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/NCT06030986</url>
    </required_header>
    <id_info>
      <org_study_id>PREDOHCA</org_study_id>
      <nct_id>NCT06030986</nct_id>
    </id_info>
    <brief_title>Prediction of Outcome in Out-of-Hospital Cardiac Arrest</brief_title>
    <acronym>PREDOHCA</acronym>
    <official_title>Prediction of Outcome in Out-of-Hospital Cardiac Arrest</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Kepler University Hospital</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Kepler University Hospital</source>
    <oversight_info>
      <has_dmc>Yes</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>
        In the course of prehospital respiratory and circulatory arrest, approximately 1000 persons&#xD;
        are resuscitated by cardiopulmonary resuscitation in Upper Austria every year. Despite&#xD;
        constant further development of methods, equipment and continuous training of the rescue and&#xD;
        emergency medical teams working on site, the majority of patients who have to be resuscitated&#xD;
        prehospital still die. However, even patients whose circulatory function can be restored&#xD;
        during prehospital resuscitation (Return of Spontaneous Circulation, ROSC) require intensive&#xD;
        medical care for days to weeks and often find it very difficult to return to a normal,&#xD;
        independent life.&#xD;
  &#xD;
        The success of resuscitation measures depends on the quality of the resuscitation performed&#xD;
        as well as on patient-specific factors. Evaluation scales such as the Cerebral Performance&#xD;
        Category score (CPC) allow a posteriori assessment of resuscitation success. Nowadays, it is&#xD;
        very difficult to estimate the outcome of resuscitation a priori. In many cases, it is not at&#xD;
        all clear at the beginning of the treatment pathway whether the individual patient is&#xD;
        expected to have an unfavorable prognosis in the context of respiratory arrest or whether a&#xD;
        restitutio ad integrum is possible.&#xD;
  &#xD;
        Thus, the decision to continue or discontinue resuscitation can only be made on the basis of&#xD;
        an individual physician's assessment. In addition to the primary concern of stopping&#xD;
        resuscitation too early, there is also the risk that medical resources are used beyond the&#xD;
        normal level after resuscitation without expecting a successful outcome. Estimating and&#xD;
        categorizing the subsequent outcome is difficult and emotionally stressful for the treating&#xD;
        team in the acute situation. Some factors that influence outcome are now known: As cerebral&#xD;
        hypoperfusion increases, the probability of survival decreases sharply with each passing&#xD;
        minute. In this context, potentially reversible causes have been identified in different&#xD;
        works, allowing causal therapy to improve neurological outcome. In addition to the most&#xD;
        important therapy bridging hypoperfusion, chest compression, with the aim of ensuring minimal&#xD;
        perfusion of the brain, immediate defibrillation should be mentioned in particular, which now&#xD;
        allows medical laypersons to use defibrillators as part of the Public Access Defibrillation&#xD;
        Network.&#xD;
  &#xD;
        Despite all efforts, however, it is not yet possible to make reliable statements about the&#xD;
        probable outcome of persons with respiratory and circulatory arrest with a high degree of&#xD;
        certainty in a large number of cases at an early stage.&#xD;
  &#xD;
        Artificial intelligence refers to the ability of machines to perform cognitive tasks, such as&#xD;
        recognizing objects in images and classifying them. For a long time, many processes were too&#xD;
        complex to explore through sufficient computing power, storage capacity, and understanding.&#xD;
        More recently, however, technological advances have brought machine learning (ML) and the&#xD;
        constructs behind it, including those based on so-called neural networks (known since about&#xD;
        1950), back to the fore. Not only the development of theoretical models, but after extensive&#xD;
        testing also devices applicable in daily routine operation are available.&#xD;
  &#xD;
        Modern machine learning methods are enabling a variety of new approaches to assessing&#xD;
        operations, including modeling complex systems and finding relationships between models.&#xD;
      </textblock>
    </brief_summary>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">October 31, 2023</start_date>
    <completion_date type="Anticipated">December 31, 2023</completion_date>
    <primary_completion_date type="Anticipated">December 31, 2023</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Cohort</observational_model>
      <time_perspective>Retrospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>AUC-ROC for Prediction of ILCOR Utstein OHCA Core Outcome</measure>
      <time_frame>2015-01-01 - 2023-10-31</time_frame>
      <description>AUC-ROC for Prediction of ILCOR Utstein OHCA Core Outcome</description>
    </primary_outcome>
    <primary_outcome>
      <measure>AUC-PRC for Prediction of ILCOR Utstein OHCA Core Outcome</measure>
      <time_frame>2015-01-01 - 2023-10-31</time_frame>
      <description>AUC-PRC for Prediction of ILCOR Utstein OHCA Core Outcome</description>
    </primary_outcome>
    <primary_outcome>
      <measure>F1-Score for Prediction of ILCOR Utstein OHCA Core Outcome</measure>
      <time_frame>2015-01-01 - 2023-10-31</time_frame>
