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An international observational study to assess the impact of the Omicron variant emergence on the clinical epidemiology of COVID-19 in hospitalised patients
Bronner P Gonçalves; - ISARIC Clinical Characterisation Group; Matthew D Hall; Waasila Jassat; Valeria Balan; Srinivas Murthy; Christiana Kartsonaki; Calum Semple; Amanda Rojek; Joaquín Baruch; Luis Felipe Reyes; Abhishek Dasgupta; Jake Dunning; Barbara Wanjiru Citarella; Mark Pritchard; Alejandro Martín-Quiros; Uluhan Sili; John Kenneth Baillie; Diptesh Aryal; Yaseen Arabi; Aasiyah Rashan; Andrea Angheben; Janice Caoili; François Martin Carrier; Ewen M Harrison; Joan Gómez-Junyent; Claudia Figueiredo-Mello; James Joshua Douglas; Mohd Basri Mat Nor; Yock Ping Chow; Xin Ci Wong; Silvia Bertagnolio; Soe Soe Thwin; Anca Streinu-Cercel; Leonardo Salazar; Asgar Rishu; Rajavardhan Rangappa; David S.Y. Ong; Madiha Hashmi; Gail Carson; Janet Diaz; Rob Fowler; Moritz U G Kraemer; Evert-Jan Wils; Peter W Horby; Laura Merson; Piero Luigi Olliaro.
Affiliation
  • Bronner P Gonçalves; University of Oxford, UK
  • - ISARIC Clinical Characterisation Group; -
  • Matthew D Hall; University of Oxford
  • Waasila Jassat; National Institute for Communicable Diseases
  • Valeria Balan; University of Oxford, UK
  • Srinivas Murthy; University of British Columbia
  • Christiana Kartsonaki; University of Oxford
  • Calum Semple; University of Liverpool
  • Amanda Rojek; University of Oxford, UK
  • Joaquín Baruch; University of Oxford
  • Luis Felipe Reyes; Universidad de La Sabana
  • Abhishek Dasgupta; University of Oxford, UK
  • Jake Dunning; University of Oxford
  • Barbara Wanjiru Citarella; University of Oxford
  • Mark Pritchard; University of Oxford
  • Alejandro Martín-Quiros; Hospital Universitario La Paz
  • Uluhan Sili; Marmara University Pendik Training and Research Hospital
  • John Kenneth Baillie; Roslin Institute, University of Edinburgh
  • Diptesh Aryal; Nepal Mediciti Hospital
  • Yaseen Arabi; King Abdullah International Medical Research Center and King Saud Bin Abdulaziz University for Health Sciences
  • Aasiyah Rashan; Critical Care Asia
  • Andrea Angheben; IRCCS Sacro Cuore Don Calabria Hospital
  • Janice Caoili; Makati Medical Center
  • François Martin Carrier; Centre hospitalier de l'Université de Montréal
  • Ewen M Harrison; University of Edinburgh
  • Joan Gómez-Junyent; Universitat Autònoma de Barcelona
  • Claudia Figueiredo-Mello; Instituto de Infectologia Emìlio Ribas
  • James Joshua Douglas; Lions Gate Hospital
  • Mohd Basri Mat Nor; International Islamic University Malaysia
  • Yock Ping Chow; Clinical Research Centre, Sunway Medical Centre
  • Xin Ci Wong; Digital Health Research and Innovation Unit, Institute for Clinical Research, National Institutes of Health (NIH)
  • Silvia Bertagnolio; World Health Organization
  • Soe Soe Thwin; World Health Organization
  • Anca Streinu-Cercel; Carol Davila University of Medicine and Pharmacy
  • Leonardo Salazar; Fundación Cardiovascular de Colombia
  • Asgar Rishu; Critical Care Research Unit, Sunnybrook Health Sciences Centre
  • Rajavardhan Rangappa; Department of Critical Care Medicine, Manipal Hospital Whitefield,
  • David S.Y. Ong; Department of Medical Microbiology and Infection Control, Franciscus Gasthuis & Vlietland
  • Madiha Hashmi; Critical Care Asia and Ziauddin University
  • Gail Carson; University of Oxford
  • Janet Diaz; World Health Organization
  • Rob Fowler; Department of Critical Care Medicine, Sunnybrook Health Sciences Centre
  • Moritz U G Kraemer; University of Oxford
  • Evert-Jan Wils; Department of Intensive Care, Franciscus Gasthuis & Vlietland
  • Peter W Horby; University of Oxford
  • Laura Merson; University of Oxford
  • Piero Luigi Olliaro; University of Oxford
Preprint in English | medRxiv | ID: ppmedrxiv-22276764
ABSTRACT
BackgroundWhilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings. MethodsHere, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. ResultsOur analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61 - 0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population. ConclusionsAlthough clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome.
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Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Observational study / Prognostic study / Qualitative research Language: English Year: 2022 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Experimental_studies / Observational study / Prognostic study / Qualitative research Language: English Year: 2022 Document type: Preprint
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