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 language | English |
|---|---|
| Pages (from-to) | 402-414 |
| Number of pages | 13 |
| Journal | Journal of the Royal Society of Medicine |
| Volume | 117 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - Dec 2024 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Clinical
- epidemiologic studies
- epidemiology
- health informatics
- infectious diseases
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