Risk Prediction Models for Frailty in Adult Maintenance Haemodialysis Patients: A Systematic Review and Methodological Appraisal

Frailty affects over 35% of maintenance haemodialysis (MHD) patients globally-2-3 times higher than the general elderly-and is strongly linked to higher mortality, hospitalisation, and functional decline. Despite its clinical impact, frailty is often underdiagnosed in dialysis settings due to inconsistent assessments and limited resources. Existing prediction models vary widely in predictors and methods, requiring systematic review to guide clinical use and improve risk-stratified care. To systematically identify, describe, and evaluate the existing risk prediction models for frailty in patients undergoing MHD. Systematic review and Methodological appraisal. A comprehensive search was conducted across multiple databases-PubMed, Web of Science Core Collection, Embase, Cochrane Library, CINAHL, China Biomedical Literature Database (CBM), Wanfang Database, VIP Database-covering studies up to November 1, 2024. Two researchers independently conducted literature searches, screening, and data extraction. They used the Prediction Model Risk of Bias Assessment Tool (PROBAST) to evaluate the risk of bias and the applicability of the included models. Fifteen studies (21 models) were analysed, with sample sizes 141-786 and frailty incidence 11.00%-59.57%. Model AUCs ranged 0.720-0.998 (potential overfitting at extreme values). Key predictors included age, serum albumin, gender, Charlson comorbidity index, and activities of daily living scores. Methodological appraisal using PROBAST revealed moderate applicability but high bias risks: 53% of studies used retrospective designs, 95% lacked external validation, and limitations included small samples, non-standard variable selection, and inadequate handling of missing data. While models demonstrate initial predictive utility, widespread bias and developmental-stage limitations hinder clinical application. Future research must prioritise TRIPOD-guided model development, emphasising large prospective cohorts, rigorous validation, and transparent reporting to enhance reliability and clinical utility in frailty risk stratification for MHD patients.