Resumen
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.
| Idioma original | Inglés |
|---|---|
| Número de artículo | 454 |
| Publicación | Scientific data |
| Volumen | 9 |
| N.º | 1 |
| DOI | |
| Estado | Publicada - 30 jul. 2022 |
Nota bibliográfica
Publisher Copyright:© The Author(s) 2022.
Financiación
| Financiadores | Número del financiador |
|---|---|
| Instituto de Salud Carlos III | |
| Institut national de la santé et de la recherche médicale | |
| University of Queensland | |
| University of Cape Town | |
| Liverpool School of Tropical Medicine | |
| Bill and Melinda Gates Foundation | |
| University of Oxford | |
| Wellcome Trust | 220757/Z/20/Z, 220757, 215091/Z/18/Z, OPP1209135, 205228/Z/16/Z, 205228 |
| NCT04262921 | |
| 825715, 101003589 | |
| 3273191 | |
| 312780 | |
| 115523 | |
| 965313 | |
| Australian Research Council | CE170100009 |
| Medical Research Council | MC_PC_19059 |
| National Institute for Health and Care Research | COCIN-01 |
| European Commission | 602525 |
| 303953/2018-7 | |
| 200907 | |
| 20-0424 | |
| C18616/A25153 | |
| APCOV22BGM | |
| T32GM112596 | |
| MR/V001671/1 | |
| IS-BRC-1215-20013 | |
| Canadian Institutes of Health Research | OV2170359 |
| Imperial College London | 200927 |
| CTN-2014-12 |