<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/NCT04416347</url>
  </required_header>
  <id_info>
    <org_study_id>2020.0115</org_study_id>
    <nct_id>NCT04416347</nct_id>
  </id_info>
  <brief_title>COVID19 Clinical Predictors and Outcome</brief_title>
  <official_title>COVID-19, Clinical Predictors and Evolution of Disease in Hospitalised and Intensive Care Patients at St George's Hospital</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>St George's University Hospitals NHS Foundation Trust</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>St George's, University of London</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>
      In December 2019, a novel coronavirus (SARS-CoV-2) emerged in Wuhan, Hubei, China, and now&#xD;
      spreads across international borders. As of 11 April 2020, the total global number of&#xD;
      confirmed SARS-CoV-2 cases reached 1,521,252 (92,798 deaths); with 65,081 (7,978 deaths)&#xD;
      being reported in the United Kingdom.&#xD;
&#xD;
      COVID-19 is the name of the disease associated with SARS-CoV-2 infection and includes a&#xD;
      spectrum of illness that ranges from mild infection to severe pneumonia that can progress to&#xD;
      respiratory failure and Acute Respiratory Distress Syndrome (ARDS) or septic shock. Between 8&#xD;
      to 15% (depending on geographical setting) of all SARS-CoV-2 positive cases can be classified&#xD;
      as severe or necessitating intensive care unit (ICU) admission.&#xD;
&#xD;
      In the early stages of the outbreak unfolding, several retrospective case studies and cases&#xD;
      series carried out in China reported that those who died were more likely to be male, and&#xD;
      more likely to have underlying comorbidities. Prevalence studies conducted in the US and&#xD;
      Italy show similar trends in the distribution of comorbidities among SARS-CoV-2 severe cases;&#xD;
      adding obesity (BMI&gt;30) to the list of factors potentially associated with disease severity.&#xD;
      However, the relative importance of different underlying health conditions remains unclear&#xD;
      owing to inadequate adjustment for important confounding factors such as age, sex, and&#xD;
      smoking status.&#xD;
&#xD;
      We propose a cohort study to evaluate predictors, clinical evolution and excess of mortality&#xD;
      of SARS-CoV-2 in hospitalised patients, with two main workstreams- the first looking at all&#xD;
      patients admitted to SGHFT and the second looking at patients admitted to ITU with&#xD;
      respiratory failure.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The majority of published reports on early clinical descriptions of COVID-19 have emerged&#xD;
      from Hubei province in China, and although these provide valuable information, the lack of&#xD;
      standardised mortality and morbidity ratios hinders comparison of outcome experience across&#xD;
      populations. Also, most of the data available originate from descriptive cases or series that&#xD;
      do not account for confounding effect; so, as yet there are no specific data on how the risks&#xD;
      associated with underlying comorbidities might vary in different population groups or&#xD;
      settings.&#xD;
&#xD;
      Recognition of risk factors for morbidity and mortality is important to determine prevention&#xD;
      strategies as well as to target high-risk populations for potential therapeutics. So, in this&#xD;
      study we aim to develop a predictive statistical model to identify baseline predictors of&#xD;
      mortality including underlying health conditions and biomarker levels at admission to improve&#xD;
      the understanding of the clinical evolution of patients with severe COVID-19.&#xD;
&#xD;
      An approximative 20-30% of regular admissions in the ICU are with respiratory failure. A&#xD;
      considerably higher number is expected in the current climate. Government policies have aimed&#xD;
      to flatten the epidemic curve to ease the pressure on the NHS to ensure as many people as&#xD;
      possible have access to the appropriate level of intensive care. However, even in the&#xD;
      best-case scenario, the number of people requiring level 3 care in ICU may be ten times the&#xD;
      current capacity.&#xD;
&#xD;
      The excess of mortality due to SARS-CoV-2 in this population hasn't been fully assessed. It&#xD;
      is unknown if the evolution of this disease shares common characteristics with other&#xD;
      bacterial or viral infections. This information is invaluable in order to shape diagnostic&#xD;
      protocols, prevent complications and design therapeutic strategies.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">June 15, 2020</start_date>
