Chairside frailty screening in hemodialysis patients: diagnostic accuracy of the Kihon Checklist combined with calf circumference

Frailty screening is important in maintenance hemodialysis (MHD), but routine implementation is limited by time, space, and mobility constraints. Self-reported tools such as the Kihon Checklist (KCL) are feasible but may not fully capture physical vulnerability. This study evaluated whether adding calf circumference (CC) to the KCL improves chairside frailty screening performance. This cross-sectional diagnostic accuracy study included 200 MHD patients at a tertiary medical center. Frailty was defined using the Physical Frailty Phenotype (PFP). Multivariable models compared a baseline KCL model with the primary KCL + CC model using bilateral mean CC. Prespecified sensitivity analyses examined bilateral maximum CC and a modified PFP reference standard without the weakness criterion. HGS-containing models were additionally evaluated as exploratory analyses. Model performance was assessed using AUC, continuous net reclassification improvement (cNRI), integrated discrimination improvement (IDI), decision curve analysis, and bootstrap internal validation. Overall, 120 patients (60.0%) were frail. The baseline KCL model showed strong discrimination (AUC, 0.923; 95% confidence interval [CI], 0.885–0.961), with 80.0% sensitivity and 91.3% specificity. Adding CC improved discrimination (AUC, 0.953; 95% CI, 0.928–0.979), sensitivity (86.7%), reclassification (cNRI, 0.850; IDI, 0.085; both p < 0.001), and net benefit while maintaining specificity (91.3%). Findings remained robust in sensitivity analyses using bilateral maximum CC and a modified PFP without the weakness criterion. The internally validated AUC of the KCL + CC model was 0.942. Adding CC to the KCL provides a feasible, non-ambulatory chairside approach for improving frailty screening in MHD patients.