Alcohol and cannabis consumption in patients with inflammatory bowel disease: prevalence, pattern of consumption and impact on the disease.

There is little guidance regarding the impact of alcohol and cannabis on the clinical course of inflammatory bowel disease. The aim of this study was to assess the prevalence, sociodemographic characteristics and impact of alcohol and cannabis use on the clinical course of the disease. We performed an analysis of prospectively collected data within the Swiss Inflammatory Bowel Disease Cohort Study with yearly follow-ups and substance-specific questionnaires. We analyzed the prevalence of use, the profile of users at risk for addiction and the impact of alcohol and cannabis on the course of the disease. We collected data of 2828 patients included between 2006 and 2018 and analyzed it according to their completion of specific surveys on alcohol and cannabis use. The prevalence of patient-reported active use was 41.3% for alcohol and 6% for cannabis. Heavy drinkers were over-represented among retired, married smokers receiving mostly aminosalicylates and less immunosuppression. In ulcerative colitis patients, low-to-moderate drinking was associated with less extensive disease. Cannabis users were often students with ileal Crohn's disease. A significant proportion of patients with inflammatory bowel disease consume alcohol or cannabis. Heavy alcohol consumption is most likely in male smokers >50 years, whereas young men with ileal disease rather use cannabis

Automated mapping of social networks in wild birds

Growing interest in the structure and dynamics of animal social networks has stimulated major advances [1], [2] and [3], but recording reliable association data for wild populations has remained challenging. While animal-borne ‘proximity’ tags have been available for some time [4], earlier devices were comparatively heavy, had limited detection ranges and/or necessitated recovery for data retrieval. We have developed wireless digital transceiver technology (‘Encounternet') that enables automated mapping of social networks in wild birds, yielding datasets of unprecedented size, quality and spatio-temporal resolution. Miniature, animal-borne tags record the proximity and duration of bird encounters, and periodically transfer logs to a grid of fixed receiver stations, from which datasets can be downloaded remotely for real-time analysis. We used our system to chart social associations in New Caledonian crows Corvus moneduloides [5] and [6]. Analysis of ca. 28,000 encounter logs for 34 crows over a 7-day period reveals a substantial degree of close-range association between non-family birds, demonstrating the potential for horizontal and oblique information exchange

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Correlation of clinical decision-making with probability of disease: A web-based study among general practitioners.

Medical decision-making relies partly on the probability of disease. Current recommendations for the management of common diseases are based increasingly on scores that use arbitrary probability thresholds. To assess decision-making in pharyngitis and appendicitis using a set of clinical vignettes, and the extent to which management is congruent with the true probability of having the disease. We developed twenty-four clinical vignettes with clinical presentations corresponding to specific probabilities of having disease defined by McIsaac (pharyngitis) or Alvarado (appendicitis) scores. Each participant answered four randomly selected web-based vignettes. General practitioners (GP) working in primary care structures in Switzerland and the USA. A comparison between the GP's management decision according to the true probability of having the disease and to the GP's estimated probability, investigating the GP's ability to estimate probability of disease. The mean age of the GPs was 48 years (SD 12) and 66% were men. The correlation between the GP's clinical management decision based on the vignette and the recommendations was stronger for appendicitis than pharyngitis (kw = 0.74, 95% CI 0.70-0.78 vs. kw = 0.66, 95% CI 0.62-0.71). On the other hand, the association between the clinical management decision and the probability of disease estimated by GPs was more congruent with recommendations for pharyngitis than appendicitis (kw = 0.70, 95% CI 0.66-0.73 vs. 0.61, 95% CI 0.56-0.66). Only a minority of GPs correctly estimated the probability of disease (29% for appendicitis and 39% for pharyngitis). Despite the fact that general practitioners often misestimate the probability of disease, their management decisions are usually in line with recommendations. This means that they use other approaches, perhaps more subjective, to make decisions, such as clinical judgment or reasoning that integrate factors other than just the risk of the disease

Raisonnement clinique : de la théorie à la pratique… et retour [Clinical decision making : from theory to practice… and backward]

Being able to analyze all the successive steps of decision making from the first contact with the patient to the final diagnosis is complex because it refers sometimes to intuitive elements proper to each clinician. However, understanding how they integrate probabilities of diseases into their clinical practice and manage diagnostic uncertainties is crucial. This allows a more rational practice of medicine and identifying factors related to the patient, physician or context that may modify the clinical decision making. Furthermore, the use of tools such as clinical scores has taken an important place with the evidence based medicine. Given the fact that they are partly theoretical, it is necessary to assess whether these recommendations are in line with clinical practice