Novel equations incorporating the sarcopenia index based on serum creatinine and cystatin C to predict appendicular skeletal muscle mass in patients with nondialysis CKD.

BACKGROUND & AIMS: Skeletal muscle mass measurements are important for customizing nutritional strategies for patients with chronic kidney disease (CKD). The serum creatinine-to-cystatin C ratio (Cr/CysC) is a potential indicator of sarcopenia. We developed simple equations to predict the appendicular skeletal muscle mass (ASM) of patients with CKD using readily available parameters and Cr/CysC.

METHODS

Overall, 573 patients with nondialysis CKD stages 3-5 were included for developing and validating the equations. The participants were randomly divided into development and validation groups in a 2:1 ratio. ASM was measured using the Body Composition Monitor (BCM), a multifrequency bioelectrical impedance spectroscopy device. The height, weight, anthropometric data, and handgrip strength (HGS) of the participants were obtained. Equations were generated using stepwise multiple linear regression models. The prognostic significance of the predicted ASM was evaluated in a CKD registry comprising 1043 patients.

RESULTS

The optimal equation without anthropometric data and HGS (Equation 1) was as follows: ASM (kg) = -7.949 - 0.049 × Age (years) - 2.213 × Woman + 0.090 × Height (cm) + 0.210 × Weight (kg) + 1.141 × Cr/CysC. The modified equation (Equation 2) with anthropometric data and HGS was as follows: ASM (kg) = -4.468 - 0.050 × Age (years) - 2.285 × Woman+ 0.079 × Height (cm) + 0.228 × Weight (kg) - 0.127 × Mid-arm muscular circumference (cm) + 1.127 × Cr/CysC. Both equations exhibited strong correlations with the ASM measured via BCM in the validation cohort (r = 0.944 and 0.943 for Equations 1 and 2, respectively) with minimal bias. When Equation 1 was applied to the CKD registry, the estimated ASM index (ASM/Height) significantly predicted overall mortality over a median of 54 months.

CONCLUSIONS

Novel ASM equations offer a simple method for predicting skeletal muscle mass and can provide valuable prognostic information regarding patients with nondialysis CKD.