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-19
  • Start & end year

    2020
    2021
  • Known Financial Commitments (USD)

    $66,631.08
  • Funder

    Department of Health and Social Care / National Institute for Health and Care Research (DHSC-NIHR), UK Research and Innovation (UKRI)
  • Principle Investigator

    Pending
  • Research Location

    United Kingdom, Europe
  • Lead Research Institution

    University of Birmingham
  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Prognostic factors for disease severity

  • Special Interest Tags

    Gender

  • Study Subject

    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.

Publicationslinked via Europe PMC

Last Updated:38 minutes ago

View all publications at Europe PMC

Machine learning of COVID-19 clinical data identifies population structures with therapeutic potential.

Development and external validation of prognostic models for COVID-19 to support risk stratification in secondary care.