Can a nomogram composed of clinical and demographic factors predict the risk of stroke recurrence among young adults after first-ever ischemic stroke?
A newly developed nomogram incorporating hypertension, diabetes, smoking, stroke cause, and education level can effectively stratify the risk of stroke recurrence in young adults.
Background and Purpose— This study aimed to develop and validate a nomogram for predicting the risk of stroke recurrence among young adults after ischemic stroke. Methods— Patients aged between 18 and 49 years with first-ever ischemic stroke were selected from the Nanjing Stroke Registry Program. A stepwise Cox proportional hazards regression model was employed to develop the best-fit nomogram. The discrimination and calibration in the training and validation cohorts were used to evaluate the nomogram. All patients were classified into low-, intermediate-, and high-risk groups based on the risk scores generated from the nomogram. Results— A total of 604 patients were enrolled in this study. Hypertension (hazard ratio HR, 2.038 95% CI, 1.504–3.942; P =0.034), diabetes mellitus (HR, 3.224 95% CI, 1.848–5.624; P 12 versus 0–6; HR, 0.070 95% CI, 0.015–0.319; P =0.001) were inversely correlated with recurrent stroke. The nomogram was composed of these factors, and successfully stratified patients into low-, intermediate-, and high-risk groups ( P <0.001). Conclusions— The nomogram composed of hypertension, diabetes mellitus, smoking status, stroke cause, and education years may predict the risk of stroke recurrence among young adults after ischemic stroke.
Yuan et al. (Mon,) studied this question.