COVID19 Clinical Predictors and Outcome

COVID-19, Clinical Predictors and Evolution of Disease in Hospitalised and Intensive Care Patients at St George's Hospital

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.

Study Overview

Status

Unknown

Conditions

Intervention / Treatment

Detailed Description

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.

Study Type

Observational

Enrollment (Anticipated)

800

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • London, United Kingdom, SW17 0RE
        • Recruiting
        • St. George's University Hospitals Foundation Trust.
        • Contact:
          • Timothy D Planche, Dr.
          • Phone Number: 02087252683

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

The study population for workstream 1, will comprise adults (>=18years) with or without laboratory confirmed SARS-CoV-2 infection admitted to SGHFT between 01 December 2019 and 30 April 2022.

The study population for workstream 2, will comprise adults (>=18years) with respiratory failure (all causes) admitted to intensive care between 01 December 2019 and 30 April 2022.

Description

Workstream 1

Inclusion Criteria:

  • Adults (aged ≥18 years).
  • Patients attending SGHFT.

Exclusion Criteria:

  • Children and adolescents (< 18 years). Workstream 2

Inclusion Criteria:

  • Adult (aged ≥18 years) patients admitted to ICU areas during the period of study
  • Presence of acute respiratory failure: this is defined by meeting all the following criteria:

    1. Onset over 1 week or less
    2. Presence of consolidation, or bilateral opacities on CT or chest radiograph.
    3. PaO2 < 8 kPa on FiO2 0.21 or requirement of non-invasive ventilation (NIV), high-flow nasal cannula (HFNC) or mechanical ventilation

Exclusion Criteria:

  • Respiratory symptoms explained by cardiac failure or fluid overload alone

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Workstream 1
Adult patients admitted to SGHFT (St. Georges Hospital Foundation Trust) with or without laboratory confirmed SARS- CoV-2.
Laboratory confirmed SARS-CoV2
Workstream 2
Adult patients admitted to to SGHFT (St. Georges Hospital Foundation Trust) ITU with respiratory failure.
Laboratory confirmed SARS-CoV2

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
SARS-CoV-2 hospital mortality
Time Frame: 6 months from admission
To assess mortality in SARS-CoV-2 patients admitted to SGHFT wards.
6 months from admission
SARS-CoV-2 mortality in critical care unit
Time Frame: 6 months from admission
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.
6 months from admission

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 15, 2020

Primary Completion (Anticipated)

April 30, 2022

Study Completion (Anticipated)

April 30, 2022

Study Registration Dates

First Submitted

May 6, 2020

First Submitted That Met QC Criteria

June 3, 2020

First Posted (Actual)

June 4, 2020

Study Record Updates

Last Update Posted (Actual)

October 22, 2020

Last Update Submitted That Met QC Criteria

October 20, 2020

Last Verified

October 1, 2020

More Information

Terms related to this study

Other Study ID Numbers

  • 2020.0115

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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