Comparisons of Predictive Equations for Resting Energy Expenditure in Patients with Cerebral Infarct during Acute Care.

Estimation of resting energy expenditure (REE) is essential in planning nutrition support. Several equations are used for this estimation in the clinical setting. The purpose of this study was to compare the predictive accuracy of existing equations for REE in patients with cerebral infarct during acute care. We assessed the Harris-Benedict, Mifflin, Owen, Japanese simplified, Wang, and Cunningham equations. The Owen and Japanese simplified equations use sex and weight as explanatory variables, the Harris-Benedict and Mifflin equations include sex, weight, age, and height, and the Wang and Cunningham equations use fat-free mass (FFM) measured using bioelectrical impedance technology. Actual REE values were measured by indirect calorimetry on days 2 and 7 and were then averaged. Applying analysis of variance, predictive accuracy was assessed by comparing the predicted and actual values. A total of 30 patients were analyzed. Actual REE values ranged from 796 to 1637 kcal (mean, 1109). The standard deviation of these values was the smallest with the Harris-Benedict equation (99), followed by the Cunningham (165), and Wang (181) equations. The Mifflin equation underestimated REE in females, whereas the Owen and Japanese simplified equations tended to overestimate it. Based on our results, the Harris-Benedict equation provides the most accurate prediction of REE. In addition, the Cunningham and Wang equations may be useful in long-term care settings involving patients at risk of malnutrition resulting in uneven loss of FFM relative to weight.

Nagano A ，Yamada Y ，Miyake H ，Domen K ，Koyama T ... -  《-》

Accurate determination of energy needs in hospitalized patients.

Boullata J ，Williams J ，Cottrell F ，Hudson L ，Compher C ... -  《journal of the american dietetic association》

Resting energy expenditure prediction using bioelectrical impedance analysis in patients with severe motor and intellectual disabilities.

Resting energy expenditure (REE) is expected to be lower in with severe motor and intellectual disabilities (SMID) patients than in healthy subjects because of their relatively low fat-free mass (FFM). Therefore, an REE predictive equation for SMID patients may be required. The aim of this study was to validate existing REE predictive weight-based equations (Harris-Benedict, WHO, Mifflin, Owen, Schofield) and FFM-based REE equations (Mifflin, Owen and Cunningham) and to develop a new SMID patient-specific FFM-based REE equation. Twenty-eight (22 males, 6 females) SMID patients over 18 years of age were included. The REE was measured using indirect calorimetry. FFM were measured using bioelectrical impedance analysis. A multiple linear regression analysis was used to develop a new FFM-based REE predictive equation. The accurate predictions compared the measured REE and root mean square error. The median measured REE was 950 (25th,75th percentile:712.75, 1102.75) kcal/day. The new FFM-based equation was as follows: REE (kcal/day) = 550.62 + 16.62 FFM (kg). The new FFM-based REE resulted in the highest percentage of accurate predictions within 10% of measured REE (42.9%). The root mean square errors were the smallest for the new FFM-based REE and largest for Harris-Benedict (91.00 and 185.22 kcal/day). For SMID patients, the REE cannot accurately be predicted using the existing weight-based REE equations. Furthermore, the existing FFM-based REE equations are less accurate with regard to the measured REE than the new FFM-based REE equation. The new FFM-based equation is advised for use in SMID patients.

Hashizume N ，Tanaka Y ，Yoshida M ，Fukahori S ，Ishii S ，Saikusa N ，Masui D ，Higashidate N ，Sakamoto S ，Tsuruhisa S ，Yuge K ，Ohya T ，Yagi M ，Yamashita Y ... -  《-》

Predicting energy expenditure in extremely obese women.

Dobratz JR ，Sibley SD ，Beckman TR ，Valentine BJ ，Kellogg TA ，Ikramuddin S ，Earthman CP ... -  《-》

Which equation best predicts energy expenditure in amyotrophic lateral sclerosis?

The purpose of this study was to compare measured resting energy expenditure (REE) with estimates from three common prediction equations with the goal of determining which equation best estimates REE in amyotrophic lateral sclerosis (ALS). Cross-sectional measurements of REE from indirect calorimetry were compared to calculations from the Harris Benedict, Mifflin-St Jeor, and Ireton-Jones equations. Additional measurements to identify predictors of REE included pulmonary function tests, fat-free mass by bioelectrical impedance, and anthropometrics. Participants were 56 men and women with ALS. For comparison, subjects were categorized by disease progression into three groups. Pearson correlations and paired t tests were used to compare measured REE with predicted REE from each equation, and the accuracy of each equation was quantified by the root mean squared prediction error and the percentage of REE estimates within 10% of measured values. Bias for each equation was calculated as the mean percentage difference between calculated and measured REE. Multiple linear regression was used to determine the best predictor variables for REE. Across the disease spectrum, the Harris Benedict and Mifflin-St Jeor equations provided clinically acceptable estimates of REE, whereas the Ireton-Jones equations consistently overestimated REE. The best predictors of REE among this cohort were fat-free mass, sex, and age. When estimating energy requirements for patients with ALS, clinicians should choose prediction equations that incorporate sex and age as predictor variables, such as the Harris Benedict and Mifflin-St Jeor equations.

Ellis AC ，Rosenfeld J 《-》