International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

Abstract Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory...

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Detalhes bibliográficos

Principais autores:	Griffin M. Weber, Chuan Hong, Zongqi Xia, Nathan P. Palmer, Paul Avillach, Sehi L’Yi, Mark S. Keller, Shawn N. Murphy, Alba Gutiérrez-Sacristán, Clara-Lea Bonzel, Arnaud Serret-Larmande, Antoine Neuraz, Gilbert S. Omenn, Shyam Visweswaran, Jeffrey G. Klann, Andrew M. South, Ne Hooi Will Loh, Mario Cannataro, Brett K. Beaulieu-Jones, Riccardo Bellazzi, Giuseppe Agapito, Mario Alessiani, Bruce J. Aronow, Douglas S. Bell, Vincent Benoit, Florence T. Bourgeois, Luca Chiovato, Kelly Cho, Arianna Dagliati, Scott L. DuVall, Noelia García Barrio, David A. Hanauer, Yuk-Lam Ho, John H. Holmes, Richard W. Issitt, Molei Liu, Yuan Luo, Kristine E. Lynch, Sarah E. Maidlow, Alberto Malovini, Kenneth D. Mandl, Chengsheng Mao, Michael E. Matheny, Jason H. Moore, Jeffrey S. Morris, Michele Morris, Danielle L. Mowery, Kee Yuan Ngiam, Lav P. Patel, Miguel Pedrera-Jimenez, Rachel B. Ramoni, Emily R. Schriver, Petra Schubert, Pablo Serrano Balazote, Anastasia Spiridou, Amelia L. M. Tan, Byorn W. L. Tan, Valentina Tibollo, Carlo Torti, Enrico M. Trecarichi, Xuan Wang, The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Isaac S. Kohane, Tianxi Cai, Gabriel A. Brat
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2022-06-01
Colecção:	npj Digital Medicine
Acesso em linha:	https://doi.org/10.1038/s41746-022-00601-0
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