Document Type

Article

Publication Date

9-14-2017

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This Document is Protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permission.

It was published in Frontiers in Neurology, Volume 8, Issue SEP, September 2017, Article number 466.

The published version is available at DOI: 10.3389/fneur.2017.00466. Copyright © Jia et al.

Abstract

BACKGROUND: Accurate recognition of stroke symptoms by Emergency Medical Services (EMS) is necessary for timely care of acute stroke patients. We assessed the accuracy of stroke diagnosis by EMS in clinical practice in a major US city.

METHODS AND RESULTS: Philadelphia Fire Department data were merged with data from a single comprehensive stroke center to identify patients diagnosed with stroke or TIA from 9/2009 to 10/2012. Sensitivity and positive predictive value (PPV) were calculated. Multivariable logistic regression identified variables associated with correct EMS diagnosis. There were 709 total cases, with 400 having a discharge diagnosis of stroke or TIA. EMS crew sensitivity was 57.5% and PPV was 69.1%. EMS crew identified 80.2% of strokes with National Institutes of Health Stroke Scale (NIHSS) ≥5 and symptom durationmodel, correct EMS crew diagnosis was positively associated with NIHSS (NIHSS 5-9, OR 2.62, 95% CI 1.41-4.89; NIHSS ≥10, OR 4.56, 95% CI 2.29-9.09) and weakness (OR 2.28, 95% CI 1.35-3.85), and negatively associated with symptom duration >270 min (OR 0.41, 95% CI 0.25-0.68). EMS dispatchers identified 90 stroke cases that the EMS crew missed. EMS dispatcher or crew identified stroke with sensitivity of 80% and PPV of 50.9%, and EMS dispatcher or crew identified 90.5% of patients with NIHSS ≥5 and symptom duration <6 >h.

CONCLUSION: Prehospital diagnosis of stroke has limited sensitivity, resulting in a high proportion of missed stroke cases. Dispatchers identified many strokes that EMS crews did not. Incorporating EMS dispatcher impression into regional protocols may maximize the effectiveness of hospital destination selection and pre-notification.

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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

PubMed ID

28959230

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