FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service
Background and Purpose: Considering the highly time-dependent therapeutic effect of endovascular treatment in patients with large vessel occlusion–associated acute ischemic stroke, prehospital identification of large vessel occlusion and subsequent triage for direct transport to a comprehensive stro...
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| Autores principales: | , , , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
SAGE Publishing
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/2d5bf63e619e4763a8d6367f0e5ed4a2 |
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| Sumario: | Background and Purpose: Considering the highly time-dependent therapeutic effect of endovascular treatment in patients with large vessel occlusion–associated acute ischemic stroke, prehospital identification of large vessel occlusion and subsequent triage for direct transport to a comprehensive stroke center offers an intriguing option for optimizing patient pathways. Methods: This prospective in-field validation study included 200 patients with suspected acute ischemic stroke who were admitted by emergency medical service to a comprehensive stroke center. Ambulances were equipped with smartphones running an app-based Field Assessment Stroke Triage for Emergency Destination scale for transmission prior to admission. The primary measure was the predictive accuracy of the transmitted Field Assessment Stroke Triage for Emergency Destination for large vessel occlusion and the secondary measure the predictive accuracy for endovascular treatment. Results: A Field Assessment Stroke Triage for Emergency Destination ⩾4 revealed very good accuracy to detect large vessel occlusion–related acute ischemic stroke with a sensitivity of 82.4% (95% confidence interval = 65.5–93.2), specificity of 78.3% (95% confidence interval = 71.3–84.3), and an area under the curve c -statistics of 0.89 (95% confidence interval = 0.85–0.94). Field Assessment Stroke Triage for Emergency Destination ⩾4 correctly identified 84% of patients who received endovascular treatment [73.5% specificity (95% confidence interval = 66.4–79.8)] with an area under the curve c -statistics of 0.82 (95% confidence interval = 0.74–0.89). In a hypothetical triage model of an urban setting, one secondary transportation would be avoided with every fifth patient screened. Conclusion: A smartphone app-based stroke triage completed by emergency medical service personnel showed adequate quality for the Field Assessment Stroke Triage for Emergency Destination to identify large vessel occlusion–associated acute ischemic stroke. We demonstrate feasibility of the use of a medical messaging service in prehospital stroke care. Based on these first results, a randomized trial evaluating the clinical benefit of such a triage system in an urban setting is currently in preparation. Clinical Trial Registration: https://clinicaltrials.gov Unique identifier: NCT04404504. |
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