Estimation of Muscle Mass Using Creatinine/Cystatin C Ratio in Japanese Community-Dwelling Older People.

Abstract Objectives Sarcopenia is defined as a combination of low skeletal muscle mass index (SMI), weak muscle strength, and reduced physical function. Recently, many studies have reported that the creatinine/cystatin C ratio (Cr/CysC) is useful for evaluating muscle mass. We designed a cross-sectional study with separate model development and validation groups to develop a prediction equation to estimate bioimpedance analysis (BIA)-measured SMI with Cr/CysC. Design The current study was a retrospective cross-sectional study. Setting and Participants The model development group included 908 subjects (288 men and 620 women) from the Frail Elderly in the Sasayama-Tamba Area (FESTA) study, and the validation group included 263 subjects (112 men and 151 women) from participants in the medical checkup program at the Anti-Aging Center in Ehime Prefecture. Measures Multivariate regression analysis indicated that age, hemoglobin (Hb), body weight (BW), and Cr/CysC were independently associated with SMI in both men and women. The SMI prediction equation was developed as follows: Men: 4.17 − 0.012 × Age + 1.24 × ( Cr / CysC ) − 0.0513 × Hb + 0.0598 × BW Women: 3.55 − 0.00765 × Age + 0.852 × ( Cr / CysC ) − 0.0627 × Hb + 0.0614 × BW Results The SMI prediction equation was applied to the validation group and strong correlations were observed between the BIA-measured and predicted SMI (pSMI) in men and women. According to the receiver operator characteristic (ROC) analysis, the areas under the curve were 0.93 (specificity 89.0%, sensitivity 87.2%) among men and 0.88 (specificity 83.6%, sensitivity 79.6%) among women for using pSMI to identify low SMI in the model development group. The pSMI also indicated high accuracy in ROC analysis for low SMI in the validation group. The Bland-Altman plot regression showed good agreement between BIA-measured and pSMI. Conclusions and Implications Our new prediction equation to estimate SMI is easy to calculate in daily clinical practice and would be useful for diagnosing sarcopenia.