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/NCT06006611</url>
    </required_header>
    <id_info>
      <org_study_id>ZDWY.BAS.001</org_study_id>
      <nct_id>NCT06006611</nct_id>
    </id_info>
    <brief_title>Risk Factors for Severe Disease in Hospitalized Patients With COVID-19 and the Effect of Azvudine Treatment: a Retrospective Cohort Study</brief_title>
    <official_title>Risk Factors for Severe Disease in Hospitalized Patients With COVID-19 and the Effect</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Fifth Affiliated Hospital, Sun Yat-Sen University</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Fifth Affiliated Hospital, Sun Yat-Sen University</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>
      <is_us_export>Yes</is_us_export>
    </oversight_info>
    <brief_summary>
      <textblock>
        The purpose of this study is to explore the factors that can affect the development of severe&#xD;
        cases in hospitalized patients with COVID-19, including basic diseases, laboratory&#xD;
        parameters, and clinical manifestations; In addition,to explore whether Azvudine can reduce&#xD;
        the mortality of hospitalized patients with COVID-19.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        4201 COVID-19 patients discharged from our hospital were enrolled. Binary logistic regression&#xD;
        analysis and ROC curve were used to investigate the role of comorbidities, laboratory&#xD;
        parameters and clinical manifestation on progression of COVID-19 patients. We used&#xD;
        propensity-score models conditional on baseline characteristics and Univariate Cox regression&#xD;
        model to examine whether Azvudine can reduce the mortality of COVID-19 patients.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Active, not recruiting</overall_status>
    <start_date type="Actual">August 5, 2023</start_date>
    <completion_date type="Anticipated">August 30, 2023</completion_date>
    <primary_completion_date type="Anticipated">August 25, 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>All-cause mortality of COVID-19 patients</measure>
      <time_frame>Time from onset to death</time_frame>
      <description>All-cause mortality of COVID-19 patients</description>
    </primary_outcome>
    <number_of_groups>3</number_of_groups>
    <enrollment type="Anticipated">4201</enrollment>
    <condition>COVID-19</condition>
    <arm_group>
      <arm_group_label>Azvudine group</arm_group_label>
      <description>Azvudine group included COVID-19 patients treated with azvudine antiviral therapy;</description>
    </arm_group>
    <arm_group>
      <arm_group_label>No antiviral group</arm_group_label>
      <description>No antiviral group included COVID-19 patients treated with no antiviral therapy;</description>
    </arm_group>
    <arm_group>
      <arm_group_label>Monotamivir</arm_group_label>
      <description>Monotamivir group included COVID-19 patients treated with monotamivir antiviral therapy</description>
    </arm_group>
    <intervention>
      <intervention_type>Drug</intervention_type>
      <intervention_name>Azvudine</intervention_name>
      <description>Received antiviral treatment with azvudine</description>
      <arm_group_label>Azvudine group</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          The COVID-19 positive patients&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
          The COVID-19 positive patients&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            1. patients treated with both azvudine and monotamivir;&#xD;
  &#xD;
            2. patients receiving other antiviral drugs such as nematavir/ritonavir;&#xD;
  &#xD;
            3. age &amp;lt; 18 years old&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <location>
      <facility>
        <name>The Fifth Affiliated Hospital of Sun Yat-sen University</name>
        <address>
          <city>Zhuhai</city>
          <state>Guangdong</state>
          <zip>519000</zip>
          <country>China</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>China</country>
    </location_countries>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>August 21, 2023</study_first_submitted>
    <study_first_submitted_qc>August 21, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 23, 2023</study_first_posted>
    <last_update_submitted>August 21, 2023</last_update_submitted>
    <last_update_submitted_qc>August 21, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 23, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>COVID-19</keyword>
    <keyword>Azvudine</keyword>
    <keyword>severity</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>COVID-19</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
      <ipd_description>Publication of academic papers</ipd_description>
    </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/NCT06006611
  org study id: ZDWY.BAS.001
  nct id: NCT06006611
  lead sponsor: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  is us export: Yes
  The purpose of this study is to explore the factors that can affect the development of severe
        cases in hospitalized patients with COVID-19, including basic diseases, laboratory
        parameters, and clinical manifestations; In addition,to explore whether Azvudine can reduce
        the mortality of hospitalized patients with COVID-19.
  4201 COVID-19 patients discharged from our hospital were enrolled. Binary logistic regression
        analysis and ROC curve were used to investigate the role of comorbidities, laboratory
        parameters and clinical manifestation on progression of COVID-19 patients. We used
        propensity-score models conditional on baseline characteristics and Univariate Cox regression
        model to examine whether Azvudine can reduce the mortality of COVID-19 patients.
  observational model: Cohort
  time perspective: Retrospective
  measure: All-cause mortality of COVID-19 patients
  time frame: Time from onset to death
  description: All-cause mortality of COVID-19 patients
  arm group label: Azvudine group
  description: Azvudine group included COVID-19 patients treated with azvudine antiviral therapy;
  arm group label: No antiviral group
  description: No antiviral group included COVID-19 patients treated with no antiviral therapy;
  arm group label: Monotamivir
  description: Monotamivir group included COVID-19 patients treated with monotamivir antiviral therapy
  intervention type: Drug
  intervention name: Azvudine
  description: Received antiviral treatment with azvudine
  arm group label: Azvudine group
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: No
  facility: 
  country: China
  responsible party type: Sponsor
  mesh term: COVID-19
  sharing ipd: No
  ipd description: Publication of academic papers