Abstract:Objective To develop a nomogram model for predicting cognitive frailty in elderly patients with stable coronary artery disease, and to provide reference for early clinical diagnosis and intervention. Methods A total of 848 elderly patients with stable coronary artery disease were selected using convenience sampling method. A self-designed general information questionnaire, the Montreal Cognitive Assessment, Clinical Dementia Rating, and Frailty Phenotype were utilized to collect data. A multivariate logistic regression was used to determine the risk factors of cognitive frailty, then a nomogram was developed based on the regression-based coefficients and was validated internally. Results The prevalence of cognitive frailty was 11.9%. Through logistic regression, age≥70 years old, sleeping≤6 h per night, history of diabetes, comorbid heart failure, history of hypertension, and exercise≤5 days/week were selected as factors predictive of cognitive frailty (P<0.05, P<0.01). On the basis of these factors, a nomogram was created and demonstrated good predictive abilities, with C-index of 0.835 (95%CI 0.771-0.899), and also Hosmer-Lemeshow test showing goodness-of-fit of the nomogram model (χ2=9.145,P=0.103). Conclusion The nomogram model can effectively predict the risk of cognitive frailty in elderly patients with stable coronary heart disease and needs to be externally validated in further study.
