Background. Patients with a history of transient ischemic attack (TIA) are known to be at higher risk for a stroke. We sought to investigate predictors of individual risk for an ischemic stroke within 30 days of a TIA. Methods and Results. A retrospective analysis of 57,585 TIA admissions was collected from 155 United States hospitals. Data describing each admission included demographic and clinical data, and information about the admitting hospital. Cerebrovascular disease was the primary readmission reason (19% of readmissions) in the TIA patient population. The prevalence of 30-day ischemic stroke readmissions was 11 per 1,000 TIA admissions; however, 53% of stroke readmissions occurred within one week. Hierarchal regression models suggested that peripheral vascular disease and hypertensive chronic kidney disease were significant individual stroke risk factors, whereas history of myocardial infarction, essential hypertension, and diabetes mellitus was not associated with significant stroke risk. Certified stroke centers were not associated with significantly lower stroke readmission rates. Conclusions. The results suggest that cardiovascular comorbidities confer the most significant risk for an ischemic stroke within 30 days of a TIA. Interestingly, certified stroke centers do not appear to be associated with significantly lower stroke-readmission rates, highlighting the challenges managing this patient population. 1. Introduction Annually, as many as 250,000 Americans may experience a transient ischemic attack (TIA); the annual worldwide incidence of TIA may exceed one million [1]. The 6-month mortality rate has been estimated to be as high as 8.3% in this patient population [2]. TIA is therefore associated with significant morbidity and mortality in the United States and globally. TIAs are significant risk factors for stroke with as many as 19% of acute strokes preceded by TIA [3, 4]. Several studies have identified risk factors for stroke in patients with history of TIA [2, 3, 5–7]; however, the contribution of these factors to a patient’s overall stroke risk has yet to be comprehensively studied. Identifying TIA patients at risk for a stroke is an important component of targeting preventive therapies. In the present study, we develop a risk-standardized model to (i) quantify the contribution of demographic and clinical factors to stroke risk and (ii) to identify TIA patients at high-risk for stroke. The model is also suitable for comparing stroke readmission rates across hospitals to gain insight into how hospitalization may affect stroke rates
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