Uncontrolled diabetes may cause a transient decrease in ovarian reserve parameters to a suboptimal level: Recovery with optimized glycemic control – A case report
Bibliographic record
Abstract
In this case report, we review a patient in whom ovarian reserve parameters increased significantly following treatment of uncontrolled diabetes. The patient is a previously healthy, lean 29-year-old woman in a same-sex relationship who was seen at a fertility clinic interested in pursuing treatment with donor sperm. Baseline fertility investigations were completed to ascertain the patient's ovarian reserve and candidacy for intrauterine insemination versus in vitro fertilization. Baseline fertility investigations revealed diminished ovarian reserve putting her at risk for a suboptimal response, with anti-Müllerian hormone level 1.5 ng/mL and antral follicle count 14. Following two unsuccessful cycles of donor sperm intrauterine insemination, the patient presented to the emergency department in diabetic ketoacidosis with hemoglobin A1C 12.3% and random glucose 20.3 mmol/L. She was diagnosed with type 1 diabetes and treated with insulin lispro and bolus insulin. Hemoglobin A1C improved to 6.0% over several months. When she returned to the fertility clinic one year after initial presentation, anti-Müllerian hormone had increased to 7.0 ng/mL and antral follicle count to 44 when performed in the original laboratory and ultrasound unit. We surmise that uncontrolled diabetes may be a cause of spuriously decreased ovarian reserve parameters, which may improve with optimized glycemic control. Further studies are needed to confirm this finding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| 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".