Initiation of opioid agonist treatment following hospital-treated opioid toxicities and the risk of repeat events in Ontario, Canada: a cohort study using inverse probability of treatment weights
Bibliographic record
Abstract
Introduction: The period following hospital discharge for opioid toxicity presents an increased risk for repeat events. While opioid agonist treatment (OAT) can reduce this risk, in-hospital initiation rates remain low, and the impact of early initiation on subsequent repeat toxicities is not well understood. Methods: We conducted a population-based cohort study of Ontario residents discharged following a hospital-treated opioid toxicity between 1 January 2014 and 31 December 2021, followed to 31 July 2022. The exposure was OAT initiation within 30 days of discharge, with a subgroup analysis of OAT initiation within 1 day. The primary outcome was repeat opioid toxicity within 6 months. Stabilised inverse probability treatment weighting (sIPTW) was used to balance baseline covariates, and Cox proportional hazards models to assess the association between OAT initiation and hazard of repeat events. Results: Our cohort included 20 523 opioid toxicities of which 68.5% were male, with a mean age of 36.5 years. Before sIPTW, important differences were observed, including more prior year opioid toxicities (mean 1.35 vs 1.05; standardised difference (Std Diff)= 0.18) and greater public drug benefit eligibility (70.1% vs 58.1%; Std Diff=0.25) among the exposed. Overall, 2544 people (12.4%) initiated OAT within 30 days of hospital discharge. In weighted models, people who initiated OAT in the month following discharge had a lower hazard of repeat toxicity (1.62 per 1000 person-days) compared with those who did not (2.04 per 1000 person-days; weighted HR=0.57; 95% CI 0.47 to 0.69). Findings were consistent in our subgroup analysis (weighted HR=0.44; 95% CI 0.57 to 0.91). Conclusions: Among the small proportion who initiated OAT after a hospital-treated opioid toxicity, there was a significant reduction in repeat toxicities, emphasising the importance of early OAT initiation. To facilitate this, care pathways between hospital and community must be strengthened through enhanced investments in addiction medicine training, hospital resources and reducing stigma in hospitals.
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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".