Teaching medicine web-based with the help of interactive audience response systems.

The COVID-19 pandemic confronted the medical community worldwide with numerous challenges, not only with respect to medical care, but also for teaching the next generation of physicians. To minimize the risk of infections patient-unrelated classes can be held digitally. Here we present a student initiated, web-based teaching approach, called "From symptom to diagnosis". In this seminar case reports of rare diseases were presented to the audience in a symptom-focused manner. The patients´ most significant symptoms were presented, followed by an in-depth discussion about differential diagnosis. First glance diagnosis pictures were shown to improve students´ ability to identify important clinical scenarios. We used chat functions as well as an audience response system to make the seminar more interactive. By this we attracted between 71 and 147 participants per session. The online seminar was very well perceived and 97% of the students saw an improvement of their diagnostic skills. In summary, we successfully established an interactive, web-based teaching format for medical students.

The Expression of Autophagy-Associated Genes Represents a Valid Footprint for Aggressive Pancreatic Neuroendocrine Neoplasms.

Pancreatic neuroendocrine neoplasms (pNEN) are rare and heterogeneous tumors. Previous investigations have shown that autophagy can be a target for cancer therapy. This study aimed to determine the association between the expression of autophagy-associated gene transcripts and clinical parameters in pNEN. In total, 54 pNEN specimens were obtained from our human biobank. The patient characteristics were retrieved from the medical record. RT-qPCR was performed to assess the expression of the autophagic transcripts BECN1, MAP1LC3B, SQSTM1, UVRAG, TFEB, PRKAA1, and PRKAA2 in the pNEN specimens. A Mann-Whitney U test was used to detect differences in the expression of autophagic gene transcripts between different tumor characteristics. This study showed that G1 sporadic pNEN have a higher expression of autophagic genes compared to G2. Lymphatic and distant metastasis occurred significantly more often in pNEN with a decreased expression of the autophagic genes. Within sporadic pNEN, the insulinomas express higher levels of autophagic transcripts than gastrinomas and non-functional pNEN. MEN1-associated pNEN show a higher expression of autophagic genes than sporadic pNEN. In summary, a decreased expression of autophagic transcripts distinguishes metastatic from non-metastatic sporadic pNEN. The significance of autophagy as a molecular marker for prognosis and therapy decisions needs to be further investigated.

Diffusion magnetic resonance imaging connectome features are predictive of functional lateralization of semantic processing in the anterior temporal lobes.

Assessment of regional language lateralization is crucial in many scenarios, but not all populations are suited for its evaluation via task-functional magnetic resonance imaging (fMRI). In this study, the utility of structural connectome features for the classification of language lateralization in the anterior temporal lobes (ATLs) was investigated. Laterality indices for semantic processing in the ATL were computed from task-fMRI in 1038 subjects from the Human Connectome Project who were labeled as stronger rightward lateralized (RL) or stronger leftward to bilaterally lateralized (LL) in a data-driven approach. Data of unrelated subjects (n = 432) were used for further analyses. Structural connectomes were generated from diffusion-MRI tractography, and graph theoretical metrics (node degree, betweenness centrality) were computed. A neural network (NN) and a random forest (RF) classifier were trained on these metrics to classify subjects as RL or LL. After classification, comparisons of network measures were conducted via permutation testing. Degree-based classifiers produced significant above-chance predictions both during cross-validation (NN: AUC-ROC[CI] = 0.68[0.64-0.73], accuracy[CI] = 68.34%[63-73.2%]; RF: AUC-ROC[CI] = 0.7[0.66-0.73], accuracy[CI] = 64.81%[60.9-68.5]) and testing (NN: AUC-ROC[CI] = 0.69[0.53-0.84], accuracy[CI] = 68.09[53.2-80.9]; RF: AUC-ROC[CI] = 0.68[0.53-0.84], accuracy[CI] = 68.09[55.3-80.9]). Comparison of network metrics revealed small effects of increased node degree within the right posterior middle temporal gyrus (pMTG) in subjects with RL, while degree was decreased in the right posterior cingulate cortex (PCC). Above-chance predictions of functional language lateralization in the ATL are possible based on diffusion-MRI connectomes alone. Increased degree within the right pMTG as a right-sided homologue of a known semantic hub, and decreased hubness of the right PCC may form a structural basis for rightward-lateralized semantic processing.

Towards a COVID-19 symptom triad: The importance of symptom constellations in the SARS-CoV-2 pandemic.

Pandemic scenarios like SARS-Cov-2 require rapid information aggregation. In the age of eHealth and data-driven medicine, publicly available symptom tracking tools offer efficient and scalable means of collecting and analyzing large amounts of data. As a result, information gains can be communicated to front-line providers. We have developed such an application in less than a month and reached more than 500 thousand users within 48 hours. The dataset contains information on basic epidemiological parameters, symptoms, risk factors and details on previous exposure to a COVID-19 patient. Exploratory Data Analysis revealed different symptoms reported by users with confirmed contacts vs. no confirmed contacts. The symptom combination of anosmia, cough and fatigue was the most important feature to differentiate the groups, while single symptoms such as anosmia, cough or fatigue alone were not sufficient. A linear regression model from the literature using the same symptom combination as features was applied on all data. Predictions matched the regional distribution of confirmed cases closely across Germany, while also indicating that the number of cases in northern federal states might be higher than officially reported. In conclusion, we report that symptom combinations anosmia, fatigue and cough are most likely to indicate an acute SARS-CoV-2 infection.

A pilot study of patient satisfaction with a self-completed tablet-based digital questionnaire for collecting the patient's medical history in an emergency department.

BACKGROUND: The increasing popularity and availability of tablet computers raises questions regarding clinical scenarios. This pilot study examined the patient's satisfaction when using a tablet-based digital questionnaire as a tool for obtaining medical history in an emergency department and to what extent gender, age, technical competence and mother tongue influence the user satisfaction. Patients were asked to complete three consecutive questionnaires: The first questionnaire collected basic epidemiological data to measure past digital usage behaviour, the second questionnaire collected the patient's medical history, and the third questionnaire assessed the overall perceived user satisfaction when using the tablet-based survey application for medical anamnesis. RESULTS: Of 111 consenting patients, 86 completed all three questionnaires. In summary, the user evaluation was positive with 97.7% (n = 84) of the patients stating that they had no major difficulties using the digital questionnaire. Only 8.1% (n = 7) of patients reported a preference to fill out a paper-and-pen version on the next visit instead, while 98.8% (n = 85) stated that they would feel confident filling out a digital questionnaire on the next visit. The variables gender, age, mother tongue and/or technical competence did not exert a statistically significant influence towards the defined scales usability, content and overall impression. CONCLUSION: In conclusion, self-administered tablet-based questionnaires are widely accepted tools for collecting medical information in the emergency room across all ages and genders, regardless of technical competence.