Prevalence and Determinants of Prehospital Impression of Stroke in Ischemic Stroke Patients.

Autor:	Caffarelli M; Department of Pediatrics, University of California, San Francisco. San Francisco, CA.; Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco. San Francisco, CA., Wood AJ; Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco. San Francisco, CA., Crowe RP; ESO, Inc., Austin, Tx., Amorim E; Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco. San Francisco, CA., Kamel H; Department of Neurology, Weill Cornell Medicine, New York, NY., Kim AS; Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco. San Francisco, CA., Guterman EL; Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco. San Francisco, CA.; UCSF Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco. San Francisco, CA.
Jazyk:	angličtina
Zdroj:	MedRxiv : the preprint server for health sciences [medRxiv] 2024 Sep 27. Date of Electronic Publication: 2024 Sep 27.
DOI:	10.1101/2024.09.25.24314407
Abstrakt:	Background: Emergency Medical Services (EMS) clinicians are front-line in evaluating patients with stroke in the community. Their ability to correctly identify stroke influences downstream management decisions. We sought to use a large national database of prehospital clinical data to determine risk factors associated with missed EMS stroke identification. Methods: Retrospective study examining EMS evaluation of adults with Emergency Department (ED) stroke diagnosis. We leveraged the ESO Data Collaborative research dataset containing EHR data from 2019-2022 that has a subset of encounters with linked hospital diagnostic codes. Our primary outcome was the presence of an EMS diagnosis of stroke. We evaluated the association between demographic and clinical variables with EMS stroke identification using Pearson χ2 test for demographic variables and multivariable GLM for clinical variables with adjustment for demographic variables. Results: We identified 34,504 EMS encounters for patients with ED stroke diagnosis. Of these, 11,077 (32.1%) strokes had missed EMS stroke identification and instead had an EMS impression of "Generalized Weakness" (25.9%), "Altered Level of Consciousness" (24.9%), and "Dizziness" (7.2%). Patients more likely to have missed prehospital stroke identification were of Black race (p=0.0001) and Hispanic ethnicity (p=0.0001). Clinical variables associated with higher risk of missed EMS stroke identification were suspected alcohol or drug use (RR 1.48, 95% CI 1.37-1.59), low GCS (RR 1.17, 95% CI 1.10-1.24), tachycardia (RR 1.05, 95% CI 1.01-1.09), and hypotension (RR 1.47, 95% CI 1.34-1.61). Conclusions: Approximately 1-in-3 patients transported by EMS did not have their stroke identified in the prehospital setting. Factors associated with lower odds of missed EMS stroke identification provide a starting point for future performance improvement initiatives.
Databáze:	MEDLINE
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