Project Details
Description
COVID-19 pandemic has affected more than 80 million people around the globe. The epidemic has evolved at different speeds and times worldwide. Thus, describing the patients and the treatments used in countries where the epidemic began (e.g., China, Italy, UK) have helped other countries to prepare before COVID-19 arrival at their own countries. Thus, observational registries and the evidence they generate are of vital importance for decision-makers, patients, and physicians around the world. As with other pulmonary infections, patients with COVID-19 may develop systemic complications (e.g., heart failure, pulmonary embolisms, among others), which can worsen clinical outcomes. The ISARIC-COVID-19 dataset is the world’s largest standardized collection of comprehensive clinical data. Importantly, this dataset is freely available, which opens the possibility for any research to address knowledge gaps. This project will produce documentation, code and pre-processing of that dataset to accelerate and optimise its use. This dataset is a rich tool for characterizing the systemic complications contributing to the morbidity and mortality of COVID-19. As data identifying the risk factor and clinical characteristics of these complications are scarce, we hypothesize that creating a detailed data descriptor manuscript, a reference tutorial-like code, and using the systemic complications analysis as an example, would allow researchers without advanced coding skills to fully utilize the ISARIC-COVID-19 dataset.Finally, ensuring the dataset is correctly used and that researchers can make the best out of this dataset will improve the understating of the COVID-19 and its systemic complications.
Layman's description
COVID-19 pandemic has affected more than 80 million people around the globe. The epidemic has evolved at different speeds and times worldwide. Thus, describing the patients and the treatments used in countries where the epidemic began (e.g., China, Italy, UK) have helped other countries to prepare before COVID-19 arrival at their own countries. Thus, observational registries and the evidence they generate are of vital importance for decision-makers, patients, and physicians around the world. As with other pulmonary infections, patients with COVID-19 may develop systemic complications (e.g., heart failure, pulmonary embolisms, among others), which can worsen clinical outcomes. The ISARIC-COVID-19 dataset is the world’s largest standardized collection of comprehensive clinical data. Importantly, this dataset is freely available, which opens the possibility for any research to address knowledge gaps. This project will produce documentation, code and pre-processing of that dataset to accelerate and optimise its use. This dataset is a rich tool for characterizing the systemic complications contributing to the morbidity and mortality of COVID-19. As data identifying the risk factor and clinical characteristics of these complications are scarce, we hypothesize that creating a detailed data descriptor manuscript, a reference tutorial-like code, and using the systemic complications analysis as an example, would allow researchers without advanced coding skills to fully utilize the ISARIC-COVID-19 dataset.Finally, ensuring the dataset is correctly used and that researchers can make the best out of this dataset will improve the understating of the COVID-19 and its systemic complications.
Key findings
COVID 19, risk factors,
| Status | Finished |
|---|---|
| Effective start/end date | 5/07/21 → 5/07/22 |
Collaborative partners
- Universidad de La Sabana (lead)
- University of Oxford (CoExecutor)
- Network Improving Critical Care Systems and Training (CoExecutor)
- BC Children’s Hospital (CoExecutor)
- Bill & Melinda Gates Foundation (CoFunder)
Project Status
- Succesfully closed
Relation Academy- enterprises
- No
Training for research
- No
Interdisciplinary
- No
Collaborative project between research groups
- No
Project with potential for technological development susceptible to intellectual property protection.
- No
Degree work - Master's or Ph
- None
Area of knowledge (OECD)
- MEDICINE - CLINICAL SCIENCES
Rol Sabana
- Executor
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Research output
- 6 Article
-
Event rates and incidence of post-COVID-19 condition in hospitalised SARS-CoV-2 positive children and young people and controls across different pandemic waves exposure-stratified prospective cohort study in Moscow (StopCOVID)
Pazukhina, E., Rumyantsev, M., Baimukhambetova, D., Bondarenko, E., Markina, N., El-Taravi, Y., Petrova, P., Ezhova, A., Andreeva, M., Iakovleva, E., Bobkova, P., Pikuza, M., Trefilova, A., Abdeeva, E., Galiautdinova, A., Filippova, Y., Bairashevskaia, A., Zolotarev, A., Bulanov, N. & DunnGalvin, A. & 30 others, , Dec 2024, In: BMC Medicine. 22, 1, 48.Research output: Contribution to journal › Article › peer-review
Open Access12 Scopus citations -
Sex differences in post-acute neurological sequelae of SARS-CoV-2 and symptom resolution in adults after coronavirus disease 2019 hospitalization: an international multi-centre prospective observational study
ISARIC Clinical Characterisation Group & Reyes, L. F., 1 Mar 2024, In: Brain Communications. 6, 2, p. 1-14 14 p., fcae036.Translated title of the contribution :Sex differences in post-acute neurological sequelae of SARS-CoV-2 and symptom resolution in adults after coronavirus disease 2019 hospitalization: an international multi-centre prospective observational study Research output: Contribution to journal › Article › peer-review
9 Scopus citations -
Effectiveness of prolonged versus standard-course of oseltamivir in critically ill patients with severe influenza infection: A multicentre cohort study
Reyes Velasco, L. F. (Another Number Author), Diaz, E. (Another Number Author), Moreno, G. (Another Number Author), Restrepo, M. I. (Another Number Author) & Martin-Loeches,, I. (Another Number Author), 3 Aug 2023, In: Journal of Medical Virology. p. 1-13 12 p.Research output: Contribution to journal › Article › peer-review
12 Scopus citations