Age and Comorbidity Burden of Patients Critically Ill with COVID-19 Affect Both Access to and Outcome of Ventilation Therapy in Intensive Care Units.

During the COVID-19 pandemic, large numbers of elderly, multimorbid people required treatment in intensive care units. This study investigated how the inherent patient factors age and comorbidity burden affected the treatment strategy and the outcome achieved. Retrospective analysis of data from intensive care patients enrolled in the Lean European Open Survey on SARS-CoV2-Infected Patients (LEOSS) cohort found that a patient's age and comorbidity burden in fact influenced their mortality rate and the use of ventilation therapy. Evidence showed that advanced age and multimorbidity were associated with the restrictive use of invasive ventilation therapies, particularly ECMO. Geriatric patients with a high comorbidity burden were clustered in the sub-cohort of non-ventilated ICU patients characterized by a high mortality rate. The risk of death generally increased with older age and accumulating comorbidity burden. Here, the more aggressive an applied procedure, the younger the age in which a majority of patients died. Clearly, geriatric, multimorbid COVID-19 patients benefit less from invasive ventilation therapies. This implies the need for a holistic approach to therapy decisions, taking into account the patient's wishes.

Use and effectiveness of remdesivir for the treatment of patients with covid-19 using data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS): a multicentre cohort study.

OBJECTIVES: The use of remdesivir (RDV) as the first drug approved for coronavirus disease 2019 (COVID-19) remains controversial. Based on the Lean European Open Survey on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infected patients (LEOSS), we aim to contribute timing-focused complementary real-world insights to its evaluation. METHODS: SARS-CoV-2 infected patients between January 2020 and December 2021 treated with RDV were matched 1:1 to controls considering sociodemographics, comorbidities and clinical status. Multiple imputations were used to account for missing data. Effects on fatal outcome were estimated using uni- and multivariable Cox regression models. RESULTS: We included 9,687 patients. For those starting RDV administration in the complicated phase, Cox regression for fatal outcome showed an adjusted hazard ratio (aHR) of 0.59 (95%CI 0.41-0.83). Positive trends could be obtained for further scenarios: an aHR of 0.51 (95%CI 0.16-1.68) when RDV was initiated in uncomplicated and of 0.76 (95% CI 0.55-1.04) in a critical phase of disease. Patients receiving RDV with concomitant steroids exhibited a further reduction in aHR in both, the complicated (aHR 0.50, 95%CI 0.29-0.88) and critical phase (aHR 0.63, 95%CI 0.39-1.02). CONCLUSION: Our study results elucidate that RDV use, in particular when initiated in the complicated phase and accompanied by steroids is associated with improved mortality. However, given the limitations of non-randomized trials in estimating the magnitude of the benefit of an intervention, further randomized trials focusing on the timing of therapy initiation seem warranted.

Disease severity in hospitalized COVID-19 patients: comparing routine surveillance with cohort data from the LEOSS study in 2020 in Germany.

INTRODUCTION: Studies investigating risk factors for severe COVID-19 often lack information on the representativeness of the study population. Here, we investigate factors associated with severe COVID-19 and compare the representativeness of the dataset to the general population. METHODS: We used data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) of hospitalized COVID-19 patients diagnosed in 2020 in Germany to identify associated factors for severe COVID-19, defined as progressing to a critical disease stage or death. To assess the representativeness, we compared the LEOSS cohort to cases of hospitalized patients in the German statutory notification data of the same time period. Descriptive methods and Poisson regression models were used. RESULTS: Overall, 6672 hospitalized patients from LEOSS and 132,943 hospitalized cases from the German statutory notification data were included. In LEOSS, patients above 76 years were less likely represented (34.3% vs. 44.1%). Moreover, mortality was lower (14.3% vs. 21.5%) especially among age groups above 66 years. Factors associated with a severe COVID-19 disease course in LEOSS included increasing age, male sex (adjusted risk ratio (aRR) 1.69, 95% confidence interval (CI) 1.53-1.86), prior stem cell transplantation (aRR 2.27, 95% CI 1.53-3.38), and an elevated C-reactive protein at day of diagnosis (aRR 2.30, 95% CI 2.03-2.62). CONCLUSION: We identified a broad range of factors associated with severe COVID-19 progression. However, the results may be less applicable for persons above 66 years since they experienced lower mortality in the LEOSS dataset compared to the statutory notification data.

