No Cover Image

Journal article 435 views 58 downloads

Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK

Jonathan Kennedy, Michael Parker Orcid Logo, Mike Seaborne Orcid Logo, Mohamed Mhereeg, A Walker, V Walker, S Denaxas, Tash Kennedy Orcid Logo, S. V Katikireddi, Sinead Brophy Orcid Logo

BMC Medicine, Volume: 21, Issue: 1

Swansea University Authors: Jonathan Kennedy, Michael Parker Orcid Logo, Mike Seaborne Orcid Logo, Mohamed Mhereeg, Tash Kennedy Orcid Logo, Sinead Brophy Orcid Logo

  • 63736.VOR.pdf

    PDF | Version of Record

    © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made

    Download (3.52MB)

Check full text

DOI (Published version): 10.1186/s12916-023-02897-5

Abstract

Background: To determine the extent and nature of changes associated with COVID-19 infection in terms of healthcare utilisation, this study observed healthcare contact 1 to 4 and 5 to 24 weeks following a COVID-19 diagnosis compared to propensity-matched controls.Methods: Two hundred forty nine thou...

Full description

Published in: BMC Medicine
ISSN: 1741-7015
Published: Springer Science and Business Media LLC 2023
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa63736
first_indexed 2023-10-02T16:35:44Z
last_indexed 2024-11-25T14:12:50Z
id cronfa63736
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2024-11-04T12:05:59.7972869</datestamp><bib-version>v2</bib-version><id>63736</id><entry>2023-06-28</entry><title>Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK</title><swanseaauthors><author><sid>08163d1f58d7fefcb1c695bcc2e0ef68</sid><ORCID/><firstname>Jonathan</firstname><surname>Kennedy</surname><name>Jonathan Kennedy</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>a4dfe07a6b18fdf6d537962b8f24fbdf</sid><ORCID>0000-0002-0350-6360</ORCID><firstname>Michael</firstname><surname>Parker</surname><name>Michael Parker</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>fcc7ece0f04577ad5f283b00dd7f52cf</sid><ORCID>0000-0002-4921-7556</ORCID><firstname>Mike</firstname><surname>Seaborne</surname><name>Mike Seaborne</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>ef78c0301f61ea4c72dd0670e61f72df</sid><firstname>Mohamed</firstname><surname>Mhereeg</surname><name>Mohamed Mhereeg</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>3f6f07de33204db4c0ab665fb4b36367</sid><ORCID>0000-0002-1500-7112</ORCID><firstname>Tash</firstname><surname>Kennedy</surname><name>Tash Kennedy</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>84f5661b35a729f55047f9e793d8798b</sid><ORCID>0000-0001-7417-2858</ORCID><firstname>Sinead</firstname><surname>Brophy</surname><name>Sinead Brophy</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2023-06-28</date><deptcode>MEDS</deptcode><abstract>Background: To determine the extent and nature of changes associated with COVID-19 infection in terms of healthcare utilisation, this study observed healthcare contact 1 to 4 and 5 to 24 weeks following a COVID-19 diagnosis compared to propensity-matched controls.Methods: Two hundred forty nine thousand three hundred ninety Welsh individuals with a positive reverse transcription&#x2013;polymerase chain reaction (RT-PCR) test were identified from data from national PCR test results. After elimination criteria, 98,600 positive individuals were matched to test negative and never tested controls using propensity matching. Cohorts were split on test location. Tests could be taken in either the hospital or community. Controls were those who had tested negative in their respective environments. Survival analysis was utilised for first clinicaloutcomes which are grouped into primary and secondary. Primary outcomes include post-viral-illness and fatigue as an indication of long-COVID. Secondary outcomes include clinical terminology concepts for embolism, respiratory conditions, mental health conditions, ft notes, or hospital attendance. Increased instantaneous risk for positive individuals was quantified using hazard ratios (HR) from Cox regression, while absolute risk (AR) and relative risk were quantified using life table analysis.Results: Analysis was conducted using all individuals and stratified by test location. Cases are compared to controls from the same test location. Fatigue (HR: 1.77, 95% CI: 1.34&#x2013;2.25, p= &lt;0.001) and embolism (HR: 1.50, 95% CI: 1.15&#x2013;1.97, p=0.003) were more likely to occur in all positive individuals in the first 4 weeks; however, anxiety and depression (HR: 0.83, 95% CI: 0.73&#x2013;0.95, p=0.007) were less likely. Positive individuals continued to be more at risk of fatigue(HR: 1.47, 95% CI: 1.24&#x2013;1.75, p= &lt;0.001) and embolism (HR: 1.51, 95% CI: 1.13&#x2013;2.02, p=0.005) after 4 weeks. All positive individuals are also at greater risk of post-viral illness (HR: 4.57, 95% CI: 1.77&#x2013;11.80, p=0.002). Despite statistical association between testing positive and several conditions, life table analysis shows that only a small minority of the studypopulation were affected.