Objectif
Coronavirus disease 2019 (COVID-19) caused by infection with SARS coronavirus 2 (SARS-CoV-2) has reached pandemic proportions with more than 7 million people infected and 0.4 million people killed worldwide. Death rates are accentuated by cardiovascular comorbidities and arrhythmias leading to unexpected major cardiovascular events. Being able to identify COVID-19 patients at risk of developing cardiovascular events leading to death would allow improving surveillance and care. Currently, there is no accurate method to predict outcome of COVID-19 patients. COVIRNA is a patient-centered Innovation Action aiming to satisfy this urgent and unmet need. COVIRNA will complete and deploy a prognostic system based on cardiovascular biomarkers of COVID-19 clinical outcomes combined with digital tools and artificial intelligence analytics (i.e. prediction model). Complementary expertise of 15 EU partners from the healthcare sector, academia, association and industry will allow conducting a large retrospective study on existing cohorts of COVID-19 patients. By upscaling the already validated and patented research use only FIMICS panel of cardiac-enriched long noncoding RNA biomarkers into an in-vitro diagnostic test (COVIRNA) adapted to COVID-19 patients, the project will quickly deliver a minimally-invasive, simple yet robust and affordable prognosis tool that can be used in the context of the current COVID-19 crisis as well as in further major health issues. By tackling the cardiovascular complications in COVID-19, known to contribute significantly to mortality, the project outputs are expected to have a major impact on the pandemic outcomes. The COVIRNA test will be CE-marked and prepared for commercialization, allowing to risk stratify patients, adapt therapies and to inform drug design.
Champ scientifique (EuroSciVoc)
CORDIS classe les projets avec EuroSciVoc, une taxonomie multilingue des domaines scientifiques, grâce à un processus semi-automatique basé sur des techniques TLN.
CORDIS classe les projets avec EuroSciVoc, une taxonomie multilingue des domaines scientifiques, grâce à un processus semi-automatique basé sur des techniques TLN.
- sciences naturellesinformatique et science de l'informationintelligence artificielle
- sciences médicales et de la santémédecine cliniquecardiologiemaladies cardiovasculairesarythmie cardiaque
- sciences socialessociologiedémographiemortalité
- sciences médicales et de la santémédecine fondamentalechimie médicinale
- sciences médicales et de la santésciences de la santémaladie infectieusevirus à ARNcoronavirus
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Mots‑clés
Programme(s)
Appel à propositions
H2020-SC1-PHE-CORONAVIRUS-2020-2
Voir d’autres projets de cet appelSous appel
H2020-SC1-PHE-CORONAVIRUS-2020-2-CNECT
Régime de financement
IA - Innovation actionCoordinateur
1445 Strassen
Luxembourg