Prognostic models for COVID-19 to support risk stratification in secondary care
- Funded by Department of Health and Social Care / National Institute for Health and Care Research (DHSC-NIHR), UK Research and Innovation (UKRI)
- Total publications:2 publications
Grant number: MR/V027913/1
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$66,631.08Funder
Department of Health and Social Care / National Institute for Health and Care Research (DHSC-NIHR), UK Research and Innovation (UKRI)Principal Investigator
PendingResearch Location
United KingdomLead Research Institution
University of BirminghamResearch Priority Alignment
N/A
Research Category
Clinical characterisation and management
Research Subcategory
Prognostic factors for disease severity
Special Interest Tags
N/A
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
As of mid-July 2020, almost 600,000 people have died with COVID-19 (coronavirus) worldwide. Some patients who are admitted to hospital with COVID-19 experience a rapid worsening of their symptoms and go on to need intensive care treatment, ventilation (to help them breathe) or die. Because the virus is new and affects different people in different ways, doctors find that their clinical experience is not enough to help them to predict which patients are most likely to develop severe symptoms or die, and there is no tool which can help them to do this. Therefore, the aim of our study is to develop tools that will help healthcare professionals to identify patients at high risk of needing intensive care treatment or ventilation, or of dying, as well as patients at low risk who can be safely discharged from hospital. This may provide an early opportunity to treat patients at high risk, while also making best use of limited hospital resources. We will do this by using anonymised patient data from hospitals in the UK to: 1. Develop a model which uses patients' symptoms, test results, and other information to predict their risk of needing intensive care treatment/ventilation, or dying. 2. Find groups of patients with similar test results and explore how their condition progresses.
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