• Benedikt Frank, Felix Fabian, Bastian Brune, Bessime Bozkurt, Cornelius Deuschl, Raul G Nogueira, Christoph Kleinschnitz, and Martin Köhrmann.
• Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Hospital Essen, Essen, Germany.
• Ther Adv Neurol Disord. 2021 Jan 1; 14: 17562864211057639.

Background And PurposeLarge 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).MethodsThis 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.ResultsThe 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.ConclusionThis validation study of a shortened FAST-ED assessment for a smartphone-app guided stroke triage yields good quality to identify patients with LVO.© The Author(s), 2021.

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