Establishment and Evaluation of a Risk-prediction Model for HBP in Elderly Patients With NAFLD From a Health Management Perspective

Abstract

Objective: Elderly patients with nonalcoholic fatty liver disease (NAFLD) are at a higher risk of developing high blood pressure (HBP) and having a low quality of life. This study established an effective, individualised, early HBP risk-prediction model and proposed health management advice for the ³60 patients with NAFLD in Shanghai, China.Methods: Questionnaire surveys, physical examinations, and biochemical tests were conducted on 7,319 cases of sample data. Risk factors were screened using the least absolute shrinkage and selection operator (Lasso) model and random forest (RF) model. A risk-prediction model was established using logistic regression analysis and dynamic nomogram was drawn. The model was evaluated for discrimination, calibration, and clinical applicability using receiver operating characteristic curves (ROC), calibration curves, decision curve analysis (DCA), net reclassification index (NRI), and external validation.Results: The results suggested the model showed moderate predictive ability. The area under curve (AUC) of internal validation was 0.707 (95% CI: 0.688-0.727), the external validation AUC was 0.688 (95% CI: 0.672-0.705). The calibration plots showed good calibration, the risk threshold of the decision curve was 30-56%, and the NRI value was 0.109.Conclusion: This HBP risk factor model may be used in clinical practice to predict the HBP risk in NAFLD patients.