[Prevalence of frailty and associated factors among kidney transplant recipients].

Objective: To investigate the prevalence of frailty among kidney transplant recipients and to analyze the influential factors of frailty after kidney transplantation. Methods: We retrospectively included 201 kidney transplant recipients who were followed up in the Department of Urology, Beijing Chao-yang Hospital, Capital Medical University from November 2020 to May 2022. We investigated the prevalence of frailty based on the Fried Frailty Scale (including unexpected shrinking, slow walking speed, poor grip strength, low physical activity, and exhaustion). Then the logistic regression model and CART decision tree model were established separately to explore the influential factors of frailty after kidney transplantation. Results: Frail kidney transplant recipients accounted for 25.9% ( n =52) of all participants. The age [ M ( Q 1 , Q 3 )] of the frailty group was higher than that of the non-frailty group, and the median ages of the two groups were 57(49, 62) and 46(38, 56) ( P< 0.001); the males accounted for 51.9% ( n =27) and 62.4% ( n =93), respectively. There was no significant difference in gender composition ( P =0.244). Among the five components of Fried Frailty Scale, the incidence of unexpected shrinking was the lowest (19.4%, 39/201). In the frailty group, the frailty combination with the highest incidence was slow walking speed+low physical activity+exhaustion, which was 19.2% (10/52). The logistic regression model showed that advanced age ( OR =1.062, 95% CI : 1.005-1.123), history of acute rejection ( OR =16.776, 95% CI : 2.288-123.028), increased neutrophil/lymphocyte ratio (NLR) ( OR =2.096, 95% CI : 1.158-3.792), and comorbidity ( OR =10.600, 95% CI : 1.828-61.482) were risk factors for frailty among kidney transplant recipients, and high serum albumin level ( OR =0.623, 95% CI : 0.488-0.795) was a protective factor. The CART decision tree grew in three layers with four terminal nodes, and three explanatory variables were screened out: serum albumin, NLR, and age. The accuracy, sensitivity, and specificity of the logistic regression model were 87.1% (95% CI : 82.5%-91.7%), 69.2% (95% CI : 54.7%-80.9%), and 93.3% (95% CI : 87.7%-96.6%), respectively. The area under the ROC curve (AUC) of the logistic regression model was 0.951 (95% CI : 0.923-0.978). The accuracy, sensitivity, and specificity of the CART decision tree model were 91.0% (95% CI : 87.0%-95.0%), 82.7% (95% CI : 69.2%-91.3%), and 94.0% (95% CI : 88.5%-97.0%), respectively. The AUC of the CART decision tree model was 0.883 (95% CI : 0.819-0.948). Conclusions: The prevalence of frailty among kidney transplant recipients in this study is 25.9%. Advanced age, history of acute rejection, low serum albumin level, increased NLR, and comorbidity are likely to be associated with the long-term frailty among kidney transplant recipients.