<![CDATA[Background: Special medical group (SMG) students at Russian universities are a heterogeneous population whose health conditions limit their participation in standard physical education. Integrated physiological characterisation remains limited, as earlier work has rarely combined body composition, hemodynamic, and autonomic data within a single protocol. Aims: The study aimed to identify the body-composition variable most strongly and independently associated with device-estimated resting cardiac output and stroke volume in SMG students, while accounting for fat mass, visceral adipose tissue, phase angle, and body mass index. Methods: In this cross-sectional study, 277 students aged 18-21 were assessed using the MS FIT diagnostic complex, which combines segmental bioimpedance, pulse-wave analysis, and short-term heart rate variability. Cardiac output and stroke volume were device-derived estimates. Spearman correlations, multiple linear regression, and tertile comparisons were computed in SPSS 26.0. Result: The full five-predictor models explained 69.2% of the variance in cardiac output and 53.3% in stroke volume. Skeletal muscle mass had the largest standardized coefficient in both models (std. β=0.84 and 0.64; p<.001), and fat mass contributed independently to cardiac output (std. β=0.41; p<.001). Visceral adipose tissue and phase angle were not significant; body mass index was significant only for stroke volume. Conclusion: Among the variables examined, skeletal muscle mass showed the strongest independent association with device-estimated resting cardiac output and stroke volume, with fat mass also contributing to cardiac output. These cross-sectional associations suggest that body mass index alone may be insufficient for describing the resting hemodynamic profile. Potential effects of skeletal muscle mass on resting hemodynamics require confirmation in longitudinal and interventional studies.]]>
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