The relationship between cannabis use and IVF outcome—a cohort study
Bibliographic record
Abstract
BACKGROUND: The effects of cannabis use on male and female reproduction have been the focus of scientific research for decades. Although initial studies raised concerns, more recent studies were reassuring. Considering the recent legalization of recreational use of cannabis in Canada, we sought to analyze IVF outcomes among users and non-users in a single IVF center. METHODS: This is a retrospective cohort study from a single IVF center assessing IVF outcomes among male-female, non-donor IVF patients that are either cannabis users or non-users. We analyzed the ongoing pregnancy rate as well as oocyte yield, fertilization rate, peak serum estradiol, sperm, and embryo quality. We used the Mann-Whitney test, chi-square test, and Kruskal-Wallis tests where appropriate. RESULTS: Overall, the study included 722 patients of which 68 (9.4%) were cannabis users, most defined as light users. The results of the study show similar implantation rate (40.74% vs. 41.13%) and ongoing pregnancy rate (35.2% vs. 29.1%) between the users and non-users, respectively. No significant difference between users and non-users in any of the other analyzed outcomes could be detected. CONCLUSIONS: The results may provide some reassurance for the lack of any demonstrable detrimental effects of cannabis consumption on IVF outcomes. This study was limited by its retrospective nature, self-reporting of cannabis use, and a small user sample size. A larger prospective study is needed to validate its findings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".