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.
Keywords: Clinical; epidemiologic studies; epidemiology; health informatics; infectious diseases.