Tighter regulations needed for over-the-counter codeine in Canada
Bibliographic record
Abstract
Since I started practising pharmacy in Ontario 5 years ago, I have felt uneasy about over-the-counter (OTC) codeine.The national Narcotic Control Regulations suggests that every pharmacist should counsel on these drugs, 1 but in my experience, this rarely happens.Most patients can easily buy 200 pills of these OTC narcotics as long as they simply tell the pharmacy cashier that they have "had it before." A change is needed to ensure safer and more effective use of OTC codeine products in Canada.When analyzing Canada's opioid epidemic, OTC codeine should not be ignored.Several studies have shown misuse of these products.A 1997 Canadian survey of regular codeine users found that 37% were dependent on codeine, 4% abused it, and one-half of all regular users obtained codeine over the counter. 2 In a retrospective chart review of patients attending a methadone maintenance treatment clinic from 1997 to 1999 in Toronto, Ontario, 46% of opioid users were using codeine and 35% of opioid users were using OTC codeine. 3In another chart review of patients attending an opioid detoxification program in Toronto, Ontario, from 2000 to 2004, 35% reported using codeine and 5% were using OTC codeine. 4Between 2011 and 2014, 514 Ontarians began methadone treatment for addiction to OTC codeine. 5nternational research provides insight into the problems with OTC codeine.In France, a study of 53 purchasers of codeine at a community pharmacy found that 15% were using codeine for nonmedical reasons, 7.5% reported dependence and 7.5% reported abuse. 6][9][10] In these reports, many patients addicted to OTC codeine had gastrointestinal-related morbidities (hemorrhage, anemia, hematemesis) secondary to the nonsteroidal anti-inflammatory drugs (NSAIDs) in codeine combination pills.OTC codeine is commonly sold in combination with acetylsalicylic acid (ASA) and acetaminophen in Canada, and both of these noncodeine drugs could cause similar collateral harms as a result of codeine misuse.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".