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Tan EH, Sena AG, Prats-Uribe A, et al. Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis. medRxiv. 2020;doi: 10.1101/2020.11.24.20236802.
Tan, E. H., Sena, A. G., Prats-Uribe, A., You, S. C., Ahmed, W. U., Kostka, K., Reich, C., Duvall, S. L., Lynch, K. E., Matheny, M. E., Duarte-Salles, T., Bertolin, S. F., Hripcsak, G., Natarajan, K., Falconer, T., Spotnitz, M., Ostropolets, A., Blacketer, C., Alshammari, T. M., Alghoul, H., Alser, O., Lane, J. C. E., Dawoud, D. M., Shah, K., Yang, Y., Zhang, L., Areia, C., Golozar, A., Relcade, M., Casajust, P., Jonnagaddala, J., Subbian, V., Vizcaya, D., Lai, L. Y., Nyberg, F., Morales, D. R., Posada, J. D., Shah, N. H., Gong, M., Vivekanantham, A., Abend, A., Minty, E. P., Suchard, M., Rijnbeek, P., Ryan, P. B., & Prieto-Alhambra, D. (2020). Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis. medRxiv : the preprint server for health sciences, . https://doi.org/10.1101/2020.11.24.20236802
Tan, Eng Hooi, et al. "Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis." medRxiv : the preprint server for health sciences vol. (2020). doi: https://doi.org/10.1101/2020.11.24.20236802
Tan EH, Sena AG, Prats-Uribe A, You SC, Ahmed WU, Kostka K, Reich C, Duvall SL, Lynch KE, Matheny ME, Duarte-Salles T, Bertolin SF, Hripcsak G, Natarajan K, Falconer T, Spotnitz M, Ostropolets A, Blacketer C, Alshammari TM, Alghoul H, Alser O, Lane JCE, Dawoud DM, Shah K, Yang Y, Zhang L, Areia C, Golozar A, Relcade M, Casajust P, Jonnagaddala J, Subbian V, Vizcaya D, Lai LY, Nyberg F, Morales DR, Posada JD, Shah NH, Gong M, Vivekanantham A, Abend A, Minty EP, Suchard M, Rijnbeek P, Ryan PB, Prieto-Alhambra D. Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis. medRxiv. 2020 Nov 27; doi: 10.1101/2020.11.24.20236802. PMID: 33269355; PMCID: PMC7709171.
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medRxiv. 2020 Nov 27; doi: 10.1101/2020.11.24.20236802.

Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis.

medRxiv : the preprint server for health sciences

Eng Hooi Tan, Anthony G Sena, Albert Prats-Uribe, Seng Chan You, Waheed-Ul-Rahman Ahmed, Kristin Kostka, Christian Reich, Scott L Duvall, Kristine E Lynch, Michael E Matheny, Talita Duarte-Salles, Sergio Fernandez Bertolin, George Hripcsak, Karthik Natarajan, Thomas Falconer, Matthew Spotnitz, Anna Ostropolets, Clair Blacketer, Thamir M Alshammari, Heba Alghoul, Osaid Alser, Jennifer C E Lane, Dalia M Dawoud, Karishma Shah, Yue Yang, Lin Zhang, Carlos Areia, Asieh Golozar, Martina Relcade, Paula Casajust, Jitendra Jonnagaddala, Vignesh Subbian, David Vizcaya, Lana Yh Lai, Fredrik Nyberg, Daniel R Morales, Jose D Posada, Nigam H Shah, Mengchun Gong, Arani Vivekanantham, Aaron Abend, Evan P Minty, Marc Suchard, Peter Rijnbeek, Patrick B Ryan, Daniel Prieto-Alhambra

