Timing of testosterone discontinuation and assisted reproductive technology outcomes in transgender patients: a cohort study
Bibliographic record
Abstract
Objective: To determine if there is an association between the timing of testosterone discontinuation and assisted reproductive technology (ART) outcomes. Design: Retrospectivse cohort study. Setting: Single academic center. Patients: We included consecutive transgender patients seeking fertility preservation between October 2019 and April 2021. Patients who identified as transgender on androgens for >1 month on presentation were included. Interventions: None. Main outcome measures: A linear regression model was used to evaluate the effect of testosterone discontinuation duration on the number of mature oocytes retrieved. Results: , mean antimüllerian hormone 27.2 [SD 11.8], median antral follicle count 20 [interquartile range (IQR) 14-32]) were included in the analysis. No patient underwent transition-related surgery (eg, oophorectomy, hysterectomy). None of the patients were previously pregnant. Mean time o,n testosterone was 44 (SD 29.6) months. The median time off testosterone until the start of ovarian stimulation was 7.7 weeks (IQR 4.3-20.7). All patients underwent oocyte cryopreservation except one who had embryo cryopreservation. The median total number of oocytes was 11 (IQR 7-14). The median number of mature oocytes was 7.5 (IQR 5-12) oocytes. The univariate regression model evaluating the duration of time off testosterone before ART demonstrated no significant association with the outcome of mature oocytes (regression coefficient, 0.19; 95% confidence interval, -0.13 to 0.50). Conclusion: In a retrospective analysis of transgender patients recently on testosterone undergoing ART, no association was detected between the timing of testosterone cessation and the number of mature oocytes.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".