Initial triage assessment is the cornerstone of first-line medical management for COVID-19 patients. Only an accurate and fast evaluation of COVID-19 patients respiratory system integrity, can allow optimal treatment care and medical resources attribution. Despite its very large deployment, the use of thoracic Computed Tomography (CT scan) for COVID-19 patients severity assessment is currently debated. Actually CT-scan use in this setting: i) it is associated with risky in/out hospital patient's transport, both in terms of medical management of patient's critical conditions and risk of COVID-19 nosocomial transmission, ii) risks related to x-ray exposure iii) CT-scan is a snapshot of respiratory system integrity and does not provide data that might be used for patient's monitoring. LUS is a non-invasive, non-ionizing, fully bedside imaging tool. Investigators team has previously contributed to the development and validation of LUS for critically ill patient's management. To the extent of our knowledge, there is neither data regarding COVID-19 patient's LUS patterns, nor about the potential link between LUS data, patient's severity and outcome.~The investigators hypothesize that the combined use of LUS and clinical data (Q-SOFA score, SpiO2/FiO2) recorded at COVID-19 patients hospital admission, will allow to accurately predict short-term outcome. The investigators expect to predict at patient's hospital admission, the patient's clinical status at 24h: favorable (spontaneous ventilation with O2 < 6 l/min) or unfavorable (spontaneous ventilation with O2 > 6 l/min or under mechanical ventilation).
The QUICK study main aim is to assess the predictive value at Day 1, of a model built on lung ultrasound (LUS) and clinical data, both recorded at hospital admission of COVID-19 patients.