</abstract><type>Journal Article</type><journal>BMC Medicine</journal><volume>21</volume><journalNumber>1</journalNumber><paginationStart/><paginationEnd/><publisher>Springer Science and Business Media LLC</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>1741-7015</issnElectronic><keywords/><publishedDay>19</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-07-19</publishedDate><doi>10.1186/s12916-023-02897-5</doi><url/><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm>External research funder(s) paid the OA fee (includes OA grants disbursed by the Library)</apcterm><funders>UKRI, MC_PC_20059, MC_PC_20030.</funders><projectreference/><lastEdited>2024-11-04T12:05:59.7972869</lastEdited><Created>2023-06-28T12:54:54.5104328</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>Jonathan</firstname><surname>Kennedy</surname><orcid/><order>1</order></author><author><firstname>Michael</firstname><surname>Parker</surname><orcid>0000-0002-0350-6360</orcid><order>2</order></author><author><firstname>Mike</firstname><surname>Seaborne</surname><orcid>0000-0002-4921-7556</orcid><order>3</order></author><author><firstname>Mohamed</firstname><surname>Mhereeg</surname><order>4</order></author><author><firstname>A</firstname><surname>Walker</surname><order>5</order></author><author><firstname>V</firstname><surname>Walker</surname><order>6</order></author><author><firstname>S</firstname><surname>Denaxas</surname><order>7</order></author><author><firstname>Tash</firstname><surname>Kennedy</surname><orcid>0000-0002-1500-7112</orcid><order>8</order></author><author><firstname>S. V</firstname><surname>Katikireddi</surname><order>9</order></author><author><firstname>Sinead</firstname><surname>Brophy</surname><orcid>0000-0001-7417-2858</orcid><order>10</order></author></authors><documents><document><filename>63736__28681__2d7365a047f34d37ab81b31faa17bcef.pdf</filename><originalFilename>63736.VOR.pdf</originalFilename><uploaded>2023-10-02T17:34:08.9652389</uploaded><type>Output</type><contentLength>3690292</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2024-11-04T12:05:59.7972869 v2 63736 2023-06-28 Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK 08163d1f58d7fefcb1c695bcc2e0ef68 Jonathan Kennedy Jonathan Kennedy true false a4dfe07a6b18fdf6d537962b8f24fbdf 0000-0002-0350-6360 Michael Parker Michael Parker true false fcc7ece0f04577ad5f283b00dd7f52cf 0000-0002-4921-7556 Mike Seaborne Mike Seaborne true false ef78c0301f61ea4c72dd0670e61f72df Mohamed Mhereeg Mohamed Mhereeg true false 3f6f07de33204db4c0ab665fb4b36367 0000-0002-1500-7112 Tash Kennedy Tash Kennedy true false 84f5661b35a729f55047f9e793d8798b 0000-0001-7417-2858 Sinead Brophy Sinead Brophy true false 2023-06-28 MEDS Background: To determine the extent and nature of changes associated with COVID-19 infection in terms of healthcare utilisation, this study observed healthcare contact 1 to 4 and 5 to 24 weeks following a COVID-19 diagnosis compared to propensity-matched controls.Methods: Two hundred forty nine thousand three hundred ninety Welsh individuals with a positive reverse transcription–polymerase chain reaction (RT-PCR) test were identified from data from national PCR test results. After elimination criteria, 98,600 positive individuals were matched to test negative and never tested controls using propensity matching. Cohorts were split on test location. Tests could be taken in either the hospital or community. Controls were those who had tested negative in their respective environments. Survival analysis was utilised for first clinicaloutcomes which are grouped into primary and secondary. Primary outcomes include post-viral-illness and fatigue as an indication of long-COVID. Secondary outcomes include clinical terminology concepts for embolism, respiratory conditions, mental health conditions, ft notes, or hospital attendance. Increased instantaneous risk for positive individuals was quantified using hazard ratios (HR) from Cox regression, while absolute risk (AR) and relative risk were quantified using life table analysis.Results: Analysis was conducted using all individuals and stratified by test location. Cases are compared to controls from the same test location. Fatigue (HR: 1.77, 95% CI: 1.34–2.25, p= <0.001) and embolism (HR: 1.50, 95% CI: 1.15–1.97, p=0.003) were more likely to occur in all positive individuals in the first 4 weeks; however, anxiety and depression (HR: 0.83, 95% CI: 0.73–0.95, p=0.007) were less likely. Positive individuals continued to be more at risk of fatigue(HR: 1.47, 95% CI: 1.24–1.75, p= <0.001) and embolism (HR: 1.51, 95% CI: 1.13–2.02, p=0.005) after 4 weeks. All positive individuals are also at greater risk of post-viral illness (HR: 4.57, 95% CI: 1.77–11.80, p=0.002). Despite statistical association between testing positive and several conditions, life table analysis shows that only a small minority of the studypopulation were affected. Journal Article BMC Medicine 21 1 Springer Science and Business Media LLC 1741-7015 19 7 2023 2023-07-19 10.1186/s12916-023-02897-5 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University External research funder(s) paid the OA fee (includes OA grants disbursed by the Library) UKRI, MC_PC_20059, MC_PC_20030. 