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A Prediction Equation to Assess Resting Energy Expenditure in Japanese Patients with COPD

Background: Medical nutrition therapy is important in the management of chronic obstructive pulmonary disease (COPD) patients. Determination of resting energy expenditure is essential to define therapeutic goals for medical nutrition. Previous studies proposed the use of equations to predict resting...

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Detalles Bibliográficos
Autores principales: Morikawa, Keisuke, Tabira, Kazuyuki, Takemura, Hiroyuki, Inaba, Shogo, Kusuki, Haruka, Hashitsume, Yu, Suzuki, Yuta, Tenpaku, Yosuke, Yasuma, Taro, D’Alessandro-Gabazza, Corina N., Gabazza, Esteban, Hataji, Osamu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7694151/
https://www.ncbi.nlm.nih.gov/pubmed/33121107
http://dx.doi.org/10.3390/jcm9113455
Descripción
Sumario:Background: Medical nutrition therapy is important in the management of chronic obstructive pulmonary disease (COPD) patients. Determination of resting energy expenditure is essential to define therapeutic goals for medical nutrition. Previous studies proposed the use of equations to predict resting energy expenditure. No prediction equation is currently available for the Japanese population. The objective of this study was to develop an equation to predict resting energy expenditure in Japanese chronic obstructive pulmonary disease patients. To this end, we investigated clinical variables that correlate with the resting energy expenditure. Methods: This study included 102 COPD patients admitted at the Matsusaka Municipal Hospital Respiratory Center. We measured resting energy expenditure by indirect calorimetry and explored the relationship of resting energy expenditure with clinical variables by univariate and stepwise linear regression analysis. Results: The resting energy expenditure by indirect calorimetry was significantly correlated with fat-free mass, body weight, body mass index, height, gender, and pulmonary function test by univariate analysis. In the stepwise linear regression analysis, the fat-free mass, body weight, and age remained significantly correlated with indirect calorimetry’s resting energy expenditure. The fat-free mass, body weight, and age explained 50.5% of the resting energy expenditure variation. Conclusion: Fat-free mass, body weight, and age were significantly correlated with resting energy expenditure by stepwise linear regression analysis, and they were used to define a predictive equation for Japanese COPD patients.