xml: <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/NCT06013852</url>
    </required_header>
    <id_info>
      <org_study_id>49RC23_0278</org_study_id>
      <nct_id>NCT06013852</nct_id>
    </id_info>
    <brief_title>Impact of Artificial Intelligence Detecting Fractures in the Emergence Department : a Pragmatic Prospective Study</brief_title>
    <official_title>Impact of Artificial Intelligence Detecting Fractures in the Emergence Department : a Pragmatic Prospective Study</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>University Hospital, Angers</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>University Hospital, Angers</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>
        Traumatic emergencies are the primary reason for consultation in emergency departments and&#xD;
        standard radiography is the primary imaging exam for osteoarticular trauma. However, with the&#xD;
        increase in the number of patients admitted to emergency departments and thus the increased&#xD;
        workload for emergency room attendants, Interpretation of radiographs in trauma emergencies&#xD;
        is made more difficult, resulting in a high risk of misinterpretation.&#xD;
  &#xD;
        The growing presence of artificial intelligence in the medical field, notably through the&#xD;
        involvement of diagnostic software on imageries, makes its use more relevant in the aid of&#xD;
        the replay of osteoarticular imageries.&#xD;
  &#xD;
        A recent meta-analysis of 32 studies evaluating the performance of artificial intelligence in&#xD;
        fracture detection found comparable performance between experienced radiologists and AI-based&#xD;
        diagnosis. However, these were mainly retrospective studies, and thus more distant from the&#xD;
        reality of its use in a care stream such as emergencies.&#xD;
  &#xD;
        The objective of this study is therefore to prospectively validate the use of artificial&#xD;
        intelligence software during its implementation in an emergency department for patients&#xD;
        admitted for a suspicion of osteoarticular trauma.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        After completing the X-ray requested, the senior emergency physician reads the X-ray (native&#xD;
        image only), gives his diagnosis (fracture yes/ no and localization) and reports if he&#xD;
        requests the specialist (orthopedist/ radiologist) or not and the reason why he asks for it&#xD;
        (urgent management, doubt about a fracture). After processing the radiography with the&#xD;
        &quot;Boneview&quot; software, the emergency physician makes a second reading taking into account the&#xD;
        analysis of artificial intelligence. It indicates its result and its decision in the same&#xD;
        way. Then, he performs the practical management of the patient: specialized call, exit,&#xD;
        urgent management.&#xD;
  &#xD;
        During the systematic rereading of the radiographs made in the emergency department the night&#xD;
        before and night by the radiology intern, he makes a first reading of the native images and&#xD;
        gives the result (fracture yes/ no and localization). Then, he makes a second reading&#xD;
        assisted by &quot;Boneview&quot; and gives the result again.&#xD;
  &#xD;
        A radiologist specialized in osteoarticular imaging will read the radiographs initially&#xD;
        native. He will note the result (fracture yes/ no and localization) then read the radiographs&#xD;
        annotated by the software. He will give the result again.&#xD;
  &#xD;
        For the patient, there will be no additional imaging exams, but the x-ray will be read a&#xD;
        secondary time with artificial intelligence assistance. This pet reading causes a change in&#xD;
        patient management.&#xD;
  &#xD;
        Indeed if a discrepancy is noted between the reading of the radiography by the internal&#xD;
        radiology or the conclusion of the emergency physician and the reading of the senior&#xD;
        radiologist specialized in osteoarticular imaging, the patient will be recalled and&#xD;
        reconvoked to the emergency department if necessary&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">October 2023</start_date>
    <completion_date type="Anticipated">June 2024</completion_date>
    <primary_completion_date type="Anticipated">March 2024</primary_completion_date>
    <phase>N/A</phase>
    <study_type>Interventional</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <allocation>N/A</allocation>
      <intervention_model>Single Group Assignment</intervention_model>
      <primary_purpose>Diagnostic</primary_purpose>
      <masking>None (Open Label)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>Change in ER support between X-ray reading without and with artificial intelligence</measure>
      <time_frame>1 year</time_frame>
      <description>Compare ER support decisions without and with fracture diagnostic software</description>
    </primary_outcome>
    <enrollment type="Anticipated">1600</enrollment>
    <condition>Fractures, Bone</condition>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>processing the radiography with the &quot;Boneview&quot; software</intervention_name>
      <description>all X-Rays will be analysed with and without the software</description>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Major patient&#xD;
  &#xD;
            -  Admitted to the emergency department after trauma less than 48 hours&#xD;
  &#xD;
            -  Patient with an indication on an x-ray of the limbs or/and pelvis&#xD;
  &#xD;
            -  Express patient consent&#xD;
  &#xD;
            -  Affiliated patient or social security beneficiary&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Polytraumatized patient&#xD;
  &#xD;
            -  X-ray of the corso-lumbar spine, skull, cervical spine (all parts of the body not&#xD;
               affected by the intended use of the software)&#xD;
  &#xD;
            -  Pregnant, lactating or parturient patient&#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_contact>
      <last_name>Damien Combes, Dr</last_name>
      <phone>+33 2 41 35 42 81</phone>
      <email>damien.combe@chu-angers.fr</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Marie Bost, study coordinator</last_name>
      <phone>+33 2 41 35 31 99</phone>
      <email>mabost@chu-angers.fr</email>
    </overall_contact_backup>
    <verification_date>July 2023</verification_date>
    <study_first_submitted>August 22, 2023</study_first_submitted>
    <study_first_submitted_qc>August 22, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 28, 2023</study_first_posted>
    <last_update_submitted>August 22, 2023</last_update_submitted>
    <last_update_submitted_qc>August 22, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 28, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Fractures, Bone</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: 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/NCT06013852
  org study id: 49RC23_0278
  nct id: NCT06013852
  lead sponsor: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  Traumatic emergencies are the primary reason for consultation in emergency departments and
        standard radiography is the primary imaging exam for osteoarticular trauma. However, with the
        increase in the number of patients admitted to emergency departments and thus the increased
        workload for emergency room attendants, Interpretation of radiographs in trauma emergencies
        is made more difficult, resulting in a high risk of misinterpretation.
  
