We report on a novel approach to the analysis of suspended particulate data in a rural setting in southern Ontario. Analyses of suspended particulate matter and associated air quality standards have conventionally focussed on 24-hour mean levels of total suspended particulates (TSP) and particulate matter <10 microns, <2.5 microns and <1 micron in diameter (PM10, PM2.5, PM1, respectively). Less emphasis has been placed on brief peaks in suspended particulate levels, which may pose a substantial nuisance, irritant, or health hazard. These events may also represent a common cause of public complaint and concern regarding air quality. Measurements of TSP, PM10, PM2.5, and PM1 levels were taken using an automated device following local complaints of dusty conditions in rural south-central Ontario, Canada. The data consisted of 126,051 by-minute TSP, PM10, PM2.5, and PM1 measurements between May and August 2012. Two analyses were performed and compared. First, conventional descriptive statistics were computed by month for TSP, PM10, PM2.5, and PM1, including mean values and percentiles (70th, 90th, and 95th). Second, a novel graphical analysis method, using density curves and line plots, was conducted to examine peak events occurring at or above the 99th percentile of per-minute TSP readings. We refer to this method as “peak event analysis”. Findings of the novel method were compared with findings from the conventional approach. Conventional analyses revealed that mean levels of all categories of suspended particulates and suspended particulate diameter ratios conformed to existing air quality standards. Our novel methodology revealed extreme outlier events above the 99th percentile of readings, with peak PM10 and TSP levels over 20 and 100 times higher than the respective mean values. Peak event analysis revealed and described rare and extreme peak dust events that would not have been detected using conventional descriptive statistics. Peak event analysis underscored extreme particulate events that may contribute to local complaints regarding intermittently dusty conditions. These outlier events may not appear through conventional analytical approaches. In comparison with conventional descriptive approaches, peak event analysis provided a more analytical and data-driven means to identify suspended particulate events with meaningful and perceptible effects on local residents.
Drug overdose causes approximately 183,000 deaths worldwide annually and 50,000 deaths in Canada and the United States combined. Drug-related deaths are concentrated among young people, leading to a substantial burden of disease and loss of potential life years. Understanding the epidemiology, patterns of care, and prognosis of drug-related prehospital emergencies may lead to improved outcomes.We conducted a retrospective cohort study of out-of-hospital cardiac arrests with drug-related and presumed cardiac causes between 2007 and 2013 using the Toronto Regional RescuNet Epistry database. The primary outcome was survival to hospital discharge. We computed standardized case fatality rates, and odds ratios of survival to hospital discharge for cardiac arrests with drug-related versus presumed cardiac causes, adjusting for confounders using logistic regression.The analysis involved 21,497 cardiac arrests, including 378 (1.8%) drug-related and 21,119 (98.2%) presumed cardiac. Compared with the presumed cardiac group, drug-related arrest patients were younger and less likely to receive bystander resuscitation, have initial shockable cardiac rhythms, or be transported to hospital. There were no significant differences in emergency medical service response times, return of spontaneous circulation, or survival to discharge. Standardized case fatality rates confirmed that these effects were not due to age or sex differences. Adjusting for known predictors of survival, drug-related cardiac arrest was associated with increased odds of survival to hospital discharge (OR1.44, 95%CI 1.15-1.81).In out-of-hospital cardiac arrest, patients with drug-related causes are less likely than those with presumed cardiac causes to receive bystander resuscitation or have an initial shockable rhythm, but are more likely to survive after accounting for predictors of survival. The demographics and outcomes among drug-related cardiac arrest patients offers unique opportunities for prehospital intervention.
Ontario patients on opioid agonist treatment (OAT) are often prescribed methadone instead of buprenorphine, despite the latter’s superior safety profile. Ontario OAT providers were surveyed to better understand their attitudes towards buprenorphine and potential barriers to its use, including the induction process. We used a convenience sample from an annual provincial conference to which Ontario physicians who are involved with OAT are invited. Based on 85 survey respondents (out of 215 attendees), only 4% of Ontario addiction physicians involved in OAT routinely used unobserved “home” buprenorphine induction: 59% of physicians felt that unobserved induction was risky because it was against “the guidelines” and 66% and 61% respectively believed that unobserved “home” induction increased the risk of diversion and of precipitated withdrawal. Ontario addiction physicians largely report following the traditional method of bringing in patients for observed in-office buprenorphine induction: they expressed fear of precipitated withdrawal, diversion, and going against clinical guidelines. The hesitance in using unobserved induction may explain, in part, Ontario’s reliance on methadone.
