Rates of Anomalous Bupropion Prescriptions in Ontario, Canada
Bibliographic record
Abstract
PURPOSE: Reports of bupropion misuse have increased since it was first reported in 2002. The purpose of this study was to explore trends in bupropion prescribing suggestive of misuse or diversion in Ontario, Canada. METHODS: A serial cross-sectional study was conducted of Ontarians aged younger than 65 years who received prescriptions under Ontario's public drug program from April 1, 2000, to March 31, 2013. We determined the number of potentially inappropriate prescriptions in each quarter, defined as early refills dispensed within 50% of the duration of the preceding prescription, as well as potentially duplicitous prescriptions, defined as similarly early refills originating from a different prescriber and different pharmacy. We replicated these analyses for citalopram and sertraline, antidepressants not known to be prone to abuse. RESULTS: We identified 1,780,802 prescriptions for bupropion, 3,402,462 for citalopram, and 1,775,285 for sertraline. Rates of early refills for bupropion declined during the study from 4.8% to 3.1%. In the final quarter, rates of early refills for bupropion were more common than for citalopram (3.1% vs 2.2%) (P <.001) but not for sertraline (3.1% vs 2.9%) (P =.16). Potentially duplicitous prescriptions for bupropion increased dramatically, from <0.05% of all prescriptions in early 2000 to 0.47% in early 2013 and by the final quarter were more common than both citalopram (0.11%) and sertraline (0.12%) (P <.001). CONCLUSIONS: Although no marked differences were seen for early refills of bupropion relative to its comparators, potentially duplicitous prescriptions have increased dramatically in Ontario, suggesting growing misuse of the drug.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".