MétaCan
Menu
Back to cohort
Record W4410638300 · doi:10.1371/journal.pone.0324732

The changing role of substances: trends, characteristics of individuals and prior healthcare utilization among individuals with accidental substance-related toxicity deaths in Ontario Canada

2025· article· en· W4410638300 on OpenAlexaffabout
Shaleesa Ledlie, Alice Holton, Pamela Leece, Bisola Hamzat, Joanna C. Yang, Gillian Kolla, Nikki Bozinoff, R. E. BOYD, Mike Franklyn, Ashley Smoke, Paul J. Newcombe, Tara Gomes

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsOntario Drug Policy Research NetworkCentre for Addiction and Mental HealthMemorial University of NewfoundlandInstitute for Clinical Evaluative SciencesNOSM UniversityPublic Health OntarioOttawa Public HealthUniversity of TorontoSt. Michael's Hospital
FundersNational Institute on Drug Abuse
KeywordsMedicineAccidentalPopulationToxicityPoison controlSubstance abuseInjury preventionYoung adultEnvironmental healthDemographyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate trends and the circumstances surrounding fatal substance-related toxicities directly attributed to alcohol, stimulants, benzodiazepines or opioids and combinations of substances in Ontario, Canada. METHODS: We conducted a population-based cross-sectional study of all accidental substance-related toxicity deaths in Ontario, Canada from January 1, 2018 to June 30, 2022. We reported monthly rates of substance-related toxicity deaths and investigated the combination of substances most commonly involved in deaths. Demographic characteristics, location of incident, and prior healthcare encounters for non-fatal toxicities and substance use disorders were examined. RESULTS: Overall, 10,022 accidental substance-related toxicity deaths occurred, with the annual number of deaths nearly doubling between the first and last 12 months of the study period (N = 1,570-2,702). Opioids were directly involved in the majority of deaths (84.1%; N = 8,431), followed by stimulants (60.9%; N = 6,108), alcohol (13.4%; N = 1,346) and benzodiazepines (7.8%; N = 782). In total, 56.9% (N = 5,698) of deaths involved combinations of substances. Approximately one-fifth of individuals were treated in a hospital setting for a substance-related toxicity in the past year, with the majority being opioid-related (17.4%; N = 1,748). Finally, 60.9% (N = 6,098) of people had a substance use disorder diagnosis at time of death. CONCLUSIONS: Our study shows not only the enormous loss of life from substance-related toxicities but also the growing importance of combinations of substances in these deaths. A large proportion of people had previously interacted within an hospital setting for prior substance-related toxicity events or related to a substance use disorder, representing important missed intervention points in providing appropriate care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.239
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicPoisoning and overdose treatmentsFrench-language works237,207