Establishment and validation of a prediction model for ischemic stroke risks in patients with type 2 diabetes

A risk scoring system for predicting ischemic stroke incidence may identify type 2 diabetes patients at high risk for ischemic stroke who can benefit from preventive intervention programs. Such a risk scoring system can serve as a benchmark to test novel putative risk factors.

The study adopted a retrospective cohort, including 28,124 Chinese patients with type 2 diabetes aged 30-84 years during 2001-2004. Participants were randomly assigned to the derivation and validation sets at a 2:1 ratio. Cox's proportional hazard regression model was used to identify risk factors of ischemic stroke incidence in the derivation set. And then the steps proposed by the Framingham Heart Study for establishing an ischemic stroke prediction model with a scoring system was used.

Among 9374 patients in the validation set, 1076 subjects (11.48%) developed ischemic stroke with a mean follow up period of 8.0 years. We identified the following risk factors: age, gender, smoking habit, duration of type 2 diabetes, blood pressure, HbA1c level, total cholesterol to high-density lipoprotein ratio, creatinine, fasting plasma glucose variation (FPG-CV), arterial embolism and thrombosis, diabetes retinopathy, hypoglycemia, anti-diabetes medication use, and cardiovascular medication. The area under receiver operating characteristic curve of the 3-year, 5-year, and 8-year ischemic stroke incidence risks were 0.72, 0.71, and 0.68 for the validation set, respectively.

This proposed ischemic stroke incidence risk prediction model is the first model established for Chinese patients with type 2 diabetes recruited from nationwide clinical settings.