Efficacy of Varenicline in Patients With Severe Alcohol Dependence: A Pilot Double-Blind Randomized and Controlled Study.

Purpose/Background: Varenicline has proven its efficacy in the treatment of nicotine dependence, and there is also evidence that it could be helpful in the treatment of alcohol dependence. In our pilot study, we investigated the feasibility and acceptability of varenicline for the treatment of a population of patients with severe alcohol dependence and multiple somatic comorbidities after alcohol detoxification. Methods/Procedures: We conducted a phase II, double-blind, placebocontrolled randomized trial of daily oral varenicline versus a placebo in alcohol-dependent men and women after alcohol detoxification (n = 28). Following our study protocol, somatic conditions and adverse events were thoroughly monitored and several study end points were investigated (percentage of abstinent days for both alcohol and nicotine, number of standardized drinks and cigarettes per day, days of heavy drinking). Findings/Results: Compared with the placebo, varenicline did not have more side effects and did not provoke more adverse events. Patients in the varenicline group did not showa significantly higher percentage of alcohol abstinent days or fewer heavy drinking days. A trend significance was found for a reduced number of standard drinks per day (P = 0.06) in the varenicline group. Implications/Conclusions: In this pilot trial, varenicline was shown to be well tolerated by our study population of severely alcohol-dependent patients with somatic conditions. Varenicline did not sustain alcohol abstinence or reduce the number of heavy drinking days, but it did reduce the daily amount of alcohol consumed

Die Randgruppe der Randgruppen – Chancengleichheit und Beeinträchtigungen

Ein Gespräch zwischen Christoph Brunner, dem Beauftragten Chancengleichheit und Inklusion HKB, und HKB-Alumnus, Autor und Performer Michael Feh

A trustworthy AI reality-check: the lack of transparency of artificial intelligence products in healthcare

Trustworthy medical AI requires transparency about the development and testing of underlying algorithms to identify biases and communicate potential risks of harm. Abundant guidance exists on how to achieve transparency for medical AI products, but it is unclear whether publicly available information adequately informs about their risks. To assess this, we retrieved public documentation on the 14 available CE-certified AI-based radiology products of the II b risk category in the EU from vendor websites, scientific publications, and the European EUDAMED database. Using a self-designed survey, we reported on their development, validation, ethical considerations, and deployment caveats, according to trustworthy AI guidelines. We scored each question with either 0, 0.5, or 1, to rate if the required information was “unavailable”, “partially available,” or “fully available.” The transparency of each product was calculated relative to all 55 questions. Transparency scores ranged from 6.4% to 60.9%, with a median of 29.1%. Major transparency gaps included missing documentation on training data, ethical considerations, and limitations for deployment. Ethical aspects like consent, safety monitoring, and GDPR-compliance were rarely documented. Furthermore, deployment caveats for different demographics and medical settings were scarce. In conclusion, public documentation of authorized medical AI products in Europe lacks sufficient public transparency to inform about safety and risks. We call on lawmakers and regulators to establish legally mandated requirements for public and substantive transparency to fulfill the promise of trustworthy AI for health

Frequency and distribution pattern of distant metastases in breast cancer patients at the time of primary presentation

Introduction.: For routine staging of patients with primary breast cancer, clinical practice guidelines of many medical societies recommend chest X-ray, liver ultrasound and bone scan. With respect to expanding health care costs and patients' psychological distress it has been supposed, that there might be a group of breast cancer patients, who do not need these imaging studies. Methods.: Four hundred and eighty-eight consecutive patients with primary breast cancer who had primary surgery at our institution and complete work-up for distant metastases including chest X-ray, liver ultrasound, and bone scan were studied. Results.: We found distant metastases at the time of primary diagnosis in 19 patients (3.9%). Bone metastases were found in 2.7%, liver metastases in 1.0%, and pulmonary metastases in 0.4%. However, in breast tumors smaller than 1cm, no metastatic lesions were found, whereas 18.2% of the patients with pT4 tumors had metastases. In 2.4% of screening imaging studies, metastases were ruled out by additional imaging. Conclusion.: Based on our data and a review of the literature, we suggest that chest X-ray, liver ultrasound and bone scan can be omitted in the staging of asymptomatic patients with pT1a or pT1b diseas

