Real-world Evidence for Impact of Opioid Agonist Therapy on Nonfatal Overdose in Patients with Opioid Use Disorder during the COVID-19 Pandemic
Bibliographic record
Abstract
OBJECTIVES: The primary objectives of this study were to describe the demographics and clinical characteristics of patients who were treated with buprenorphine extended-release versus buprenorphine-naloxone sublingual tablets versus methadone in a real-world setting and to evaluate the difference in nonfatal overdose events between treatment cohorts. METHODS: This study was a retrospective chart review of patients with opioid use disorder initiating opioid agonist therapy in Canada during the outset of the COVID-19 pandemic (March 11, 2020 to October 31, 2021). Three treatment cohorts were defined by the initial prescribed opioid agonist therapy regimen: buprenorphine extended-release, buprenorphine-naloxone sublingual tablets, and methadone. Baseline characteristics, as well as treatment status, overdose events, and substance use 6 months after treatment initiation were collected using a standardized form. RESULTS: Nine clinics provided data on 379 patient cases. The incidence rate (number of events per 100 person-years) for a self-reported nonfatal overdose was 46.8 (n = 18), 19.3 (n = 10), and 1.7 (n = 1) in the methadone, buprenorphine-naloxone sublingual tablets, and buprenorphine extended-release cohorts, respectively. The risk-adjusted difference for the proportion of patients with nonfatal overdose was 8.59% (95% confidence interval, 3.10-14.08%; P = 0.0022) for methadone versus buprenorphine extended-release and 6.51% (95% confidence interval, 1.46-11.56%; P = 0.0115) for buprenorphine-naloxone sublingual tablets versus buprenorphine extended-release. CONCLUSIONS: Buprenorphine extended-release was associated with lower rates of nonfatal overdose events compared with daily opioid agonist therapy. Given the limitations of this naturalistic, retrospective design, further prospective studies are needed to validate these findings and demonstrate the potential for long-acting opioid agonist therapy in addressing the opioid crisis.
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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 | 0.008 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".