Accuracy of surrogate methods to estimate skeletal muscle mass in non-dialysis dependent patients with chronic kidney disease and in kidney transplant recipients

Bioelectrical impedance analysis (BIA) and anthropometric predictive equations have been proposed to estimate whole-body (SMM) and appendicular skeletal muscle mass (ASM) as surrogate for dual energy X-ray absorptiometry (DXA) in distinct population groups. However, their accuracy in estimating body composition in non-dialysis dependent patients with chronic kidney disease (NDD-CKD) and kidney transplant recipients (KTR) is unknown. The aim of this study was to investigate the accuracy and reproducibility of BIA and anthropometric predictive equations in estimating SMM and ASM compared to DXA, in NDD-CKD patients and KTR. A cross-sectional study including adult NDD-CKD patients and KTR, with body mass index (BMI) ≥18.5 kg/m2. ASM and estimated SMM were evaluated by DXA, BIA (Janssen, Kyle and MacDonald equations) and anthropometry (Lee and Baumgartner equations). Low muscle mass (LowMM) was defined according to cutoffs proposed by guidelines for ASM, ASM/height2 and ASM/BMI. The best performing equation as surrogate for DXA, considering both groups of studied patients, was defined based in the highest Lin's concordance correlation coefficient (CCC) value, the lowest Bland–Altman bias (