Studying the Neurobiology of Social Interaction with Transcranial Direct Current Stimulation—The Example of Punishing Unfairness

Studying social behavior often requires the simultaneous interaction of many subjects. As yet, however, no painless, noninvasive brain stimulation tool existed that allowed the simultaneous affection of brain processes in many interacting subjects. Here we show that transcranial direct current stimulation (tDCS) can overcome these limits. We apply right prefrontal cathodal tDCS and show that subjects' propensity to punish unfair behavior is reduced significantl

Ready-To-Go Questionnaire - Development and validation of a novel medical pre-travel risk stratification tool

Background There are no validated pre-travel self-assessment tools to stratify travellers' health risks and identify their needs for pre-travel medical preparation. This study presents a novel pre-travel risk stratification tool (Ready-To-Go Questionnaire). Methods The Ready-To-Go Questionnaire was developed by travel medical experts. It assesses information on travellers' itinerary and current health status, thereby assigning travellers to one out of four risk categories. To explore the Ready-To-Go Questionnaire's validity, we analysed the agreement between the risk categories resulting from the questionnaire and predefined validation criteria. This study was carried out at the Travel Clinic, University of Zurich, Switzerland. Results One hundred travellers attending a pre-travel consultation were included. 82% corresponded to the substantial-risk category, 17% to the high-risk category, 1% to the moderate-risk category and 0% to the low-risk category. The concordance between the risk categories and the consultants' risk assessment, was 0.39 and 0.29 (unweighted/weighted Cohen's Kappa). No significant concordance was found between the risk categories and additional validation criteria. Conclusion The Ready-To-Go Questionnaire is a medical triage tool developed to identify different levels of travel-related health risks. This tool assists in better understanding travellers' needs, shaping modern travel consultations and offering patient-centred travel medicine services

Risk Factors for Surgical Site Infection in a Tanzanian District Hospital: A Challenge for the Traditional National Nosocomial Infections Surveillance System Index

The incidence of surgical site infections (SSIs) was 24% in a district hospital in Tanzania. Wound classification was not an independent risk factor for SSI, indicating that risk scores developed in industrialized countries may require adjustments for nonindustrialized countries. The National Nosocomial Infections Surveillance system score required adjustments to reliably predict SSI, probably to account for improper hygiene and the lack of adjustment for the duration of surgery (defined as the 75th percentile of the duration for each type of operative procedure) to reflect local circumstances. Multidrug-resistant pathogens, such as methicillin-resistant Staphylococcus aureus and gram-negative pathogens expressing broad-spectrum β-lactamases, have already emerge

The Ready-To-Go Questionnaire predicts health outcomes during travel: a smartphone application-based analysis

