female and 2500 kcal for male) were added. The percentage of accurate predicted REE was low in all equations, ranging from 8 to 49%. Overall the new equation performed equal to the best performing Korth equation and slightly better than the well-known WHO equation based on weight and height (49% vs 45% accurate). Categorized by BMI subgroups, the new equation, Korth and the WHO equation based on weight and height performed best in all categories except from the obese subgroup. The original Harris and Benedict (HB) equation was best for obese patients.
  
  
  CONCLUSIONS
  REE predictive equations are only accurate in about half the patients. The WHO equation is advised up to BMI 30, and HB equation is advised for obese (over BMI 30). Measuring REE with indirect calorimetry is preferred, and should be used when available and feasible in order to optimize nutritional support in hospital inpatients and outpatients with different degrees of malnutrition.
authors.affiliation: Department of Nutrition and Dietetics, Internal Medicine, VU University Medical Center, P.O. Box 7057, Amsterdam, 1007 MB The Netherlands.
authors.forename: Hinke M
authors.initials: HM
authors.lastname: Kruizenga
authors.affiliation: Department of Nutrition and Dietetics, Internal Medicine, VU University Medical Center, P.O. Box 7057, Amsterdam, 1007 MB The Netherlands.
authors.forename: Geesje H
authors.initials: GH
authors.lastname: Hofsteenge
authors.affiliation: Department of Nutrition and Dietetics, Internal Medicine, VU University Medical Center, P.O. Box 7057, Amsterdam, 1007 MB The Netherlands ; Department of Nutrition and Dietetics, School of Sports and Nutrition, Amsterdam University of Applied Sciences, Amsterdam, The Netherlands.
authors.forename: Peter J M
authors.initials: PJ
authors.lastname: Weijs
keywords: BMI; Equation; Indirect calorimetry; Normal weight; Obese; Overweight; Prediction; Resting energy expenditure; Underweight; Validity