Development and validation of a multifrequency bioimpedance spectroscopy equation to predict appendicular skeletal muscle mass in hemodialysis patients. Issue 5 (May 2021)

• Record Type: Journal Article
• Authors: Lin, Ting-Yun; Wu, Ming-Ying; Chen, Huan-Sheng; Hung, Szu-Chun; Lim, Paik-Seong
• Is Part Of: Clinical nutrition. Volume 40:Issue 5(2021)
• Page Start: 3288
• Page End: 3295
• Publication Date: 2021-05
• Subjects: Appendicular skeletal muscle mass -- Dual-energy X-ray absorptiometry -- Hemodialysis -- Mortality -- Multifrequency bioimpedance spectroscopy -- Sarcopenia; Critically ill -- Nutrition -- Periodicals; Diet therapy -- Periodicals; Parenteral feeding -- Periodicals; Enteral feeding -- Periodicals; Enteral Nutrition -- Periodicals; Parenteral Nutrition -- Periodicals; Metabolism -- Periodicals; Diétothérapie -- Périodiques; Alimentation parentérale -- Périodiques; Alimentation entérale -- Périodiques; Nutrition -- Périodiques; Diet therapy; Enteral feeding; Nutrition; Parenteral feeding; Electronic journals; Periodicals; Electronic journals; 615.854
• DOI: 10.1016/j.clnu.2020.10.056
• Languages: English
• ISSNs: 0261-5614

Abstract

Summary: Background & aims: The Body Composition Monitor (BCM), a multifrequency bioimpedance spectroscopy device, has been widely used to assess body composition in hemodialysis patients because its measurement is not affected by overhydration commonly seen in chronic kidney disease. We aimed to develop and validate an equation for obtaining appendicular skeletal muscle mass (ASM) from BCM taking dual-energy X-ray absorptiometry (DXA) as the reference among hemodialysis patients. Methods: A total of 322 consecutive body composition measurements with BCM and DXA in 263 hemodialysis patients were randomly divided at a ratio of 2:1 into development and validation groups. Stepwise multiple regression modeling was applied to develop the ASM prediction equation. We evaluated the model as a diagnostic tool for sarcopenia using cutoffs of ASM defined by the Asian Working Group for Sarcopenia (AWGS). We further explored the association between ASM predicted by the BCM equation and all-cause mortality in two independent cohorts: one with 326 stage 3–5 CKD patients and one with 629 hemodialysis patients. Results: BCM yielded the following equation: ASM (kg) = −1.838 + 0.395 × total body water (L) + 0.105 × body weight (kg) + 1.231 × male sex – 0.026 × age (years) (R 2 = 0.914, standard error of estimate = 1.35 kg). In the validation group, Bland–Altman reliability analysis showed no significant bias of 0.098 kg and limits of agreement ±2.440 kg. Using the AWGS criteria, the model was found to have a sensitivity of 94.1%, a specificity of 98.8%, a positive predictive value of 84.2%, and a negative predictive value of 99.6% for the diagnosis of sarcopenia. Low ASM predicted by the BCM equation was associated with significantly worse overall survival among CKD patients but not hemodialysis patients. Conclusions: The new BCM equation provides a feasible and valid option for assessing ASM in hemodialysis patients.