@Article{duepublico_mods_00076290, author = {Frank, Benedikt and Fabian, Felix and Brune, Bastian and Bozkurt, Bessime and Deuschl, Cornelius and Nogueira, Raul G. and Kleinschnitz, Christoph and K{\"o}hrmann, Martin}, title = {Validation of a shortened FAST-ED algorithm for smartphone app guided stroke triage}, year = {2021}, month = {Nov}, day = {23}, keywords = {EMS; FAST-ED; identification; LVO; prehospital; Stroke Triage; thrombectomy}, abstract = {Background and Purpose: Large vessel occlusion (LVO) recognition scales were developed to identify patients with LVO-related acute ischemic stroke (AIS) on the scene of emergency. Thus, they may enable direct transport to a comprehensive stroke centre (CSC). In this study, we aim to validate a smartphone app-based stroke triage with a shortened form of the Field Assessment Stroke Triage for Emergency Destination (FAST-ED). Methods: This retrospective validation study included 2815 patients with confirmed acute stroke and suspected acute stroke but final diagnosis other than stroke (stroke mimics) who were admitted by emergency medical service (EMS) to the CSC of the Neurological University Hospital Essen, Germany. We analysed the predictive accuracy of a shortened digital app-based FAST-ED ( 'FAST-ED App') for LVO-related AIS and yield comparison to various other LVO recognition scales. Results: The shortened FAST-ED App had comparable test quality (Area under ROC = 0.887) to predict LVO-related AIS to the original FAST-ED (0.889) and RACE (0.883) and was superior to Cincinnati Prehospital Stroke Severity (CPSS), 3-Item Stroke Scale (3-ISS) and National Institute of Health Stroke Scale (NIHSS). A FAST-ED App ⩾ 4 revealed very good accuracy to detect LVO related AIS (sensitivity of 77{\%} and a specificity 87{\%}) with an area under the curve c-statistics of 0.89 (95{\%} CI: 0.87-0.90). In a hypothetical triage model, the number needed to screen in order to avoid one secondary transportation in an urban setting would be five. Conclusion: This validation study of a shortened FAST-ED assessment for a smartphone-app guided stroke triage yields good quality to identify patients with LVO.}, note = {<p>Frank, B., Fabian, F., Brune, B., Bozkurt, B., Deuschl, C., Nogueira, R. G., Kleinschnitz, C., {\&}amp; K{\"o}hrmann, M. (2021). Validation of a shortened FAST-ED algorithm for smartphone app guided stroke triage. <em>Therapeutic Advances in Neurological Disorders</em>. <a href="https://doi.org/10.1177{\%}2F17562864211057639">https://doi.org/10.1177/17562864211057639</a></p> <p>Article first published online: November 23, 2021</p>}, note = {Version of Record / Verlagsversion}, note = {<p>The publication of this article was supported by the Publication Fund of the University of Duisburg-Essen.</p>}, doi = {10.1177/17562864211057639}, url = {https://duepublico2.uni-due.de/receive/duepublico_mods_00076290}, url = {https://doi.org/10.1177/17562864211057639}, file = {:https://duepublico2.uni-due.de/servlets/MCRFileNodeServlet/duepublico_derivate_00076050/Frank_et_al_2021_Validation_shortened_FAST-ED.pdf:PDF}, language = {en} }