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.

Purpose While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization. Methods We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16). Results The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface. Conclusion We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.

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.

ICB-1 chromosome 1 open reading frame 38 (C1orf38) is a human gene initially described by our group to be involved in differentiation processes of cancer cells. Recently, we have reported ICB-1 as a novel estrogen target gene and identified an estrogen response element in its promoter. In this study, we examined the role of ICB-1 in regulation of proliferation of breast and ovarian cancer cells. We knocked down its expression in estrogen-dependent MCF-7 breast cancer cells and hormone-unresponsive SK-OV-3 ovarian cancer cells by stable transfection with a specific shRNA plasmid followed by G-418 selection. Knockdown of ICB-1 enabled a considerable estrogen response of SK-OV-3 cells in terms of proliferation. This transformation of SK-OV-3 cells into an estrogen-responsive phenotype was accompanied by upregulation of estrogen receptor a (ERa) expression and a significant decrease of ERb expression on the mRNA level. Expression of ERa-dependent genes progesterone receptor, pS2, fibulin 1c, and c-fos was elevated in SK-OV-3 cells stably expressing ICB-1 shRNA. In MCF-7 cells, ICB-1 knockdown exerted similar effects on gene expression, supporting a general role of ICB-1 in estrogen responsiveness. Our data suggest that differentiation-associated gene ICB-1 might exert antagonistic actions on cellular estrogen response, which can result in inhibition of estradiol-triggered proliferation. The molecular mechanisms mediating this inhibitory effect of ICB-1 on estrogen signaling are suggested to be limitation of ERa transcript levels but sustaining high levels of ERb, reducing both activation of ERa target genes and cellular proliferation. The identification of ICB-1 as a new player in endocrine-related cancer encourages further studies on the significance of this gene in cancer development and therapy.

Aims Coagulopathy and venous thromboembolism are common findings in coronavirus disease 2019 (COVID-19) and are associated with poor outcome. Timely initiation of anticoagulation after hospital admission was shown to be beneficial. In this study we aim to examine the association of pre-existing oral anticoagulation (OAC) with outcome among a cohort of SARS-CoV-2 infected patients. Methods and results We analysed the data from the large multi-national Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) from March to August 2020. Patients with SARS-CoV-2 infection were eligible for inclusion. We retrospectively analysed the association of pre-existing OAC with all-cause mortality. Secondary outcome measures included COVID-19-related mortality, recovery and composite endpoints combining death and/or thrombotic event and death and/or bleeding event. We restricted bleeding events to intracerebral bleeding in this analysis to ensure clinical relevance and to limit reporting errors. A total of 1 433 SARS-CoV-2 infected patients were analysed, while 334 patients (23.3%) had an existing premedication with OAC and 1 099 patients (79.7%) had no OAC. After risk adjustment for comorbidities, pre-existing OAC showed a protective influence on the endpoint death (OR 0.62, P = 0.013) as well as the secondary endpoints COVID-19-related death (OR 0.64, P = 0.023) and non-recovery (OR 0.66, P = 0.014). The combined endpoint death or thrombotic event tended to be less frequent in patients on OAC (OR 0.71, P = 0.056). Conclusions Pre-existing OAC is protective in COVID-19, irrespective of anticoagulation regime during hospital stay and independent of the stage and course of disease. Graphic abstract