A Gender-Affirming Approach to Fertility Care for Transgender and Gender-Diverse Patients
Bibliographic record
Abstract
Although many transgender and gender-diverse (TGD) people express a desire to become parents, providing quality counseling that encompasses patients' short-term and long-term fertility options often represents a challenge for health care professionals. Fertility care (from preservation to restoration or assisted reproduction or both) has a low uptake in the TGD population, with barriers including financial cost, concerns regarding health care professionals' biases, and patient misconceptions or lack of awareness of fertility outcomes. Fertility care is particularly important for the TGD population, because gender-affirming hormone therapy can negatively affect fertility. Despite this importance, existing guidelines and research on this subject are limited. This article summarizes the currently available fertility care options for TGD patients and provides our clinical opinion on their best provision. We highlight that it is essential for health care professionals to provide TGD patients with holistic counseling to facilitate informed decision making about their reproductive health before initiating gender-affirming therapy. Fertility counseling should outline the options available for the patient, keeping their needs and preferences at the center of the conversation while advising on the associated risks and financial costs.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".