  <completion_date type="Anticipated">April 30, 2022</completion_date>
  <primary_completion_date type="Anticipated">April 30, 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>Retrospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>SARS-CoV-2 hospital mortality</measure>
    <time_frame>6 months from admission</time_frame>
    <description>To assess mortality in SARS-CoV-2 patients admitted to SGHFT wards.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>SARS-CoV-2 mortality in critical care unit</measure>
    <time_frame>6 months from admission</time_frame>
    <description>To assess the risk of death attributable to COVID-19, in comparison with non-Covid-19, in patients admitted to critical care with respiratory failure.</description>
  </primary_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Anticipated">800</enrollment>
  <condition>COVID</condition>
  <condition>SARS-CoV 2</condition>
  <arm_group>
    <arm_group_label>Workstream 1</arm_group_label>
    <description>Adult patients admitted to SGHFT (St. Georges Hospital Foundation Trust) with or without laboratory confirmed SARS- CoV-2.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Workstream 2</arm_group_label>
    <description>Adult patients admitted to to SGHFT (St. Georges Hospital Foundation Trust) ITU with respiratory failure.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>SARS-CoV2 Infection</intervention_name>
    <description>Laboratory confirmed SARS-CoV2</description>
    <arm_group_label>Workstream 1</arm_group_label>
    <arm_group_label>Workstream 2</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        The study population for workstream 1, will comprise adults (&gt;=18years) with or without&#xD;
        laboratory confirmed SARS-CoV-2 infection admitted to SGHFT between 01 December 2019 and 30&#xD;
        April 2022.&#xD;
&#xD;
        The study population for workstream 2, will comprise adults (&gt;=18years) with respiratory&#xD;
        failure (all causes) admitted to intensive care between 01 December 2019 and 30 April 2022.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Workstream 1&#xD;
&#xD;
        Inclusion Criteria:&#xD;
&#xD;
          -  Adults (aged ≥18 years).&#xD;
&#xD;
          -  Patients attending SGHFT.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Children and adolescents (&lt; 18 years). Workstream 2&#xD;
&#xD;
        Inclusion Criteria:&#xD;
&#xD;
          -  Adult (aged ≥18 years) patients admitted to ICU areas during the period of study&#xD;
&#xD;
          -  Presence of acute respiratory failure: this is defined by meeting all the following&#xD;
             criteria:&#xD;
&#xD;
               1. Onset over 1 week or less&#xD;
&#xD;
               2. Presence of consolidation, or bilateral opacities on CT or chest radiograph.&#xD;
&#xD;
               3. PaO2 &lt; 8 kPa on FiO2 0.21 or requirement of non-invasive ventilation (NIV),&#xD;
                  high-flow nasal cannula (HFNC) or mechanical ventilation&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Respiratory symptoms explained by cardiac failure or fluid overload alone&#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>Timothy D Planche, Dr.</last_name>
    <phone>02087252683</phone>
    <email>tim.planche@nhs.net</email>
  </overall_contact>
  <location>
    <facility>
      <name>St. George's University Hospitals Foundation Trust.</name>
      <address>
        <city>London</city>
        <zip>SW17 0RE</zip>
        <country>United Kingdom</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Timothy D Planche, Dr.</last_name>
      <phone>02087252683</phone>
    </contact>
  </location>
  <location_countries>
    <country>United Kingdom</country>
  </location_countries>
  <verification_date>October 2020</verification_date>
  <study_first_submitted>May 6, 2020</study_first_submitted>
  <study_first_submitted_qc>June 3, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 4, 2020</study_first_posted>
  <last_update_submitted>October 20, 2020</last_update_submitted>
  <last_update_submitted_qc>October 20, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">October 22, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <patient_data>
    <sharing_ipd>No</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/NCT04416347
org study id: 2020.0115
nct id: NCT04416347
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
In December 2019, a novel coronavirus (SARS-CoV-2) emerged in Wuhan, Hubei, China, and now
      spreads across international borders. As of 11 April 2020, the total global number of
      confirmed SARS-CoV-2 cases reached 1,521,252 (92,798 deaths); with 65,081 (7,978 deaths)
      being reported in the United Kingdom.

