Bibliographic Details
| Title: |
Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study |
| Authors: |
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) |
| Publisher Information: |
Nature Portfolio, 2020. |
| Publication Year: |
2020 |
| Collection: |
LCC:Science |
| Subject Terms: |
Science |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2041-1723 |
| Relation: |
https://doaj.org/toc/2041-1723 |
| DOI: |
10.1038/s41467-020-18849-z |
| Access URL: |
https://doaj.org/article/cfa5ce1ceb5b40e2835e784a7ff0057c |
| Accession Number: |
edsdoj.fa5ce1ceb5b40e2835e784a7ff0057c |
| Database: |
Directory of Open Access Journals |
