<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/NCT04476589</url>
  </required_header>
  <id_info>
    <org_study_id>2020P001616</org_study_id>
    <nct_id>NCT04476589</nct_id>
  </id_info>
  <brief_title>Prognostication of Recovery in Early Disorders of Consciousness After COVID-19</brief_title>
  <acronym>PREDICT-COVID</acronym>
  <official_title>Prognostication of Recovery in Early Disorders of Consciousness After COVID-19</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Massachusetts General Hospital</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Massachusetts General Hospital</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 primary aim of this research proposal is to use multimodal metrics (e.g., clinical data&#xD;
      and advanced neuroimaging) in the early (i.e., acute hospitalization) phase of recovery from&#xD;
      COVID-19-related disorders of consciousness to predict outcome at 3, 6, and 12 months&#xD;
      post-hospitalization. We aim to construct an algorithm that synthesizes the results of these&#xD;
      metrics to help predict recovery.&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">July 1, 2020</start_date>
  <completion_date type="Actual">April 7, 2022</completion_date>
  <primary_completion_date type="Actual">April 7, 2022</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>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Disability Rating Scale score</measure>
    <time_frame>6 months</time_frame>
    <description>Functional outcome measure. Maximum score of 29 represents high disability, minimum score of 0 represents no disability. Higher scores represent higher level of disability.</description>
  </primary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Actual">12</enrollment>
  <condition>Covid19</condition>
  <condition>Coma</condition>
  <condition>Consciousness Disorder</condition>
  <arm_group>
    <arm_group_label>COVID-19 Disorders of Consciousness</arm_group_label>
    <description>Patients with COVID-19 and disorders of consciousness</description>
  </arm_group>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Functional MRI</intervention_name>
    <description>measurement of functional brain networks</description>
    <arm_group_label>COVID-19 Disorders of Consciousness</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Survivors of severe COVID-19 who have disorders of consciousness&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. age 18 or older,&#xD;
&#xD;
          2. positive diagnosis of COVID-19,&#xD;
&#xD;
          3. diagnosis of coma, vegetative state or minimally conscious state per Glasgow Coma&#xD;
             Scale (GCS) at time of enrollment (excluding confounders such as sedation) and&#xD;
&#xD;
          4. clinical team plan for an MRI for clinical management.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
        A subject with any of the following MRI contraindications will not be eligible for this&#xD;
        study:&#xD;
&#xD;
          -  electrical implants such as cardiac pacemakers or perfusion pumps&#xD;
&#xD;
          -  ferromagnetic implants such as aneurysm clips, surgical clips, prostheses, artificial&#xD;
             hearts, valves with steel parts, metal fragments, shrapnel, tattoos near the eye, or&#xD;
             steel implants&#xD;
&#xD;
          -  ferromagnetic objects such as jewelry or metal clips in clothing that cannnot be&#xD;
             easily removed for scanning&#xD;
&#xD;
          -  pregnant volunteers&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
  </eligibility>
  <location>
    <facility>
      <name>Massachusetts General Hospital</name>
      <address>
        <city>Boston</city>
        <state>Massachusetts</state>
        <zip>02114</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <results_reference>
    <citation>Fischer D, Threlkeld ZD, Bodien YG, Kirsch JE, Huang SY, Schaefer PW, Rapalino O, Hochberg LR, Rosen BR, Edlow BL. Intact Brain Network Function in an Unresponsive Patient with COVID-19. Ann Neurol. 2020 Oct;88(4):851-854. doi: 10.1002/ana.25838. Epub 2020 Aug 6.</citation>
    <PMID>32613682</PMID>
  </results_reference>
  <verification_date>April 2023</verification_date>
  <study_first_submitted>July 16, 2020</study_first_submitted>
  <study_first_submitted_qc>July 16, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 20, 2020</study_first_posted>
  <last_update_submitted>April 3, 2023</last_update_submitted>
  <last_update_submitted_qc>April 3, 2023</last_update_submitted_qc>
  <last_update_posted type="Actual">April 4, 2023</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Massachusetts General Hospital</investigator_affiliation>
    <investigator_full_name>Brian L. Edlow, M.D.</investigator_full_name>
    <investigator_title>Neurocritical Care Faculty</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>COVID-19</mesh_term>
    <mesh_term>Consciousness Disorders</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Undecided</sharing_ipd>
  </patient_data>
  <!-- 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/NCT04476589
org study id: 2020P001616
nct id: NCT04476589
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The primary aim of this research proposal is to use multimodal metrics (e.g., clinical data
      and advanced neuroimaging) in the early (i.e., acute hospitalization) phase of recovery from
      COVID-19-related disorders of consciousness to predict outcome at 3, 6, and 12 months
      post-hospitalization. We aim to construct an algorithm that synthesizes the results of these
      metrics to help predict recovery.
observational model: Cohort
time perspective: Prospective
measure: Disability Rating Scale score
time frame: 6 months
description: Functional outcome measure. Maximum score of 29 represents high disability, minimum score of 0 represents no disability. Higher scores represent higher level of disability.
arm group label: COVID-19 Disorders of Consciousness
description: Patients with COVID-19 and disorders of consciousness
intervention type: Diagnostic Test
intervention name: Functional MRI
description: measurement of functional brain networks
arm group label: COVID-19 Disorders of Consciousness
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
facility: 
country: United States
citation: Fischer D, Threlkeld ZD, Bodien YG, Kirsch JE, Huang SY, Schaefer PW, Rapalino O, Hochberg LR, Rosen BR, Edlow BL. Intact Brain Network Function in an Unresponsive Patient with COVID-19. Ann Neurol. 2020 Oct;88(4):851-854. doi: 10.1002/ana.25838. Epub 2020 Aug 6.
PMID: 32613682
responsible party type: Principal Investigator
investigator affiliation: Massachusetts General Hospital
investigator full name: Brian L. Edlow, M.D.
investigator title: Neurocritical Care Faculty
mesh term: COVID-19
mesh term: Consciousness Disorders
sharing ipd: Undecided