Reductions in reported deaths following the introduction of extended‐release oxycodone (OxyContin) with an abuse‐deterrent formulation
Bibliographic record
Abstract
PURPOSE: Abuse of opioid analgesics for their psychoactive effects is associated with a large number of fatalities. The effect of making opioid tablets harder to crush/dissolve on opioid-related fatalities has not been assessed. The objective of this study was to assess the impact of introducing extended-release oxycodone (ERO [OxyContin(®) ]) tablets containing physicochemical barriers to crushing/dissolving (reformulated ERO) on deaths reported to the manufacturer. METHODS: All spontaneous adverse event reports of death in the US reported to the manufacturer between 3Q2009 and 3Q2013 involving ERO were used. The mean numbers of deaths/quarter in the 3 years after reformulated ERO introduction were compared with the year before. Changes in the slope of trends in deaths were assessed using spline regression. Comparison groups consisted of non-fatal reports involving ERO and fatality reports involving ER morphine. RESULTS: Reports of death decreased 82% (95% CI: -89, -73) from the year before to the third year after (131 to 23 deaths per year) reformulation; overdose death reports decreased 87% (95% CI: -93, -78) and overdose deaths with mention of abuse-related behavior decreased 86% (95% CI:-92, -75). In contrast, non-fatal ERO reports did not decrease post-reformulation, and reported ER morphine fatalities remained unchanged. The ratio of ERO fatalities to all oxycodone fatalities decreased from 21% to 8% in the year pre-reformulation to the second year post-reformulation. CONCLUSIONS: These findings, when considered in the context of previously published studies using other surveillance systems, suggest that the abuse-deterrent characteristics of reformulated ERO have decreased the fatalities associated with its misuse/abuse. © 2014 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".