Deriving and validating a risk prediction model for long COVID : a population-based, retrospective cohort study in Scotland
Jeffrey, Karen and Hammersley, Vicky and Maini, Rishma and Crawford, Anna and Woolford, Lana and Batchelor, Ashleigh and Weatherill, David and White, Chris and Millington, Tristan and Kerr, Robin and Basetti, Siddharth and Macdonald, Calum and Quint, Jennifer K and Kerr, Steven and Shah, Syed Ahmar and Kurdi, Amanj and Simpson, Colin R and Katikireddi, Srinivasa Vittal and Rudan, Igor and Robertson, Chris and Ritchie, Lewis and Sheikh, Aziz and Daines, Luke (2024) Deriving and validating a risk prediction model for long COVID : a population-based, retrospective cohort study in Scotland. Journal of the Royal Society of Medicine. pp. 1-13. ISSN 0141-0768 (https://doi.org/10.1177/01410768241297833)
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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 March 1, 2020 and October 20, 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: 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
ORCID iDs
Jeffrey, Karen, Hammersley, Vicky, Maini, Rishma, Crawford, Anna, Woolford, Lana, Batchelor, Ashleigh, Weatherill, David, White, Chris, Millington, Tristan, Kerr, Robin, Basetti, Siddharth, Macdonald, Calum, Quint, Jennifer K, Kerr, Steven, Shah, Syed Ahmar, Kurdi, Amanj ORCID: https://orcid.org/0000-0001-5036-1988, Simpson, Colin R, Katikireddi, Srinivasa Vittal, Rudan, Igor, Robertson, Chris, Ritchie, Lewis, Sheikh, Aziz and Daines, Luke;-
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Item type: Article ID code: 90951 Dates: DateEvent18 November 2024Published18 November 2024Published Online21 October 2024AcceptedSubjects: Medicine Department: Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical Sciences
Strategic Research Themes > Health and Wellbeing
Faculty of Science > Mathematics and StatisticsDepositing user: Pure Administrator Date deposited: 24 Oct 2024 15:50 Last modified: 20 Nov 2024 01:29 URI: https://strathprints.strath.ac.uk/id/eprint/90951