Back to Search Start Over

Clinical coding of long COVID in primary care 2020–2023 in a cohort of 19 million adults: an OpenSAFELY analysisResearch in context

Authors :
Alasdair D. Henderson
Ben FC. Butler-Cole
John Tazare
Laurie A. Tomlinson
Michael Marks
Mark Jit
Andrew Briggs
Liang-Yu Lin
Oliver Carlile
Chris Bates
John Parry
Sebastian CJ. Bacon
Iain Dillingham
William A. Dennison
Ruth E. Costello
Yinghui Wei
Alex J. Walker
William Hulme
Ben Goldacre
Amir Mehrkar
Brian MacKenna
Emily Herrett
Rosalind M. Eggo
Alex Walker
Amelia Green
Andrea Schaffer
Andrew Brown
Ben Butler-Cole
Caroline Morton
Caroline Walters
Catherine Stables
Christine Cunningham
Christopher Wood
Colm Andrews
David Evans
George Hickman
Helen Curtis
Henry Drysdale
Jessica Morley
Jon Massey
Linda Nab
Lisa Hopcroft
Louis Fisher
Lucy Bridges
Milan Wiedemann
Nicholas DeVito
Orla Macdonald
Peter Inglesby
Rebecca Smith
Richard Croker
Robin Park
Rose Higgins
Sebastian Bacon
Simon Davy
Steven Maude
Thomas O'Dwyer
Tom Ward
Victoria Speed
Liam Hart
Pete Stokes
Krishnan Bhaskaran
Ruth Costello
Thomas Cowling
Ian Douglas
Rosalind Eggo
Stephen Evans
Harriet Forbes
Richard Grieve
Daniel Grint
Sinead Langan
Viyaasan Mahalingasivam
Kathryn Mansfield
Rohini Mathur
Helen McDonald
Edward Parker
Christopher Rentsch
Anna Schultze
Liam Smeeth
Laurie Tomlinson
Jemma Walker
Elizabeth Williamson
Kevin Wing
Angel Wong
Bang Zheng
Christopher Bates
Jonathan Cockburn
Frank Hester
Sam Harper
Shaun O'Hanlon
Alex Eavis
Richard Jarvis
Dima Avramov
Paul Griffiths
Aaron Fowles
Nasreen Parkes
Rafael Perera
David Harrison
Kamlesh Khunti
Jonathan Sterne
Jennifer Quint
Source :
EClinicalMedicine, Vol 72, Iss , Pp 102638- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Summary: Background: Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe the incidence and differences in demographic and clinical characteristics in recorded long COVID in primary care records in England. Methods: With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. Using OpenSAFELY, we calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and adjusted (for age, sex, 9 NHS regions of England, and the dominant variant circulating) rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. Findings: We identified a total of 55,465 people recorded to have long COVID over the study period, which included 20,025 diagnoses codes and 35,440 codes for further assessment. The incidence of new long COVID records increased steadily over 2021, and declined over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5–179) and 100.5 in men (99.5–102). The majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 or more weeks before the long COVID record. Interpretation: In this descriptive study, EHR recorded long COVID was very low between 2020 and 2023, and incident records of long COVID declined over 2022. Using EHR diagnostic or referral codes unfortunately has major limitations in identifying and ascertaining true cases and timing of long COVID. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Details

Language :
English
ISSN :
25895370
Volume :
72
Issue :
102638-
Database :
Directory of Open Access Journals
Journal :
EClinicalMedicine
Publication Type :
Academic Journal
Accession number :
edsdoj.44f9e56ee26a435d9956ffa4a1354eaa
Document Type :
article
Full Text :
https://doi.org/10.1016/j.eclinm.2024.102638