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Abstract Details

Evaluation of Acute Stroke and Stroke Mimics in the Emergency Department
Cerebrovascular Disease and Interventional Neurology
P7 - Poster Session 7 (5:30 PM-6:30 PM)
4-017
To determine the characteristics of patients who present with acute stroke versus stroke mimics.

Identifying patients with acute stroke symptoms quickly is a process primarily based on history and neurological exam in order to determine eligibility for tissue plasminogen activator (tPA). There is a risk for misdiagnosis that puts the patient at risk for receiving tPA unnecessarily. Therefore, differentiating stroke from mimics is necessary to improve patient safety.
Retrospective chart review of all patients who underwent a stroke code at a comprehensive stroke center in Newark, NJ in 2016. Acute stroke (ischemic or hemorrhagic) was confirmed with MRI or CT scan changes commensurate with clinical presentation. TIA patients were excluded from intergroup analysis given that their presentation at time of ED evaluation differs from their presentation before arriving.
499 stroke codes were analyzed. 262 (52%) patients were diagnosed with acute ischemic or hemorrhagic events (mean age 63). Of these, 61% were ischemic, 22% hemorrhagic and 16% TIA. 48% of stroke codes were ultimately stroke mimics (mean age 58). Seizure was the most common stroke mimic (12%), followed by non-physiological events (6%), sepsis (3%), and cardiogenic events (3%). Male sex, history of hypertension, atrial fibrillation, facial palsy or unilateral weakness were strong predictive factors for stroke with significant differences between the two groups. History of seizure disorder and seizure at presentation, migraine, chronic alcohol use, chest pain, sensory deficit in extremities and high oral temperature were strong predictors for stroke mimics. Total NIH Stroke Scale score was significantly different between the two groups, though a higher score was not predictive for acute stroke.

Almost half of the patients who had a stroke code were diagnosed with a stroke mimic. Further work is underway to investigate whether a predictive model can be used to detect stroke mimics based on our patient population.
Authors/Disclosures
Yasser Tajali, MD (Harford Healthcare)
PRESENTER 		No disclosure on file
Julian Agin-Liebes, MD (Columbia University Medical Center) Dr. Agin-Liebes has nothing to disclose.
No disclosure on file
Kevin Spiegler, MD, PhD (NYU Langone Health) Dr. Spiegler has nothing to disclose.
Nora Montealegre, MD Dr. Montealegre has nothing to disclose.
Tina Lulla No disclosure on file
Carly N. Ray, MD (Icahn School of Medicine at Mount Sinai) No disclosure on file
Prateeka Koul, MD Dr. Koul has nothing to disclose.
Anusha Boyanpally, MBBS No disclosure on file
Francisco E. Gomez III, MD (UPenn) No disclosure on file
Andrea Hidalgo, MD (Rutgers New Jersey Medical School) Dr. Hidalgo has nothing to disclose.