Background: Sarcopenia is an aging and disease-related syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength, with the risk of frailty and poor quality of life. Sarcopenia is diagnosed by a decrease in skeletal muscle index (SMI) and reduction of either handgrip strength or gait speed. However, measurement of SMI is difficult for general physicians because it requires special equipment for bioelectrical impedance assay or dual-energy X-ray absorptiometry. The purpose of this study was, therefore, to explore a novel, simple diagnostic method of sarcopenia evaluation in patients with cardiovascular diseases (CVD).
Methods: We retrospectively investigated 132 inpatients with CVD (age: 72±12 years, age range: 27-93 years, males: 61%) Binomial logistic regression and correlation analyses were used to assess the associations of sarcopenia with simple physical data and biomarkers, including muscle-related inflammation makers and nutritional markers.
Results: Sarcopenia was present in 29.5% of the study population. Serum concentrations of adiponectin and sialic acid were significantly higher in sarcopenic than non-sarcopenic CVD patients. Stepwise multivariate binomial logistic regression analysis revealed that adiponectin, sialic acid, sex, age, and body mass index were independent factors for sarcopenia detection. Sarcopenia index, obtained from the diagnostic regression formula for sarcopenia detection including the five independent factors, indicated a high accuracy in ROC curve analysis (sensitivity 94.9%, specificity 69.9%) and the cutoff value for sarcopenia detection was -1.6134. Sarcopenia index had a significant correlation with the conventional diagnostic parameters of sarcopenia.
Conclusions: Our new sarcopenia index using simple parameters would be useful for diagnosing sarcopenia in CVD patients.