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  • Title: Comparison of resting energy expenditure prediction methods with measured resting energy expenditure in obese, hospitalized adults.
    Author: Anderegg BA, Worrall C, Barbour E, Simpson KN, Delegge M.
    Journal: JPEN J Parenter Enteral Nutr; 2009; 33(2):168-75. PubMed ID: 19251910.
    Abstract:
    BACKGROUND: Several methods are available to estimate caloric needs in hospitalized, obese patients who require specialized nutrition support; however, it is unclear which of these strategies most accurately approximates the caloric needs of this patient population. The purpose of this study was to determine which strategy most accurately predicts resting energy expenditure in this subset of patients. METHODS: Patients assessed at high nutrition risk who required specialized nutrition support and met inclusion and exclusion criteria were enrolled in this observational study. Adult patients were included if they were admitted to a medical or surgical service with a body mass index > or = 30 kg/m(2). Criteria excluding patient enrollment were pregnancy and intolerance or contraindication to indirect calorimetry procedures. Investigators calculated estimations of resting energy expenditure for each patient using variations on the following equations: Harris-Benedict, Mifflin-St. Jeor, Ireton-Jones, 21 kcal/kg body weight, and 25 kcal/kg body weight. For nonventilated patients, the MedGem handheld indirect calorimeter was used. For ventilated patients, the metabolic cart was used. The primary endpoint was to identify which estimation strategy calculated energy expenditures to within 10% of measured energy expenditures. RESULTS: The Harris-Benedict equation, using adjusted body weight with a stress factor, most frequently estimated resting energy expenditure to within 10% measured resting energy expenditure at 50% of patients. CONCLUSION: Measured energy expenditure with indirect calorimetry should be employed when developing nutrition support regimens in obese, hospitalized patients, as estimation strategies are inconsistent and lead to inaccurate predictions of energy expenditure in this patient population.
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