Evidence map›Paper›PMID 41340109›Full record

ArticleBMC public health2025

Substances and substance combinations among accidental substance-related acute toxicity deaths (AATDs) in Canada from 2016 to 2017.

Raahyma Ahmad, Tanya Kakkar, Jenny Rotondo, Keltie Hamilton, Matthew J Bowes, Graham Jones, Cindy Leung Soo, Amanda VanSteelandt

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Raahyma AhmadSubstance-Related Harms Division, Public Health Agency of Canada, 785 Carling Ave, Ottawa, ON, K1A 0K9, Canada. raahyma.ahmad@phac-aspc.gc.ca.
Tanya KakkarSubstance-Related Harms Division, Public Health Agency of Canada, 785 Carling Ave, Ottawa, ON, K1A 0K9, Canada.
Jenny RotondoSubstance-Related Harms Division, Public Health Agency of Canada, 785 Carling Ave, Ottawa, ON, K1A 0K9, Canada.
Keltie HamiltonSubstance-Related Harms Division, Public Health Agency of Canada, 785 Carling Ave, Ottawa, ON, K1A 0K9, Canada.
Matthew J BowesNova Scotia Medical Examiner Service, Department of Justice, Halifax, NS, Canada.
Graham JonesDepartment of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.
Cindy Leung SooCentre for Emergency Preparedness, Public Health Agency of Canada, Ottawa, ON, Canada.
Amanda VanSteelandtSubstance-Related Harms Division, Public Health Agency of Canada, 785 Carling Ave, Ottawa, ON, K1A 0K9, Canada. amanda.vansteelandt@phac-aspc.gc.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCanada has seen a rise in substance-related accidental acute toxicity deaths (AATDs) in recent years. Research indicates that fentanyl opioids, non-fentanyl opioids, and stimulants are classes of concern and that multidrug AATDs have increased. However, there is limited information regarding the specific substances involved. This study aims to identify the substances and substance combinations as well as substance classes and substance class combinations most often involved in AATDs across Canada between 2016 and 2017. It also examines variations in substances by year and across sociodemographic, socioeconomic, and geographic factors.

methodsData were abstracted from the coroner and medical examiner files of all AATDs that occurred across Canada between 2016 and 2017. Top substances and classes detected in or contributing to AATDs were identified based on toxicology reports and cause of death statements. AATDs were stratified by year of death, age, sex, residence community type, neighbourhood income quintile, and province/region to understand variations in the substances contributing to AATDs. Combinations of substances and classes contributing to death were examined with UpSet plots and trends of select substances were visualized over time with ribbon charts. An algorithm was developed to report the source and origin of the substances based on prescription history and scene evidence.

resultsFentanyl, cocaine, alcohol, and methamphetamine were the top substances contributing to the 7,902 AATDs identified between 2016 and 2017 in Canada. While stimulants and opioids were the most common substance classes contributing to AATDs, other classes, including benzodiazepines and acetaminophen also emerged as classes among the top contributors. Between 2016 and 2017, the proportion of AATDs attributable to diacetylmorphine (heroin) per quarter decreased while the proportion of AATDs attributable to carfentanil per quarter increased. AATDs involving more than one substance occurred across all sociodemographic, socioeconomic, and geographic groups. Substances contributing to AATDs more commonly originated from non-pharmaceutical sources than from pharmaceutical sources. CONCLUSIONS AND IMPACTS: Specific substances and substance combinations contributing to deaths vary over time and geographic areas. Opioids and stimulants are both detected in and contribute to a majority of AATDs, but the substance-related acute toxicity death crisis is complex and attributable to many substance classes. Understanding these differences will allow for targeted substance-related policies, prevention, and harm reduction efforts.

Indexed as

Drug OverdoseSubstance-Related DisordersAdolescentAdultAgedAnalgesics, OpioidCanadaFemaleFentanylHumansMaleMiddle AgedYoung AdultAnalgesics, OpioidFentanylAcute toxicityCanadaChart review studyCoronerDeath investigationsDrug overdoseMedical examinerMixed-drug toxicityMortalityOpioidsPoisoningPolydrugPolysubstance

Identifiers

PMID41340109
PMCPMC12781315

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.