Ricerc@Sapienza

Since the most frequent symptoms of novel coronavi- rus 2019 disease (COVID-19) are common in influenza A/B (FLU), predictive models to distinguish between COVID-19 and FLU using standardized non-specif- ic laboratory indicators are needed. The aim of our study was to evaluate whether a recently dynamic nomogram, established in the Chinese population and based on age, lymphocyte percentage and monocyte absolute count, might apply to a different context. We collected data from 299 patients (243 with COVID-19 and 56 with FLU) at Policlinico Umberto I, Sapienza University of Rome.

Background: So far, only a few studies evaluated the correlation between CT features and clinical outcome in patients with COVID-19 pneumonia. Purpose: To evaluate CT ability in differentiating critically ill patients requiring invasive ventilation from patients with less severe disease. Methods: We retrospectively collected data from patients admitted to our institution for COVID-19 pneumonia between March 5th-24th. Patients were considered critically ill or non-critically ill, depending on the need for mechanical ventilation.