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ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19
The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of h...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9339000/ https://www.ncbi.nlm.nih.gov/pubmed/35908040 http://dx.doi.org/10.1038/s41597-022-01534-9 |
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author | Garcia-Gallo, Esteban Merson, Laura Kennon, Kalynn Kelly, Sadie Citarella, Barbara Wanjiru Fryer, Daniel Vidali Shrapnel, Sally Lee, James Duque, Sara Fuentes, Yuli V. Balan, Valeria Smith, Sue Wei, Jia Gonçalves, Bronner P. Russell, Clark D. Sigfrid, Louise Dagens, Andrew Olliaro, Piero L. Baruch, Joaquin Kartsonaki, Christiana Dunning, Jake Rojek, Amanda Rashan, Aasiyah Beane, Abi Murthy, Srinivas Reyes, Luis Felipe |
author_facet | Garcia-Gallo, Esteban Merson, Laura Kennon, Kalynn Kelly, Sadie Citarella, Barbara Wanjiru Fryer, Daniel Vidali Shrapnel, Sally Lee, James Duque, Sara Fuentes, Yuli V. Balan, Valeria Smith, Sue Wei, Jia Gonçalves, Bronner P. Russell, Clark D. Sigfrid, Louise Dagens, Andrew Olliaro, Piero L. Baruch, Joaquin Kartsonaki, Christiana Dunning, Jake Rojek, Amanda Rashan, Aasiyah Beane, Abi Murthy, Srinivas Reyes, Luis Felipe |
collection | PubMed |
description | The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use. |
format | Online Article Text |
id | pubmed-9339000 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93390002022-08-01 ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19 Garcia-Gallo, Esteban Merson, Laura Kennon, Kalynn Kelly, Sadie Citarella, Barbara Wanjiru Fryer, Daniel Vidali Shrapnel, Sally Lee, James Duque, Sara Fuentes, Yuli V. Balan, Valeria Smith, Sue Wei, Jia Gonçalves, Bronner P. Russell, Clark D. Sigfrid, Louise Dagens, Andrew Olliaro, Piero L. Baruch, Joaquin Kartsonaki, Christiana Dunning, Jake Rojek, Amanda Rashan, Aasiyah Beane, Abi Murthy, Srinivas Reyes, Luis Felipe Sci Data Data Descriptor The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use. Nature Publishing Group UK 2022-07-30 /pmc/articles/PMC9339000/ /pubmed/35908040 http://dx.doi.org/10.1038/s41597-022-01534-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Garcia-Gallo, Esteban Merson, Laura Kennon, Kalynn Kelly, Sadie Citarella, Barbara Wanjiru Fryer, Daniel Vidali Shrapnel, Sally Lee, James Duque, Sara Fuentes, Yuli V. Balan, Valeria Smith, Sue Wei, Jia Gonçalves, Bronner P. Russell, Clark D. Sigfrid, Louise Dagens, Andrew Olliaro, Piero L. Baruch, Joaquin Kartsonaki, Christiana Dunning, Jake Rojek, Amanda Rashan, Aasiyah Beane, Abi Murthy, Srinivas Reyes, Luis Felipe ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19 |
title | ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19 |
title_full | ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19 |
title_fullStr | ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19 |
title_full_unstemmed | ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19 |
title_short | ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19 |
title_sort | isaric-covid-19 dataset: a prospective, standardized, global dataset of patients hospitalized with covid-19 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9339000/ https://www.ncbi.nlm.nih.gov/pubmed/35908040 http://dx.doi.org/10.1038/s41597-022-01534-9 |
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