The impact of cannabis use on male sexual function: A 10-year, single-center experience
Bibliographic record
Abstract
INTRODUCTION: Despite increasing consumption rates in much of the world, the impact of cannabis use on various components of male sexual function remains poorly established. The purpose of this study was to further evaluate the relationship between cannabis use and reproductive and sexual function using a large patient cohort from a single academic andrology clinic. METHODS: This is a historical cohort study from a single academic center andrology clinic. Patients from 2008-2017 were included. Intake questionnaires provided baseline demographic information, as well as data regarding substance use and various sexual function parameters. Subjects were categorized as cannabis users or non-users. Cannabis users and non-users were compared using descriptive statistics and Chi-squared tests, and regression analyses were performed to test for association. RESULTS: A total of 7809 males were included in the study; 993 (12.7%) were cannabis users and 6816 (87.3%) were non-users. Cannabis users had a higher mean Sexual Health Inventory for Men (SHIM) score (21.9±4.4 vs. 21.2±4.8, p<0.001) and mean serum total testosterone (13.4±12.0 nmol/L vs. 12.6±11.8 nmol/L, p=0.04) than non-users, although they also had a higher rate of positive Androgen Deficiency in the Aging Male (ADAM) scores (52% vs. 46%, p<0.001). Cannabis users also reported higher sexual frequency compared to non-users (8.8 events/month vs. 7.8 events/month, p<0.05). On multivariate analysis, cannabis use was not associated with SHIM score or serum testosterone concentration. Cannabis use was associated with positive ADAM scores. CONCLUSIONS: Cannabis use was not associated with clinically significant deleterious effects on male sexual parameters in this cohort.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".