학술논문
Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study
Document Type
article
Author
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
Source
Nature Communications, Vol 11, Iss 1, Pp 1-11 (2020)
Subject
Language
English
ISSN
2041-1723
Abstract
Detailed knowledge of the characteristics of COVID-19 patients helps with public health planning. Here, the authors use routinely-collected data from seven databases in three countries to describe the characteristics of >30,000 patients admitted with COVID-19 and compare them with those admitted for influenza in previous years.