Opioid agonist treatment and risk of mortality during opioid overdose public health emergency: population based retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: To compare the risk of mortality among people with opioid use disorder on and off opioid agonist treatment (OAT) in a setting with a high prevalence of illicitly manufactured fentanyl and other potent synthetic opioids in the illicit drug supply. DESIGN: Population based retrospective cohort study. SETTING: Individual level linkage of five health administrative datasets capturing drug dispensations, hospital admissions, physician billing records, ambulatory care reports, and deaths in British Columbia, Canada. PARTICIPANTS: 55 347 people with opioid use disorder who received OAT between 1 January 1996 and 30 September 2018. MAIN OUTCOME MEASURES: All cause and cause specific crude mortality rates (per 1000 person years) to determine absolute risk of mortality and all cause age and sex standardised mortality ratios to determine relative risk of mortality compared with the general population. Mortality risk was calculated according to treatment status (on OAT, off OAT), time since starting and stopping treatment (1, 2, 3-4, 5-12, >12 weeks), and medication type (methadone, buprenorphine/naloxone). Adjusted risk ratios compared the relative risk of mortality on and off OAT over time as fentanyl became more prevalent in the illicit drug supply. RESULTS: 7030 (12.7%) of 55 347 OAT recipients died during follow-up. The all cause standardised mortality ratio was substantially lower on OAT (4.6, 95% confidence interval 4.4 to 4.8) than off OAT (9.7, 9.5 to 10.0). In a period of increasing prevalence of fentanyl, the relative risk of mortality off OAT was 2.1 (95% confidence interval 1.8 to 2.4) times higher than on OAT before the introduction of fentanyl, increasing to 3.4 (2.8 to 4.3) at the end of the study period (65% increase in relative risk). CONCLUSIONS: Retention on OAT is associated with substantial reductions in the risk of mortality for people with opioid use disorder. The protective effect of OAT on mortality increased as fentanyl and other synthetic opioids became common in the illicit drug supply, whereas the risk of mortality remained high off OAT. As fentanyl becomes more widespread globally, these findings highlight the importance of interventions that improve retention on opioid agonist treatment and prevent recipients from stopping treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".