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Abstract: PO2041

Development and Validation of a Multifrequency Bioimpedance Spectroscopy Equation to Predict Appendicular Skeletal Muscle Mass in Hemodialysis Patients

Session Information

Category: Health Maintenance, Nutrition, and Metabolism

  • 1300 Health Maintenance, Nutrition, and Metabolism


  • Lin, Ting-yun, Taipei Tzu Chi Hospital, Taipei, Taiwan

Sarcopenia is prevalent and associated with poor outcomes in patients with chronic kidney disease (CKD). Although bioimpedance analysis is accepted by major consensus statements as an alternative for muscle mass assessment, it can be affected by hydration status in CKD patients. The Body Composition Monitor (BCM), a multifrequency bioimpedance spectroscopy device, has been widely used to assess body composition and dry weight in hemodialysis patients because it can distinguish normally hydrated lean tissues from overly hydrated tissues. Therefore, our study aimed to develop and validate an equation for obtaining appendicular skeletal muscle mass (ASM) from BCM using dual-energy X-ray absorptiometry (DXA) as the reference among hemodialysis patients.


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. Tests for agreement included mean differences and Bland-Altman plots. 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.


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) (R2 = 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.


The new BCM equation provides a feasible and valid option for assessing ASM in hemodialysis patients. Its utility in clinical practice requires further research.


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