The impact of frailty on the survival prognosis of maintenance hemodialysis patients and the construction and validation of a survival prediction model.

OBJECTIVE

This study aims to examine the impact of frailty on the survival outcomes of patients undergoing maintenance hemodialysis (HD) and to develop a predictive model for mortality risk.

METHODS

In this prospective cohort study, 400 HD patients were enrolled and followed for 24 months. Frailty was assessed by the Fried phenotype. Depression and anxiety were evaluated using the PHQ-9 and GAD-7 scales, respectively. Patients were randomly split into a model development group (n = 280) and a validation group (n = 120). Kaplan-Meier curves and the log-rank test were used for survival analysis. Independent predictors were identified using LASSO-Cox regression to construct a nomogram. Model performance was evaluated using the C-index, calibration curves, and decision curve analysis (DCA).

RESULTS

The prevalence of frailty was 45.75%. Multivariable analysis identified frailty (HR = 1.85, 95% CI 1.03-3.36), age (HR = 1.04, 95% CI 1.01-1.07), depression (HR = 4.91, 95% CI 2.00-12.04), anxiety (HR = 3.49, 95% CI 1.78-6.83), cardiovascular disease (HR = 2.06, 95% CI 1.13-3.78), serum creatinine (HR = 1.004, 95% CI 1.003-1.005), and total cholesterol (HR = 1.50, 95% CI 1.13-2.00) as independent risk factors (all P < 0.05). The model demonstrated a C-index of 0.903. In the validation cohort, the AUCs were 0.889 (6-month), 0.897 (1-year), and 0.941 (2-year). Calibration and DCA confirmed good accuracy and clinical utility.

CONCLUSION

Frailty is prevalent and independently associated with mortality in HD patients. The developed nomogram provides an accurate tool for individualized risk prediction. The particularly strong influence of depression and anxiety on survival underscores the critical need for integrating routine psychological screening into the clinical management of hemodialysis patients.