Background Opioid-related mortality continues to rise across North America, and mortality rates have been further exacerbated by the COVID-19 pandemic. This study sought to provide an updated picture of trends of opioid-related mortality for Ontario, Canada between January 2003 and December 2020, in relation to age and sex. Methods Using mortality data from the Office of the Chief Coroner for Ontario, we applied Bayesian Poisson regression to model age/sex mortality per 100,000 person-years, including random walks to flexibly capture age and time effects. Models were also used to explore how trends might continue into 2022, considering both pre- and post-COVID-19 courses. Results From 2003 to 2020, there were 11,633 opioid-related deaths in Ontario. A shift in the age distribution of mortality was observed, with the greatest mortality rates now among younger individuals. In 2003, mortality rates reached maximums at 5.5 deaths per 100,000 person-years (95% credible interval: 4.0–7.6) for males around age 44 and 2.2 deaths per 100,000 person-years (95% CI: 1.5–3.2) for females around age 51. As of 2020, rates have reached maximums at 67.2 deaths per 100,000 person-years (95% CI: 55.3–81.5) for males around age 35 and 16.8 deaths per 100,000 person-years (95% CI: 12.8–22.0) for females around age 37. Our models estimate that opioid-related mortality among the younger population will continue to grow, and that current conditions could lead to male mortality rates that are more than quadruple those of pre-pandemic estimations. Conclusions This analysis may inform a refocusing of public health strategy for reducing rising rates of opioid-related mortality, including effectively reaching both older and younger males, as well as young females, with health and social supports such as treatment and harm reduction measures.
To the Editor: In the era of multiauthored scientific papers, critics have warned that credit and accountability cannot be determined without explicit report of author contributions.1,2 We assessed how academic readers interpret the order of authors and designation of "corresponding author" in assigning credit and accountability for scientific research. We created a fictitious study title with 5 fictitious authors. We provided only the initials of the authors' first names to avoid sex-biased response. Two authorship bylines were constructed, one with the first author as corresponding author, and the other with the last author as corresponding author. Respondents were asked to infer the authors' specific contributions for each set of authorship bylines. We sent the survey to the chairs of 32 departments of surgery or medicine in all 16 Canadian university medical facilities. Each respondent received up to 5 follow-up telephone calls after the initial mailing in September 2002. Twenty-two (69%) department chairs (11 medical, 11 surgical) completed the survey. When the first author was also the corresponding author, all respondents credited the author with the analysis and interpretation of data and with drafting the manuscript. Most respondents inferred that the first author was also involved in the process of study conception and design (82%) and acquisition of data (95%). Respondents varied in their inferences about the first author's involvement in the other areas. The only contribution ascribed to the second, third, fourth, and last authors by at least 50% of respondents was critical revision of the manuscript. When the last author was labeled as the corresponding author, the last author was much more likely to be given credit for study conception and design (increasing from 36–77%), for administrative support (from 41–77%), and for supervision (from 46–86%) (Table 1).TABLE 1: Percent of Canadian Medical and Surgical Department Chairs (N = 22) Who Assign the Following Credit to First or Last Authors, According to the Position of the Corresponding Author in the List of AuthorsMost respondents felt the authorship order should be determined by amount of work done (95%) and contributions to writing the manuscript (91%). Responses did not differ between surgical and medical department chairpersons. Our study demonstrates that 1) labeling an author as corresponding author increased the author's credit for contributions to the study; 2) beyond the first author's contribution to design, conduct of the study, and writing the paper, respondents appear to have little idea of the roles of any author; and 3) respondents endorse manuscript writing and the amount of work done on the study as legitimate criteria for designating authorship order. Our findings suggest that experienced readers with responsibility for determining academic advancement of their faculty are inconsistent in their interpretation of authors' contributions in the absence of explicit reporting. Unless journals report authors' explicit contributions in research papers, many readers will continue to remain uncertain or draw false conclusions about appropriate author credit and accountability. [Acknowledging the authors' arguments in favor of publishing author contributions, we have permitted these to be listed below.—The Editors] AUTHOR CONTRIBUTIONS Study Conception and Design: Mohit Bhandari, Jason Busse, and Abhaya Kulkarni. Acquisition of Data: Mohit Bhandari and Pamela Leece. Analysis and Interpretation of Data: Mohit Bhandari, Jason Busse, Abhaya Kulkarni, P. J. Devereaux, and Gordon H. Guyatt. Drafting of the Manuscript: Mohit Bhandari. Critical Revision of the Manuscript: Mohit Bhandari, Jason Busse, Pamela Leece, Abhaya Kulkarni, P. J. Devereaux, and Gordon H. Guyatt. Statistical Expertise: Mohit Bhandari, P. J. Devereaux, and Gordon H. Guyatt. Administrative, Technical, or Material Support: Pamela Leece and Mohit Bhandari. Study Supervision: Mohit Bhandari. Mohit Bhari Jason W. Busse Abhaya V. Kulkarni P. J. Devereaux Pamela Leece Gordon H. Guyatt Department of Clinical Epidemiology and Biostatistics McMaster University Medical Centre 1200 Main Street West Room 2C9 Hamilton, Ontario, L8N 3Z5 Canada [email protected]