        The growing presence of artificial intelligence in the medical field, notably through the
        involvement of diagnostic software on imageries, makes its use more relevant in the aid of
        the replay of osteoarticular imageries.
  
        A recent meta-analysis of 32 studies evaluating the performance of artificial intelligence in
        fracture detection found comparable performance between experienced radiologists and AI-based
        diagnosis. However, these were mainly retrospective studies, and thus more distant from the
        reality of its use in a care stream such as emergencies.
  
        The objective of this study is therefore to prospectively validate the use of artificial
        intelligence software during its implementation in an emergency department for patients
        admitted for a suspicion of osteoarticular trauma.
  After completing the X-ray requested, the senior emergency physician reads the X-ray (native
        image only), gives his diagnosis (fracture yes/ no and localization) and reports if he
        requests the specialist (orthopedist/ radiologist) or not and the reason why he asks for it
        (urgent management, doubt about a fracture). After processing the radiography with the
        "Boneview" software, the emergency physician makes a second reading taking into account the
        analysis of artificial intelligence. It indicates its result and its decision in the same
        way. Then, he performs the practical management of the patient: specialized call, exit,
        urgent management.
  
        During the systematic rereading of the radiographs made in the emergency department the night
        before and night by the radiology intern, he makes a first reading of the native images and
        gives the result (fracture yes/ no and localization). Then, he makes a second reading
        assisted by "Boneview" and gives the result again.
  
        A radiologist specialized in osteoarticular imaging will read the radiographs initially
        native. He will note the result (fracture yes/ no and localization) then read the radiographs
        annotated by the software. He will give the result again.
  
        For the patient, there will be no additional imaging exams, but the x-ray will be read a
        secondary time with artificial intelligence assistance. This pet reading causes a change in
        patient management.
  
        Indeed if a discrepancy is noted between the reading of the radiography by the internal
        radiology or the conclusion of the emergency physician and the reading of the senior
        radiologist specialized in osteoarticular imaging, the patient will be recalled and
        reconvoked to the emergency department if necessary
  allocation: N/A
  intervention model: Single Group Assignment
  primary purpose: Diagnostic
  masking: None (Open Label)
  measure: Change in ER support between X-ray reading without and with artificial intelligence
  time frame: 1 year
  description: Compare ER support decisions without and with fracture diagnostic software
  intervention type: Diagnostic Test
  intervention name: processing the radiography with the "Boneview" software
  description: all X-Rays will be analysed with and without the software
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: No
  last name: Damien Combes, Dr
  phone: +33 2 41 35 42 81
  email: damien.combe@chu-angers.fr
  last name: Marie Bost, study coordinator
  phone: +33 2 41 35 31 99
  email: mabost@chu-angers.fr
  responsible party type: Sponsor
  mesh term: Fractures, Bone
  sharing ipd: No