Entwicklung und Validierung potenzieller Strukturindikatoren zur Evaluierung des klinisch-infektiologischen Versorgungsangebots in deutschen Krankenhäusern während der COVID-19-Pandemie Development and validation of potential structure indicators for clinical infectious disease (ID) care in German hospitals during the COVID-19 pandemic

Hintergrund Diese Studie beschreibt die Entwicklung und Validierung von Strukturindikatoren für das klinisch-infektiologische Versorgungsangebot in deutschen Krankenhäusern. Ein solches ist notwendig, um den künftigen Herausforderungen in der Infektionsmedizin adäquat begegnen zu können. Methode Ein Expert*innenteam entwickelte die Strukturindikatoren im Rahmen eines dreistufigen Entscheidungsverfahrens: (1) Identifizierung potenzieller Strukturindikatoren basierend auf einer Literaturrecherche, (2) schriftliches Bewertungsverfahren sowie eine (3) persönliche Diskussion zur Konsensfindung und finalen Auswahl geeigneter Strukturindikatoren. Zur Pilotierung der entwickelten Strukturindikatoren wurde eine Feldstudie durchgeführt. Ein auf den Strukturindikatoren basierender Score wurde für jedes Krankenhaus ermittelt und über eine Receiver-Operator-Charakteristik-Kurve (ROC) anhand extern validierter infektiologischer Expertise (Zentrum der Deutschen Gesellschaft für Infektiologie [DGI]) validiert. Ergebnisse Auf der Basis einer Liste von 45 potenziellen Strukturindikatoren wurden 18 geeignete Strukturindikatoren für das klinisch-infektiologische Versorgungsangebot entwickelt. Von diesen wurden zehn Schlüsselindikatoren für das allgemeine bzw. Coronavirus-Krankheit-2019 (COVID-19)-spezifische klinisch-infektiologische Versorgungsangebot definiert. Bei der Felderhebung des Versorgungsangebots für COVID-19-Patient*innen in 40 deutschen Krankenhäusern erreichten die teilnehmenden Einrichtungen 0 bis 9 Punkte (Median 4) im ermittelten Score. Die Fläche unter der ROC-Kurve betrug 0,893 (95%-Konfidenzintervall (KI): 0,797, 0,988;p < 0,001). Diskussion/Schlussfolgerung Die im Rahmen eines transparenten und etablierten Entwicklungsprozesses entwickelten Strukturindikatoren können perspektivisch genutzt werden, um den aktuellen Zustand und zukünftige Entwicklungen der infektiologischen Versorgungsqualität in Deutschland zu erfassen und Vergleiche zu ermöglichen.

Consistency as a Data Quality Measure for German Corona Consensus Items Mapped from National Pandemic Cohort Network Data Collections.

BACKGROUND: As a national effort to better understand the current pandemic, three cohorts collect sociodemographic and clinical data from coronavirus disease 2019 (COVID-19) patients from different target populations within the German National Pandemic Cohort Network (NAPKON). Furthermore, the German Corona Consensus Dataset (GECCO) was introduced as a harmonized basic information model for COVID-19 patients in clinical routine. To compare the cohort data with other GECCO-based studies, data items are mapped to GECCO. As mapping from one information model to another is complex, an additional consistency evaluation of the mapped items is recommended to detect possible mapping issues or source data inconsistencies. OBJECTIVES: The goal of this work is to assure high consistency of research data mapped to the GECCO data model. In particular, it aims at identifying contradictions within interdependent GECCO data items of the German national COVID-19 cohorts to allow investigation of possible reasons for identified contradictions. We furthermore aim at enabling other researchers to easily perform data quality evaluation on GECCO-based datasets and adapt to similar data models. METHODS: All suitable data items from each of the three NAPKON cohorts are mapped to the GECCO items. A consistency assessment tool (dqGecco) is implemented, following the design of an existing quality assessment framework, retaining their-defined consistency taxonomies, including logical and empirical contradictions. Results of the assessment are verified independently on the primary data source. RESULTS: Our consistency assessment tool helped in correcting the mapping procedure and reveals remaining contradictory value combinations within COVID-19 symptoms, vital signs, and COVID-19 severity. Consistency rates differ between the different indicators and cohorts ranging from 95.84% up to 100%. CONCLUSION: An efficient and portable tool capable of discovering inconsistencies in the COVID-19 domain has been developed and applied to three different cohorts. As the GECCO dataset is employed in different platforms and studies, the tool can be directly applied there or adapted to similar information models.

