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    • Antifungal management in ICU careful follow-up of voriconazole prescription needed!
    Authors: Florian, Reizine; Jean-Pierre, Gangneux;  Advisor: -;  Co-Author: - (2023)

    Over the last 5 years, viral induced acute respiratory distress syndrome (ARDS) has emerged as a major risk factor for invasive fungal infections in ICU patients worldwide [1, 2]. Pulmonary aspergillosis, being reported in 15–27% of critical COVID-19 patients [2, 3] and in nearly 20% of Influenza associated ARDS patients [1], appears to be the main fungal infection involved.
    • Physiological adaptations during weaning from veno-venous extracorporeal membrane oxygenation
    Authors: Patrick Duncan, Collins; Lorenzo, Giosa; Valentina, Camarda;  Advisor: -;  Co-Author: - (2023)

    Veno-venous extracorporeal membrane oxygenation (V–V ECMO) has an established evidence base in acute respiratory distress syndrome (ARDS) and has seen exponential growth in its use over the past decades. However, there is a paucity of evidence regarding the approach to weaning, with variation of practice and outcomes between centres. Preconditions for weaning, management of patients’ sedation and mechanical ventilation during this phase, criteria defining success or failure, and the optimal duration of a trial prior to decannulation are all debated subjects. Moreover, there is no prospective evidence demonstrating the superiority of weaning the sweep gas flow (SGF), the extracorporeal blood flow (ECBF) or the fraction of oxygen of the SGF (FdO2), thereby a broad inter-centre variabi...
    • Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS
    Authors: Ludmilla, Penarrubia; Aude, Verstraete; Maciej, Orkisz;  Advisor: -;  Co-Author: - (2023)

    Assessing measurement error in alveolar recruitment on computed tomography (CT) is of paramount importance to select a reliable threshold identifying patients with high potential for alveolar recruitment and to rationalize positive end-expiratory pressure (PEEP) setting in acute respiratory distress syndrome (ARDS). The aim of this study was to assess both intra- and inter-observer smallest real difference (SRD) exceeding measurement error of recruitment using both human and machine learning-made lung segmentation (i.e., delineation) on CT. This single-center observational study was performed on adult ARDS patients. CT were acquired at end-expiration and end-inspiration at the PEEP level selected by clinicians, and at end-expiration at PEEP 5 and 15 cmH2O.