<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04404504</url>
  </required_header>
  <id_info>
    <org_study_id>18-8162</org_study_id>
    <nct_id>NCT04404504</nct_id>
  </id_info>
  <brief_title>Smartphone-App Based Prediction of Large Vessel Occlusion</brief_title>
  <official_title>Smartphone-App Based Prediction of Large Vessel Occlusion in Suspected Stroke by Emergency Medical Service Using FAST-ED</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University Hospital, Essen</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>University Hospital, Essen</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The aim of this non-interventional study is to evaluate a German version of the triage&#xD;
      stroke-score FAST-ED performed by ambulance service personnel in a pre-hospital setting using&#xD;
      a smartphone app (Join-Triage, Allm).&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The emergency service of the city of Essen (NRW, Germany), which is organised by the Essen&#xD;
      fire-department, will perform a prehospital triage stroke-score using a smartphone-app&#xD;
      (Join-Triage, Allm) when referring patients with suspected stroke to the university clinic&#xD;
      Essen. The triage stroke-score FAST-ED (Field Assessment Stroke Triage for Emergency&#xD;
      Destination), as well as the expected time of arrival will be transmitted by an additional&#xD;
      smartphone-app in advance of the arrival (Join, Allm). Patients will receive emergency workup&#xD;
      to identify stroke etiology and presence of large vessel occlusion. Final diagnosis, presence&#xD;
      of large vessel occlusion and type of revascularisation treatment will be registered.&#xD;
      Sensitivity, specificity and further criteria for test quality will be calculated for the&#xD;
      stroke triage by emergency service in field using the FAST-ED.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">March 20, 2019</start_date>
  <completion_date type="Actual">December 30, 2020</completion_date>
  <primary_completion_date type="Actual">August 1, 2020</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Other</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Presence of large vessel occlusion</measure>
    <time_frame>Baseline</time_frame>
    <description>Acute stroke due to large vessel occlusion as measured by computed tomography angiography (CT-A)</description>
  </primary_outcome>
  <enrollment type="Actual">200</enrollment>
  <condition>Acute Stroke</condition>
  <eligibility>
    <study_pop>
      <textblock>
        All adult patients with suspected acute stroke that are transferred by the Essen emergency&#xD;
        service to the university hospital Essen shall be recruited&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        All patients above the age of 18 with suspected acute stroke transferred to the university&#xD;
        hospital Essen.&#xD;
&#xD;
        Inclusion criteria: suspected acute stroke, age above 18 years and a digitally transmitted&#xD;
        FAST-ED by EMS prior to admission.&#xD;
&#xD;
        Exclusion criteria: Known symptom onset beyond 24 Hours.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Martin Köhrmann, Prof. Dr.</last_name>
    <role>Study Director</role>
    <affiliation>University Hospital, Essen</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University Hospital, Essen</name>
      <address>
        <city>Essen</city>
        <state>NRW</state>
        <zip>45147</zip>
        <country>Germany</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Germany</country>
  </location_countries>
  <results_reference>
    <citation>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.</citation>
    <PMID>34804205</PMID>
  </results_reference>
  <verification_date>August 2022</verification_date>
  <study_first_submitted>May 18, 2020</study_first_submitted>
  <study_first_submitted_qc>May 21, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">May 27, 2020</study_first_posted>
  <last_update_submitted>August 29, 2022</last_update_submitted>
  <last_update_submitted_qc>August 29, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">September 1, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University Hospital, Essen</investigator_affiliation>
    <investigator_full_name>Martin Köhrmann</investigator_full_name>
    <investigator_title>Prof. Dr. med.</investigator_title>
  </responsible_party>
  <keyword>Prehospital Triage</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Stroke</mesh_term>
  </condition_browse>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04404504
org study id: 18-8162
nct id: NCT04404504
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
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.
observational model: Other
time perspective: Prospective
measure: Presence of large vessel occlusion
time frame: Baseline
description: Acute stroke due to large vessel occlusion as measured by computed tomography angiography (CT-A)
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Martin Köhrmann, Prof. Dr.
role: Study Director
affiliation: University Hospital, Essen
facility: 
country: Germany
citation: 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: 34804205
responsible party type: Principal Investigator
investigator affiliation: University Hospital, Essen
investigator full name: Martin Köhrmann
investigator title: Prof. Dr. med.
mesh term: Stroke