Non-Invasive Isthmocele Treatment: A New Therapeutic Option During Assisted Reproductive Technology Cycles?
Bibliographic record
Abstract
Background: The objective of the study was to evaluate a new medical treatment strategy for infertile patients with isthmocele. Methods: This was a retrospective evaluation of the records of infertile patients with symptomatic isthmocele who received non-invasive isthmocele treatment (NIIT) before in vitro fertilization (IVF) treatment cycles. Isthmocele volumes were measured before and after NIIT. The IVF results and isthmocele-related complaints were also analyzed. The patients were treated with a depot gonadotropin-releasing hormone agonist for 3 months before frozen-thawed embryo transfer cycles. Results: The mean isthmocele volume was 471.06 ± 182.81 mm 3 (range: 289.43 - 765.4 mm 3 ) in fresh cycles, but was reduced to 47.94 ± 29.48 mm 3 (range: 18.70 - 105.6 mm 3 ) in frozen-thawed cycles (P < 0.05). Intrauterine fluid was observed in two patients during fresh cycles, but was absent after NIIT during frozen-thawed cycles. There was no brown bloody discharge on the tip of the embryo transfer catheter in any case after NIIT. Two patients became pregnant and underwent term cesarean delivery (25%). Conclusions: NIIT can serve as an alternative pretreatment option for patients with isthmocele during IVF cycles. J Clin Med Res. 2020;12(5):307-314 doi: https://doi.org/10.14740/jocmr4140
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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 | 0.001 |
| 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".