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ObjectiveThis study aimed to examine German patients’: (1) self-estimation of the impact of the pandemic on their health and healthcare; and (2) use of digital self-care practices during the pandemic.DesignCross-sectional mixed-methods survey.Setting and participantsGeneral practice patients from four physicians’ offices located in urban and rural areas of Bavaria, Germany, between 21 July 2020 and 17 October 2020. A total of 254 patients participated (55% response rate); 57% (262 of 459) identified as female and participants had an average age of 39.3 years. Patients were eligible to participate if they were 18 years or older and spoke German, and had access to the internet.Results(1) Healthcare for patients was affected by the pandemic, and the mental health of a small group of respondents was particularly affected. The risk of depression and anxiety disorder was significantly increased in patients with quarantine experience. (2) Self-care practices have increased; more than one-third (39%) of participants indicated that they started a new or additional self-care practice during the pandemic, and about a quarter (23%) of patients who were not previously engaged in self-care practices started new self-care activities for the first time; however, such practices were not necessarily digital.ConclusionsFurther investigation is required to understand the relationship between digital self-care and public health events such as the COVID-19 pandemic, and to develop strategies to alleviate the burden of the quarantine experience for patients.

indexed per patient was 3.5 (range 0-29). Notably, 25 cases showed actionable mutated genes, including PTEN, mTOR, FGFR3, FGFR4. Most of the cases showed low TMB, the median value being 4.5 (range 0-28). MSI status was high only in 2 cases. Common CNAs included 13q (10%), 5q (9%) and 17p (6%). Eight out of ten canonical cancer pathways (cell cycle, Hippo, MYC, NOTCH, PI3K, RTK-RAS, TGFb and b-catenin/ WNT) were altered by both mutational and CNA events occurring at different proportions, with mutational events involving up to 33%, and CNA involving up to 42% of genes of the altered pathway. In the Hippo and RTK-RAS pathways the two types of alterations were instead equally represented whereas the remaining pathways (bcatenin/WNT, TGFb, PI3K, NOTCH, MYC and Cell cycle) were more affected by CNA than mutations. NRF2 and TP53 signaling pathways were instead activated by mutational events only.Conclusions: Mutational and copy number alterations conveyed complementary information in MPBC cooperating in activation of cancer pathways.These findings suggest to further study the value of CNAs in MPBC biological processes, especially immunogenicity, which cannot be explained by the low TMB and MSI found. Extended data with matched immune profile will be presented at the meeting.

Background Risk factors of severe COVID-19 have mainly been investigated in the hospital setting. We investigated pre-defined risk factors for testing positive for SARS-CoV-2 infection and cardiovascular or pulmonary complications in the outpatient setting. Methods The present cohort study makes use of ambulatory claims data of statutory health insurance physicians in Bavaria, Germany, with polymerase chain reaction (PCR) test confirmed or excluded SARS-CoV-2 infection in first three quarters of 2020. Statistical modelling and machine learning were used for effect estimation and for hypothesis testing of risk factors, and for prognostic modelling of cardiovascular or pulmonary complications. Results A cohort of 99 811 participants with PCR test was identified. In a fully adjusted multivariable regression model, dementia (odds ratio (OR) = 1.36), type 2 diabetes (OR = 1.14) and obesity (OR = 1.08) were identified as significantly associated with a positive PCR test result. Significant risk factors for cardiovascular or pulmonary complications were coronary heart disease (CHD) (OR = 2.58), hypertension (OR = 1.65), tobacco consumption (OR = 1.56), chronic obstructive pulmonary disease (COPD) (OR = 1.53), previous pneumonia (OR = 1.53), chronic kidney disease (CKD) (OR = 1.25) and type 2 diabetes (OR = 1.23). Three simple decision rules derived from prognostic modelling based on age, hypertension, CKD, COPD and CHD were able to identify high risk patients with a sensitivity of 74.8% and a specificity of 80.0%. Conclusions The decision rules achieved a high prognostic accuracy non-inferior to complex machine learning methods. They might help to identify patients at risk, who should receive special attention and intensified protection in ambulatory care.

This study is aimed at assessing the distinctive features of patients with infected ascites and liver cirrhosis and developing a scoring system to allow for the accurate identification of patients not requiring abdominocentesis to rule out infected ascites. A total of 700 episodes of patients with decompensated liver cirrhosis undergoing abdominocentesis between 2006 and 2020 were included. Overall, 34 clinical, drug, and laboratory features were evaluated using machine learning to identify key differentiation criteria and integrate them into a point-score model. In total, 11 discriminatory features were selected using a Lasso regression model to establish a point-score model. Considering pre-test probabilities for infected ascites of 10%, 15%, and 25%, the negative and positive predictive values of the point-score model for infected ascites were 98.1%, 97.0%, 94.6% and 14.9%, 21.8%, and 34.5%, respectively. Besides the main model, a simplified model was generated, containing only features that are fast to collect, which revealed similar predictive values. Our point-score model appears to be a promising non-invasive approach to rule out infected ascites in clinical routine with high negative predictive values in patients with hydropic decompensated liver cirrhosis, but further external validation in a prospective study is needed.