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A Nomogram-Based Clinical Tool for Acute Ischemic Stroke Screening in Prehospital Setting Publisher



Baratloo A1, 2 ; Ramezani M3, 4 ; Rafiemanesh H5, 6 ; Sharifi M2 ; Karimi S2
Authors
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Authors Affiliations
  1. 1. Research Center for Trauma in Police Operations, Directorate of Health, Rescue & Treatment, Police Headquarter, Tehran, Iran
  2. 2. Prehospital and Hospital Emergency Research Center, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Department of Neurology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  4. 4. Skull Base Research Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  5. 5. Non-Communicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran
  6. 6. Department of Epidemiology and Biostatistics, School of Public Health, Alborz University of Medical Sciences, Karaj, Iran

Source: Current Journal of Neurology Published:2023


Abstract

Background: We believe that designing a new tool which is comparable in terms of both sensitivity and specificity may play an important role in rapid and more accurate diagnosis of acute ischemic stroke (AIS) in prehospital stage. Therefore, we intended to develop a new clinical tool for the diagnosis of AIS in the prehospital stage. Methods: This was a cross-sectional diagnostic accuracy study. All patients transferred to the emergency department (ED) who underwent brain magnetic resonance imaging (MRI) with impression of AIS were evaluated by 9 clinical tools for stroke diagnosis in the pre-hospital phase including Rapid Arterial Occlusion Evaluation (RACE), Cincinnati Prehospital Stroke Scale (CPSS), Los Angeles Prehospital Stroke Screen (LAPSS), Melbourne Ambulance Stroke Screen (MASS), Medic Prehospital Assessment for Code Stroke (Med PACS), Ontario Prehospital Stroke Screening Tool (OPSS), PreHospital Ambulance Stroke Test (PreHAST), Recognition of Stroke in the Emergency Room (ROSIER), and Face Arm Speech Test (FAST), and totally 19 items were reviewed and recorded. The new clinical tool was developed based on backward method of multivariable logistic regression analysis. The discrimination power of the new clinical tool for diagnosis of AIS was assessed with the area under the receiver operating characteristic curve (AUC-ROC). © 2023 Iranian Neurological Association, and Tehran University of Medical Sciences Corresponding Author: Somayeh Karimi Published by Tehran University of Medical Sciences.