Suboptimal response to GnRH-agonist trigger during oocyte cryopreservation: a case series
Bibliographic record
Abstract
BACKGROUND: Random-start, controlled ovarian stimulation (COS) has advanced the field of fertility preservation, allowing patients to expedite fertility treatment and avoid further delays to their cancer therapy. This novel approach allows patients to initiate ovarian stimulation at any point, regardless of where they are in their menstrual cycle. Luteal-phase start (LPS) protocols describe treatment cycles where COS is initiated during the luteal-phase of the menstrual cycle. LPS protocols have not been studied or optimized to the same degree as conventional, early-follicular COS. Particularly, there is a paucity of evidence evaluating treatment outcomes using different trigger medications in LPS protocols. The present study aims to evaluate the efficacy of using a GnRH agonist (GnRH-a) trigger in patients undergoing oocyte cryopreservation in LPS protocols. METHODS: This descriptive case series describes two patients, recently diagnosed with cancer, who underwent oocyte cryopreservation using an LPS protocol and a GnRH-a trigger at a university-affiliated, academic center. RESULTS: The patients described in our case series both failed to adequately respond to a GnRH-a trigger, based on their serum levels of luteinizing hormone (LH) and progesterone 12 h after their GnRH-a trigger. They both required a single rescue dose of human chorionic gonadotropin (hCG). CONCLUSIONS: These findings highlight the potential risk of a suboptimal response to a GnRH-a trigger in patients undergoing LPS, controlled ovarian stimulation for oocyte cryopreservation. This risk might be attributed to the downregulation of GnRH receptors by elevated serum progesterone levels during the luteal phase. Currently, there is insufficient evidence to recommend for or against the use of a GnRH-a trigger during LPS controlled ovarian stimulation. This case series offers a number of management strategies to mitigate this risk and emphasizes the need for further research in this area.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".