Non-ART Treatment of Unexplained Infertility - Waiting, Tubal Flushing, Ovulation Assisting Agents?
Bibliographic record
Abstract
Unexplained infertility is a common diagnosis affecting 20-25% of couples seeking infertility care. Till now, treatment of unexplained infertility remains empirical as no treatable cause of is identified. Interestingly the word “Unexplained Infertility” is used where physicians failed to come into conclusion to a diagnosis or failed to identify a detectable cause for couple’s infertility. There are many reasons why the diagnosis of infertility with detectable causes are difficult. It is not taken for granted that even in a well-documented diagnosis, that cause could be the sole reason of infertility. There is high observer to observer variations in the interpretation of diagnostic findings, sometimes diagnosis of endometriosis is missed and that couple is labelled as unexplained infertility. Unexplained infertility is inevitably diagnosed by exclusion after routine standard investigations. Unfortunately, a real standardization of the diagnostic workup is still missing. Management of unexplained infertility is basically empirical as far as the efficacies, safety, cost, and risks of each treatment option regards. The main problem of treating this couple is disagreement of physicians on the management plan. Failure in implementation of standard practice for treatment leads to over treatment in most of the cases. This practice is mainly accompanied with misdiagnosis of eligible cases of expected management. Existing guideline for Unexplained Infertility were released from Canadian Fertility and Andrology Society in 2019 and from ASRM in 2022. Based on these comprehensive guidelines, ESHRE special interest group (SIG) –Reproductive Endocrinology initiated the development of an ESHRE guideline focusing on the diagnosis and therapeutic management of couples with unexplained infertility. My presentation will be based on the non-ART management of unexplained infertility both expectant and active.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".