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 Robertson; Lewis Ritchie; Aziz Sheikh; Luke Daines

doi:10.1177/01410768241297833

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 journal › Article › peer-review

2 Citations (Scopus)

2 Downloads (Pure)

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
Early online date	18 Nov 2024
DOIs	https://doi.org/10.1177/01410768241297833
Publication status	Published - 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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1177/01410768241297833Licence: CC BY 4.0

Jeffrey-etal-JRSM-2024-Deriving-and-validating-a-risk-prediction-modelFinal published version, 1.25 MBLicence: CC BY 4.0

Cite this

Jeffrey, K., Hammersley, V., Maini, R., Crawford, A., Woolford, L., Batchelor, A., Weatherill, D., White, C., Millington, T., Kerr, R., Basetti, S., Macdonald, C., Quint, J. K., Kerr, S., Shah, S. A., Kurdi, A., Simpson, C. R., Katikireddi, S. V., Rudan, I., ... Daines, L. (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, 117(12), 402-414. https://doi.org/10.1177/01410768241297833

@article{a70058388c5b49fbb79ecca86c26e002,

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

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{\textquoteright} 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 = "Covid 19, long Covid, risk prediction, Scotland",

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

year = "2024",

month = dec,

doi = "10.1177/01410768241297833",

language = "English",

volume = "117",

pages = "402--414",

journal = "Journal of the Royal Society of Medicine",

issn = "0141-0768",

publisher = "SAGE Publications Ltd",

number = "12",

}

Jeffrey, K, Hammersley, V, Maini, R, Crawford, A, Woolford, L, Batchelor, A, Weatherill, D, White, C, Millington, T, Kerr, R, Basetti, S, Macdonald, C, Quint, JK, Kerr, S, Shah, SA, Kurdi, A, Simpson, CR, Katikireddi, SV, Rudan, I, Robertson, C, Ritchie, L, Sheikh, A & Daines, L 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, vol. 117, no. 12, pp. 402-414. https://doi.org/10.1177/01410768241297833

TY - JOUR

T1 - Deriving and validating a risk prediction model for long COVID

T2 - a population-based, retrospective cohort study in Scotland

AU - Jeffrey, Karen

AU - Hammersley, Vicky

AU - Maini, Rishma

AU - Crawford, Anna

AU - Woolford, Lana

AU - Batchelor, Ashleigh

AU - Weatherill, David

AU - White, Chris

AU - Millington, Tristan

AU - Kerr, Robin

AU - Basetti, Siddharth

AU - Macdonald, Calum

AU - Quint, Jennifer K

AU - Kerr, Steven

AU - Shah, Syed Ahmar

AU - Kurdi, Amanj

AU - Simpson, Colin R

AU - Katikireddi, Srinivasa Vittal

AU - Rudan, Igor

AU - Robertson, Chris

AU - Ritchie, Lewis

AU - Sheikh, Aziz

AU - Daines, Luke

PY - 2024/12

Y1 - 2024/12

N2 - 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.

AB - 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.

KW - Covid 19

KW - long Covid

KW - risk prediction

KW - Scotland

U2 - 10.1177/01410768241297833

DO - 10.1177/01410768241297833

M3 - Article

SN - 0141-0768

VL - 117

SP - 402

EP - 414

JO - Journal of the Royal Society of Medicine

JF - Journal of the Royal Society of Medicine

IS - 12

ER -

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

Abstract

Funding

Keywords

UN SDGs

Access to Document

Fingerprint

Cite this