T O Obisesan1, M J Toth, E T Poehlman. 1. Department of Internal Medicine, Howard University College of Medicine, Washington DC 20060, USA.
Abstract
OBJECTIVES: Patients with congestive heart failure are often undernourished. The measurement of resting energy expenditure has served as the basis upon which estimates of daily caloric needs have been developed. Resting energy needs, however, in heart failure patients are unknown. We have developed a new equation to predict resting energy needs in heart failure patients that takes into account easily measured clinical variables and symptom severity. DESIGN: Observational. SETTING: Baltimore VA Medical Center. SUBJECTS: Forty male patients with heart failure aged, 57-85 y; (27 Class II; 13 Class IV). MEASUREMENTS: Resting metabolic rate was measured by indirect calorimetry, fat-free mass and fat mass by dual energy X-ray absorptiometry, peak VO2 by a treadmill test. Symptom severity was measured by the New York Heart Association classification. Ejection fraction, plasma albumin and plasma glucose were also assessed. RESULTS: Stepwise regression analysis showed that body weight, fasting glucose, plasma albumin and New York Heart Association classification accounted for 83% of the variation in resting energy needs. The regression equation had a root mean square error of 130 kcal (544 kJ) per day. The equation is: RMR (kcal/d) = 12.2 (wt, kg) + 1.6 (glucose, gm/dl) + 103 (NYHA; III, IV)-144 (albumin, mg/dl) + 755. Moreover, prediction equations based on observations in healthy individuals significantly underestimated resting energy needs in heart failure patients. CONCLUSION: We offer a new equation to predict resting energy needs in heart failure patients based upon readily available clinical measurements. Further studies are needed to cross-validate our equation.
OBJECTIVES:Patients with congestive heart failure are often undernourished. The measurement of resting energy expenditure has served as the basis upon which estimates of daily caloric needs have been developed. Resting energy needs, however, in heart failurepatients are unknown. We have developed a new equation to predict resting energy needs in heart failurepatients that takes into account easily measured clinical variables and symptom severity. DESIGN: Observational. SETTING: Baltimore VA Medical Center. SUBJECTS: Forty male patients with heart failure aged, 57-85 y; (27 Class II; 13 Class IV). MEASUREMENTS: Resting metabolic rate was measured by indirect calorimetry, fat-free mass and fat mass by dual energy X-ray absorptiometry, peak VO2 by a treadmill test. Symptom severity was measured by the New York Heart Association classification. Ejection fraction, plasma albumin and plasma glucose were also assessed. RESULTS: Stepwise regression analysis showed that body weight, fasting glucose, plasma albumin and New York Heart Association classification accounted for 83% of the variation in resting energy needs. The regression equation had a root mean square error of 130 kcal (544 kJ) per day. The equation is: RMR (kcal/d) = 12.2 (wt, kg) + 1.6 (glucose, gm/dl) + 103 (NYHA; III, IV)-144 (albumin, mg/dl) + 755. Moreover, prediction equations based on observations in healthy individuals significantly underestimated resting energy needs in heart failurepatients. CONCLUSION: We offer a new equation to predict resting energy needs in heart failurepatients based upon readily available clinical measurements. Further studies are needed to cross-validate our equation.