Background COVID-19 is a novel viral disease. Severe courses may present as ARDS. Several publications report a high incidence of coagulation abnormalities in these patients. We aimed to compare coagulation and inflammation parameters in patients with ARDS due to SARS-CoV-2 infection versus patients with ARDS due to other causes. Methods This retrospective study included intubated patients admitted with the diagnosis of ARDS to the ICU at Munich university hospital. 22 patients had confirmed SARS-CoV2-infection (COVID-19 group), 14 patients had bacterial or other viral pneumonia (control group). Demographic, clinical parameters and laboratory tests including coagulation parameters and thromboelastometry were analysed. Results No differences were found in gender ratios, BMI, Horovitz quotients and haemoglobin values. The median SOFA score, serum lactate levels, renal function parameters (creatinine, urea) and all inflammation markers (IL-6, PCT, CRP) were lower in the COVID-19 group (all: p < 0.05). INR (p < 0.001) and antithrombin (p < 0.001) were higher in COVID-19 patients. D-dimer levels (p = 0.004) and consecutively the DIC score (p = 0.003) were lower in this group. In ExTEM®, Time-to-Twenty (TT20) was shorter in the COVID-19 group (p = 0.047), these patients also had higher FibTEM® MCF (p = 0.005). Further, these patients presented with elevated antigen and activity levels of von-Willebrand-Factor (VWF). Conclusion COVID-19 patients presented with higher coagulatory potential (shortened global clotting tests, increased viscoelastic and VWF parameters), while DIC scores were lower. An intensified anticoagulation regimen based on an individual risk assessment is advisable to avoid thromboembolic complications.

There are different methods of artificial liver support for patients with acute liver dysfunction (ALD). However, CytoSorb (CS) might be a new approved option for those patients. Question of interest is whether the elimination performance of CS was comparable to that of advanced organ support (ADVOS). Patients, treated with CS (integrated into high-flux dialysis) or ADVOS and a total bilirubin > 10 mg/dl were included. Laboratory parameters were evaluated before starting therapy (d0) and 12–24 h thereafter (d1). The Wilcoxon-test with associated samples was used for statistical analysis. Thirty-nine patients (33 CS, 6 ADVOS) were included. The median bilirubin at d0 was 16.9 and 17.7 mg/dl and at d1 was 13.2 and 15.9 mg/dl, in the CS and ADVOS group, respectively. There was a significant bilirubin reduction as well in the CS group (p < 0.001, median relative reduction: 22.5%) as in the ADVOS group (p = 0.028, median relative reduction: 22.8%). There was no significant difference in the relative bilirubin reduction between CS and ADVOS therapies. The use of CytoSorb and ADVOS in patients with ALD led to a significant and comparable decrease in total bilirubin. The easy use of CS might be an advantage compared to other procedures.

Aims This study aimed to determine whether anthropometric markers of thoracic skeletal muscle and abdominal visceral fat tissue correlate with outcome parameters in critically ill COVID-19 patients. Methods We retrospectively analysed thoracic CT-scans of 67 patients in four ICUs at a university hospital. Thoracic skeletal muscle (total cross-sectional area(CSA); pectoralis muscle area(PMA)) and abdominal visceral fat tissue(VAT) were quantified using a semi-automated method. Point-biserial-correlation-coefficient, Spearman-correlation-coefficient, Wilcoxon rank-sum test and logistic regression were used to assess the correlation and test for differences between anthropometric parameters and death, ventilator- and ICU-free days and initial inflammatory laboratory values. Results Deceased patients had lower CSA and PMA values, but higher VAT values(p < 0.001). Male patients with higher CSA values had more ventilator-free days(p = 0.047) and ICU-free days(p = 0.017). Higher VAT/CSA and VAT/PMA values were associated with higher mortality(p < 0.001), but were negatively correlated with ICU length of stay in female patients only(p < 0.016). There was no association between anthropometric parameters and initial inflammatory biomarker levels. Logistic regression revealed no significant independent predictor for death. Conclusion Our study suggests that pathologic body composition assessed by planimetric measurements using thoracic CT-scans is associated with worse outcome in critically ill COVID-19 patients.

Background In the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data. Aim We applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata. Methods We investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission. Results We identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions. Conclusions Early spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.