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The aim of this non-interventional study is to evaluate a German version of the triage stroke-score FAST-ED performed by ambulance service personnel in a pre-hospital setting using a smartphone app (Join-Triage, Allm).
The emergency service of the city of Essen (NRW, Germany), which is organised by the Essen fire-department, will perform a prehospital triage stroke-score using a smartphone-app (Join-Triage, Allm) when referring patients with suspected stroke to the university clinic Essen. The triage stroke-score FAST-ED (Field Assessment Stroke Triage for Emergency Destination), as well as the expected time of arrival will be transmitted by an additional smartphone-app in advance of the arrival (Join, Allm). Patients will receive emergency workup to identify stroke etiology and presence of large vessel occlusion. Final diagnosis, presence of large vessel occlusion and type of revascularisation treatment will be registered. Sensitivity, specificity and further criteria for test quality will be calculated for the stroke triage by emergency service in field using the FAST-ED.
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| Measure | Description | Time Frame |
|---|---|---|
| Presence of large vessel occlusion | Acute stroke due to large vessel occlusion as measured by computed tomography angiography (CT-A) | Baseline |
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All patients above the age of 18 with suspected acute stroke transferred to the university hospital Essen.
Inclusion criteria: suspected acute stroke, age above 18 years and a digitally transmitted FAST-ED by EMS prior to admission.
Exclusion criteria: Known symptom onset beyond 24 Hours.
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All adult patients with suspected acute stroke that are transferred by the Essen emergency service to the university hospital Essen shall be recruited
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| Name | Affiliation | Role |
|---|---|---|
| Martin Köhrmann, Prof. Dr. | University Hospital, Essen | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University Hospital, Essen | Essen | North Rhine-Westphalia | 45147 | Germany |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34804205 | Result | Frank B, Lembeck T, Toppe N, Brune B, Bozkurt B, Deuschl C, Nogueira RG, Dudda M, Risse J, Kill C, Forsting M, Kleinschnitz C, Kohrmann M. FAST-ED scale smartphone app-based prediction of large vessel occlusion in suspected stroke by emergency medical service. Ther Adv Neurol Disord. 2021 Nov 14;14:17562864211054962. doi: 10.1177/17562864211054962. eCollection 2021. |
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| ID | Term |
|---|---|
| D020521 | Stroke |
| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |