Ultrasound Characterization of Disordered Antral Follicle Development in Women with Polycystic Ovary Syndrome
Bibliographic record
Abstract
CONTEXT: The mechanism of oligo-anovulation in polycystic ovary syndrome (PCOS) is unknown. OBJECTIVES: To evaluate follicular and endocrine characteristics of anovulatory and sporadic ovulatory cycles in women with PCOS. DESIGN: Prospective, longitudinal study. SETTING: Academic clinical research unit. PARTICIPANTS: 26 reproductive-aged women (18-38 years) with PCOS, observed during natural anovulatory (PCOS-Anov; n = 12) and sporadic ovulatory cycles (PCOS-Ov; n = 14), and 12 controls. INTERVENTIONS: Transvaginal ultrasonography and venipuncture were performed every other day for 4 to 6 weeks in women with PCOS or at 1 interovulatory interval in control subjects. MAIN OUTCOME MEASURES: Follicle number and diameter (ie, ≥2 mm) were quantified at each visit. Individual growth profiles were assessed for all follicles that grew to ≥7 mm. Blood samples were assayed for follicle-stimulating hormone, luteinizing hormone, estradiol, and progesterone. RESULTS: Follicular excess, or heightened follicle number versus controls, was observed across anovulatory and sporadic ovulatory cycles in PCOS. In PCOS-Anov, follicles emerged cyclically in some women (6/12; 50%) and continuously in others (6/12; 50%), then grew to a mean maximum diameter of 7.2 mm and regressed within 4.7 days. In PCOS-Ov, follicles mostly emerged cyclically as part of a cohort and dominant follicles showed normal growth to ovulation-albeit mean and maximum luteal progesterone concentrations were significantly lower versus controls. CONCLUSIONS: Follicle growth and regression were detected on ultrasonography amidst perpetual follicular excess in PCOS. Documentation of continuous follicle recruitment and turnover, the absence of persistence, and altered luteal progesterone following sporadic ovulation, provide formative data on antral follicle development in PCOS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".