Journal article 545 views 26 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
The Lancet Digital Health, Volume: 3, Issue: 7, Pages: e425 - e433
Swansea University Author: Ronan Lyons
-
PDF | Version of Record
Distributed under the terms of a Creative Commons CC-BY-NC-ND License.
Download (1.24MB)
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!
|
first_indexed |
2021-03-11T09:16:19Z |
---|---|
last_indexed |
2023-01-11T14:35:35Z |
id |
cronfa56397 |
recordtype |
SURis |
fullrecord |
<?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>56397</id><entry>2021-03-11</entry><title>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</title><swanseaauthors><author><sid>83efcf2a9dfcf8b55586999d3d152ac6</sid><ORCID>0000-0001-5225-000X</ORCID><firstname>Ronan</firstname><surname>Lyons</surname><name>Ronan Lyons</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-03-11</date><deptcode>MEDS</deptcode><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.</abstract><type>Journal Article</type><journal>The Lancet Digital Health</journal><volume>3</volume><journalNumber>7</journalNumber><paginationStart>e425</paginationStart><paginationEnd>e433</paginationEnd><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2589-7500</issnPrint><issnElectronic/><keywords/><publishedDay>1</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-07-01</publishedDate><doi>10.1016/s2589-7500(21)00080-7</doi><url/><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm>Other</apcterm><funders>Funding: UK National Institute for Health Research.</funders><projectreference/><lastEdited>2022-08-15T12:50:38.8204357</lastEdited><Created>2021-03-11T09:10:10.3853928</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Vahé</firstname><surname>Nafilyan</surname><order>1</order></author><author><firstname>Ben</firstname><surname>Humberstone</surname><order>2</order></author><author><firstname>Nisha</firstname><surname>Mehta</surname><order>3</order></author><author><firstname>Ian</firstname><surname>Diamond</surname><order>4</order></author><author><firstname>Carol</firstname><surname>Coupland</surname><order>5</order></author><author><firstname>Luke</firstname><surname>Lorenzi</surname><order>6</order></author><author><firstname>Piotr</firstname><surname>Pawelek</surname><order>7</order></author><author><firstname>Ryan</firstname><surname>Schofield</surname><order>8</order></author><author><firstname>Jasper</firstname><surname>Morgan</surname><order>9</order></author><author><firstname>Paul</firstname><surname>Brown</surname><order>10</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>11</order></author><author><firstname>Aziz</firstname><surname>Sheikh</surname><order>12</order></author><author><firstname>Julia</firstname><surname>Hippisley-Cox</surname><order>13</order></author></authors><documents><document><filename>56397__24918__b6ce998c12f94f199e3faad7ab5fb914.pdf</filename><originalFilename>56397.VOR.pdf</originalFilename><uploaded>2022-08-15T12:48:16.1992138</uploaded><type>Output</type><contentLength>1295657</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>Distributed under the terms of a Creative Commons CC-BY-NC-ND License.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by-nc-nd/4.0/</licence></document></documents><OutputDurs/></rfc1807> |
spelling |
v2 56397 2021-03-11 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 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 2021-03-11 MEDS 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. Journal Article The Lancet Digital Health 3 7 e425 e433 Elsevier BV 2589-7500 1 7 2021 2021-07-01 10.1016/s2589-7500(21)00080-7 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Other Funding: UK National Institute for Health Research. 2022-08-15T12:50:38.8204357 2021-03-11T09:10:10.3853928 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Vahé Nafilyan 1 Ben Humberstone 2 Nisha Mehta 3 Ian Diamond 4 Carol Coupland 5 Luke Lorenzi 6 Piotr Pawelek 7 Ryan Schofield 8 Jasper Morgan 9 Paul Brown 10 Ronan Lyons 0000-0001-5225-000X 11 Aziz Sheikh 12 Julia Hippisley-Cox 13 56397__24918__b6ce998c12f94f199e3faad7ab5fb914.pdf 56397.VOR.pdf 2022-08-15T12:48:16.1992138 Output 1295657 application/pdf Version of Record true Distributed under the terms of a Creative Commons CC-BY-NC-ND License. true eng https://creativecommons.org/licenses/by-nc-nd/4.0/ |
title |
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 |
spellingShingle |
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 Ronan Lyons |
title_short |
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 |
title_full |
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 |
title_fullStr |
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 |
title_full_unstemmed |
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 |
title_sort |
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 |
author_id_str_mv |
83efcf2a9dfcf8b55586999d3d152ac6 |
author_id_fullname_str_mv |
83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons |
author |
Ronan Lyons |
author2 |
Vahé Nafilyan Ben Humberstone Nisha Mehta Ian Diamond Carol Coupland Luke Lorenzi Piotr Pawelek Ryan Schofield Jasper Morgan Paul Brown Ronan Lyons Aziz Sheikh Julia Hippisley-Cox |
format |
Journal article |
container_title |
The Lancet Digital Health |
container_volume |
3 |
container_issue |
7 |
container_start_page |
e425 |
publishDate |
2021 |
institution |
Swansea University |
issn |
2589-7500 |
doi_str_mv |
10.1016/s2589-7500(21)00080-7 |
publisher |
Elsevier BV |
college_str |
Faculty of Medicine, Health and Life Sciences |
hierarchytype |
|
hierarchy_top_id |
facultyofmedicinehealthandlifesciences |
hierarchy_top_title |
Faculty of Medicine, Health and Life Sciences |
hierarchy_parent_id |
facultyofmedicinehealthandlifesciences |
hierarchy_parent_title |
Faculty of Medicine, Health and Life Sciences |
department_str |
Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine |
document_store_str |
1 |
active_str |
0 |
description |
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_date |
2021-07-01T11:45:24Z |
_version_ |
1799115163880652800 |
score |
11.037166 |