[Development and validation of potential structure indicators for clinical infectious disease (ID) care in German hospitals during the COVID-19 pandemic]. / Entwicklung und Validierung potenzieller Strukturindikatoren zur Evaluierung des klinisch-infektiologischen Versorgungsangebots in deutschen Krankenhäusern während der COVID-19-Pandemie.

INTRODUCTION: This study describes the development and validation of structure indicators for clinical infectious disease (ID) care in German hospitals, which is important to adequately face the future challenges in ID medicine. METHODS: A team of experts developed the structure indicators in a three-stage, multicriteria decision-making process: (1) identification of potential structure indicators based on a literature review, (2) written assessment process, and (3) face-to-face discussion to reach consensus and final selection of appropriate structure indicators. A field study was conducted to assess the developed structure indicators. A score based on the structure indicators was determined for each hospital and validated via receiver operator characteristic (ROC) curves using externally validated ID expertise (German Society of ID (DGI) Centre). RESULTS: Based on a list of 45 potential structure indicators, 18 suitable indicators were developed for clinical ID care structures in German hospitals. Out of these, ten key indicators were defined for the general and coronavirus disease 2019- (COVID-19-) specific clinical ID care structures. In the field survey of clinical ID care provision for COVID-19 patients in 40 German hospitals, the participating facilities achieved 0 to 9 points (median 4) in the determined score. The area under the ROC curve was 0.893 (95% CI: 0.797, 0.988; p < 0.001). DISCUSSION/CONCLUSION: The structure indicators developed within the framework of a transparent and established development process can be used in the future to both capture the current state and future developments of ID care quality in Germany and enable comparisons.

SARS-CoV-2 infection in chronic kidney disease patients with pre-existing dialysis: description across different pandemic intervals and effect on disease course (mortality).

PURPOSE: Patients suffering from chronic kidney disease (CKD) are in general at high risk for severe coronavirus disease (COVID-19) but dialysis-dependency (CKD5D) is poorly understood. We aimed to describe CKD5D patients in the different intervals of the pandemic and to evaluate pre-existing dialysis dependency as a potential risk factor for mortality. METHODS: In this multicentre cohort study, data from German study sites of the Lean European Open Survey on SARS-CoV-2-infected patients (LEOSS) were used. We multiply imputed missing data, performed subsequent analyses in each of the imputed data sets and pooled the results. Cases (CKD5D) and controls (CKD not requiring dialysis) were matched 1:1 by propensity-scoring. Effects on fatal outcome were calculated by multivariable logistic regression. RESULTS: The cohort consisted of 207 patients suffering from CKD5D and 964 potential controls. Multivariable regression of the whole cohort identified age (> 85 years adjusted odds ratio (aOR) 7.34, 95% CI 2.45-21.99), chronic heart failure (aOR 1.67, 95% CI 1.25-2.23), coronary artery disease (aOR 1.41, 95% CI 1.05-1.89) and active oncological disease (aOR 1.73, 95% CI 1.07-2.80) as risk factors for fatal outcome. Dialysis-dependency was not associated with a fatal outcome-neither in this analysis (aOR 1.08, 95% CI 0.75-1.54) nor in the conditional multivariable regression after matching (aOR 1.34, 95% CI 0.70-2.59). CONCLUSIONS: In the present multicentre German cohort, dialysis dependency is not linked to fatal outcome in SARS-CoV-2-infected CKD patients. However, the mortality rate of 26% demonstrates that CKD patients are an extreme vulnerable population, irrespective of pre-existing dialysis-dependency.

Convalescent plasma treatment for SARS-CoV-2 infected high-risk patients: a matched pair analysis to the LEOSS cohort.

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 (CP) has been considered as therapeutic approach, but reliable data are lacking, especially for high-risk patients. We performed a retrospective analysis of 55 hospitalized COVID-19 patients from University Hospital Duesseldorf (UKD) at high risk for disease progression, in a substantial proportion 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 CP. 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%. In our cohort of COVID-19 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 by early CP administration.

COVID-19 Severity and Thrombo-Inflammatory Response Linked to Ethnicity.

