Frailty in maintenance hemodialysis: a systematic review and meta-analysis of prevalence and risk factors.

PURPOSE: To determine the prevalence of frailty in maintenance hemodialysis (MHD) patients and its influencing factors.

DESIGN

A systematic review and meta-analysis.

METHODS

PubMed, Embase, Web of Science, Cochrane Library, CINAHL, SinoMed, China Knowledge Resource Integrated Database, Wanfang Database, and Weipu Database were searched from inception until June 2025. Reviewers independently selected studies, extracted data, and assessed study quality. Data were analyzed using STATA software version 17.0. The PRISMA checklist was used to review this study.

RESULTS

A total of 30 studies were included in this meta-analysis, involving 6,944 participants. The overall prevalence of frailty in MHD patients was 36.5%. Twenty-nine influencing factors were included in the analysis, and we screened ten risk factors associated with MHD frailty. Among socio-demographic factors, older age (P < 0.001) and living alone (P = 0.033) were significant predictors of frailty in MHD patients. Comorbidities (P = 0.014) are also one of the important risk factors. Complications include Charlson comorbidity index (P = 0.002), diabetes mellitus (P = 0.028), cardiovascular disease (P = 0.014), and cerebrovascular diseases (P = 0.029). In dialysis-related factors, only inadequate dialysis adequacy (P = 0.027) showed a significant correlation with MHD frailty. Depression (P = 0.005) is the only psychological factor associated with MHD frailty. Among physiological factors, lower serum albumin (P = 0.004), C-reactive protein (P = 0.005), nutrition with lower the Malnutrition-Inflammation Score (P = 0.002), lower grip strength (P = 0.001), and sleep disorders (P = 0.047) are the main risk factors.

CONCLUSION

The results of this study suggest that frailty has a relatively high prevalence in MHD patients. Ten risk factors for frailty in MHD patients were identified. Healthcare professionals should regularly assess the signs of frailty in MHD patients and construct risk prediction models to identify high-risk groups. In addition, we should pay further attention to modifiable risk factors and provide early targeted interventions to reduce the incidence of adverse events.