| Objective: To explore the present condition of cognitive frailty in elderly patients with hypertension and analyze its influencing factors,construct a risk prediction model for cognitive frailty in elderly patients with hypertension,draw a nomogram,compile a risk score table and assess the predictive power of the model and score table,in order to help nurses evaluate the risk of cognitive frailty in elderly hypertensive patients.Methods:(1)From February 2022 to August 2022,a cohort of 450 elderly people suffering from hypertension in the Cardiology Department of a hospital in Hangzhou was selected as the modeling group.Binary logistic regression was employed to analyze the independent risk factors of cognitive frailty in elderly hypertension patients.A risk prediction model was established according to the partial regression coefficient of the influencing factors and a nomogram was created.(2)168 elderly patients with hypertension in the Department of Cardiology of a hospital in Hangzhou from September 2022 to November 2022 were chosen as the validation group for the questionnaire.The nomogram model’s goodness of fit and discriminant validity was evaluated by the H-L test,the area under the ROC curve test,sensitivity,specificity and Youden index,and its prediction accuracy was calculated.(3)The partial regression coefficients of independent risk factors were allocated to construct the cognitive frailty risk assessment scale for elderly hypertensive patients and the best cut-off score of the scale was obtained.The data of the validation group was used to verify the actual predictive ability of the risk assessment scale.The comparison of the risk prediction model’s and the risk assessment scale’s prediction results was made using the Kappa consistency test.Results:(1)In the modeling group,the elderly hypertensive patients exhibited a cognitive frailty rate of 27.1%.(2)The analysis of binary Logistic regression demonstrated that age ≥70 years,hypertension duration ≥10 years,malnutrition,depression,no physical exercise,poor blood pressure control,and sleep time < 6 hours per night were independent risk factors for cognitive frailty(P < 0.05).(3)The model of cognitive frailty in elderly hypertensive patients was formulated and the nomogram was created to forecast risk.In internal verification,H-L test P=0.266 > 0.05,yielded the AUC of 0.905,95%CI was 0.874-0.936,P < 0.001;When the optimal risk cut-off is 0.122,the model’s sensitivity was 91.0%,its specificity 73.8%,and its Youden index was 0.648.(4)In the validation group,168 elderly hypertensive patients exhibited a cognitive frailty rate of 26.1%.By drawing the ROC curve of the validation group,the AUC was 0.903,95%CI was 0.843-0.963,indicating that the discriminant validity of the model was good.When the optimal risk cut-off is 0.152,the model’s sensitivity was 81.8%,its specificity 90.3%,its Youden index 0.721,and its prediction accuracy was 89.3%.(5)The best cut-off score of the cognitive frailty risk assessment scale in elderly hypertensive patients was 6 points.The prediction accuracy of the risk assessment scale was 81.0%,and the Kappa coefficient value of consistency test was0.812,P < 0.001.Conclusion:(1)The incidence of cognitive frailty is high in elderly patients with hypertension.(2)Elderly hypertension patients with age ≥70 years,hypertension duration ≥10 years,malnutrition,depression,no physical exercise,poor blood pressure control,and sleep time < 6 hours per night have a higher risk of cognitive frailty.(3)A good practical predictive capacity is provided by the constructed risk prediction nomogram model and the risk assessment scale for cognitive frailty in elderly hypertensive patients,which can be used as a reference for assessing cognitive frailty in elderly hypertensive patients in China. |
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