Although there is strong evidence that SARS-CoV-2 infection is associated with adverse outcomes in certain ethnic groups, the association of disease severity and risk factors such as comorbidities and biomarkers with racial disparities remains undefined. This retrospective study between March 2020 and February 2021 explores COVID-19 risk factors as predictors for patients' disease progression through country comparison. Disease severity predictors in Germany and Japan were cardiovascular-associated comorbidities, dementia, and age. We adjusted age, sex, body mass index, and history of cardiovascular disease comorbidity in the country cohorts using a propensity score matching (PSM) technique to reduce the influence of differences in sample size and the surprisingly young, lean Japanese cohort. Analysis of the 170 PSM pairs confirmed that 65.29% of German and 85.29% of Japanese patients were in the uncomplicated phase. More German than Japanese patients were admitted in the complicated and critical phase. Ethnic differences were identified in patients without cardiovascular comorbidities. Japanese patients in the uncomplicated phase presented a suppressed inflammatory response and coagulopathy with hypocoagulation. In contrast, German patients exhibited a hyperactive inflammatory response and coagulopathy with hypercoagulation. These differences were less pronounced in patients in the complicated phase or with cardiovascular diseases. Coagulation/fibrinolysis-associated biomarkers rather than inflammatory-related biomarkers predicted disease severity in patients with cardiovascular comorbidities: platelet counts were associated with severe illness in German patients. In contrast, high D-dimer and fibrinogen levels predicted disease severity in Japanese patients. Our comparative study indicates that ethnicity influences COVID-19-associated biomarker expression linked to the inflammatory and coagulation (thrombo-inflammatory) response. Future studies will be necessary to determine whether these differences contributed to the less severe disease progression observed in Japanese COVID-19 patients compared with those in Germany.

Invasiveness of Ventilation Therapy Is Associated to Prevalence of Secondary Bacterial and Fungal Infections in Critically Ill COVID-19 Patients.

Superinfections are a fundamental critical care problem, and their significance in severe COVID-19 cases needs to be determined. This study analyzed data from the Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort focusing on intensive care patients. A retrospective analysis of patient data from 840 cases of COVID-19 with critical courses demonstrated that co-infections were frequently present and were primarily of nosocomial origin. Furthermore, our analysis showed that invasive therapy procedures accompanied an increased risk for healthcare-associated infections. Non-ventilated ICU patients were rarely affected by secondary infections. The risk of infection, however, increased even when non-invasive ventilation was used. A further, significant increase in infection rates was seen with the use of invasive ventilation and even more so with extracorporeal membrane oxygenation (ECMO) therapy. The marked differences among ICU techniques used for the treatment of COVID-19-induced respiratory failure in terms of secondary infection risk profile should be taken into account for the optimal management of critically ill COVID-19 patients, as well as for adequate antimicrobial therapy.

Hospitalized patients dying with SARS-CoV-2 infection-An analysis of patient characteristics and management in ICU and general ward of the LEOSS registry.

BACKGROUND: COVID-19 is a severe disease with a high need for intensive care treatment and a high mortality rate in hospitalized patients. The objective of this study was to describe and compare the clinical characteristics and the management of patients dying with SARS-CoV-2 infection in the acute medical and intensive care setting. METHODS: Descriptive analysis of dying patients enrolled in the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS), a non-interventional cohort study, between March 18 and November 18, 2020. Symptoms, comorbidities and management of patients, including palliative care involvement, were compared between general ward and intensive care unit (ICU) by univariate analysis. RESULTS: 580/4310 (13%) SARS-CoV-2 infected patients died. Among 580 patients 67% were treated on ICU and 33% on a general ward. The spectrum of comorbidities and symptoms was broad with more comorbidities (≥ four comorbidities: 52% versus 25%) and a higher age distribution (>65 years: 98% versus 70%) in patients on the general ward. 69% of patients were in an at least complicated phase at diagnosis of the SARS-CoV-2 infection with a higher proportion of patients in a critical phase or dying the day of diagnosis treated on ICU (36% versus 11%). While most patients admitted to ICU came from home (71%), patients treated on the general ward came likewise from home and nursing home (44% respectively) and were more frequently on palliative care before admission (29% versus 7%). A palliative care team was involved in dying patients in 15%. Personal contacts were limited but more often documented in patients treated on ICU (68% versus 47%). CONCLUSION: Patients dying with SARS-CoV-2 infection suffer from high symptom burden and often deteriorate early with a demand for ICU treatment. Therefor a demand for palliative care expertise with early involvement seems to exist.

The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics.

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 registration https://clinicaltrials.gov/ct2/show/NCT04768998 . https://clinicaltrials.gov/ct2/show/NCT04747366 . https://clinicaltrials.gov/ct2/show/NCT04679584.

