Fentanyl-related deaths in Ontario, Canada: toxicological findings and circumstances of death in 4395 cases (2020–22)
Bibliographic record
Abstract
Over the last 20 years, there has been a significant increase in fentanyl-related deaths in Ontario, Canada. This report examines toxicological findings in a series of death investigations in which fentanyl was quantitated to identify the prevalence, trends, and demographic data associated with fentanyl in Ontario, Canada, and to highlight the changes in these trends since fentanyl began appearing in casework in Ontario in the early 2000s. A retrospective study of all cases in which fentanyl was quantitated in blood, using liquid chromatography (LC)-tandem mass spectrometry (MS-MS), was conducted for the time period between 1 January 2020 and 31 December 2022. A total of 4395 cases were included; 77% of the decedents were male, and 23% was female with ages ranging from 0 to 95 years. The most frequently classified cause of death was mixed drug toxicity (69%) followed by fentanyl intoxication at 19%. Less than 10% of cases where fentanyl was quantitated were classified as nondrug-related deaths. Fentanyl concentrations in all cases ranged from 1.3 to >2000 ng/mL. Other drugs were frequently detected with fentanyl. In mixed drug toxicity cases, stimulants were the most frequently encountered class of drugs: cocaine was identified in 51.8%, and methamphetamine was observed in 43.0% of cases. Detailed reports for select cases were included to provide additional insight into the different case types and to show the difficulty in interpreting blood concentrations without additional detailed case histories. This study provides valuable information for the scientific and medical community regarding the continued use of fentanyl and how patterns of fentanyl use have evolved since it began to appear in forensic casework.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".