Impact of Invasive Pulmonary Aspergillosis in Critically Ill Surgical Patients with or without Solid Organ Transplantation.

BACKGROUND: Critically ill patients, especially those who have undergone solid organ transplantation (SOT), are at risk of invasive pulmonary aspergillosis (IPA). The outcome relevance of adequately treated putative IPA (pIPA) is a matter of debate. The aim of this study is to assess the outcome relevance of pIPA in a cohort of critically ill patients with and without SOT. METHODS: Data from 121 surgical critically ill patients with pIPA (n = 30) or non-pIPA (n = 91) were included. Cox regression analysis was used to identify risk factors for mortality and unfavourable outcomes after 28 and 90 days. RESULTS: Mortality rates at 28 days were similar across the whole cohort of patients (pIPA: 31% vs. non-pIPA: 27%) and did not differ in the subgroup of patients after SOT (pIPA: 17% vs. non-pIPA: 22%). A higher Sequential Organ Failure Assessment (SOFA) score and evidence of bacteraemia were identified as risk factors for mortality and unfavourable outcome, whereas pIPA itself was not identified as an independent predictor for poor outcomes. CONCLUSIONS: Adequately treated pIPA did not increase the risk of death or an unfavourable outcome in this mixed cohort of critically ill patients with or without SOT, whereas higher disease severity and bacteraemia negatively affected the outcome.

COVID-19 pneumonia and its lookalikes: How radiologists perform in differentiating atypical pneumonias.

PURPOSE: To examine the performance of radiologists in differentiating COVID-19 from non-COVID-19 atypical pneumonia and to perform an analysis of CT patterns in a study cohort including viral, fungal and atypical bacterial pathogens. METHODS: Patients with positive RT-PCR tests for COVID-19 pneumonia (n = 90) and non-COVID-19 atypical pneumonia (n = 294) were retrospectively included. Five radiologists, blinded to the pathogen test results, assessed the CT scans and classified them as COVID-19 or non-COVID-19 pneumonia. For both groups specific CT features were recorded and a multivariate logistic regression model was used to calculate their ability to predict COVID-19 pneumonia. RESULTS: The radiologists differentiated between COVID-19 and non-COVID-19 pneumonia with an overall accuracy, sensitivity, and specificity of 88% ± 4 (SD), 79% ± 6 (SD), and 90% ± 6 (SD), respectively. The percentage of correct ratings was lower in the early and late stage of COVID-19 pneumonia compared to the progressive and peak stage (68 and 71% vs 85 and 89%). The variables associated with the most increased risk of COVID-19 pneumonia were band like subpleural opacities (OR 5.55, p < 0.001), vascular enlargement (OR 2.63, p = 0.071), and subpleural curvilinear lines (OR 2.52, p = 0.021). Bronchial wall thickening and centrilobular nodules were associated with decreased risk of COVID-19 pneumonia with OR of 0.30 (p = 0.013) and 0.10 (p < 0.001), respectively. CONCLUSIONS: Radiologists can differentiate between COVID-19 and non-COVID-19 atypical pneumonias at chest CT with high overall accuracy, although a lower performance was observed in the early and late stage of COVID 19 pneumonia. Specific CT features might help to make the correct diagnosis.