Cocaine Use in the Infertile Male Population: A Marker for Conditions Resulting in Subfertility
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: We sought to evaluate the incidence and effect of cocaine use in the infertile male population. MATERIALS AND METHODS: Men presenting for fertility evaluation reporting cocaine usage were identified via prospectively collected database. Data were analyzed for usage patterns, reproductive history, associated drug use and medical conditions, hormonal and semen parameters. RESULTS: Thirty-eight out of 4,400 (0.9%) men reported cocaine use. Most used cocaine every 3 months or less. Compared with non-cocaine using men, cocaine users reported more recreational drug use (89 vs. 9.2%), marijuana use (78.9 vs. 11.4%), chlamydia (10.5 vs. 3%), herpes (7.9 vs. 2.5%), and tobacco use (55.3 vs. 19.5%). After excluding men with causes for azoospermia, the mean semen parameters for cocaine users were: volume 2.47 ± 1.02 ml; concentration 53.55 ± 84.04 × 10(6)/ml; motility 15.72 ± 12.26%; total motile sperm count 76.67 ± 180.30 × 10(6). CONCLUSIONS: Few (< 1%) men in our infertile population reported the use of cocaine, and the frequency of use was low. Given the low use rates and limitations of reporting bias, it is difficult to determine the direct effect of cocaine use on male fertility. However, while infrequent cocaine use seems to have limited impact on semen parameters, men reporting cocaine use represent a different cohort of men than the overall infertile population, with higher rates of concurrent substance abuse, tobacco use and infections, all of which may negatively impact their fertility. Reported cocaine users should be screened for concurrent drug use and infections.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it