FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service

Abstract

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://ichgcp.net/clinical-trials-registry/NCT04404504" title="See in ClinicalTrials.gov">NCT04404504.

Keywords: EMS; FAST-ED; prehospital LVO thrombectomy identification; stroke; triage.

Conflict of interest statement

Conflict of interest statement: The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: No authors received any payments for work on the submitted manuscript. B.F. and M.K. report modest fees for advisory roles with Allm Inc. R.G.N. reports consulting fees for advisory roles with Anaconda, Biogen, Cerenovus, Genentech, Imperative Care, Medtronic, Phenox, Prolong Pharmaceuticals, and Stryker Neurovascular and stock options for advisory roles with Astrocyte, Brainomix, Cerebrotech, Ceretrieve, Corindus Vascular Robotics, Vesalio, Viz-AI, and Perfuze. The other authors refer no conflicts of interest.

© The Author(s), 2021.

Figures

Figure 1.

Flow chart of the algorithm used in JoinTriage.

Figure 2.

Flow chart with description of subgroups based on final discharge diagnosis and FAST-ED scale dichotomized between 3 and 4.

Figure 3.

Sensitivity (squares), specificity (circles), and positive predictive value (triangles) of different cut-off values of the FAST-ED scale for the detection of large vessel occlusion.

Figure 4.

Distribution of acute ischemic stroke with large vessel occlusion (AIS with LVO; black), without LVO (AIS without LVO; gray), intracranial hemorrhage (ICH; dashed), and stroke mimics (mimic; white) across FAST-ED scores.