Use of the Vascular Overload Index to Predict Cardiovascular Disease in a Rural Population of China

Abstract

Objective. To explore the relationship between vascular overload index (VOI) and cardiovascular disease (CVD) in rural population and find effective ways to prevent cardiovascular disease in rural low-income populations. Methods. The data for this study was obtained from a large cohort study called the Northeast China Rural Cardiovascular Health Study (NCRCHS) conducted in 2013 and followed up during 2015-2018. 10,174 subjects completed at least one follow-up visit. Cox regression equation was used to explore whether VOI and cardiovascular disease were independently related. The Kaplan-Meier curves were used to calculate the cumulative incidence of any adverse outcome, and the log-rank test and restrict mean survival analysis were used to compare group differences. Reclassification and discrimination statistics were used to determine whether VOI could strengthen the ability of the model to predict CVD events. Results. The prevalence of CVD in the VOI quartiles was 1.92%, 3.96%, 5.42%, and 11.34% for Q1–Q4, respectively ( $P$ for trend <0.001). After adjusting for multiple confounders, there was a 2.466-fold increased risk of CVD when comparing the highest and lowest groups. Besides, this study found that for every standard deviation increase, the results still exist. The risk of cardiovascular disease increased by 1.358-fold in this model. The restrict mean survival analysis results show that with the increase of VOI, the restrict mean survival time (RMST) within 5 years gradually became shorter. Reclassification and discrimination statistics indicated that VOI significantly enhanced the ability to estimate CVD events within 4 years. Conclusion. Analyses showed that VOI was significantly associated with CVD. VOI is a simple and accurate prognostic marker of CVD risk, which has the potential ability to improve the risk stratification of CVD.