Abstract
Objectives: Sarcopenia has been highlighted as a common comorbidity in patients with cardiovascular disease (CVD), which is related to poor prognosis. Sarcopenia is generally diagnosed based on the decrease in skeletal muscle index (SMI) and the reduction of either handgrip strength or gait speed. However, SMI is difficult to measure for general physicians or cardiologists, because special, expensive equipment (i.e. bioelectrical impedance assay (BIA) or dual-energy X-ray absorptiometry) is necessary. Therefore, the aim of this study was to investigate a new, simple index to detect sarcopenia in CVD patients. Design and Methods: We retrospectively investigated the association of sarcopenia with physical examination data and circulating biomarkers of nutrition, inflammation, skeletal muscle homeostasis in CVD patients who admitted in our hospital. Sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia (AWGS) guidelines using SMI measurements by BIA method. The age criterion was not adopted for sarcopenia diagnosis in this study. Results: This study included 132 consecutive inpatients (72 [27–93] years, 80 males) with CVD and/or undergoing cardiovascular surgery. According to the modified AWGS guidelines, 39 patients were diagnosed as having sarcopenia and 93 patients as not having sarcopenia. Sarcopenic patients were older and had lower estimated glomerular filtration rates (eGFR) and lower Barthel index, and included higher numbers of females and subjects with chronic kidney disease, as compared with non-sarcopenic patients. Among the screened biomarkers (e.g. hsCRP and IL-6), serum adiponectin and sialic acid was significantly higher in sarcopenic patients than non-sarcopenic patients. On stepwise multivariate regression analysis, adiponectin, sialic acid, sex, age, and body mass index were independent detecting factors for sarcopenia based on the modified AWGS criteria. Sarcopenia index was obtained from the diagnostic regression formula for sarcopenia detection including the five independent factors. Sarcopenia index 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. Conclusion: Novel biomarker-based sarcopenia index would be a simple, useful tool for detecting sarcopenia in CVD patients.
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