Construction and validation of a nomogram to predict frailty in Chinese patients with hypertension: evidence from the China Health and Retirement Longitudinal Study (CHARLS)

Background Frailty is common in patients with hypertension and predisposes patients to poor postoperative outcomes. However, there is a lack of a prediction model for frailty in patients with hypertension. Therefore, we established a nomogram to identify those at risk for frailty in hypertension, providing implications for health interventions and community services. Methods The patients diagnosed with hypertension were collected from the the China Health and Retirement Longitudinal Study (CHARLS) database and were randomly divided into a training cohort and a validation group at a ratio of 7:3. The independent risk factors of frailty were determined by LASSO regression and multivariable logistic regression and a nomogram predict model for frailty was established. The performance of the nomogram was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA). Results The content of the nomogram includes age, health status, cognitive function, and the Center for Epidemiological Studies Depression (CES-D). The AUCs of the training cohort and validation cohort (0.830 and 0.854) suggested good discrimination of the nomogram. Calibration curves and DCA curves proved accuracy and clinical applicability. Conclusion The nomogram we created for the frailty in hypertensive patients had good performance and applicability, which could help clinicians in the medical decision-making process.