TY - JOUR
AU - Henderson, Alasdair D.
AU - Butler-Cole, Ben FC.
AU - Tazare, John
AU - Tomlinson, Laurie A.
AU - Marks, Michael
AU - Jit, Mark
AU - Briggs, Andrew
AU - Lin, Liang-Yu
AU - Carlile, Oliver
AU - Bates, Chris J.
AU - Parry, John
AU - CJ. Bacon, Sebastian
AU - Dillingham, Iain
AU - Dennison, William A.
AU - Costello, Ruth E.
AU - Wei, Yinghui
AU - Walker, Alex J.
AU - Hulme, William
AU - Goldacre, Ben
AU - Mehrkar, Amir
AU - Mackenna, Brian
AU - Walker, Alex
AU - Green, Amelia C.A.
AU - Mehrkar, Amir
AU - Schaffer, Andrea
AU - Brown, Andrew
AU - Goldacre, Ben
AU - FC. Butler-Cole, Ben
AU - Mackenna, Brian
AU - Morton, Caroline E.
AU - Walters, Caroline
AU - Stables, Catherine
AU - Cunningham, Christine
AU - Wood, Christopher
AU - Andrews, Colm
AU - Evans, David
AU - Hickman, George
AU - Curtis, Helen J.
AU - Drysdale, Henry
AU - Dillingham, Iain
AU - Morley, Jessica
AU - Massey, Jon
AU - Nab, Linda
AU - Hopcroft, Lisa E.M.
AU - Fisher, Louis
AU - Bridges, Lucy
AU - Wiedemann, Milan
AU - DeVito, Nicholas J.
AU - Macdonald, Orla
AU - Inglesby, Peter
AU - Smith, Rebecca
AU - Croker, Richard
AU - Park, Robin
AU - Higgins, Rose
AU - Bacon, Sebastian C.J.
AU - Davy, Simon
AU - Maude, Steven
AU - O'Dwyer, Thomas
AU - Ward, Tom
AU - Speed, Victoria
AU - Hulme, William
AU - Hart, Liam
AU - Stokes, Pete
AU - Bhaskaran, Krishnan
AU - Costello, Ruth E.
AU - Cowling, Thomas
AU - Douglas, Ian J.
AU - Eggo, Rosalind M
AU - Evans, Stephen J.W.
AU - Forbes, Harriet
AU - Grieve, Richard
AU - Grint, Daniel J.
AU - Herrett, Emily
AU - Langan, Sinead
AU - Mahalingasivam, Viyaasan
AU - Mansfield, Kathryn E.
AU - Mathur, Rohini
AU - McDonald, Helen I.
AU - Parker, Edward
AU - Rentsch, Christopher T.
AU - Schultze, Anna
AU - Smeeth, Liam
AU - Tazare, John
AU - Tomlinson, Laurie
AU - Walker, Jemma
AU - Williamson, Elizabeth
AU - Wing, Kevin
AU - Wong, Angel Y S
AU - Zheng, Bang
AU - Bates, Christopher
AU - Cockburn, Jonathan
AU - Parry, John
AU - Hester, Frank
AU - Harper, Sam
AU - O'Hanlon, Shaun
AU - Eavis, Alex
AU - Jarvis, Richard
AU - Avramov, Dima
AU - Griffiths, Paul
AU - Fowles, Aaron
AU - Parkes, Nasreen
AU - Perera, Rafael
AU - Harrison, David A.
AU - Khunti, Kamlesh
AU - Sterne, Jonathan
AU - Quint, Jennifer K.
AU - Herrett, Emily
AU - Eggo, Rosalind M.
PY - 2024
DA - May
TI - Clinical coding of long COVID in primary care 2020–2023 in a cohort of 19 million adults: an OpenSAFELY analysis
JO - eClinicalMedicine
VL - 72
DO - http://dx.doi.org/10.1016/j.eclinm.2024.102638
AB - 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.
PB - Elsevier
UR - https://eprints.gla.ac.uk/334106/
KW - Coronavirus (COVID-19)
KW - Primary care
ER