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Construction and validation of a risk prediction model for cognitive frailty in older patients with chronic heart
Siqian Li1, Weiying Zhang2, Kongyan Zhang1
1Department of Geriatrics, Fuyang Hospital of Anhui Medical University, Fuyang 236000, China.
Background:
As physiological and pathological changes make older patients with chronic heart failure prone to cognitive frailty, cognitive frailty affecting the clinical outcome of older patients with chronic heart failure.
Methods:
This was a cross-sectional study. Convenience sampling was used to randomly select 622 patients hospitalized.The stepwise regression was used to select predictors, and the logistic regression analysis was conducted to construct the model. The model was internal and external validation.
Results:
According to the logistic regression results, 5 predictive factors were screened out.The AUC values for the internal and external validation in the model were 0.867 and 0.848. Hosmer and Lemeshow test values for the internal validationand for the external validation were p > 0.05.
Conclusions:
The nomogram prediction model established in this study can help clinical staff to screen high-risk for cognitive frailty in older patients with chronic heart failure, and provide reference for optimizing the management of cognitive frailty.
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