Awareness of fentanyl exposure and the associated overdose risks among people who inject drugs in a Canadian setting
Bibliographic record
Abstract
INTRODUCTION: Illicitly manufactured fentanyl continues to fuel the opioid overdose crisis throughout the USA and Canada. However, little is known about factors associated with knowingly or unknowingly using fentanyl. Therefore, we sought to identify the prevalence and correlates of suspected/known and unknown exposure to fentanyl (excluding the prescribed one) among people who inject drugs (PWID), including associated overdose risks. METHODS: Data were derived from three prospective cohort studies of community-recruited people who use drugs in Vancouver, Canada in 2016-2017. Multivariable logistic regression was used to identify correlates of suspected/known exposure (i.e. urine drug screen positive and self-reporting past 3-day exposure) and unknown exposure to fentanyl (i.e. urine drug screen positive and self-reporting no past three-day exposure), respectively. RESULTS: Among 590 PWID, 296 (50.2%) tested positive for fentanyl. Of those, 143 (48.3%) had suspected/known and 153 (51.7%) had unknown exposure to fentanyl. In multivariable analyses, using supervised injection sites and possessing naloxone were associated with both suspected/known and unknown exposure (all P < 0.05). Injecting drugs alone (adjusted odds ratio 3.26; 95% confidence interval: 1.72-6.16) was associated with known exposure, but not with unknown exposure. DISCUSSION AND CONCLUSIONS: We found a high prevalence of fentanyl exposure in our sample of PWID, with one half of those exposed consuming fentanyl unknowingly. While those exposed to fentanyl appeared more likely to utilise some overdose prevention services, PWID with suspected/known fentanyl exposure were more likely to inject alone, indicating a need for additional overdose prevention efforts for this group.
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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 | 0.001 | 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".