To develop and independently externally validate a novel, simple, and validated tool to assess the risk of cognitive frailty in older adult patients with heart failure based on these factors. A cross-sectional study. A novel nomogram risk prediction model was developed by recruiting older adult patients with heart failure for data collection from October 2022 to August 2023 at a university general hospital in China. Independent external validation of the developed model was performed on patients collected from March 2023 to June 2023 at a university general hospital at the same level. Univariate and multivariate logistic regression analyses were performed for variables that may influence the prevalence of cognitive frailty. The fit and predictive performance of the nomogram risk prediction model was evaluated based on the area under the characteristic curve of the subjects and decision curve analysis. The overall prevalence of cognitive frailty in older adult patients with heart failure was 44.5%. The results showed that the predictive ability of the model development cohort was 0.807(95%CI = 0.7640.851, P <0.001). And the predictive ability of the validation cohort was 0.770(95%CI = 0.6670.874, P <0.001), indicating that the model has high accuracy. The results showed satisfactory predictive performance. The use of this tool helps clinical caregivers to quickly and intuitively identify patients at high risk for the development of cognitive frailty on admission, thus providing evidence to support the early development and implementation of personalized strategies.
Liu et al. (Sat,) studied this question.