Development and validation of risk forecasting model for frailty among maintenance hemodialysis patients

Objective  To establish a prediction model for frailty risk in maintenance hemodialysis (MHD ) patients and verify its effectiveness.

Methods  A retrospective survey was conducted retrospectively for 200 patients undergoing regular hemodialysis treatment at Yidu Central Municipal Hospital. General data were collected and Fried phenotype was utilized for frailty scores. They were assigned into two groups of frailty (≥3 points) and non-frail (<3 points). Patient health questionnaire-9 (PHQ-9) scale was employed for depression scoring and GAD-7 (generalized anxiety disorder-7) scale for anxiety scoring. They were randomized into training set (n=140) and validation set (n=60) in a 7∶3 ratio using R software. Based upon training group, univariate and multivariate logistic regression analysis was performed for screening for independent influencing factors of weakness and the final predictors were selected based on the minimum value of Akaike Information Criterion (AIC). A nomogram was constructed for verifying the predictive performance of model based upon validation group.

Results  The incidence of frailty in MHD patients was 43.5%. Age, depression, activity level and number of comorbidities were independent influencing factors of the occurrence of frailty. A nomogram model was constructed for predicting the risk of frailty in MHD patients. Area under the ROC curve of the model was 0.880 with a sensitivity of 82.5% and a specificity of 81.7%. And the correction curve fitted well with the ideal curve.

Conclusions  The above model offers an excellent predictive capability for the occurring probability of frailty in MHD patients. It is helpful for an early identification of high-risk groups and a proper formulation of clinical interventions.