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Background Optimal prophylactic and therapeutic management of thromboembolic disease in patients with COVID-19 remains a major challenge for clinicians. The aim of this study was to define the incidence of thrombotic and haemorrhagic complications in critically ill patients with COVID-19. In addition, we sought to characterise coagulation profiles using thromboelastography and explore possible biological differences between patients with and without thrombotic complications. Methods We conducted a multicentre retrospective observational study evaluating all the COVID-19 patients received in four intensive care units (ICUs) of four tertiary hospitals in the UK between March 15, 2020, and May 05, 2020. Clinical characteristics, laboratory data, thromboelastography profiles and clinical outcome data were evaluated between patients with and without thrombotic complications. Results A total of 187 patients were included. Their median (interquartile (IQR)) age was 57 (49–64) years and 124 (66.3%) patients were male. Eighty-one (43.3%) patients experienced one or more clinically relevant thrombotic complications, which were mainly pulmonary emboli (n = 42 (22.5%)). Arterial embolic complications were reported in 25 (13.3%) patients. ICU length of stay was longer in patients with thrombotic complications when compared with those without. Fifteen (8.0%) patients experienced haemorrhagic complications, of which nine (4.8%) were classified as major bleeding. Thromboelastography demonstrated a hypercoagulable profile in patients tested but lacked discriminatory value between those with and without thrombotic complications. Patients who experienced thrombotic complications had higher D-dimer, ferritin, troponin and white cell count levels at ICU admission compared with those that did not. Conclusion Critically ill patients with COVID-19 experience high rates of venous and arterial thrombotic complications. The rates of bleeding may be higher than previously reported and re-iterate the need for randomised trials to better understand the risk-benefit ratio of different anticoagulation strategies. Graphical abstract

Dear Editor, Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory coronavirus 2 (SARS-CoV-2) was declared a pandemic on March 11, 2020 [1]. Risk factors associated with respiratory failure in patients with COVID-19 include older age, neutrophilia and elevated inflammatory and coagulation markers [1]. Inflammation is often accompanied by systemic hypoferremia and low iron levels may impair hypoxia sensing and immunity [2], and increase the risk of thromboembolic complications [3]-which are all of significant concern in COVID-19. However, the iron status of COVID-19 patients is unclear. Therefore, we sought to characterise iron parameters, including serum iron, in COVID-19 intensive care unit (ICU) patients and relate these to disease severity. Methods We retrospectively evaluated any serum iron profiles that were measured in critically ill patients with COVID-19 within 24 h of admission to the ICU, John Radcliffe Hospital, Oxford, UK, between March 31, 2020, and April 25, 2020. Relevant clinical and laboratory data were extracted from routine datasets. The number of patients who had died, had been discharged, and were still in ICU as of May 12, 2020 was recorded. We stratified patients according to severity of hypoxemic respiratory failure on admission to ICU-severe (PaO 2 /FiO 2 ratio < 100 mmHg) versus non-severe (PaO 2 /FiO 2 ratio 100-300 mmHg). All patients with severe hypoxemia required invasive mechanical ventilation and prone positioning. Mann-Whitney rank

IntroductionCommunity acquired pneumonia (CAP) is the most common infectious reason for admission to the Intensive Care Unit (ICU). The GenOSept study was designed to determine genetic influences on sepsis outcome. Phenotypic data was recorded using a robust clinical database allowing a contemporary analysis of the clinical characteristics, microbiology, outcomes and independent risk factors in patients with severe CAP admitted to ICUs across Europe.MethodsKaplan-Meier analysis was used to determine mortality rates. A Cox Proportional Hazards (PH) model was used to identify variables independently associated with 28-day and six-month mortality.ResultsData from 1166 patients admitted to 102 centres across 17 countries was extracted. Median age was 64 years, 62% were male. Mortality rate at 28 days was 17%, rising to 27% at six months. Streptococcus pneumoniae was the commonest organism isolated (28% of cases) with no organism identified in 36%. Independent risk factors associated with an increased risk of death at six months included APACHE II score (hazard ratio, HR, 1.03; confidence interval, CI, 1.01-1.05), bilateral pulmonary infiltrates (HR1.44; CI 1.11-1.87) and ventilator support (HR 3.04; CI 1.64-5.62). Haematocrit, pH and urine volume on day one were all associated with a worse outcome.ConclusionsThe mortality rate in patients with severe CAP admitted to European ICUs was 27% at six months. Streptococcus pneumoniae was the commonest organism isolated. In many cases the infecting organism was not identified. Ventilator support, the presence of diffuse pulmonary infiltrates, lower haematocrit, urine volume and pH on admission were independent predictors of a worse outcome.

SummaryAllogeneic red cell transfusion is a commonly used treatment to improve the oxygen carrying capacity of blood during the peri-operative period. Increasing arterial oxygen content by increasing haemoglobin does not necessarily increase tissue oxygen delivery or uptake. Although the evidence-base for red cell transfusion practice is incomplete, randomised studies across a range of clinical settings, including surgery, consistently support the restrictive use of red cells, with no evidence of benefit for maintaining patients at higher haemoglobin thresholds (liberal strategy). A recent meta-analysis of 7593 patients concluded that a restrictive transfusion strategy was associated with a reduced risk of healthcare-associated infections (pneumonia, mediastinitis, wound infection, sepsis) when compared with a liberal transfusion strategy. The degree to which the optimal haemoglobin concentration or transfusion trigger should be modified for patients with additional specific risk factors (e.g. ischaemic heart disease), remains less clear and requires further research. Although most clinical practice guidelines recommend restrictive use of red cells, and many blood transfusion services have seen marked falls in overall usage of red cells, the use of other blood components such as fresh frozen plasma, platelets, and cryoprecipitate has risen. In clinical practice, administration of fresh frozen plasma is usually guided by laboratory tests of coagulation, mainly prothrombin time, international normalised ratio and activated partial thromboplastin time, but the predictive value of these tests to predict bleeding is poor.

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Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).