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ABSTRACT: BACKGROUND: Although estimation of energy needs by mathematical equation is common in practice, there is relatively little validation data for the equations. This is especially true at the upper and lower extremes of body size. The purpose of the current study was to provide validation data for several common equations in underweight and morbidly obese critically ill patients. METHODS: In mechanically ventilated, critical care patients with body mass index ≤21.0 or ≥45.0 kg/m(2), indirect calorimetry was used to measure resting metabolic rate. Several equation methods were then compared with these measurements, including the Penn State equation, Faisy equation, Ireton-Jones equation, Mifflin-St Jeor equation, Harris-Benedict equation, and American College of Chest Physicians (ACCP) standard using ideal, actual, or metabolically active body weight. RESULTS: Accuracy (percentage of estimates falling within 10% of measured) in the morbidly obese group was highest for the Penn State equation (76%) and lowest for the ACCP standard using actual body weight (0%). For the underweight group, the Penn State equation was accurate 63% of the time, but below a body mass index of 20.5, the accuracy rate dropped to 58%. No other equation was more accurate than this in the underweight patients. Conclusion: The Penn State equation is valid in morbid obesity, but the accuracy rate is much lower in underweight critically ill patients. A modification to the equation is suggested to improve accuracy in this group. (JPEN J Parenter Enteral Nutr. XXXX;xx:xx-xx).
Journal of Parenteral and Enteral Nutrition 08/2012; · 3.29 Impact Factor
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ABSTRACT: Background: Indirect calorimetry is the criterion method for assessment of energy expenditure in critically ill patients but is decidedly uncommon. Thus, calculation methods proliferate. Even if indirect calorimetry is available, it usually is not repeated more than weekly on the same patient, creating potential for error. The purpose of the current study was to quantify estimation errors against indirect calorimetry measurements in critically ill patients over time. Methods: In mechanically ventilated, critical care patients, indirect calorimetry was used to measure resting metabolic rate for 7 days. Three estimation methods were compared with the cumulative measurement: the Penn State equations, the American College of Chest Physicians (ACCP) standard (25 kcal/kg body weight), and an extrapolated value based on the first measurement multiplied by 7 days. Results: The cumulative difference between measured resting metabolic rate and the rate predicted by the Penn State equations was -468 ± 642 kcal (-3.7% ± 5.1% of the measured value). The difference for the ACCP was smaller, but variation was much wider (-387 ± 1597 kcal or -2.2% ± 11.9% of the measured value). The extrapolated value was -684 ± 1731 kcal (-4.1% ± 11.4% of measured expenditure). Conclusion: On average, the Penn State equations predict resting metabolic rate over time within 5% of the measured value. This performance is similar to the practice of making 1 measurement and extrapolating it over 1 week. The ACCP method has an unacceptably wide limit of agreement.
Journal of Parenteral and Enteral Nutrition 05/2012; 36(6):700-12. · 3.29 Impact Factor
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ABSTRACT: To compare the effect of stroke on the metabolic rate compared with the effect of traumatic brain injury and to determine whether the metabolic rate is predictable in both types of brain injury.
Indirect calorimetry was conducted prospectively in mechanically ventilated patients within the first 6 d of admission to a critical care unit owing to ischemic stroke, hemorrhagic stroke, isolated traumatic brain injury, or traumatic brain injury with collateral injuries. Clinical data were collected simultaneously and a predicted value of the resting metabolic rate was calculated using the Penn State equation (using body size, body temperature, and minute ventilation).
One hundred thirty patients were measured. Ischemic stroke showed a lower incidence of fever, a lower body temperature, and a lower resting metabolic rate than the other groups; whereas in hemorrhagic stroke, these variables were similar to the trauma groups. Sedation decreased the resting metabolic rate, but this effect seemed particular to the trauma patients. The Penn State equation predicted the resting metabolic rate accurately 72% of the time, and when its component variables of body temperature and minute ventilation were controlled in an analysis of variance, all the differences among the brain injury and sedation groups were eliminated.
Stroke is a hypermetabolic event most of the time. Body size, temperature, and minute ventilation explain most of the variation in the resting metabolic rate after traumatic and non-traumatic brain injuries. The Penn State equation therefore predicts the resting metabolic rate in brain-injured patients no matter the mechanism of injury.
Nutrition 03/2012; 28(9):906-11. · 3.03 Impact Factor
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ABSTRACT: Determination of energy needs is a fundamental part of nutrition support. The amount of metabolically active tissue mass is the major determinant of metabolic rate. The other components of total energy requirement in an adult are physical activity, diet-induced thermogenesis, and illness hypermetabolism. Measurement with indirect calorimetry is possible but not common. Measurement can capture the effect of body size, diet-induced thermogenesis, and illness on metabolic rate but usually not the effect of physical activity. More often, the energy need is calculated based on its association with body weight and composition. Many equations have been proposed over the years, as have adjustments to body weight in an attempt to capture the distorting effect of body composition in obesity and emaciation. Some equations capture the effects of illness and diet-induced thermogenesis without the need for modification; some require multiplication with various factors. None predict the energy expenditure from physical activity. In determining the energy prescription, all of the component parts must be considered, regardless of whether energy expenditure is measured or calculated.
Journal of Parenteral and Enteral Nutrition 08/2011; 35(5):563-70. · 3.29 Impact Factor