Obesity and Impaired Metabolic Health Increase Risk of COVID-19-Related Mortality in Young and Middle-Aged Adults to the Level Observed in Older People: The LEOSS Registry.

Advanced age, followed by male sex, by far poses the greatest risk for severe COVID-19. An unresolved question is the extent to which modifiable comorbidities increase the risk of COVID-19-related mortality among younger patients, in whom COVID-19-related hospitalization strongly increased in 2021. A total of 3,163 patients with SARS-COV-2 diagnosis in the Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort were studied. LEOSS is a European non-interventional multi-center cohort study established in March 2020 to investigate the epidemiology and clinical course of SARS-CoV-2 infection. Data from hospitalized patients and those who received ambulatory care, with a positive SARS-CoV-2 test, were included in the study. An additive effect of obesity, diabetes and hypertension on the risk of mortality was observed, which was particularly strong in young and middle-aged patients. Compared to young and middle-aged (18-55 years) patients without obesity, diabetes and hypertension (non-obese and metabolically healthy; n = 593), young and middle-aged adult patients with all three risk parameters (obese and metabolically unhealthy; n = 31) had a similar adjusted increased risk of mortality [OR 7.42 (95% CI 1.55-27.3)] as older (56-75 years) non-obese and metabolically healthy patients [n = 339; OR 8.21 (95% CI 4.10-18.3)]. Furthermore, increased CRP levels explained part of the elevated risk of COVID-19-related mortality with age, specifically in the absence of obesity and impaired metabolic health. In conclusion, the modifiable risk factors obesity, diabetes and hypertension increase the risk of COVID-19-related mortality in young and middle-aged patients to the level of risk observed in advanced age.

COVID-19 mortality in cirrhosis is determined by cirrhosis-associated comorbidities and extrahepatic organ failure: Results from the multinational LEOSS registry.

BACKGROUND AND OBJECTIVE: International registries have reported high mortality rates in patients with liver disease and COVID-19. However, the extent to which comorbidities contribute to excess COVID-19 mortality in cirrhosis is controversial. METHODS: We used the multinational Lean European Open Survey on SARS-CoV-2-infected patients (LEOSS) to identify patients with cirrhosis documented between March 2020 and March 2021, when the wild-type and alpha variant were predominant. We compared symptoms, disease progression and mortality after propensity score matching (PSM) for age, sex, obesity, smoking status, and concomitant diseases. Mortality was also compared with that of patients with spontaneous bacterial peritonitis (SBP) without SARS-CoV-2 infection, a common bacterial infection and well-described precipitator of acute-on-chronic liver failure. RESULTS: Among 7096 patients with SARS-CoV-2 infection eligible for analysis, 70 (0.99%) had cirrhosis, and all were hospitalized. Risk factors for severe COVID-19, such as diabetes, renal disease, and cardiovascular disease were more frequent in patients with cirrhosis. Case fatality rate in patients with cirrhosis was 31.4% with the highest odds of death in patients older than 65 years (43.6% mortality; odds ratio [OR] 4.02; p = 0.018), Child-Pugh class C (57.1%; OR 4.00; p = 0.026), and failure of two or more organs (81.8%; OR 19.93; p = 0.001). After PSM for demographics and comorbidity, the COVID-19 case fatality of patients with cirrhosis did not significantly differ from that of matched patients without cirrhosis (28.8% vs. 26.1%; p = 0.644) and was similar to the 28-day mortality in a comparison group of patients with cirrhosis and SBP (33.3% vs. 31.5%; p = 1.000). CONCLUSIONS: In immunologically naïve patients with cirrhosis, mortality from wild-type SARS-CoV-2 and the alpha variant is high and is largely determined by cirrhosis-associated comorbidities and extrahepatic organ failure.

Corrigendum to "Machine Learning Based Prediction of COVID-19 Mortality Suggests Repositioning of Anticancer Drug for Treating Severe Cases"[Artificial Intelligence in Life Sciences] 1(2021), 100020.

[This corrects the article DOI: 10.1016/j.ailsci.2021.100020.].

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

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 Alzheimer's 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.

Neurological symptoms and complications in predominantly hospitalized COVID-19 patients: Results of the European multinational Lean European Open Survey on SARS-Infected Patients (LEOSS).

