Circumstances surrounding alcohol toxicity deaths and prior pharmacotherapy for alcohol use disorder in Ontario, Canada
Bibliographic record
Abstract
INTRODUCTION: Despite a high prevalence of alcohol use disorder (AUD) in Canada, access to medication-based treatment remains poor. Therefore, our aim was to explore patterns of alcohol toxicity deaths in Ontario, Canada, circumstances surrounding death, prior healthcare interactions, and pharmacotherapy for AUD. METHODS: We conducted a population-based repeated cross-sectional study of alcohol toxicity deaths occurring between 1 January 2018 and 30 June 2022 in Ontario, Canada. We reported trends in deaths over time and determined demographic characteristics of decedents, circumstances surrounding death, and prior healthcare interactions. Among a subset of the cohort with an AUD diagnosis eligible for public drug benefits, we reported receipt of medications used to treat AUD before death. RESULTS: We identified 1346 alcohol toxicity deaths over the study period, at a median age of 42 years, with 73.8% occurring among men. The majority of alcohol toxicity deaths involved other substances, including opioids (75.2%), benzodiazepines (10.8%), and/or stimulants (45.2%). Half had an AUD (50.4%) and 62.7% had an opioid, benzodiazepine or stimulant use disorder. Among decedents who were public drug beneficiaries with an AUD (N = 361), only 3.6% were actively prescribed first-line AUD pharmacotherapies (naltrexone and/or acamprosate) at time of death. CONCLUSIONS: We found that the majority of alcohol toxicity deaths in Ontario involved other non-alcohol substances. We also detected a high prevalence of prior healthcare encounters for substance use disorders (SUDs) and low prevalence of evidence-based AUD pharmacotherapy. This suggests a need for integrated treatment across concurrent SUDs and improved access to pharmacotherapies for AUD across Ontario.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".