Fertility journey of a patient with McCune-Albright syndrome associated with bilateral ovarian involvement
Bibliographic record
Abstract
Objective: To report a patient with McCune-Albright syndrome (MAS) with bilateral ovarian involvement who had achieved a pregnancy through in vitro fertilization (IVF). Design: Case report. Setting: Academic fertility center. Patients: A 33-year-old female with McCune-Albright syndrome who presented with primary infertility because of ovulatory dysfunction secondary to excessive secretion of growth hormone in addition to autonomous estrogen secretion by her ovaries. Exposure: In vitro fertilization and near-normalization of insulin-like growth factor-1 (IGF-1) using somatostatin analogue lanreotide. Main Outcome Measures: Reproductive outcomes after medical treatment for MAS-associated anovulatory infertility involving bilateral MAS ovarian involvement and growth hormone excess. Results: Spontaneous ovulation was resumed in this patient using lanreotide which regulated IGF-1 levels after unsuccessful ovulation induction with letrozole. Despite documented ovulation, she failed to conceive and subsequently, underwent an IVF cycle using an antagonist cycle with recombinant follicular stimulating hormone and recombinant luteinizing hormone stimulation. A total of 13 oocytes were retrieved and three good quality blastocysts were cryopreserved. Two frozen embryo transfer cycles were completed and she achieved a pregnancy, which unfortunately ended in an incomplete miscarriage. Conclusions: Through IVF and near-normalization of IGF-1 using lanreotide, pregnancy was achieved in a patient with MAS who had achieved good ovarian stimulation despite a history of bilateral ovarian involvement and associated hyperfunctioning endocrinopathies.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".