AI Article Synopsis
- The study investigates the relationship between the C-reactive protein-triglyceride-glucose index (CTI) and stroke risk in hypertensive patients, proposing CTI as a comprehensive marker for assessing insulin resistance and inflammation.
- After following 3,834 patients over 7 years, results indicated a 21% increased stroke risk for each unit increase in CTI and a 66% higher likelihood of stroke for those in the highest quartile compared to the lowest.
- The study supports the idea that higher CTI levels correlate with increased stroke risk and highlights CTI as a valuable tool for stroke prediction in hypertensive individuals.
Article Abstract
Background: Both the triglyceride-glucose (TyG) index, a predictor of insulin resistance (IR), and inflammation are risk factors for stroke in hypertensive patients. However, only a handful of studies have coupled the TyG index and inflammation indices to predict stroke risk in hypertensive patients. The C-reactive protein-triglyceride-glucose index (CTI) is a novel marker that comprehensively assesses the severity of IR and inflammation. The present study explored the association between CTI and the risk of stroke in patients with hypertension.
Methods: A total of 3,834 hypertensive patients without a history of stroke at baseline were recruited from the China Health and Retirement Longitudinal Study (CHARLS). Multivariate Cox regression and restricted cubic spline (RCS) analyses were employed to assess the relationship between CTI and stroke risk in hypertensive patients. Furthermore, the Boruta algorithm was applied to evaluate the importance of CTI and construct prediction models to forecast the incidence of stroke in the study cohort.
Results: After 7 years of follow-up, the incidence of stroke in hypertensive patients was 9.6% (368 cases). Multivariate Cox regression analysis revealed a 21% increase in stroke risk with an increase in each CTI unit (hazard ratio (HR) = 1.21, 95% confidence interval (CI) = 1.08-1.37). The top quartile group was 66% more likely to have a stroke than the bottom quartile group (HR = 1.66, 95% CI = 1.23-2.25). RCS analysis confirmed a linear relationship between CTI and stroke risk. The Boruta algorithm validated CTI as a crucial indicator of stroke risk. The Support Vector Machine (SVM) survival model exhibited the best predictive performance for stroke risk in hypertensive patients, with an area under the curve (AUC) of 0.956.
Conclusions: An increase in CTI levels is associated with a higher risk of stroke in hypertensive patients. This study suggests that CTI may emerge as a unique predictive marker for stroke risk.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11580337 | PMC |
| http://dx.doi.org/10.1186/s13098-024-01529-z | DOI Listing |
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