Influence of a structured microbiological endotracheal monitoring on the outcome of critically ill COVID-19 patients: an observational study (preprint)

Purpose In past influenza pandemics and the current COVID-19 pandemic, bacterial endotracheal superinfections are a well-known risk factor for higher morbidity and mortality. The goal of this study was to investigate the influence of a structured, objective, microbiological monitoring on the prognosis of COVID-19 patients with mechanical ventilation. Methods A structured microbiological monitoring (at intubation, then every 3 days) included collection of endotracheal material. Data analysis focused on the spectrum of bacterial pathogens, mortality, as well as ICU-, hospital-, and mechanical ventilation duration. Results 29% of the patients showed bacterial coinfection at the time of intubation or within 48h, 56% developed ventilator-associated pneumonia (VAP). Even though patients with VAP had significantly longer ICU-, hospital and mechanical ventilation duration, there was no significant difference in mortality between patients with ventilator-associated pneumonia and patients without bacterial infection. Conclusion Bacterial coinfections and ventilator-associated pneumonia are common complications in influenza and COVID-19 patients. In contrast to already published studies, in our study implementing a structured microbiological monitoring, COVID-19 patients with ventilator-associated pneumonia did not show higher mortality. Thus, a standardized, objective, microbiological screening can help detect coinfections and ventilator-associated infections, refining the anti-infective therapy and influencing the patient outcome positively.

Convalescent Plasma Treatment for SARS-CoV-2 Infected High-risk Patients - a Matched Pair Analysis to the LEOSS Cohort (preprint)

Background: Establishing the optimal treatment for COVID-19 patients remains challenging. Specifically, immunocompromised and pre-diseased patients are at high risk for severe disease course and face limited therapeutic options. Convalescent plasma has been considered as therapeutic approach, but reliable data are lacking, especially for high-risk patients. Methods: We performed a retrospective analysis of 55 hospitalized COVID-19 patients with high risk for disease progression, primarily due to immunosuppression from cancer, solid organ transplantation, autoimmune disease, dialysis. A matched-pairs analysis (1:4) was performed with 220 patients from the Lean European Open Survey on SARS-CoV-2-infected Patients (LEOSS) who were treated or not treated with convalescent plasma. Results: Both cohorts, had high mortality (UKD 41.8%, LEOSS 34.1%). A matched-pairs analysis showed no significant effect on mortality. CP administration before the formation of pulmonary infiltrates showed the lowest mortality in both cohorts (10%), whereas mortality in the complicated phase was 27.8%. CP administration during the critical phase revealed the highest mortality; UKD 60.9%, LEOSS 48.3%. Conclusion: In our cohort of SARS-CoV-2 infected patients with severe comorbidities CP did not significantly reduce mortality in a retrospective matched pairs analysis. However, our data supports the concept that a reduction in mortality is achievable when CP is administered early.

Machine Learning Based Prediction of COVID-19 Mortality Suggests Repositioning of Anticancer Drug for Treating Severe Cases (preprint)

Despite available vaccinations COVID-19 case numbers around the world are still growing, and effective medications against severe cases are lacking. In this work, we developed a machine learning model which predicts mortality for COVID-19 patients using data from the multi-center Lean European Open Survey on SARS-CoV-2-infected patients (LEOSS) observational study (>100 active sites in Europe, primarily in Germany), resulting into an AUC of almost 80%. We showed that molecular mechanisms related to dementia, one of the relevant predictors in our model, intersect with those associated to COVID-19. Most notably, among these molecules was tyrosine kinase 2 (TYK2), a protein that has been patented as drug target in Alzheimers Disease but also genetically associated with severe COVID-19 outcomes. We experimentally verified that anti-cancer drugs Sorafenib and Regorafenib showed a clear anti-cytopathic effect in Caco2 and VERO-E6 cells and can thus be regarded as potential treatments against COVID-19. Altogether, our work demonstrates that interpretation of machine learning based risk models can point towards drug targets and new treatment options, which are strongly needed for COVID-19.

