Construction of an Early Warning Model for Ischemic Stroke Recurrence Based on Generalized Estimating Equation

Objective: To explore the appropriate modeling method of the early warning model of ischemic stroke recurrence in TCM. Methods: This was a prospective, multi-center and registered study conducted in 7 clinical subcenters from 8 provinces and 10 cities in China between 3 rd November 2016 and 27 th April, 2019. 1,741 patients with first-ever ischemic stroke were recruited. Univariate analysis was carried out using distance correlation coefficient, mutual information entropy, and statistical correlation test. Multivariate analysis adopted multi-factor Cox regression model and combined with expert opinions in the field of stroke to determine modeling variables. The generalized estimating equation of longitudinal data and the Cox proportional hazard regression model of cross-sectional data were used to construct and compare in the early warning model of ischemic stroke recalls. The area under the ROC curve(AUC value) was used to evaluate the early warning capability of the model. Results: The follow-up time was 1-3 years, and the median follow-up time was 1.42 years(95% CI: 1.37-1.47). Recurrence events occurred in 175 cases, and the cumulative recurrence rate was 10.05%(95% CI: 8.64%-11.47%). The AUC values of the TCM syndrome and TCM constitution model were 0.71809 and 0.72668 based on the generalized estimating equation and the AUC values. Conclusion: The generalized estimating equation may be more suitable for the construction of early warning models of stroke recurrence with TCM characteristics, which provides a certain reference for the evaluation of secondary prevention of ischemic stroke.