2024-11-04T12:05:59.7972869 2023-06-28T12:54:54.5104328 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Jonathan Kennedy 1 Michael Parker 0000-0002-0350-6360 2 Mike Seaborne 0000-0002-4921-7556 3 Mohamed Mhereeg 4 A Walker 5 V Walker 6 S Denaxas 7 Tash Kennedy 0000-0002-1500-7112 8 S. V Katikireddi 9 Sinead Brophy 0000-0001-7417-2858 10 63736__28681__2d7365a047f34d37ab81b31faa17bcef.pdf 63736.VOR.pdf 2023-10-02T17:34:08.9652389 Output 3690292 application/pdf Version of Record true © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made true eng http://creativecommons.org/licenses/by/4.0/
title Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK
spellingShingle Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK
Jonathan Kennedy
Michael Parker
Mike Seaborne
Mohamed Mhereeg
Tash Kennedy
Sinead Brophy
title_short Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK
title_full Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK
title_fullStr Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK
title_full_unstemmed Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK
title_sort Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK
author_id_str_mv 08163d1f58d7fefcb1c695bcc2e0ef68
a4dfe07a6b18fdf6d537962b8f24fbdf
fcc7ece0f04577ad5f283b00dd7f52cf
ef78c0301f61ea4c72dd0670e61f72df
3f6f07de33204db4c0ab665fb4b36367
84f5661b35a729f55047f9e793d8798b
author_id_fullname_str_mv 08163d1f58d7fefcb1c695bcc2e0ef68_***_Jonathan Kennedy
a4dfe07a6b18fdf6d537962b8f24fbdf_***_Michael Parker
fcc7ece0f04577ad5f283b00dd7f52cf_***_Mike Seaborne
ef78c0301f61ea4c72dd0670e61f72df_***_Mohamed Mhereeg
3f6f07de33204db4c0ab665fb4b36367_***_Tash Kennedy
84f5661b35a729f55047f9e793d8798b_***_Sinead Brophy
author Jonathan Kennedy
Michael Parker
Mike Seaborne
Mohamed Mhereeg
Tash Kennedy
Sinead Brophy
author2 Jonathan Kennedy
Michael Parker
Mike Seaborne
Mohamed Mhereeg
A Walker
V Walker
S Denaxas
Tash Kennedy
S. V Katikireddi
Sinead Brophy
format Journal article
container_title BMC Medicine
container_volume 21
container_issue 1
publishDate 2023
institution Swansea University
issn 1741-7015
doi_str_mv 10.1186/s12916-023-02897-5
publisher Springer Science and Business Media LLC
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 Background: To determine the extent and nature of changes associated with COVID-19 infection in terms of healthcare utilisation, this study observed healthcare contact 1 to 4 and 5 to 24 weeks following a COVID-19 diagnosis compared to propensity-matched controls.Methods: Two hundred forty nine thousand three hundred ninety Welsh individuals with a positive reverse transcription–polymerase chain reaction (RT-PCR) test were identified from data from national PCR test results. After elimination criteria, 98,600 positive individuals were matched to test negative and never tested controls using propensity matching. Cohorts were split on test location. Tests could be taken in either the hospital or community. Controls were those who had tested negative in their respective environments. Survival analysis was utilised for first clinicaloutcomes which are grouped into primary and secondary. Primary outcomes include post-viral-illness and fatigue as an indication of long-COVID. Secondary outcomes include clinical terminology concepts for embolism, respiratory conditions, mental health conditions, ft notes, or hospital attendance. Increased instantaneous risk for positive individuals was quantified using hazard ratios (HR) from Cox regression, while absolute risk (AR) and relative risk were quantified using life table analysis.Results: Analysis was conducted using all individuals and stratified by test location. Cases are compared to controls from the same test location. Fatigue (HR: 1.77, 95% CI: 1.34–2.25, p= <0.001) and embolism (HR: 1.50, 95% CI: 1.15–1.97, p=0.003) were more likely to occur in all positive individuals in the first 4 weeks; however, anxiety and depression (HR: 0.83, 95% CI: 0.73–0.95, p=0.007) were less likely. Positive individuals continued to be more at risk of fatigue(HR: 1.47, 95% CI: 1.24–1.75, p= <0.001) and embolism (HR: 1.51, 95% CI: 1.13–2.02, p=0.005) after 4 weeks. All positive individuals are also at greater risk of post-viral illness (HR: 4.57, 95% CI: 1.77–11.80, p=0.002). Despite statistical association between testing positive and several conditions, life table analysis shows that only a small minority of the studypopulation were affected.
published_date 2023-07-19T02:40:34Z
_version_ 1821371514740539392
score 11.04748

Similar Items