Gut Bacterial Dysbiosis and Instability is Associated with the Onset of Complications and Mortality in COVID-19 (preprint)

ObjectiveThere is a growing debate about the involvement of the gut microbiome in COVID-19, although it is not conclusively understood whether the microbiome has an impact on COVID-19, or vice versa, especially as analysis of amplicon data in hospitalized patients requires sophisticated cohort recruitment and integration of clinical parameters. Here, we analyzed fecal and saliva samples from SARS-CoV-2 infected and post COVID-19 patients and controls considering multiple influencing factors during hospitalization. Design16S rRNA gene sequencing was performed on fecal and saliva samples from 108 COVID-19 and 22 post COVID-19 patients, 20 pneumonia controls and 26 asymptomatic controls. Patients were recruited over the first and second corona wave in Germany and detailed clinical parameters were considered. Serial samples per individual allowed intra-individual analysis. ResultsWe found the gut and oral microbiota to be altered depending on number and type of COVID-19-associated complications and disease severity. The occurrence of individual complications was correlated with low-risk (e.g., Faecalibacterium prausznitzii) and high-risk bacteria (e.g., Parabacteroides). We demonstrated that a stable gut bacterial composition was associated with a favorable disease progression. Based on gut microbial profiles, we identified a model to estimate mortality in COVID-19. ConclusionGut microbiota are associated with the occurrence of complications in COVID-19 and may thereby influencing disease severity. A stable gut microbial composition may contribute to a favorable disease progression and using bacterial signatures to estimate mortality could contribute to diagnostic approaches. Importantly, we highlight challenges in the analysis of microbial data in the context of hospitalization.

New susceptibility loci for severe COVID-19 by detailed GWAS analysis in European populations (preprint)

Due to the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), deepening the host genetic contribution to severe COVID-19 may further improve our understanding about underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany, as well as hypothesis-driven targeted analysis of the human leukocyte antigen (HLA) region and chromosome Y haplotypes. We include detailed stratified analyses based on age, sex and disease severity. In addition to already established risk loci, our data identify and replicate two genome-wide significant loci at 17q21.31 and 19q13.33 associated with severe COVID-19 with respiratory failure. These associations implicate a highly pleiotropic ~0.9-Mb 17q21.31 inversion polymorphism, which affects lung function and immune and blood cell counts, and the NAPSA gene, involved in lung surfactant protein production, in COVID-19 pathogenesis.

Development and Validation of a Simplified Risk Score for the Prediction of Critical COVID-19 Illness in Newly Diagnosed Patients (preprint)

Scores for identifying patients at high risk of progression of the coronavirus disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), are discussed as key instruments for clinical decision-making and patient management during the current pandemic. Here we used the patient data from the multicenter Lean European Open Survey on SARS-CoV-2 - Infected Patients (LEOSS) and applied a technique of variable selection in order to develop a simplified score to identify patients at increased risk of critical illness or death. A total of 1,946 patients, who were tested positive for SARS-CoV-2 were included in the initial analysis. They were split into a derivation and a validation cohort (n=1,297 and 649, respectively). A stability selection among a total of 105 baseline predictors for the combined endpoint of progression to critical phase or COVID-19-related death allowed us to develop a simplified score consisting of five predictors: CRP, Age, clinical disease phase (uncomplicated vs. complicated), serum urea and D-dimer (abbreviated as CAPS-D score). This score showed an AUC of 0.81 (CI95%: 0.77-0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (CI95%: 0.77-0.85) during the full follow-up. Finally, we used an additional prospective cohort of 682 patients, who were diagnosed largely after the “first wave” of the pandemic to validate predictive accuracy of the score, observing similar results (AUC for an event within 7 days: 0.83, CI95%, 0.78-0.87; for full follow-up: 0.82, CI95%, 0.78-0.86). We thus successfully establish and validate an easily applicable score to calculate the risk of disease progression of COVID-19 to critical illness or death.

COVID-19 severity and complications associated with low diversity, dysbiosis and predictive metagenome features of the oropharyngeal microbiome. (preprint)

Coronavirus 2 (SARS-CoV-2) infection and the resulting COVID-19 illness vary from asymptomatic disease, mild upper respiratory tract infection, pneumonia1, to a life-threatening multi-organ failure with case fatality rates ranging from 0.27–13.4%2,3. Despite increasing knowledge of the clinical and immunological features underlying COVID-191,4−6, biological variables explaining the course of infection and its severity remain elusive. At the entry site of SARS-CoV2, the oropharyngeal microbiome represents a hub integrating viral and immune signals at the start of the infection7–10. To evaluate the role of the oropharyngeal microbiome in COVID-19, we performed a multi-center, cross-sectional clinical study analyzing the oropharyngeal microbial metagenomes in healthy adults, patients with non-SARS-CoV-2 infections, or with mild, moderate and severe COVID-19 encompassing a total of 345 participants. Significantly reduced microbiome diversity and high dysbiosis were observed in hospitalized patients with severe COVID-19, which was further associated with a loss of microbial genes and metabolic pathways. In this cohort, diversity measures were also associated with need for intensive care treatments as major clinical parameters in COVID-19. We further applied random forest machine learning to unravel microbial features for segregating clinical outcomes in hospitalized cases, and observed oropharyngeal microbiome abundances of Haemophilus or Streptococcus species as most important features. These findings provide insights into the role of the oropharyngeal microbiome in SARS-CoV-2 infection, and may suggest new biomarkers for COVID-19 severity.

Increased extravascular lung water index (EVLWI) reflects rapid inflammatory oedema and mortality in COVID-19 associated ARDS (preprint)

OBJECTIVENearly 5 % of the patients with COVID-19 develop an acute respiratory distress syndrome (ARDS). Extravascular lung water index (EVLWI) is a marker of pulmonary oedema which is associated with mortality in ARDS. In this study we evaluate whether EVLWI is higher in patients with COVID-19 associated ARDS as compared to controls and whether EVLWI has the potential to monitor disease progression. METHODSFrom the day of intubation, EVLWI, cardiac function were monitored by transpulmonary thermodilution in n=25 patients with COVID-19 and compared to a control group of 49 non-COVID-19 ARDS-patients. RESULTSEVLWI in COVID-19-patients was noticeably elevated and significantly higher than in the control group (17 (11-38) vs. 11 (6-26) mL/kg; p<0.001). High pulmonary vascular permeability index values (2.9 (1.0-5.2) versus 1.9 (1.0-5.2); p=0.003) suggest inflammatory oedema. By contrast, the cardiac parameters SVI, GEF and GEDVI were comparable. High EVLWI values were associated with viral persistence, prolonged intensive care treatment and mortality (23.2{+/-}6.7% vs. 30.3{+/-}6.0%, p=0.025). CONCLUSIONSCompared to the control group, COVID-19 results in markedly elevated EVLWI-values in patients with ARDS. EVLWI reflects a non-cardiogenic pulmonary oedema in COVID-19 associated ARDS and could serve as parameter to monitor ARDS progression.

SARS-CoV-2 serology increases diagnostic accuracy in CT-suspected, PCR-negative COVID-19 patients during pandemic (preprint)

Background:In the absence of PCR detection of SARS-CoV-2 RNA, accurate diagnosis of COVID-19 is challenging. Low-dose computed tomography (CT) detects pulmonary infiltrates with high sensitivity, but findings may be non-specific. This study assesses the diagnostic value of SARS-CoV-2 serology for patients with distinct CT features but negative PCR.Methods:IgM/IgG chemiluminescent immunoassay was performed for 107 patients with confirmed (group A: PCR+; CT±) and 46 patients with suspected (group B: repetitive PCR-; CT+) COVID-19, admitted to a German university hospital during the pandemic’s first wave. A standardized, in-house CT classification of radiological signs of a viral pneumonia was used to assess the probability of COVID-19.Results:Seroconversion rates (SR) determined on day 5, 10, 15, 20 and 25 after symptom onset (SO) were 8%, 25%, 65%, 76% and 91% for group A, and 0%, 10%, 19%, 37% and 46% for group B, respectively; (p<0.01). Compared to hospitalized patients with a non-complicated course, seroconversion tended to occur at lower frequency and delayed in patients on intensive care units. SR of patients with CT findings classified as high certainty for COVID-19 were 8%, 22%, 68%, 79% and 93% in group A, compared with 0%, 15%, 28%, 50% and 50% in group B (p<0.01). SARS-CoV-2 serology established a definite diagnosis in 12/46 group B patients. In 88% (8/9) of patients with negative serology >14 days after symptom onset (group B), clinico-radiological consensus reassessment revealed probable diagnoses other than COVID-19. Sensitivity of SARS-CoV-2 serology was superior to PCR >17d after symptom onset.Conclusions:Approximately one-third of patients with distinct COVID-19 CT findings are tested negative for SARS-CoV-2 RNA by PCR rendering correct diagnosis difficult. Implementation of SARS-CoV-2 serology testing alongside current CT/PCR-based diagnostic algorithms improves discrimination between COVID-19-related and non-related pulmonary infiltrates in PCR negative patients. However, sensitivity of SARS-CoV-2 serology strongly depends on the time of testing and becomes superior to PCR after the 2nd week following symptom onset.