Prevention of multiple pregnancies in gonadotropin-insemination cycles
Bibliographic record
Abstract
PURPOSE OF REVIEW: Although elective single embryo transfer has significantly reduced, the rate of multiple pregnancy in IVF cycles, this rate is still relatively high in gonadotropin-insemination cycles. Patients who fail to ovulate or to conceive with oral agents and have constraints for IVF are usually candidates for gonadotropin injections. The current review article provides an up-to-date summation of the different strategies that can be adopted to reduce the risk of multiple pregnancies in gonadotropin-stimulated intrauterine insemination cycles. RECENT FINDINGS: Gonadotropin-insemination treatments should be used judiciously by experienced providers. One should always start with the lowest effective gonadotropin dose (∼37.5 IU), monitor closely the ovarian response, and consider cycle cancellation or conversion to IVF whenever a high response is encountered. Therefore, every infertility practice should define its own cancellation and 'rescue IVF' criteria depending on the number of mature ovarian follicles and the age of the female partner. SUMMARY: These preventive measures amongst others should mitigate the risk of multiple pregnancies that can arise from gonadotropin-insemination cycles.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.004 | 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".