Intrauterine adhesions after abdominal myomectomy: A systematic review
Bibliographic record
Abstract
BACKGROUND: Abdominal myomectomy is associated with postoperative intrauterine adhesions, which can affect a patient's fertility. AIM: To evaluate the incidence and possible risk factors of intrauterine adhesions after abdominal myomectomy. METHODS: A systematic search of PubMed, Embase and Web of Science was undertaken for cohort studies published in peer-reviewed journals up to 19 June 2023. The studies were assessed using the Newcastle-Ottawa scale. RESULTS: Eleven eligible studies were found. The frequency of postoperative intrauterine adhesions ranged from 1 % to 50 %. Due to the substantial clinical heterogeneity in these studies, a meta-analysis was not feasible. Intrauterine adhesions were seen in 98 of 758 patients overall [12.9 %, 95 % confidence interval (CI) 10.6-15.5]: 9.4 % (95 % CI 6.3-13.5) after minimally invasive surgery and 23.0 % (95 % CI 18.2-28.6) after open abdominal surgery. The adhesions were classified as severe in 34.6 % of cases. Only two studies found correlation between intrauterine adhesions and cavity breach, while four studies could not confirm an association. Fibroid features, such as size, number and submucous type, were found to be a risk factor in three studies. No other unanimous risk factors were identified. CONCLUSION: Abdominal myomectomy is associated with intrauterine adhesions. The incidence is probably underestimated and unpredictable, and may be an indication for follow-up hysteroscopy. Further studies are needed to evaluate the incidence, severity and risk factors for intrauterine adhesions after abdominal myomectomy.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".