Ning-ning Xia, Jing Liu, Hongying Wang

Blood Purification Center, Nanjing BenQ Medical Center, the Affiliated BenQ Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, People’s Republic of China

Correspondence: Jing Liu, Email liujing66382@126.com Ning-ning Xia, Email 781901805@qq.com

Introduction: Cognitive frailty is increasingly recognized among older adults receiving maintenance hemodialysis (MHD), yet effective screening tools tailored for this population are lacking. This study aimed to develop a predictive model to identify MHD patients of advanced age who are at high risk for cognitive frailty, thereby facilitating early detection and intervention.
Methods: A cross-sectional study was conducted between February and December 2024, enrolling 223 older individuals undergoing MHD at a tertiary hospital in Nanjing, China. Data on demographic and clinical characteristics were collected, along with assessments using standardized instruments, including the Kidney Disease Quality of Life Instrument, Geriatric Depression Scale-5, Subjective Cognitive Decline Questionnaire-9, Montreal Cognitive Assessment, Clinical Dementia Rating, Fried Frailty Phenotype, and Cognitive Reserve Index Questionnaire. Least absolute shrinkage and selection operator (LASSO) regression was used to identify relevant variables, which were subsequently entered into multivariate logistic regression to determine independent risk factors. A nomogram was constructed based on the final model.
Results: Cognitive frailty was identified in 85 patients, indicating a prevalence of 38.1%. Eight variables were found to be independent risk factors: serum phosphorus, hemoglobin level, depression score, cognitive reserve, age, dialysis duration, dialysis adequacy (Kt/V), and intradialytic hypotension. The predictive nomogram showed excellent discriminative performance, with an area under the receiver operating characteristic curve of 0.986 (95% confidence interval: 0.970– 0.999), sensitivity of 94.9%, and specificity of 97.6%. Decision curve analysis demonstrated favorable clinical utility.
Conclusion: Cognitive frailty is prevalent among older patients receiving MHD. The nomogram incorporating eight key variables provides a practical tool for early screening and personalized intervention in this high-risk population.

Keywords: cognitive frailty, CF, cognitive reserve, maintenance hemodialysis, MHD, prediction model