Cannabis use in pregnancy and breastfeeding: The pharmacist’s role
Bibliographic record
Abstract
Background: The recent legalization of cannabis use in Canada requires pharmacists to be able to support their patients with accurate knowledge of its known risks and benefits. Certain populations, such as pregnant and breastfeeding women and their developing children, may be at higher risk than other populations. Methods: The authors independently searched the literature for clinical reports or reviews of the literature regarding the safety of cannabis use in pregnancy and breastfeeding using search terms such as cannabis, marijuana, pregnancy and breastfeeding. Results: This review combines the relevant pharmacological, pharmacokinetic and clinical evidence for the effects of cannabis in this special patient population. The literature demonstrates that some of the constituents of cannabis can reach children in utero and through breastmilk. Given that Δ⁹-tetrahydrocannabinol can be present in breastmilk as quickly as 1 hour after consumption and last up to 6 days, it may not be possible to use cannabis and avoid infant exposure. There is evidence that this exposure may result in cognitive, social and motor defects. Some of these effects may be long term, lasting years. The pharmacist must be able to educate and screen patients regarding marijuana use in pregnancy and breastfeeding, with the ultimate aim of harm reduction.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".