Affiliations

  1. Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, OX3 7LD, UK.
  2. Janssen Research and Development, Titusville, NJ USA.
  3. Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands.
  4. Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.
  5. Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Windmill Road, Oxford, OX3 7LD, UK.
  6. College of Medicine and Health, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK.
  7. Real World Solutions, IQVIA, Cambridge, MA USA.
  8. VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA.
  9. Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA.
  10. Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA.
  11. Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
  12. Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
  13. Department of Biomedical Informatics, Columbia University, New York, NY, US.
  14. New York-Presbyterian Hospital, New York, NY, US.
  15. Medication Safety Research Chair, King Saud Univeristy.
  16. Faculty of Medicine, Islamic University of Gaza, Palestine.
  17. Massachusetts General Hospital, Harvard Medical School, Boston, 02114, Massachusetts, USA.
  18. Cairo University, Faculty of Pharmacy, Cairo, Egypt.
  19. DHC Technologies Co., LTD.
  20. School of Population Medicine and Public Health, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100730, China.
  21. Melbourne School of Population and Global Health, The University of Melbourne, Victoria 3015, Australia.
  22. Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU, UK.
  23. Regeneron Pharmaceuticals, NY US.
  24. Departament of Epidemiology, Johns Hopkins School of Public, Baltimore MD.
  25. Universitat Autonoma de Barcelona, Spain.
  26. Real-World Evidence, Trial Form Support, Barcelona, Spain.
  27. School of Public Health and Community Medicine, UNSW Sydney.
  28. College of Engineering, The University of Arizona Tucson, Arizona, USA.
  29. Bayer Pharmaceuticals, Sant Joan Despi, Spain.
  30. School of Medical Sciences, University of Manchester, UK.
  31. School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  32. Division of Population Health Sciences, University of Dundee.
  33. Stanford Center for Biomedical Informatics Research, Department of Medicine, School of Medicine, Stanford University.
  34. Health Management Institute, Southern Medical University.
  35. Autoimmune Registry Inc., 125 West Lane, Guilford, CT 06437.
  36. O'Brien School for Public Health, Faculty of Medicine, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada.
  37. Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA USA.

PMID: 33269355 PMCID: PMC7709171 DOI: 10.1101/2020.11.24.20236802

Abstract

OBJECTIVE: Patients with autoimmune diseases were advised to shield to avoid COVID-19, but information on their prognosis is lacking. We characterised 30-day outcomes and mortality after hospitalisation with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza.

DESIGN: Multinational network cohort study.

SETTING: Electronic health records data from Columbia University Irving Medical Center (CUIMC) (NYC, United States [US]), Optum [US], Department of Veterans Affairs (VA) (US), Information System for Research in Primary Care-Hospitalisation Linked Data (SIDIAP-H) (Spain), and claims data from IQVIA Open Claims (US) and Health Insurance and Review Assessment (HIRA) (South Korea).

PARTICIPANTS: All patients with prevalent autoimmune diseases, diagnosed and/or hospitalised between January and June 2020 with COVID-19, and similar patients hospitalised with influenza in 2017-2018 were included.

MAIN OUTCOME MEASURES: 30-day complications during hospitalisation and death.

RESULTS: We studied 133,589 patients diagnosed and 48,418 hospitalised with COVID-19 with prevalent autoimmune diseases. The majority of participants were female (60.5% to 65.9%) and aged ≥50 years. The most prevalent autoimmune conditions were psoriasis (3.5 to 32.5%), rheumatoid arthritis (3.9 to 18.9%), and vasculitis (3.3 to 17.6%). Amongst hospitalised patients, Type 1 diabetes was the most common autoimmune condition (4.8% to 7.5%) in US databases, rheumatoid arthritis in HIRA (18.9%), and psoriasis in SIDIAP-H (26.4%).Compared to 70,660 hospitalised with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2% to 4.3% versus 6.3% to 24.6%).

CONCLUSIONS: Patients with autoimmune diseases had high rates of respiratory complications and 30-day mortality following a hospitalization with COVID-19. Compared to influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality. Future studies should investigate predictors of poor outcomes in COVID-19 patients with autoimmune diseases.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC: Patients with autoimmune conditions may be at increased risk of COVID-19 infection andcomplications.There is a paucity of evidence characterising the outcomes of hospitalised COVID-19 patients with prevalent autoimmune conditions.

WHAT THIS STUDY ADDS: Most people with autoimmune diseases who required hospitalisation for COVID-19 were women, aged 50 years or older, and had substantial previous comorbidities.Patients who were hospitalised with COVID-19 and had prevalent autoimmune diseases had higher prevalence of hypertension, chronic kidney disease, heart disease, and Type 2 diabetes as compared to those with prevalent autoimmune diseases who were diagnosed with COVID-19.A variable proportion of 6% to 25% across data sources died within one month of hospitalisation with COVID-19 and prevalent autoimmune diseases.For people with autoimmune diseases, COVID-19 hospitalisation was associated with worse outcomes and 30-day mortality compared to admission with influenza in the 2017-2018 season.

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