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Which equation best predicts energy expenditure in amyotrophic lateral sclerosis?
J Am Diet Assoc 2011; 111(11):1680-7JA

Abstract

OBJECTIVE

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).

DESIGN

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.

SUBJECTS/SETTING

Participants were 56 men and women with ALS. For comparison, subjects were categorized by disease progression into three groups.

STATISTICAL ANALYSES

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.

RESULTS

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.

CONCLUSIONS

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.

Authors+Show Affiliations

Department of Nutrition Sciences, University of Alabama at Birmingham, AL, USA. aellis04@uab.eduNo affiliation info available

Pub Type(s)

Comparative Study
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

22027050

Citation

Ellis, Amy C., and Jeffrey Rosenfeld. "Which Equation Best Predicts Energy Expenditure in Amyotrophic Lateral Sclerosis?" Journal of the American Dietetic Association, vol. 111, no. 11, 2011, pp. 1680-7.
Ellis AC, Rosenfeld J. Which equation best predicts energy expenditure in amyotrophic lateral sclerosis? J Am Diet Assoc. 2011;111(11):1680-7.
Ellis, A. C., & Rosenfeld, J. (2011). Which equation best predicts energy expenditure in amyotrophic lateral sclerosis? Journal of the American Dietetic Association, 111(11), pp. 1680-7. doi:10.1016/j.jada.2011.08.002.
Ellis AC, Rosenfeld J. Which Equation Best Predicts Energy Expenditure in Amyotrophic Lateral Sclerosis. J Am Diet Assoc. 2011;111(11):1680-7. PubMed PMID: 22027050.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Which equation best predicts energy expenditure in amyotrophic lateral sclerosis? AU - Ellis,Amy C, AU - Rosenfeld,Jeffrey, PY - 2010/08/19/received PY - 2011/03/18/accepted PY - 2011/10/27/entrez PY - 2011/10/27/pubmed PY - 2011/12/13/medline SP - 1680 EP - 7 JF - Journal of the American Dietetic Association JO - J Am Diet Assoc VL - 111 IS - 11 N2 - OBJECTIVE: 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). DESIGN: 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. SUBJECTS/SETTING: Participants were 56 men and women with ALS. For comparison, subjects were categorized by disease progression into three groups. STATISTICAL ANALYSES: 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. RESULTS: 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. CONCLUSIONS: 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. SN - 1878-3570 UR - https://www.unboundmedicine.com/medline/citation/22027050/Which_equation_best_predicts_energy_expenditure_in_amyotrophic_lateral_sclerosis L2 - https://linkinghub.elsevier.com/retrieve/pii/S0002-8223(11)01372-1 DB - PRIME DP - Unbound Medicine ER -