Data Entry: Please note that the research database will be replaced by UNIverse by the end of October 2023. Please enter your data into the system https://universe-intern.unibas.ch. Thanks

Login for users with Unibas email account...

Login for registered users without Unibas email account...

 
COVID-evidence: a living database of trials on interventions for COVID-19
Third-party funded project
Project title COVID-evidence: a living database of trials on interventions for COVID-19
Principal Investigator(s) Hemkens, Lars G.
Project Members Düblin, Pascal
Organisation / Research unit Departement Klinische Forschung / Klinische Epidemiologie (Bucher H)
Project start 01.06.2020
Probable end 30.11.2021
Status Completed
Abstract

The COVID-19 pandemic is characterized by an unprecedented urgency to obtain reliable information on therapeutic options and their evaluation in clinical trials.Objective: We aim to provide a freely available and continuously updated online database of worldwide trial evidence on benefits and harms of interventions for COVID-19, including interventions for prevention, diagnosis, treatment and clinical management.Data sources include literature databases (e.g. PubMed), trial registries (e.g. ClinicalTrials.gov, WHO's International Clinical Trials Registry Platform (WHO-ICTRP) and Chinese Clinical Trial Registry (ChiCTR)) and preprint servers (medRxiv and bioRxiv).Selection criteria: We will include reports, registry entries, and manuscripts of trials testing any intervention actively allocated to humans with COVID-19. We will include a broad range of trial designs (including multi-arm but also uncontrolled trials) and interventions (including drug and non-drug treatments, vaccines, diagnostic procedures, and decision algorithms) without restrictions to language, region, or healthcare setting. Design and Methods: In close collaboration with a world-wide network of partners, we will use a multi-method approach combining peer-reviewed search strategies, continuous automated extraction of search results, automated classifications combined with crowd-based manual screening and data extraction, and quality control through expert review. We will start with a set of core variables and gradually expand the amount of information based on the needs of different stakeholders (including patients, clinicians, systematic reviewers, guideline developers and policy makers). The new website COVID-evidence.org will provide both the extracted information and links to the original data sources. The modular design of the database will allow continuous updates, addition of new data sources and content, and flexible adjustments to future projects.Relevance of the project: COVID-evidence.org will continuously monitor the clinical trial research agenda on COVID-19 and present decision-makers and researchers with the latest available trial evidence on how to prevent, diagnose, treat and manage COVID-19. Finally, by including key experts in the field and catalyzing international collaborations, we aim to foster evidence-based decisions on all levels of health policy and practice.

Financed by Swiss National Science Foundation (SNSF)
   

MCSS v5.8 PRO. 0.467 sec, queries - 0.000 sec ©Universität Basel  |  Impressum   |    
26/04/2024