Clinical characterization, prediction of severity of SARS-CoV-2 infection among US adults

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What The Study Did: Researchers used a large data resource of U.S. COVID-19 cases and control patients who tested negative from multiple health systems across the country to evaluate COVID-19 severity and risk factors over time and assess the use of machine learning to predict clinical severity.

Authors: Tellen D. Bennett, M.D., of the University of Colorado School of Medicine in Aurora, and Christopher G. Chute, M.D., of Johns Hopkins University in Baltimore, are corresponding authors.

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/

(doi:10.1001/jamanetworkopen.2021.16901)

Editor’s Note: The article includes conflict of interest and funding/support disclosures. Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

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Media advisory: The full study and commentary are linked to this news release.

 

Embed this link to provide your readers free access to the full-text article This link will be live at the embargo time http://jamanetwork.com/journals/jamanetworkopen/fullarticle/10.1001/jamanetworkopen.2021.16901?utm_source=For_The_Media&utm_medium=referral&utm_campaign=ftm_links&utm_term=071321

About JAMA Network Open: JAMA Network Open is the new online-only open access general medical journal from the JAMA Network. On weekdays, the journal publishes peer-reviewed clinical research and commentary in more than 40 medical and health subject areas. Every article is free online from the day of publication.

Source: Clinical characterization, prediction of severity of SARS-CoV-2 infection among US adults



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