No Cover Image

Journal article 452 views 16 downloads

An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: a national validation cohort study in England

Vahé Nafilyan, Ben Humberstone, Nisha Mehta, Ian Diamond, Carol Coupland, Luke Lorenzi, Piotr Pawelek, Ryan Schofield, Jasper Morgan, Paul Brown, Ronan Lyons Orcid Logo, Aziz Sheikh, Julia Hippisley-Cox

The Lancet Digital Health, Volume: 3, Issue: 7, Pages: e425 - e433

Swansea University Author: Ronan Lyons Orcid Logo

  • 56397.VOR.pdf

    PDF | Version of Record

    Distributed under the terms of a Creative Commons CC-BY-NC-ND License.

    Download (1.24MB)

Check full text

DOI (Published version): 10.1016/s2589-7500(21)00080-7

Abstract

Public policy measures and clinical risk assessments relevant to COVID-19 need to be aided by risk prediction models that are rigorously developed and validated. We aimed to externally validate a risk prediction algorithm (QCovid) to estimate mortality outcomes from COVID-19 in adults in England.

Published in: The Lancet Digital Health
ISSN: 2589-7500
Published: Elsevier BV 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa56397
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: Public policy measures and clinical risk assessments relevant to COVID-19 need to be aided by risk prediction models that are rigorously developed and validated. We aimed to externally validate a risk prediction algorithm (QCovid) to estimate mortality outcomes from COVID-19 in adults in England.
College: Faculty of Medicine, Health and Life Sciences
Funders: Funding: UK National Institute for Health Research.
Issue: 7
Start Page: e425
End Page: e433

Similar Items