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. 2024 Dec;117(12):402-414.
doi: 10.1177/01410768241297833. Epub 2024 Nov 18.

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

Karen Jeffrey  1 , Vicky Hammersley  1 , Rishma Maini  2 , Anna Crawford  1 , Lana Woolford  1 , Ashleigh Batchelor  1 , David Weatherill  1 , Chris White  1 , Tristan Millington  1 , Robin Kerr  3 , Siddharth Basetti  4 , Calum Macdonald  1 , Jennifer K Quint  5 , Steven Kerr  1 , Syed Ahmar Shah  1 , Amanj Kurdi  6   7   8   9 , Colin R Simpson  1   10 , Srinivasa Vittal Katikireddi  2   11 , Igor Rudan  1 , Chris Robertson  2   12 , Lewis Ritchie  13   14 , Aziz Sheikh  1   15 , Luke Daines  1
Affiliations

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

Karen Jeffrey et al. J R Soc Med. 2024 Dec.

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.

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

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Conflict of interest statement

AS reports grants from HDRUK, grants from NIHR, grants from MRC, grants from ICSF, during the conduct of the study; and Member of Scottish Government’s CMO COVID-19 Advisory Group and Standing Committee on Pandemics. CR reports support from PHS and MRC. CS reports grants from MBIE (New Zealand), Ministry of Health (New Zealand), and HRC (New Zealand). JKQ reports grants from MRC, HDR UK, GlaxoSmithKline, BI, Asthma+Lung UK and AstraZeneca and consulting fees from GlaxoSmithKline, Evidera, AstraZeneca, Insmed. SVK reports grants from MRC and Scottish Government CSO. KJ, VH, RM, AC, LW, AB, DW, CW, TM, RK, SB, CM, SK, SAS, AK, IR, LR and LD report no competing interests.

Figures

Figure 1.
Figure 1.
Participants identified as having long COVID in the training and holdout datasets.
Figure 2.
Figure 2.
Long COVID outcome measure. Individuals were classified as having long COVID if they had any of the indicators described in boxes 1–4 recorded in their EHR.
Figure 3.
Figure 3.
Adjusted odds ratios for predictors of long COVID. The plot illustrates the adjusted odds ratios and 95% confidence intervals for all predictors of long COVID included in the main multivariable logistic regression model. The model was trained on the training dataset (n = 882,782) using multivariable logistic regression with 10-fold cross-validation. SIMD quintiles relate to quintiles of the Scottish Index of Multiple Deprivation.
Figure 4.
Figure 4.
Predicted probability of long COVID by age, sex, BMI and variant period. (a) Predicted probabilities of long COVID by age and sex. (b) Predicted probabilities of long COVID by age and dominant SARS-CoV-2 variant in circulation when an individual received a positive RT-PCR test. (c) Predicted probabilities of long COVID by BMI and sex. (d) Predicted probabilities of long COVID by BMI and dominant SARS-CoV-2 variant in circulation when an individual received a positive RT-PCR test. Predicted probabilities were estimated by applying the main multivariable regression model to the training dataset (N = 876,885). Shading indicates 95% confidence intervals.
See this image and copyright information in PMC

Comment in

  • Low muscle mass and the risk of long COVID.
    Jawad F, Jawad AS. Jawad F, et al. J R Soc Med. 2025 Apr;118(4):108. doi: 10.1177/01410768251326488. Epub 2025 Apr 9. J R Soc Med. 2025. PMID: 40202056 Free PMC article. No abstract available.

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