Comparison of in vitro fertilization cycles stimulated with 20 mg letrozole daily versus high‐dose gonadotropins in Rotterdam Consensus ultra‐poor responders: A proof of concept
Bibliographic record
Abstract
OBJECTIVE: To evaluate if high-dose letrozole can be used successfully to stimulate poor responders for in vitro fertilization (IVF). METHODS: This was a retrospective study conducted at a university hospital reproductive center. The analysis included women who were up to 42 years of age and were Rotterdam Consensus poor responders. A total of 247 patients received gonadotropins (300-450 IU daily) and 62 patients were stimulated with letrozole (20 mg daily) as part of an antagonist IVF protocol. RESULTS: The use of 20 mg of letrozole decreased the total dose of gonadotropins used (645 ± 175 IU vs. 5360 ± 1028 IU, P = 0.001) and resulted in lower costs of stimulation medications ($ 555.56 ± $ 150 vs. $ 4616 ± $ 885 Canadian Dollars; P = 0.001). Pregnancy per cycle (14.5%) and per transfer (16%) rates were legitimate for this low prognosis group and may have been better than or similar to those with high-dose gonadotropins. The rate of cycle cancellation may have been reduced in the letrozole versus gonadotropin group (11% vs. 38%; P = 0.001). CONCLUSION: Letrozole (20 mg daily) may be used to reduce the cost of ovarian stimulation in ultra-poor responders, significantly reducing the cost of the IVF cycle with probably at least similar outcomes to high-dose gonadotropins.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".