Abstract
BACKGROUND/AIM: The Sarco-Detect study aim was to test the suitability of bioimpedance analysis (BIA) as a cost-efficient and practical alternative to computed tomography (CT) for diagnosing sarcopenia and to assess the agreement between CT and BIA. PATIENTS AND METHODS: In this study, the skeletal muscle cross-sectional area (SMA) was measured at the third lumbar vertebra (L3) on CT images, and the skeletal muscle index (SMI) was calculated. BIA skeletal muscle mass (SMM) and appendicular SMM (ASMM) were determined using the manufacturer's software (SMM-Seca, ASMM-Seca) and using the Sergi and Kyle equations. All calculated masses were converted to height-normalized index values and compared with the European Working Group on Sarcopenia in Older People cut-offs. RESULTS: A total of 70 patients were included, with mean (± standard deviation) age of 66±11 years, body mass index of 25±5 kg/m(2), CT-SMA of 135.55±32.01 cm(2), and CT-SMI of 44.28±8.14 cm(2). BIA results were 13.85±3.85 kg according to ASMM-Seca, 23.45±5.64 kg using ASMM-Sergi, and 21.86±5.74 kg using ASMM-Kyle. The highest Pearson correlation was determined between SMI-Seca and CT-SMI (r=0.839, p<0.01), followed by ASMI-Sergi (r=0.831, p<0.01). Comparing absolute SMM values, SMM-Seca showed the highest correlation with CT-SMA (r=0.917, p<0.01) followed by ASMM-Kyle and ASMM-Sergi (r=0.905 and r=0.904, respectively; p<0.01). When diagnosing sarcopenia, SMI-Seca showed the highest sensitivity of 50% (specificity 73%) followed by ASMI-Kyle at 38% (specificity 81%) and ASMI-Sergi at 13% (specificity 91%). Compared to the reference method (CT-SMI), 17 patients were falsely identified as having sarcopenia via the calculation of SMI-Seca and four patients with sarcopenia were not detected. CONCLUSION: The results indicate limited congruence of BIA and CT in the diagnosis of sarcopenia.