      COVID-19 is the name of the disease associated with SARS-CoV-2 infection and includes a
      spectrum of illness that ranges from mild infection to severe pneumonia that can progress to
      respiratory failure and Acute Respiratory Distress Syndrome (ARDS) or septic shock. Between 8
      to 15% (depending on geographical setting) of all SARS-CoV-2 positive cases can be classified
      as severe or necessitating intensive care unit (ICU) admission.

      In the early stages of the outbreak unfolding, several retrospective case studies and cases
      series carried out in China reported that those who died were more likely to be male, and
      more likely to have underlying comorbidities. Prevalence studies conducted in the US and
      Italy show similar trends in the distribution of comorbidities among SARS-CoV-2 severe cases;
      adding obesity (BMI>30) to the list of factors potentially associated with disease severity.
      However, the relative importance of different underlying health conditions remains unclear
      owing to inadequate adjustment for important confounding factors such as age, sex, and
      smoking status.

      We propose a cohort study to evaluate predictors, clinical evolution and excess of mortality
      of SARS-CoV-2 in hospitalised patients, with two main workstreams- the first looking at all
      patients admitted to SGHFT and the second looking at patients admitted to ITU with
      respiratory failure.
The majority of published reports on early clinical descriptions of COVID-19 have emerged
      from Hubei province in China, and although these provide valuable information, the lack of
      standardised mortality and morbidity ratios hinders comparison of outcome experience across
      populations. Also, most of the data available originate from descriptive cases or series that
      do not account for confounding effect; so, as yet there are no specific data on how the risks
      associated with underlying comorbidities might vary in different population groups or
      settings.

      Recognition of risk factors for morbidity and mortality is important to determine prevention
      strategies as well as to target high-risk populations for potential therapeutics. So, in this
      study we aim to develop a predictive statistical model to identify baseline predictors of
      mortality including underlying health conditions and biomarker levels at admission to improve
      the understanding of the clinical evolution of patients with severe COVID-19.

      An approximative 20-30% of regular admissions in the ICU are with respiratory failure. A
      considerably higher number is expected in the current climate. Government policies have aimed
      to flatten the epidemic curve to ease the pressure on the NHS to ensure as many people as
      possible have access to the appropriate level of intensive care. However, even in the
      best-case scenario, the number of people requiring level 3 care in ICU may be ten times the
      current capacity.

      The excess of mortality due to SARS-CoV-2 in this population hasn't been fully assessed. It
      is unknown if the evolution of this disease shares common characteristics with other
      bacterial or viral infections. This information is invaluable in order to shape diagnostic
      protocols, prevent complications and design therapeutic strategies.
observational model: Cohort
time perspective: Retrospective
measure: SARS-CoV-2 hospital mortality
time frame: 6 months from admission
description: To assess mortality in SARS-CoV-2 patients admitted to SGHFT wards.
measure: SARS-CoV-2 mortality in critical care unit
time frame: 6 months from admission
description: To assess the risk of death attributable to COVID-19, in comparison with non-Covid-19, in patients admitted to critical care with respiratory failure.
arm group label: Workstream 1
description: Adult patients admitted to SGHFT (St. Georges Hospital Foundation Trust) with or without laboratory confirmed SARS- CoV-2.
arm group label: Workstream 2
description: Adult patients admitted to to SGHFT (St. Georges Hospital Foundation Trust) ITU with respiratory failure.
intervention type: Other
intervention name: SARS-CoV2 Infection
description: Laboratory confirmed SARS-CoV2
arm group label: Workstream 1
arm group label: Workstream 2
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Timothy D Planche, Dr.
phone: 02087252683
email: tim.planche@nhs.net
facility: 
status: Recruiting
contact: 
country: United Kingdom
responsible party type: Sponsor
sharing ipd: No