Development of a predictive risk stratification tool to identify population over 45 at risk of new-onset stroke in seven years

Abstract Background and Purpose: With the aging of society, stroke has become a vital health problem for the middle-aged and elderly. Amounts of stroke's new risk factors have been found recently. It is necessary to develop a predictive risk stratification tool containing multi-dimensional risk factors for identifying high-risk people.Methods: The study included 5844 people (Age≥45) who participated in the China Health and Retirement Longitudinal Study, in 2011 and follow-up to 2018. Randomly divided the population into training and validation set by 1:1. Lasso Cox screened predictors for new-onset stroke. Developed a nomogram and stratified the population according to the score calculated in the nomogram through the X-tile program. Internal and external verification of nomogram was performed by ROC and calibration curves, and the Kaplan-Meier method was applied to identify the performance of the risk stratification system.Results: Lasso COX regression screened out 13 candidate predictors from 50 risk factors. Finally, nine predictors, including low physical performance, triglyceride-glucose index, etc., were included in the nomogram. The nomogram's overall performance was good in both internal and external validation (AUCs of three-year, five-year, seven-year in the training set was 0.71, 0.71, 0.71, and 0.67, 0.65, 0.66 in the validation set, respectively). The nomogram was proven to could excellently discriminate between low-, moderate-, and high-risk groups with the 7-year new-onset stroke of 3.36%, 8.32%, and 20.13%, respectively (P<0.001).Conclusions: This research developed a clinical predictive risk stratification tool that can effectively identify the different risks of new-onset stroke incidents in 7-years in the middle-aged and elderly Chinese.