BACKGROUND The Ready-To-Go (R2G) Questionnaire is a tool for rapid assessment of health risks for travel consultation. This study aims to assess the utility of the R2G Questionnaire in identifying high-risk travellers and predicting health events and behaviour during travel in the TOURIST2 prospective cohort. METHODS TOURIST2 data were used to calculate the R2G medical and travel risk scores and categorize each participant based on their risk. The TOURIST2 study enrolled 1000 participants from Switzerland's largest travel clinics between 2017 and 2019. Participants completed daily smartphone application surveys before, during and after travel on health events and behaviours. We used regression models to analyse incidence of overall health events and of similar health events grouped into health domains (e.g. respiratory, gastrointestinal, accident/injury). Incidence rate ratios (IRR) are displayed with 95% confidence intervals (95% CI). RESULTS R2G high-risk travellers experienced significantly greater incidence of health events compared to lower-risk travellers (IRR = 1.27, 95% CI: 1.22-1.33). Both the medical and travel scores showed significant positive associations with incidence of health events during travel (IRR = 1.11, 95% CI: 1.07-1.16; IRR = 1.07, 95% CI: 1.03-1.12, respectively), with significant increases in all health domains except skin disorders. Medical and travel risk scores were associated with different patterns in behaviour. Travellers with chronic health conditions accessed medical care during travel more often (IRR = 1.16, 95% CI: 1.03-1.31), had greater difficulty in carrying out planned activities (IRR = -0.04, 95% CI: -0.05, -0.02), and rated their travel experience lower (IRR = -0.04, 95% CI: -0.06, -0.02). Travellers with increased travel-related risks due to planned travel itinerary had more frequent animal contact (IRR = 1.09, 95% CI: 1.01-1.18) and accidents/injuries (IRR = 1.28, 95% CI: 1.15-1.44). CONCLUSIONS The R2G Questionnaire is a promising risk assessment tool that offers a timesaving and reliable means to identify high-risk travellers. Incorporated into travel medicine websites, it could serve as a pre-consultation triage to help travellers self-identify their risk level, direct them to the appropriate medical provider(s), and help practitioners in giving more tailored advice

BMI1 is a target gene of E2F-1 and is strongly expressed in primary neuroblastomas

The oncogene BMI1 encodes a polycomb group transcription factor that is required for embryonic development and self-renewal of stem cells. Despite these important functions little is known about the regulation of BMI1 expression. A cDNA microarray based search for target genes of E2F-1 in neuroblastoma cells expressing a 4-OHT-regulated E2F-1-ER fusion protein identified many hitherto unknown E2F-1 regulated genes. A total of 10% of these genes, including BMI1, encode proteins that function primarily in the regulation of gene expression. The BMI1 promoter contains a putative E2F binding site that was required for the activation of a BMI1 promoter-dependent reporter construct by E2F-1. Chromatin immunoprecipitation revealed 4-OHT-dependent binding of E2F-1-ER and binding of endogenous E2F-1 to the BMI1 promoter in tumor cells. We have previously shown activation of the oncogene MYCN by E2F. Thus, in neuroblastomas deregulated E2F-1 can activate two oncogenes, MYCN and BMI1 that are known to co-operate in tumor formation. Consistent with a role of Bmi1 in neuroblastoma tumorigenesis we found strong Bmi1 expression in primary neuroblastomas. Our results reveal a novel link between E2F and polycomb transcription factors and suggest a role of Bmi1 in neuroblastomas

Inferring on the intentions of others by hierarchical Bayesian learning

Inferring on others' (potentially time-varying) intentions is a fundamental problem during many social transactions. To investigate the underlying mechanisms, we applied computational modeling to behavioral data from an economic game in which 16 pairs of volunteers (randomly assigned to "player" or "adviser" roles) interacted. The player performed a probabilistic reinforcement learning task, receiving information about a binary lottery from a visual pie chart. The adviser, who received more predictive information, issued an additional recommendation. Critically, the game was structured such that the adviser's incentives to provide helpful or misleading information varied in time. Using a meta-Bayesian modeling framework, we found that the players' behavior was best explained by the deployment of hierarchical learning: they inferred upon the volatility of the advisers' intentions in order to optimize their predictions about the validity of their advice. Beyond learning, volatility estimates also affected the trial-by-trial variability of decisions: participants were more likely to rely on their estimates of advice accuracy for making choices when they believed that the adviser's intentions were presently stable. Finally, our model of the players' inference predicted the players' interpersonal reactivity index (IRI) scores, explicit ratings of the advisers' helpfulness and the advisers' self-reports on their chosen strategy. Overall, our results suggest that humans (i) employ hierarchical generative models to infer on the changing intentions of others, (ii) use volatility estimates to inform decision-making in social interactions, and (iii) integrate estimates of advice accuracy with non-social sources of information. The Bayesian framework presented here can quantify individual differences in these mechanisms from simple behavioral readouts and may prove useful in future clinical studies of maladaptive social cognition