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Updated: May 10, 2026

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide
Published on: January 15, 2017
Identification of stroke mimics in the emergency department setting
W Oliver Tobin1, Joseph G Hentz, Bentley J Bobrow
1Department of Neurology, Adelaide and Meath Hospital, Dublin, incorporating the National Children's Hospital, Trinity College Dublin, Republic of Ireland. ; Department of Neurology, Mayo Clinic Arizona, U.S.A.
Background And Purpose:
Previous studies have shown a stroke mimic rate of 9%-31%. We aimed to establish the proportion of stroke mimics amongst suspected acute strokes, to clarify the aetiology of stroke mimic and to develop a prediction model to identify stroke mimics.
Methods:
This was a retrospective cohort observational study. Consecutive "stroke alert" patients were identified over nine months in a primary stroke centre. 31 variables were collected. Final diagnosis was defined as "stroke" or "stroke mimic". Multivariable regression analysis was used to define clinical predictors of stroke mimic.
Results:
206 patients were reviewed. 22% were classified as stroke mimics. Multivariable scoring did not help in identification of stroke mimics. 99.5% of patients had a neurological diagnosis at final diagnosis.
Discussion:
22% of patients with suspected acute stroke had a stroke mimic. The aetiology of stroke mimics was varied, with seizure, encephalopathy, syncope and migraine being commonest. Multivariable scoring for identification of stroke mimics is not feasible. 99.5% of patients had a neurological diagnosis. This strengthens the case for the involvement of stroke neurologists/stroke physicians in acute stroke care.
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