Concordance of self-reported drug use and saliva drug tests in a sample of emergency department patients

The purpose of this study was to assess the concordance of self-reports of cannabis, cocaine and amphetamines usage, with a saliva point-of-collection drug test, the DrugWipe 5+, in an emergency department (ED) setting. Methods: A random sample of people admitted to either of two emergency departments at hospitals in British Columbia, Canada were asked to participate in an interview on their substance use and provide a saliva test for the detection of drugs. Analyses: Concordance of self-reports and drug tests were calculated. Prior to DrugWipe 5+, sensitivity and specificity estimates were compared against a gold standard of mass spectrometry and chromatography (MS/GC). This was used as a basis to assess the truthfulness of self-reports for each drug. Results: Of the 1584 patients approached, 1190 agreed to participate, which is a response rate of 75.1%. For cannabis, among those who acknowledged use, only 21.1% had a positive test and 2.1% of those who reported no use had a positive test. For cocaine and amphetamines respectively, 50.0% and 57.1% tested positive among those reporting use, while 2.1% and 1.3%, respectively, reported no use and tested positive. Self-reports of cannabis and amphetamines use appear more truthful than self-reports of cocaine use

Bicycling crash circumstances vary by route type: a cross-sectional analysis

Abstract Background Widely varying crash circumstances have been reported for bicycling injuries, likely because of differing bicycling populations and environments. We used data from the Bicyclists’ Injuries and the Cycling Environment Study in Vancouver and Toronto, Canada, to describe the crash circumstances of people injured while cycling for utilitarian and leisure purposes. We examined the association of crash circumstances with route type. Methods Adult cyclists injured and treated in a hospital emergency department described their crash circumstances. These were classified into major categories (collision vs. fall, motor vehicle involved vs. not) and subcategories. The distribution of circumstances was tallied for each of 14 route types defined in an earlier analysis. Ratios of observed vs. expected were tallied for each circumstance and route type combination. Results Of 690 crashes, 683 could be characterized for this analysis. Most (74%) were collisions. Collisions included those with motor vehicles (34%), streetcar (tram) or train tracks (14%), other surface features (10%), infrastructure (10%), and pedestrians, cyclists, or animals (6%). The remainder of the crashes were falls (26%), many as a result of collision avoidance manoeuvres. Motor vehicles were involved directly or indirectly with 48% of crashes. Crash circumstances were distributed differently by route type, for example, collisions with motor vehicles, including “doorings”, were overrepresented on major streets with parked cars. Collisions involving streetcar tracks were overrepresented on major streets. Collisions involving infrastructure (curbs, posts, bollards, street furniture) were overrepresented on multiuse paths and bike paths. Conclusions These data supplement our previous analyses of relative risks by route type by indicating the types of crashes that occur on each route type. This information can guide municipal engineers and planners towards improvements that would make cycling safer