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Background Numerous predictive clinical scores with varying discriminatory performance have been developed in the context of the current coronavirus disease 2019 (COVID-19) pandemic. To support clinical application, we test the transferability of the frequently applied 4C mortality score (4C score) to the German prospective Cross-Sectoral Platform (SUEP) of the National Pandemic Cohort Network (NAPKON) compared to the non COVID-19 specific quick sequential organ failure assessment score (qSOFA). Our project aims to externally validate these two scores, stratified for the most prevalent variants of concerns (VOCs) of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) in Germany. Methods A total of 685 adults with polymerase chain reaction (PCR)-detected SARS-CoV-2 infection were included from NAPKON-SUEP. Patients were recruited from 11/2020 to 03/2022 at 34 university and non-university hospitals across Germany. Missing values were complemented using multiple imputation. Predictive performance for in-hospital mortality at day of baseline visit was determined by area under the curve (AUC) with 95%-confidence interval (CI) stratified by VOCs of SARS-CoV-2 (alpha, delta, omicron) (Figure 1). Figure 1:Study flow chart with inclusion criteria and methodological workflow. Results Preliminary results suggest a high predictive performance of the 4C score for in-hospital mortality (Table 1). This applies for the overall cohort (AUC 0.813 (95%CI 0.738-0.888)) as well as the VOC-strata (alpha: AUC 0.859 (95%CI 0.748-0.970); delta: AUC 0.769 (95%CI 0.657-0.882); omicron: AUC 0.866 (95%CI 0.724-1.000)). The overall mortality rates across the defined 4C score risk groups are 0.3% (low), 3.2% (intermediate), 11.6% (high), and 49.5% (very high). The 4C score performs significantly better than the qSOFA (Chi2-test: p=0.001) and the qSOFA does not seem to be a suitable tool in this context. Table 1:Discriminatory performance of the 4C Mortality Score and the qSOFA score within the validation cohort NAPKON-SUEP stratified by the Variant of Concerns of SARS-CoV-2. Conclusion Despite its development in the early phase of the pandemic and improved treatment, external validation of the 4C score in NAPKON-SUEP indicates a high predictive performance for in-hospital mortality across all VOCs. However, since the qSOFA was not specifically designed for this predictive issue, it shows low discriminatory performance, as in other validation studies. Any interpretations regarding the omicron stratum are limited due to the sample size. Disclosures Daniel Pape, Dr., Advanz Pharma Germany: Support for attending meetings and/or travel for ECCMID 2021 Martin Hower, n/a, MSD: Advisor/Consultant|Trogarzo: Advisor/Consultant|ViiV Healthcare: Advisor/Consultant Björn-Erik O. Jensen, Dr. med., GILEAD: Advisor/Consultant|GILEAD: Lectures, Travel|GSK: Lectures, Travel Jörg J. Vehreschild, Univ.-Prof. Dr. med., Ärztekammer Nordrhein: Honoraria|Academy for Infectious Medicine, University Manchester: Honoraria|Astellas Pharma: Grant/Research Support|Astellas Pharma: Honoraria|Back Bay Strategies: Honoraria|Basilea: Grant/Research Support|Basilea: Honoraria|Deutsches Zetrum für Luft- und Raumfahrt (DLR): Grant/Research Support|German Centre for Infection Research (DZIF): Grant/Research Support|German Centre for Infection Research (DZIF): Honoraria|German Federal Ministry of Education and Research (BMBF): Grant/Research Support|German Society for Infectious Diseases (DGI): Honoraria|German Society for Internal Medicine (DGIM): Honoraria|GILEAD: Advisor/Consultant|GILEAD: Grant/Research Support|GILEAD: Honoraria|Janssen: Honoraria|Merck / MSD: Grant/Research Support|Merck / MSD: Honoraria|Molecular Health: Honoraria|Netzwerk Universitätsmedizin: Honoraria|NordForsk: Honoraria|Pfizer: Advisor/Consultant|Pfizer: Grant/Research Support|Pfizer: Honoraria|Rigshospitalet Copenhagen: Grant/Research Support|Shionogi: Advisor/Consultant|Shionogi: Honoraria|University Hospital Aachen: Honoraria|University Hospital Freiburg/ Congress and Communication: Honoraria|University of Bristol: Grant/Research Support.

The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON’s goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany. Within NAPKON, adult and pediatric patients are observed in three complementary cohort platforms (Cross-Sectoral, High-Resolution and Population-Based) from the initial infection until up to three years of follow-up. Study procedures comprise comprehensive clinical and imaging diagnostics, quality-of-life assessment, patient-reported outcomes and biosampling. The three cohort platforms build on four infrastructure core units (Interaction, Biosampling, Epidemiology, and Integration) and collaborations with NUM projects. Key components of the data capture, regulatory, and data privacy are based on the German Centre for Cardiovascular Research. By December 01, 2021, 34 university and 34 non-university hospitals have enrolled 4,241 patients with local data quality reviews performed on 2,812 (66%). 47% were female, the median age was 53 (IQR: 38-63)) and 3 pediatric cases were included. 30% of patients were hospitalized, 11% admitted to an intensive care unit, and 4% of patients deceased while enrolled. 7,143 visits with biosampling in 3,595 patients were conducted by November 29, 2021. In this overview article, we summarize NAPKON’s design, relevant milestones including first study population characteristics, and outline the potential of NAPKON for German and international research activities.Trial registration:· https://clinicaltrials.gov/ct2/show/NCT04768998· https://clinicaltrials.gov/ct2/show/NCT04747366· https://clinicaltrials.gov/ct2/show/NCT04679584

The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON’s goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany. Within NAPKON, adult and pediatric patients are observed in three complementary cohort platforms (Cross-Sectoral, High-Resolution and Population-Based) from the initial infection until up to three years of follow-up. Study procedures comprise comprehensive clinical and imaging diagnostics, quality-of-life assessment, patient-reported outcomes and biosampling. The three cohort platforms build on four infrastructure core units (Interaction, Biosampling, Epidemiology, and Integration) and collaborations with NUM projects. Key components of the data capture, regulatory, and data privacy are based on the German Centre for Cardiovascular Research. By April 01, 2022, 34 university and 40 non-university hospitals have enrolled 5298 patients with local data quality reviews performed on 4727 (89%). 47% were female, the median age was 52 (IQR 36–62-) and 50 pediatric cases were included. 44% of patients were hospitalized, 15% admitted to an intensive care unit, and 12% of patients deceased while enrolled. 8845 visits with biosampling in 4349 patients were conducted by April 03, 2022. In this overview article, we summarize NAPKON’s design, relevant milestones including first study population characteristics, and outline the potential of NAPKON for German and international research activities.Trial registrationhttps://clinicaltrials.gov/ct2/show/NCT04768998.https://clinicaltrials.gov/ct2/show/NCT04747366.https://clinicaltrials.gov/ct2/show/NCT04679584

This article examines contextual explanations for public support for European integration. Apart from economic and identity-based theories, there may also be a religious dimension that could help to explain why some countries are principally pro-European while others are largely eurosceptic. It is argued that differences between nations are embedded in historical alliances between Catholic and Protestant denominations and political systems. Hierarchical linear model analyses of data from the European Social Survey (ESS) show that: (1) citizens from Catholic countries are more likely to support European unification than the inhabitants of Protestant countries; and (2) this effect conditions the individual-level effect of welfare attitudes. This suggests that in Protestant countries support for welfare redistribution is associated with low support for the EU, while in Catholic countries support for welfare redistribution is associated with high support for the EU.