Introduction: Unrecognized, high-risk conditions like transient ischemic attack (TIA) are missed opportunities to initiate timely preventive treatment to reduce the risk of subsequent stroke, disability, and death. Up to 50% of patients with a TIA may have a subsequent disabling stroke, many within 30 days.
Hypothesis: Among patients with an Emergency Department (ED) visit at which no diagnosis of TIA or stroke was recorded, analysis of electronic health record (EHR) data can help predict risk of subsequent stroke.
Methods: We performed a retrospective cohort study of EHR data (2011-2015) from a high-volume comprehensive stroke center with an annual ED volume of >85,000. Patients age 60-89 years who were discharged to home from the ED in <24 hours without ICD-9 diagnosis of TIA or stroke were included for analysis. If patients had >1 qualifying index visit during the study period, we used the first. For each patient we determined presence or absence during the ED visit of a head CT and/or any of these strings in the ED chief complaint (“Symptoms”): slur, speech, aphasia, confuse, word, difficult, comprehen, weak, clumsy, clumsiness, droop, paralysis, move, moving, face, or facial (but not “facial injury”). In four mutually-exclusive categories, CT (Yes/No) by Symptoms (Yes/No), we calculated rate of stroke in the 30, 90, and 365-day periods after discharge from the ED. Ischemic stroke ascertainment was based on diagnostic codes at subsequent ED or hospital visits.
Results: Among 40,450 patients, mean age was 69 years, and 59% were women. Race was 57% white, 15% African-American, 23% other, and 4% unknown. Numbers of patients and rates of stroke by category are shown in the table.
Conclusion: This simple approach established a clinically meaningful risk gradient across four groups. Present and future work to refine this model may contribute to comparative effectiveness research that evaluates management and triage strategies for patients across the stroke risk spectrum.