Risk prediction models for frailty in maintenance hemodialysis patients:a scoping review
MA Bingying
MA Mingzhu
XU Sujia
Abstract：Objective: To conduct a systematic review of frailty risk prediction models for patients on chronic hemodialysis. Methods: A systematic search was conducted in databases including CNKI, Wanfang, VIP, China Biomedical Literature Service System, PubMed, Web of Science, EMbase, The Cochrane Library, Scopus, and CINAHL, for studies related to frailty risk prediction models in patients on chronic hemodialysis. The risk of bias in the included literature was assessed, and information such as the prevalence of frailty, predictive factors of the model, and model performance was extracted and summarized. Results: A total of 11 articles were included, involving 11 frailty risk prediction models. The prevalence of frailty among patients on chronic hemodialysis ranged from 17.25% to 74.06%. The overall performance of the models was relatively good, but the construction methods of the models were relatively single. Age, depression, nutrition, Charlson Comorbidity Index, and gender were important predictors of frailty in patients on chronic hemodialysis. Conclusion: Nursing staff should pay attention to the high-risk factors for frailty in patients on chronic hemodialysis. Future research could integrate artificial intelligence technology to build prediction models, further improve model validation methods, and enhance model predictive efficiency, providing the best predictive tools for clinical nursing decisions.
Keywords：maintenance hemodialysisfrailtyrisk prediction modelscoping reviewnursing
Publication Date：2025-05-10
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1729-1734 )