Developing and validating a risk prediction model for long COVID-19

Grant number: COV/LTE/20/15

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Key facts

  • Disease

    COVID-19
  • Known Financial Commitments (USD)

    $259,832.83
  • Funder

    CSO Scotland
  • Principal Investigator

    Prof. Aziz Sheikh
  • Research Location

    United Kingdom, United Kingdom
  • Lead Research Institution

    University of Edinburgh
  • Research Priority Alignment

    N/A
  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Post acute and long term health consequences

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Most patients with coronavirus disease 2019 (COVID-19) recover within a few weeks. However, around 10-20% of people continue to have symptoms that last for many weeks or months. These ongoing symptoms can involve different parts of the body, including the heart, lungs, nervous system and they may also result in mental health problems. It is still unclear which patients will develop these long-term problems also sometimes known as "long-COVID". Our team has been involved in developing a calculator for the UK and Scottish Governments to identify people at risk of serious COVID-19 that results in hospital admission or death. We now plan to build on this and develop the world's first calculator to identify who is at greatest risk of developing long-COVID. We will do this by analysing data from a unique COVID19 data platform that we have created, which securely holds information on .4 million people (~99% of the Scottish population). We will work with the Scottish Government and NHS leaders to make this calculator available for routine clinical use, which will offer opportunities for the more focused and efficient targeting of resources to reduce the long-term risk of disability and death from COVID-19.

Publicationslinked via Europe PMC

Deriving and validating a risk prediction model for long COVID: a population-based, retrospective cohort study in Scotland.

Deriving and validating a risk prediction model for long COVID-19: protocol for an observational cohort study using linked Scottish data.

Symptoms and signs of long COVID: A rapid review and meta-analysis.

A clinical review of long-COVID with a focus on the respiratory system.

Long-Term Sequelae of COVID-19: A Systematic Review and Meta-Analysis of One-Year Follow-Up Studies on Post-COVID Symptoms.