Unit-Dose Packaging and Unintentional Buprenorphine-Naloxone Exposures
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Buprenorphine accounts for the most opioid-related pediatric hospital admissions when compared with other opioid analgesics. Since 2010, several manufacturers began distributing their buprenorphine products with unit-dose packaging (UDP). Our main objective in this study is to evaluate the impact of UDP on unintentional pediatric buprenorphine-naloxone poison center exposures. METHODS: This is an observational surveillance study in which the Researched Abuse, Diversion, and Addiction-Related Surveillance System Poison Center Program is used. The main outcome was cases of unintentional ingestions involving children <6 years old and buprenorphine-naloxone (combination) products. The study was split into 3 periods: pre-UDP (first quarter 2008 through fourth quarter 2010), transition to UDP (first quarter 2011 through fourth quarter 2012), and post-UDP (first quarter 2013 through fourth quarter 2016). RESULTS: Overall, there were 6217 exposures to combination products. In the pre-UDP period, there were 20.57 pediatric unintentional exposures per 100 000 prescriptions dispensed; in the transition to UDP period, there were 8.77 pediatric unintentional exposures per 100 000 prescriptions dispensed; and in the post-UDP period, there were 4.36 pediatric unintentional exposures per 100 000 prescriptions dispensed. This represents a 78.8% (95% confidence interval: 76.1%–81.3%; P < .001) relative decrease from the pre-UDP period. CONCLUSIONS: The shift from non-UDP to UDP in over 80% of buprenorphine-naloxone products was associated with a significant decrease in unintentional pediatric exposures reported to poison centers. Packaging controls should be a mainstay in the approach to the prevention of unintentional buprenorphine pediatric exposures as well as exposures to other prescription opioids.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".