A potential bioelectrical impedance equation for estimating skeletal muscle area using computed tomography in...

Bioelectrical impedance analysis (BIA) requires validated equations tailored to specific populations and devices to estimate body composition. In this study, we aimed to develop a predictive equation for BIA to evaluate skeletal muscle area (SMA) using computed tomography (CT) as the reference method. This is bi-center cross-sectional study, involving 211 patients. BIA was conducted using a tetrapolar model, measuring resistance (R), and reactance (Xc) values. The equation was developed using a linear regression model, maintaining variables that best correlate to SMA_CT. Validity was assessed using Bland-Altman plots and bootstrapping resampling method. Lins' concordance correlation coefficient (CCC), root mean squared error (RMSE), and mean absolute error (MAE) were calculated before and after resampling. The proposed equation included sex, age, weight, height, resistance and reactance. This model accounted for more than 85% of the variability in SMA_CT (R² _adjusted = 0.86), with a RMSE of 10.37 cm² and MAE of 8.28 cm². SMA_BIA was highly correlated with SMA_CT (ρ = 0.93, P < .001). Bland-Altman plots and CCC (0.92) demonstrated a moderate agreement between SMA_BIA and SMA_CT. The newly proposed BIA equation demonstrated potential for predicting SMA_CT as the reference standard. Our hypothesis requires further investigation in both healthy and clinical populations.