BACKGROUND AND PURPOSE: During acute coronavirus disease 2019 (COVID-19) infection, neurological signs, symptoms and complications occur. We aimed to assess their clinical relevance by evaluating real-world data from a multinational registry. METHODS: We analyzed COVID-19 patients from 127 centers, diagnosed between January 2020 and February 2021, and registered in the European multinational LEOSS (Lean European Open Survey on SARS-Infected Patients) registry. The effects of prior neurological diseases and the effect of neurological symptoms on outcome were studied using multivariate logistic regression. RESULTS: A total of 6537 COVID-19 patients (97.7% PCR-confirmed) were analyzed, of whom 92.1% were hospitalized and 14.7% died. Commonly, excessive tiredness (28.0%), headache (18.5%), nausea/emesis (16.6%), muscular weakness (17.0%), impaired sense of smell (9.0%) and taste (12.8%), and delirium (6.7%) were reported. In patients with a complicated or critical disease course (53%) the most frequent neurological complications were ischemic stroke (1.0%) and intracerebral bleeding (ICB; 2.2%). ICB peaked in the critical disease phase (5%) and was associated with the administration of anticoagulation and extracorporeal membrane oxygenation (ECMO). Excessive tiredness (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.20-1.68) and prior neurodegenerative diseases (OR 1.32, 95% CI 1.07-1.63) were associated with an increased risk of an unfavorable outcome. Prior cerebrovascular and neuroimmunological diseases were not associated with an unfavorable short-term outcome of COVID-19. CONCLUSION: Our data on mostly hospitalized COVID-19 patients show that excessive tiredness or prior neurodegenerative disease at first presentation increase the risk of an unfavorable short-term outcome. ICB in critical COVID-19 was associated with therapeutic interventions, such as anticoagulation and ECMO, and thus may be an indirect complication of a life-threatening systemic viral infection.

Stable and safe organ procurement and transplantation during SARS-CoV-2 pandemic in Germany

Solid organ transplantation is a lifesaving routine procedure. In the wake of the COVID-19 pandemic, procurement and transplantation programs in many countries experienced a considerable reduction of organ donation and transplantation by up to 90% caused by an capacity overload of health care providers but also for fear of increased COVID-19 related risks for transplant recipients acquired by viral transmissions from donor to recipient or early after transplantation. Competition for intensive care capacity for severely ill COVID-19 patients versus transplant recipients and organ donors could also have played a role. In Germany, early pandemic management with high capacity testing including all potential organ donors, marked extension of intensive care capacities, structural health care system with a relatively high number of hospitals with intensive care units (1248) as well as transplant centers (40) with high capacities and regional organization of organ donation and transplantation may have been advantageous.

[The COVID-19 Pandemic as an Opportunity and Challenge for Registries in Health Services Research: Lessons Learned from the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS)]. / Die COVID-19 Pandemie als Herausforderung und Chance für Register in der Versorgungsforschung: Erfahrungen aus Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS).

OBJECTIVE: The Coronavirus Disease-2019 (COVID-19) pandemic has brought opportunities and challenges, especially for health services research based on routine data. In this article we will demonstrate this by presenting lessons learned from establishing the currently largest registry in Germany providing a detailed clinical dataset on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected patients: the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS). METHODS: LEOSS is based on a collaborative and integrative research approach with anonymous recruitment and collection of routine data and the early provision of data in an open science context. The only requirement for inclusion was a SARS-CoV-2 infection confirmed by virological diagnosis. Crucial strategies to successfully realize the project included the dynamic reallocation of available staff and technical resources, an early and direct involvement of data protection experts and the ethics committee as well as the decision for an iterative and dynamic process of improvement and further development. RESULTS: Thanks to the commitment of numerous institutions, a transsectoral and transnational network of currently 133 actively recruiting sites with 7,227 documented cases could be established (status: 18.03.2021). Tools for data exploration on the project website, as well as the partially automated provision of datasets according to use cases with varying requirements, enabled us to utilize the data collected within a short period of time. Data use and access processes were carried out for 97 proposals assigned to 27 different research areas. So far, nine articles have been published in peer-reviewed international journals. CONCLUSION: As a collaborative effort of the whole network, LEOSS developed into a large collection of clinical data on COVID-19 in Germany. Even though in other international projects, much larger data sets could be analysed to investigate specific research questions through direct access to source systems, the uniformly maintained and technically verified documentation standard with many discipline-specific details resulted in a large valuable data set with unique characteristics. The lessons learned while establishing LEOSS during the current pandemic have already created important implications for the design of future registries and for pandemic preparedness and response.