      <description>F1-Score for Prediction of ILCOR Utstein OHCA Core Outcome</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Confusion Matrix for Prediction of ILCOR Utstein OHCA Core Outcome</measure>
      <time_frame>2015-01-01 to 2023-10-31</time_frame>
      <description>Confusion Matrix for Prediction of ILCOR Utstein OHCA Core Outcome</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>AUC-ROC for Prediction of Diagnosis at Hospital Discharge</measure>
      <time_frame>2015-01-01 - 2023-10-31</time_frame>
      <description>AUC-ROC for Prediction of Diagnosis at Hospital Discharge</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>AUC-PRC for Prediction of Diagnosis at Hospital Discharge</measure>
      <time_frame>2015-01-01 - 2023-10-31</time_frame>
      <description>AUC-PRC for Prediction of Diagnosis at Hospital Discharge</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>F1-Score for Prediction of Diagnosis at Hospital Discharge</measure>
      <time_frame>2015-01-01 - 2023-10-31</time_frame>
      <description>F1-Score for Prediction of Diagnosis at Hospital Discharge</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Confusion Matrix for Prediction of Diagnosis at Hospital Discharge</measure>
      <time_frame>2015-01-01 - 2023-10-31</time_frame>
      <description>Confusion Matrix for Prediction of Diagnosis at Hospital Discharge</description>
    </secondary_outcome>
    <number_of_groups>2</number_of_groups>
    <enrollment type="Anticipated">10000</enrollment>
    <condition>Cardiac Arrest</condition>
    <arm_group>
      <arm_group_label>ILCOR Utstein OHCA Core Outcome Positive</arm_group_label>
      <description>Respectively for all core outcomes defined.</description>
    </arm_group>
    <arm_group>
      <arm_group_label>ILCOR Utstein OHCA Core Outcome Negative</arm_group_label>
      <description>Respectively for all core outcomes defined.</description>
    </arm_group>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>ILCOR Utstein OHCA Core Outcome</intervention_name>
      <description>ILCOR Utstein OHCA Core Outcome</description>
      <arm_group_label>ILCOR Utstein OHCA Core Outcome Negative</arm_group_label>
      <arm_group_label>ILCOR Utstein OHCA Core Outcome Positive</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          As described in the inclusion criteria.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Patients 18 years or older AND&#xD;
  &#xD;
            -  between 2015-01-01 and 2023-10-31 AND&#xD;
  &#xD;
            -  have been treated by emergency medical teams of the Austrian Red Cross, District&#xD;
               Branch of Upper Austria AND&#xD;
  &#xD;
            -  have suffered out-of-hospital cardiac arrest AND&#xD;
  &#xD;
            -  have been treated by emergency physicians while out of hospital AND&#xD;
  &#xD;
            -  have been transported to the Kepler University Hospital, Linz, Austria&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
          - none&#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>Thomas Tschoellitsch, MD</last_name>
      <phone>+435768083</phone>
      <phone_ext>78132</phone_ext>
      <email>thomas.tschoellitsch@jku.at</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Jens Meier, MD</last_name>
      <phone>+435768083</phone>
      <phone_ext>2158</phone_ext>
      <email>jens.meier@kepleruniklinikum.at</email>
    </overall_contact_backup>
    <location>
      <facility>
        <name>Kepler University Hospital</name>
        <address>
          <city>Linz</city>
          <state>Upper Austria</state>
          <zip>4020</zip>
          <country>Austria</country>
        </address>
      </facility>
      <contact>
        <last_name>Jens Meier, MD</last_name>
        <phone>+435768083</phone>
        <phone_ext>2158</phone_ext>
        <email>jens.meier@kepleruniklinikum.at</email>
      </contact>
      <contact_backup>
        <last_name>Thomas Tschoellitsch, MD</last_name>
        <phone>+435768083</phone>
        <phone_ext>78132</phone_ext>
        <email>thomas.tschoellitsch@jku.at</email>
      </contact_backup>
    </location>
    <location_countries>
      <country>Austria</country>
    </location_countries>
    <verification_date>September 2023</verification_date>
    <study_first_submitted>September 3, 2023</study_first_submitted>
    <study_first_submitted_qc>September 3, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">September 11, 2023</study_first_posted>
    <last_update_submitted>September 3, 2023</last_update_submitted>
    <last_update_submitted_qc>September 3, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">September 11, 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>Heart Arrest</mesh_term>
      <mesh_term>Out-of-Hospital Cardiac Arrest</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/NCT06030986
  org study id: PREDOHCA
  nct id: NCT06030986
  lead sponsor: 
  has dmc: Yes
  is fda regulated drug: No
  is fda regulated device: No
  In the course of prehospital respiratory and circulatory arrest, approximately 1000 persons
        are resuscitated by cardiopulmonary resuscitation in Upper Austria every year. Despite
        constant further development of methods, equipment and continuous training of the rescue and
        emergency medical teams working on site, the majority of patients who have to be resuscitated
        prehospital still die. However, even patients whose circulatory function can be restored
        during prehospital resuscitation (Return of Spontaneous Circulation, ROSC) require intensive
        medical care for days to weeks and often find it very difficult to return to a normal,
        independent life.
  
