[E-cigarette use among cannabis users and multi-users of psychoactive products: A cohort study]. / L'usage d'e-cigarette chez les usagers de cannabis et les polyconsommateurs : étude de cohorte.

INTRODUCTION: There is no evidence in the literature relating to the evolution of e-cigarette use among cannabis users and multi-users (of alcohol, tobacco or cannabis). OBJECTIVE: To describe the evolution over 12 months of e-cigarette use in cannabis users and multi-users. METHODS: A prospective observational cohort study in general practice, between 2015 and 2016. RESULTS: A total of 4.8% of monitored cannabis users remained or became current users of e-cigarettes by the end of the monitoring period versus 4.5% among non-users of cannabis, with no statistically significant difference. A total of 5.1% of monitored multi-users remained or became current users of e-cigarettes by the end of the monitoring period versus 2.4% among the non-multi-users, with no statistically significant difference. Cannabis users and multi-users reported more e-cigarette experimentation through curiosity and following someone's suggestion, compared to non-cannabis users or non multi-users. No statistically significant association was found between cannabis or multi-drug use and staying or becoming a current e-cigarette user over 12 months. CONCLUSION: Cannabis users and multi-users would tend to experiment with e-cigarettes more than other patients but this use would not be sustained.

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs.

BACKGROUND: Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics. METHODS: We investigated two methods ("exclusion" versus "scoring") for reproducing this reasoning based on antibiotic properties. RESULTS: The "exclusion" method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations. DISCUSSION: This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs.