Background In this study we evaluated the incidence of invasive pulmonary aspergillosis among intubated patients with critical coronavirus disease 2019 (COVID-19) and evaluated different case definitions of invasive aspergillosis. Methods Prospective, multicentre study on adult patients with microbiologically confirmed COVID-19 receiving mechanical ventilation. All included participants underwent screening protocol for invasive pulmonary aspergillosis with bronchoalveolar lavage galactomannan and cultures performed on admission at 7 days and in case of clinical deterioration. Cases were classified as coronavirus associated pulmonary aspergillosis (CAPA) according to previous consensus definitions. The new definition was compared with putative invasive pulmonary aspergillosis (PIPA). Results A total of 108 patients were enrolled. Probable CAPA was diagnosed in 30 (27.7%) of patients after a median of 4 (2-8) days from intensive care unit (ICU) admission. Kaplan-Meier curves showed a significant higher 30-day mortality rate from ICU admission among patients with either CAPA (44% vs 19%, p= 0.002) or PIPA (74% vs 26%, p<0.001) when compared with patients not fulfilling criteria for aspergillosis. The association between CAPA [OR 3.53 (95%CI 1.29-9.67), P=0.014] or PIPA [OR 11.60 (95%CI 3.24-41.29) p<0.001] with 30-day mortality from ICU admission was confirmed even after adjustment for confounders with a logistic regression model. Among patients with CAPA receiving voriconazole treatment (13 patients, 43%) A trend toward lower mortality (46% vs 59% p=0.30) and reduction of galactomannan index in consecutive samples was observed. Conclusion We found a high incidence of CAPA among critically ill COVID-19 patients and that its occurrence seems to change the natural history of disease

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Background Carbapenem‐resistant Enterobacterales (CRE) colonisation at liver transplantation (LT) increases the risk of CRE infection after LT, which impacts on recipients’ survival. Colonization status usually becomes evident only near LT. Thus, predictive models can be useful to guide antibiotic prophylaxis in endemic centres. Aims This study aimed to identify risk factors for CRE colonisation at LT in order to build a predictive model. Methods Retrospective multicentre study including consecutive adult patients who underwent LT, from 2010 to 2019, at two large teaching hospitals. We excluded patients who had CRE infections within 90 days before LT. CRE screening was performed in all patients on the day of LT. Exposure variables were considered within 90 days before LT and included cirrhosis complications, underlying disease, time on the waiting list, MELD and CLIF‐SOFA scores, antibiotic use, intensive care unit and hospital stay, and infections. A machine learning model was trained to detect the probability of a patient being colonized with CRE at LT. Results A total of 1544 patients were analyzed, 116 (7.5%) patients were colonized by CRE at LT. The median time from CRE isolation to LT was 5 days. Use of antibiotics, hepato‐renal syndrome, worst CLIF sofa score, and use of beta‐lactam/beta‐lactamase inhibitor increased the probability of a patient having pre‐LT CRE. The proposed algorithm had a sensitivity of 66% and a specificity of 83% with a negative predictive value of 97%. Conclusions We created a model able to predict CRE colonization at LT based on easy‐to‐obtain features that could guide antibiotic prophylaxis

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