Restoration of Ovarian Function After Orthotopic Ovarian Autotransplant and Follow-Up: A Case Report
Bibliographic record
Abstract
A 40-year-old married nulliparous female diagnosed with breast cancer was referred for fertility preservation before initiation of chemotherapy. Various options were discussed and she decided for ovarian tissue cryopreservation to avoid delay in treatment for cancer. She underwent laparoscopic left oophorectomy and the retrieved ovarian cortex was cryopreserved in liquid nitrogen. Two months after initiation of chemotherapy, her menses stopped and she started experiencing hot flushes leading to a diagnosis of premature menopause based on her hormone levels. Two years later after being certified free of malignancy, she underwent orthotopic transplant of the cryopreserved ovarian tissue into the other ovary and ovarian fossa. She resumed menstruation 3 months later and her hormone analysis showed a significant drop in follicle-stimulating hormone levels and luteinizing hormone levels and rise in estrogen levels. At this point of time, she lost interest in fertility and declined in vitro fertilization. On regular follow-up to assess her ovarian function, she reported regular monthly menses for 2 years which then started becoming irregular and less frequent. During her recent review 4 years after the transplant, her menses is less frequent once in 2 - 3 months with light flow but free of menopausal symptoms. Ovarian cryopreservation and autotransplant is usually done to restore fertility in women undergoing gonadotoxic treatment. This case shows that this procedure can also be considered for women who wish to restore hormonal function thereby alleviating menopausal symptoms and improving bone and cardiovascular health even though such benefits are yet to be proven scientifically. Careful selection of cases and adequate counselling regarding the benefits, risks, cost of the procedure, uncertainty of duration of ovarian function and multidisciplinary approach are important to optimize outcome in such patients. J Med Cases. 2017;8(1):14-16 doi: https://doi.org/10.14740/jmc2701w
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| 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".