Deriving and validating a risk prediction model for long COVID: a population-based, retrospective cohort study in Scotland

Karen Jeffrey, Vicky Hammersley, Rishma Maini, Anna Crawford, Lana Woolford, Ashleigh Batchelor, David Weatherill, Chris White, Tristan Millington, Robin Kerr, Siddharth Basetti, Calum Macdonald, Jennifer K Quint, Steven Kerr, Syed Ahmar Shah, Amanj Kurdi, Colin R Simpson, Srinivasa Vittal Katikireddi, Igor Rudan, Chris RobertsonLewis Ritchie, Aziz Sheikh, Luke Daines*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
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Abstract

Objectives Using electronic health records, we derived and internally validated a prediction model to estimate risk factors for long COVID and predict individual risk of developing long COVID. Design Population-based, retrospective cohort study. Setting Scotland. Participants Adults (≥18 years) with a positive COVID-19 test, registered with a general medical practice between 1 March 2020 and 20 October 2022. Main outcome measures Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for predictors of long COVID, and patients’ predicted probabilities of developing long COVID. Results A total of 68,486 (5.6%) patients were identified as having long COVID. Predictors of long COVID were increasing age (aOR: 3.84; 95% CI: 3.66–4.03 and aOR: 3.66; 95% CI: 3.27–4.09 in first and second splines), increasing body mass index (BMI) (aOR: 3.17; 95% CI: 2.78–3.61 and aOR: 3.09; 95% CI: 2.13–4.49 in first and second splines), severe COVID-19 (aOR: 1.78; 95% CI: 1.72–1.84); female sex (aOR: 1.56; 95% CI: 1.53–1.60), deprivation (most versus least deprived quintile, aOR: 1.40; 95% CI: 1.36–1.44), several existing health conditions. Predictors associated with reduced long COVID risk were testing positive while Delta or Omicron variants were dominant, relative to when the Wild-type variant was dominant (aOR: 0.85; 95% CI: 0.81–0.88 and aOR: 0.64; 95% CI: 0.61–0.67, respectively) having received one or two doses of COVID-19 vaccination, relative to unvaccinated (aOR: 0.90; 95% CI: 0.86–0.95 and aOR: 0.96; 95% CI: 0.93–1.00). Conclusions Older age, higher BMI, severe COVID-19 infection, female sex, deprivation and comorbidities were predictors of long COVID. Vaccination against COVID-19 and testing positive while Delta or Omicron variants were dominant predicted reduced risk.
Original languageEnglish
Pages (from-to)402-414
Number of pages13
JournalJournal of the Royal Society of Medicine
Volume117
Issue number12
Early online date18 Nov 2024
DOIs
Publication statusPublished - Dec 2024

Funding

This work was supported by the Chief Scientist Office, grant number COV/LTE/20/15 and Health Data Research UK (HDRUK2023.0027), an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and the devolved administrations and leading medical research charities. EAVE II is supported by a grant (MC_PC_19075) from the Medical Research Council; a grant (MC_PC_19004) from BREATHE – The Health Data Research Hub for Respiratory Health, funded through the UK. Public Health Scotland; and the Scottish Government Director General for Health and Social Care. The sponsor was the University of Edinburgh. LD was supported by a post-doctoral clinical fellowship from the Asthma UK Centre for Applied Research. SVK acknowledges funding from a NRS Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17).

Keywords

  • Covid 19
  • long Covid
  • risk prediction
  • Scotland

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