Hysteroscopic Resection for Missed Abortion: Feasibility, Operative Technique and Potential Benefit Compared to Curettage
Bibliographic record
Abstract
Objective: To evaluate the feasibility of hysteroscopic resection (HsR) for primary surgical management of missed abortion. Reproductive outcomes and potential benefit of this technique will be compared to traditional dilatation and curettage (D&C). Design: Retrospective cohort study in two Departments (Gynecology and Obstetrics) of a tertiary medical care center (Canadian Task Force classification II-2). Patients: Women with first trimester missed abortion. Intervention: Two techniques were used for the management of missed abortion: ultrasound-guided dilatation and curettage (D&C) and hysteroscopic resection (HsR). Results: We evaluated 358 patients who underwent primary surgical removal of missed abortion. 173 patients have been treated by D&C and 185 underwent HsR. In the HsR group, 110 patients (59.5%) have obtained their pregnancy with in vitro fertilization (IVF) versus 7 patients (4.0%) in the D&C group which make the HsR population hypofertile in comparison to the D&C population. The intra- and post-operative complication rates are low and comparable. Intrauterine anomalies were diagnosed during the HsR in 10 patients (5.4%) and could be investigated after the intervention as a possible cause of miscarriage. Because of the difference in term of fertility, the reproductive outcomes have been analyzed by multivariate analysis. The hazard ratio of pregnancy at 6 months, adjusted to the factor IVF for D&C compared to HsR is 0.69 [0.49-0.96] (p=0.026). That could represent a significant benefit in the particular population followed in IVF, but regarding the retrospective analysis, and the very different population in the 2 groups, it doesn’t allow us to draw any evidence based conclusion. Conclusion: Hysteroscopic resection is a feasible and safe procedure for the management of missed abortion that could increase the diagnosis of uterine abnormalities. With all the limitation of the design of our study, our data seems to show a trend to a potential benefit in term of reproductive outcomes for hypofertile patient undergoing IVF treatment.
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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 | 0.008 |
| 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 | 0.000 | 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".