A predictive model of cognitive impairment risk in older adults with hypertension

Background: Hypertension is one of the most common diseases in the world, impacting global life expectancy and associated with an increased risk of cognitive impairment.

Objective: This study aimed to develop a nomogram that accurately predicts the risk of cognitive impairment in hypertensive patients using the National Health and Nutrition Examination Study (NHANES).

Methods: A total of 1517 hypertensive patients from NHANES 2011-2014 were included in this study. The population was divided into two groups: 1065 cases (70 %) in the train set and 452 cases (30 %) in the test set. Lasso regression model and multivariate logistic regression analyses identified predictors significantly associated with cognitive impairment, and the nomogram was constructed using these predictors. The performance of the model was assessed using metrics such as area under the curve (AUC) of receiver operating characteristic (ROC), calibration curves, and decision curve analysis (DCA).

Results: The nomogram identified seven predictors, including sex, age, education, poverty income ratio (PIR), depression, vigorous work activity, and creatinine. A web-based dynamic nomogram (https://cognitive-impairment-in-hypertension.shinyapps.io/DynNomapp/) was constructed based on these factors. The AUC of the train set was 0.802 and the AUC of the test set was 0.756, indicating that the model had excellent discriminative ability. The calibration curve showed that the model was well-calibrated. The DCA indicated that early intervention for those at risk would result in a net benefit.

Conclusion: The model performed well and was clinically predictive, making it easy for clinicians to use and screen for possible cognitive impairment in elderly hypertensive patients.