Effect of high LH/FSH ratio on women with polycystic ovary syndrome undergoing in vitro maturation treatment.
Bibliographic record
Abstract
OBJECTIVE: To determine whether high luteinizing hormone/follicle-stimulating hormone (LH/FSH) ratios have a clinical impact on women with polycystic ovary syndrome (PCOS) undergoing in vitro maturation (IVM) treatment. STUDY DESIGN: Women with PCOS who underwent IVM treatment were divided into those with LH/FSH ratio > 1.5 and LH/FSH 0.5-1.5. We analyzed baseline characteristics of the patients, number of oocytes retrieved, number of mature oocytes, and pregnancy rates. RESULTS: Women with LH/FSH ratio of > 1.5 had higher basal serum testosterone (2.2 vs. 1.4, p < 0.005, CI 0.1-1.0) and estradiol (188.7 +/- 16.2 vs. 143.7 +/- 6.9, p < 0.01, CI 23-96). The antral follicle count (AFC) was also higher in the patients with high LH/FSH (46.2 +/- 3.5 vs. 32.9 +/- 1.3, p < 0.001, CI 7-21). The total number of retrieved oocytes and number of mature oocytes was also significantly higher in women with LH/FSH ratio of > 1.5 than in those with a lower ratio. However, the pregnancy rate in women with LH/FSH ratio of > 1.5 (16.7%) was significantly lower than in those with a ratio of 0.5-1.5 (40.4%), p < 0.05, odds ratio 0.32. CONCLUSION: PCOS patients with LH/FSH ratio of > 1.5 had higher basal testosterone, E2, and AFC but decreased pregnancy rate. This could be due to the deleterious effect of LH on folliculogenesis and endometrial receptivity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".