Predicting all-cause and cardiovascular mortality in hypertensive patients by combining the CHG index and its obesity indicators: a prospective cohort study with survival prediction model.

Abstract

Background: Hypertension is closely related to the development and mortality of cardiovascular disease (CVD), insulin resistance (IR) plays a key role in hypertension-related metabolic dysfunction, but there is no universally accepted IR marker for hypertensive populations. Recently, the cholesterol-HDL-glucose (CHG) index and its obesity indicators (CHG-BMl, CHG-WC, and CHG-WHtR) have emerged as reliable IR markers. In this research, we aimed to assess their associations with all-cause and cardiovascular mortality among hypertensive patients with machine learning analysis.

Methods: Data from 4661 hypertensive participants in the the China Health and Retirement Longitudinal Study (CHARLS) were analysed. Survival machine learning models (Cox, Cox-LASSO, Survival XGBoost) were applied. Model discrimination was assessed by Harrell's C-index and time-dependent ROC (tdAUC) at 3, 5, 7 years. Incremental predictive value was evaluated using continuous net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Competing-risk (Fine-Gray) regression was performed for cardiovascular mortality.

Results: The CHG index and its obesity indicators were independent predictors of both all-cause and cardiovascular mortality among hypertensive patients. The CHG-WHtR showed strong associations with both all-cause (HR = 2.060, 95% CI: 1.852-2.292, P < 0.001) and cardiovascular mortality (HR = 2.020, 95% CI 1.816-2.247, P < 0.001) per 1-SD increase. The test C-index of Cox-LASSO was 0.920 (95% CI 0.878-0.962), with tdAUC ranging 0.851-0.916 across 3, 5 and 7 years. Adding CHG indices substantially improved reclassification (continuous NRI ranging: 0.349-0.496, IDI ranging: 0.024-0.040). L-shaped relationships were observed with both all-cause (non-linear P < 0.001) and cardiovascular mortality (non-linear P < 0.001). The combination of the CHG index or its obesity indicators into predictive models substantially improved the prediction performance for mortality outcomes.

Conclusions: The CHG index and its obesity indicators are significant predictors of all-cause and cardiovascular mortality in hypertensive patients, and CHG-WHtR exhibits better prognostic performance in terms of mortality risk. The inclusion of obesity indicators enhances risk stratification and may benefit from tailored interventions among hypertension population.