The use of aromatase inhibitors for ovulation induction
Bibliographic record
Abstract
PURPOSE OF REVIEW: Approximately 15% of the infertile population faces an ovulatory disorder; most of them classified as WHO class two anovulation [polycystic ovarian syndrome (PCOS) prototype]. Worldwide, this translates into millions of patients and emphasizes the need of a simple, effective and well tolerated method of ovulation induction. In this review, we will revisit letrozole use in the subset of WHO class two ovulatory problems and evaluate the contribution of the last year's literature to its practice. RECENT FINDINGS: In a multicentre, randomized controlled trial comparing letrozole with clomiphene in 750 PCOS patients having regular intercourse, live birth rates were significantly higher for the letrozole group [rate ratio 1.44, 95% confidence interval (95% CI) 1.10-1.87]. In a meta-analysis summarizing clinical trials testing aromatase inhibitors used alone or with other medical therapies for ovulation induction in PCOS patients, live birth rates were again significantly higher when letrozole was compared with clomiphene citrate [odds ratio (OR) 1.64, 95% CI 1.32-2.04]. A retrospective analysis of children born to infertile women assessed the congenital malformation rate after exposure to letrozole in comparison to clomiphene citrate and to natural conceptions. No significant differences in malformation rates were detected between the groups (2.9, 2.5 and 3.9%, respectively). SUMMARY: High-level evidence supports letrozole as the first drug of choice for ovulation induction in the PCOS population. The increasing use of letrozole with pregnancy follow-up provides additional reassurance for foetal safety.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".