title: Patient characteristics affecting stroke identification by emergency medical service providers in Brooklyn, New York.
abstract: Early identification of stroke should begin in the prehospital phase because the benefits of thrombolysis and clot extraction are time dependent. This study aims to identify patient characteristics that affect prehospital identification of stroke by Long Island college hospital (LICH) emergency medical services (EMS). All suspected strokes brought to LICH by LICH ambulances from January 1, 2010 to December 31, 2011 were included in the study. We compared prehospital care report-based diagnosis against the get with the guidelines (GWTG) database. Age-adjusted logistic regression models were used to study that the effect of individual patient characteristics have on EMS providers' diagnosis. Included in the study were 10,384 patients with mean age 43.9 years. Of whom, 75 had a GWTG cerebrovascular diagnosis: 53 were ischemic strokes, 7 transient ischemic attacks, 3 subarachnoid hemorrhage, and 12 intercerebral bleeds. LICH EMS correctly identified 44 of 75 GWTG strokes. Fifty-one patients were overcalled as stroke by the EMS. Overall EMS sensitivity was 58.7 % and specificity was 99.5 %. Dispatcher call type of altered mental status, stroke, unconsciousness, and increasing prehospital blood pressure quartile were found to be significantly predictive of a true stroke diagnosis. Patients with a past medical history and EMS providers' impression of seizures were more likely to be overcalled as a stroke in the field. More than a third of actual stroke patients were missed in the field in our study. Our results show that the patients' past medical history, dispatcher collected information and prehospital vital sign measurements are associated with a true diagnosis of stroke.
authors.affiliation: Department of Community Medicine, Government Medical College and Guru Nanak Dev Hospital, Amritsar, 143001, India. mohitsharma.dr@gmail.com.
authors.forename: Mohit
authors.initials: M
authors.lastname: Sharma
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Medical Center, Brooklyn, NY, USA. elizabeth.helzner@downstate.edu.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Helzner
authors.affiliation: Department of Emergency Medicine, SUNY Downstate Medical Center and Kings County Hospital Center, Brooklyn, NY, USA. richard.sinert@downstate.edu.
authors.forename: Richard
authors.initials: R
authors.lastname: Sinert
authors.affiliation: Department of Emergency Medicine, SUNY Downstate Medical Center and Kings County Hospital Center, Brooklyn, NY, USA. steven.levine@downstate.edu.|Department of Neurology, SUNY Downstate Medical Center and Kings County Hospital Center, Brooklyn, NY, USA. steven.levine@downstate.edu.
authors.forename: Steven Richard
authors.initials: SR
authors.lastname: Levine
authors.affiliation: Department of Emergency Medicine, SUNY Stony Brook Medicine, Stony Brook, NY, USA. ethan.brandler@stonybrookmedicine.edu.
authors.forename: Ethan Samuel
authors.initials: ES
authors.lastname: Brandler
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D004632:Emergency Medical Services; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009519:New York City; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D020521:Stroke / Q000175:diagnosis*; D055815:Young Adult
keywords: Ambulance; Emergency medical services; Prehospital; Stroke