The study hypothesis is that low-dose computed tomography (LDCT) coupled with artificial intelligence by deep learning would generate imaging biomarkers linked to the patient's short- and medium-term prognosis. The purpose of this study is to rapidly make available an early decision-making tool (from the first hospital consultation of the patient with symptoms related to SARS-CoV-2) based on the integration of several biomarkers (clinical, biological, imaging by thoracic scanner) allowing both personalized medicine and better anticipation of the patient's evolution in terms of care organization.
Diagnostic Test: Imaging by thoracic scanner
Low-dose computed tomography
Inclusion Criteria:
- Patients positive for SARS-CoV-2 according to RT-PCR test between 1st March and 31st
May 2020
- Patients undergoing low dose CT scan to establish Covid-19 lung damage
- Available for at least 8 days follow-up
Exclusion Criteria:
• Patients opposing the retrospective use of their data
CHU la Timone
Marseille, France
CHU Montpellier
Montpellier, France
CHU de Nimes
Nîmes, France
CHU Poitiers
Poitiers, France
CHU Strasbourg
Strasbourg, France
CHU Martinique
Fort-de-France, Martinique
Julien Frandon, Principal Investigator
CHU Nimes