CLINICAL AND GENETIC PREDICTORS OF STROKE RECURRENCE AFTER ISCHEMIC EVENTS

Abstract

Stroke recurrence remains a leading cause of disability and death among ischemic stroke survivors. In a prospective cohort of 500 adults (aged 45–85 years) with first-ever ischemic stroke, we evaluated the combined utility of clinical risk factors and a genome-wide polygenic risk score (PRS) for predicting recurrent events over 12 months. Baseline prevalence of hypertension (68%), diabetes (24%), dyslipidemia (57%), and atrial fibrillation (18%) was consistent with high-risk profiles. In univariable Cox analyses, hypertension (HR 1.80, 95% CI 1.50–2.15), atrial fibrillation (HR 2.10, 95% CI 1.65–2.65), diabetes (HR 1.45, 95% CI 1.10–1.90), and each SD increase in PRS (HR 1.25, 95% CI 1.10–1.42) were all significant predictors (p < 0.01). Patients in the highest PRS tertile experienced a 25.1% one-year recurrence rate versus 9.0% in the lowest tertile (HR 2.90, 95% CI 1.70–4.95; p < 0.001). A combined clinical-genetic Cox model achieved a C-index of 0.81 and demonstrated superior calibration compared with clinical-only (C-index 0.72) or genetic-only (C-index 0.68) models. Random forest analyses corroborated the primacy of atrial fibrillation and hypertension but also ranked PRS, age, and diabetes among the top five importance metrics. Semi-structured interviews (n = 40) identified medication adherence barriers and lifestyle modification challenges as prevalent patient-reported obstacles to effective secondary prevention. Our findings support an integrative risk-stratification paradigm that merges genomic profiling with traditional clinical assessment to identify high-risk survivors for targeted interventions—such as intensified blood pressure control, novel antithrombotic therapy, and adherence support—to reduce recurrent stroke burden.