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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: Frank, Benedikt, Lembeck, Thomas, Toppe, Nina, Brune, Bastian, Bozkurt, Bessime, Deuschl, Cornelius, Nogueira, Raul G., Dudda, Marcel, Risse, Joachim, Kill, Clemens, Forsting, Michael, Kleinschnitz, Christoph, Köhrmann, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8597063/
https://www.ncbi.nlm.nih.gov/pubmed/34804205
http://dx.doi.org/10.1177/17562864211054962
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author Frank, Benedikt
Lembeck, Thomas
Toppe, Nina
Brune, Bastian
Bozkurt, Bessime
Deuschl, Cornelius
Nogueira, Raul G.
Dudda, Marcel
Risse, Joachim
Kill, Clemens
Forsting, Michael
Kleinschnitz, Christoph
Köhrmann, Martin
author_facet Frank, Benedikt
Lembeck, Thomas
Toppe, Nina
Brune, Bastian
Bozkurt, Bessime
Deuschl, Cornelius
Nogueira, Raul G.
Dudda, Marcel
Risse, Joachim
Kill, Clemens
Forsting, Michael
Kleinschnitz, Christoph
Köhrmann, Martin
author_sort Frank, Benedikt
collection PubMed
description 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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spelling pubmed-85970632021-11-18 FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service Frank, Benedikt Lembeck, Thomas Toppe, Nina Brune, Bastian Bozkurt, Bessime Deuschl, Cornelius Nogueira, Raul G. Dudda, Marcel Risse, Joachim Kill, Clemens Forsting, Michael Kleinschnitz, Christoph Köhrmann, Martin Ther Adv Neurol Disord Original Research 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. SAGE Publications 2021-11-14 /pmc/articles/PMC8597063/ /pubmed/34804205 http://dx.doi.org/10.1177/17562864211054962 Text en © The Author(s), 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Frank, Benedikt
Lembeck, Thomas
Toppe, Nina
Brune, Bastian
Bozkurt, Bessime
Deuschl, Cornelius
Nogueira, Raul G.
Dudda, Marcel
Risse, Joachim
Kill, Clemens
Forsting, Michael
Kleinschnitz, Christoph
Köhrmann, Martin
FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service
title FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service
title_full FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service
title_fullStr FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service
title_full_unstemmed FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service
title_short FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service
title_sort fast-ed scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8597063/
https://www.ncbi.nlm.nih.gov/pubmed/34804205
http://dx.doi.org/10.1177/17562864211054962
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