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Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study

  • Edward Burn
  • , Seng Chan You
  • , Anthony G. Sena
  • , Kristin Kostka
  • , Hamed Abedtash
  • , Maria Tereza F. Abrahão
  • , Amanda Alberga
  • , Heba Alghoul
  • , Osaid Alser
  • , Thamir M. Alshammari
  • , Maria Aragon
  • , Carlos Areia
  • , Juan M. Banda
  • , Jaehyeong Cho
  • , Aedin C. Culhane
  • , Alexander Davydov
  • , Frank J. DeFalco
  • , Talita Duarte-Salles
  • , Scott DuVall
  • , Thomas Falconer
  • Sergio Fernandez-Bertolin, Weihua Gao, Asieh Golozar, Jill Hardin, George Hripcsak, Vojtech Huser, Hokyun Jeon, Yonghua Jing, Chi Young Jung, Benjamin Skov Kaas-Hansen, Denys Kaduk, Seamus Kent, Yeesuk Kim, Spyros Kolovos, Jennifer C.E. Lane, Hyejin Lee, Kristine E. Lynch, Rupa Makadia, Michael E. Matheny, Paras P. Mehta, Daniel R. Morales, Karthik Natarajan, Fredrik Nyberg, Anna Ostropolets, Rae Woong Park, Jimyung Park, Jose D. Posada, Albert Prats-Uribe, Gowtham Rao, Christian Reich, Yeunsook Rho, Peter Rijnbeek, Lisa M. Schilling, Martijn Schuemie, Nigam H. Shah, Azza Shoaibi, Seokyoung Song, Matthew Spotnitz, Marc A. Suchard, Joel N. Swerdel, David Vizcaya, Salvatore Volpe, Haini Wen, Andrew E. Williams, Belay B. Yimer, Lin Zhang, Oleg Zhuk, Daniel Prieto-Alhambra, Patrick Ryan
  • Fundacio Institut Universitari per a la recerca a l’Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol)
  • University of Oxford
  • Ajou University
  • Johnson & Johnson
  • Erasmus University Rotterdam
  • IQVIA Inc.
  • Eli Lilly
  • Universidade de São Paulo
  • Observational Health Data Sciences and Informatics Network
  • Islamic University of Gaza
  • Harvard University
  • King Saud University
  • Georgia State University
  • Dana-Farber Cancer Institute
  • Odysseus Data Services
  • Belarusian State Medical University
  • Department of Veterans Affairs
  • University of Utah
  • Columbia University
  • AbbVie
  • Pharmacoepidemiology
  • Johns Hopkins University
  • New York Presbyterian Hospital
  • National Institutes of Health
  • Catholic University of Daegu
  • Sjællands Universitetshospital
  • University of Copenhagen
  • V. N. Karazin Kharkiv National University
  • National Institute for Health and Care Research
  • Hanyang University
  • Health Insurance Review & Assessment Service
  • GRECC
  • Vanderbilt University
  • University of Arizona
  • University of Dundee
  • University of Gothenburg
  • Stanford University
  • University of Colorado Anschutz Medical Campus
  • University of California at Los Angeles
  • Bayer Pharmaceuticals
  • Shanghai University of Traditional Chinese Medicine
  • Tufts Institute for Clinical Research and Health Policy Studies
  • University of Manchester
  • School of Public Health, Peking Union Medical College
  • University of Melbourne

Research output: Contribution to journalArticlepeer-review

Abstract

Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.

Original languageEnglish
Article number5009
JournalNature Communications
Volume11
Issue number1
DOIs
Publication statusPublished - 1 Dec 2020
Externally publishedYes

UN SDGs

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

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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