        The success of resuscitation measures depends on the quality of the resuscitation performed
        as well as on patient-specific factors. Evaluation scales such as the Cerebral Performance
        Category score (CPC) allow a posteriori assessment of resuscitation success. Nowadays, it is
        very difficult to estimate the outcome of resuscitation a priori. In many cases, it is not at
        all clear at the beginning of the treatment pathway whether the individual patient is
        expected to have an unfavorable prognosis in the context of respiratory arrest or whether a
        restitutio ad integrum is possible.
  
        Thus, the decision to continue or discontinue resuscitation can only be made on the basis of
        an individual physician's assessment. In addition to the primary concern of stopping
        resuscitation too early, there is also the risk that medical resources are used beyond the
        normal level after resuscitation without expecting a successful outcome. Estimating and
        categorizing the subsequent outcome is difficult and emotionally stressful for the treating
        team in the acute situation. Some factors that influence outcome are now known: As cerebral
        hypoperfusion increases, the probability of survival decreases sharply with each passing
        minute. In this context, potentially reversible causes have been identified in different
        works, allowing causal therapy to improve neurological outcome. In addition to the most
        important therapy bridging hypoperfusion, chest compression, with the aim of ensuring minimal
        perfusion of the brain, immediate defibrillation should be mentioned in particular, which now
        allows medical laypersons to use defibrillators as part of the Public Access Defibrillation
        Network.
  
        Despite all efforts, however, it is not yet possible to make reliable statements about the
        probable outcome of persons with respiratory and circulatory arrest with a high degree of
        certainty in a large number of cases at an early stage.
  
        Artificial intelligence refers to the ability of machines to perform cognitive tasks, such as
        recognizing objects in images and classifying them. For a long time, many processes were too
        complex to explore through sufficient computing power, storage capacity, and understanding.
        More recently, however, technological advances have brought machine learning (ML) and the
        constructs behind it, including those based on so-called neural networks (known since about
        1950), back to the fore. Not only the development of theoretical models, but after extensive
        testing also devices applicable in daily routine operation are available.
  
        Modern machine learning methods are enabling a variety of new approaches to assessing
        operations, including modeling complex systems and finding relationships between models.
  observational model: Cohort
  time perspective: Retrospective
  measure: AUC-ROC for Prediction of ILCOR Utstein OHCA Core Outcome
  time frame: 2015-01-01 - 2023-10-31
  description: AUC-ROC for Prediction of ILCOR Utstein OHCA Core Outcome
  measure: AUC-PRC for Prediction of ILCOR Utstein OHCA Core Outcome
  time frame: 2015-01-01 - 2023-10-31
  description: AUC-PRC for Prediction of ILCOR Utstein OHCA Core Outcome
  measure: F1-Score for Prediction of ILCOR Utstein OHCA Core Outcome
  time frame: 2015-01-01 - 2023-10-31
  description: F1-Score for Prediction of ILCOR Utstein OHCA Core Outcome
  measure: Confusion Matrix for Prediction of ILCOR Utstein OHCA Core Outcome
  time frame: 2015-01-01 to 2023-10-31
  description: Confusion Matrix for Prediction of ILCOR Utstein OHCA Core Outcome
  measure: AUC-ROC for Prediction of Diagnosis at Hospital Discharge
  time frame: 2015-01-01 - 2023-10-31
  description: AUC-ROC for Prediction of Diagnosis at Hospital Discharge
  measure: AUC-PRC for Prediction of Diagnosis at Hospital Discharge
  time frame: 2015-01-01 - 2023-10-31
  description: AUC-PRC for Prediction of Diagnosis at Hospital Discharge
  measure: F1-Score for Prediction of Diagnosis at Hospital Discharge
  time frame: 2015-01-01 - 2023-10-31
  description: F1-Score for Prediction of Diagnosis at Hospital Discharge
  measure: Confusion Matrix for Prediction of Diagnosis at Hospital Discharge
  time frame: 2015-01-01 - 2023-10-31
  description: Confusion Matrix for Prediction of Diagnosis at Hospital Discharge
  arm group label: ILCOR Utstein OHCA Core Outcome Positive
  description: Respectively for all core outcomes defined.
  arm group label: ILCOR Utstein OHCA Core Outcome Negative
  description: Respectively for all core outcomes defined.
  intervention type: Diagnostic Test
  intervention name: ILCOR Utstein OHCA Core Outcome
  description: ILCOR Utstein OHCA Core Outcome
  arm group label: ILCOR Utstein OHCA Core Outcome Negative
  arm group label: ILCOR Utstein OHCA Core Outcome Positive
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: No
  last name: Thomas Tschoellitsch, MD
  phone: +435768083
  phone ext: 78132
  email: thomas.tschoellitsch@jku.at
  last name: Jens Meier, MD
  phone: +435768083
  phone ext: 2158
  email: jens.meier@kepleruniklinikum.at
  facility: 
  contact: 
  contact backup: 
  country: Austria
  responsible party type: Sponsor
  mesh term: Heart Arrest
  mesh term: Out-of-Hospital Cardiac Arrest
  sharing ipd: No