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
{"title":"长 COVID 风险预测模型的得出与验证：苏格兰一项基于人群的回顾性队列研究。","authors":"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","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>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.</p><p><strong>Design: </strong>Population-based, retrospective cohort study.</p><p><strong>Setting: </strong>Scotland.</p><p><strong>Participants: </strong>Adults (≥18 years) with a positive COVID-19 test, registered with a general medical practice between 1 March 2020 and 20 October 2022.</p><p><strong>Main outcome measures: </strong>Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for predictors of long COVID, and patients' predicted probabilities of developing long COVID.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":17271,"journal":{"name":"Journal of the Royal Society of Medicine","volume":" ","pages":"1410768241297833"},"PeriodicalIF":8.8000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11574934/pdf/","citationCount":"0","resultStr":"{\"title\":\"Deriving and validating a risk prediction model for long COVID: a population-based, retrospective cohort study in Scotland.\",\"authors\":\"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\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>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.</p><p><strong>Design: </strong>Population-based, retrospective cohort study.</p><p><strong>Setting: </strong>Scotland.</p><p><strong>Participants: </strong>Adults (≥18 years) with a positive COVID-19 test, registered with a general medical practice between 1 March 2020 and 20 October 2022.</p><p><strong>Main outcome measures: </strong>Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for predictors of long COVID, and patients' predicted probabilities of developing long COVID.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":17271,\"journal\":{\"name\":\"Journal of the Royal Society of Medicine\",\"volume\":\" \",\"pages\":\"1410768241297833\"},\"PeriodicalIF\":8.8000,\"publicationDate\":\"2024-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11574934/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Royal Society of Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/01410768241297833\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Royal Society of Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/01410768241297833","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Deriving and validating a risk prediction model for long COVID: a population-based, retrospective cohort study in Scotland.
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.
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.
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Since 1809, the Journal of the Royal Society of Medicine (JRSM) has been a trusted source of information in the medical field. Our publication covers a wide range of topics, including evidence-based reviews, original research papers, commentaries, and personal perspectives. As an independent scientific and educational journal, we strive to foster constructive discussions on vital clinical matters. While we are based in the UK, our articles address issues that are globally relevant and of interest to healthcare professionals worldwide.
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