Smartphone-App Based Prediction of Large Vessel Occlusion
1 other identifier
observational
200
1 country
1
Brief Summary
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).
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Mar 2019
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
March 20, 2019
CompletedFirst Submitted
Initial submission to the registry
May 18, 2020
CompletedFirst Posted
Study publicly available on registry
May 27, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
August 1, 2020
CompletedStudy Completion
Last participant's last visit for all outcomes
December 30, 2020
CompletedSeptember 1, 2022
August 1, 2022
1.4 years
May 18, 2020
August 29, 2022
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Presence of large vessel occlusion
Acute stroke due to large vessel occlusion as measured by computed tomography angiography (CT-A)
Baseline
Eligibility Criteria
All adult patients with suspected acute stroke that are transferred by the Essen emergency service to the university hospital Essen shall be recruited
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
University Hospital, Essen
Essen, North Rhine-Westphalia, 45147, Germany
Related Publications (1)
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.
PMID: 34804205RESULT
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- STUDY DIRECTOR
Martin Köhrmann, Prof. Dr.
University Hospital, Essen
Study Design
- Study Type
- observational
- Observational Model
- OTHER
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Prof. Dr. med.
Study Record Dates
First Submitted
May 18, 2020
First Posted
May 27, 2020
Study Start
March 20, 2019
Primary Completion
August 1, 2020
Study Completion
December 30, 2020
Last Updated
September 1, 2022
Record last verified: 2022-08