Effectiveness of intraoperative ultrasound in reducing recurrent fibroids during laparoscopic myomectomy.
Bibliographic record
Abstract
OBJECTIVE: To detect and study residual fibroids, their recurrence after laparoscopic myomectomy (LM) and the risk factors. STUDY DESIGN: A prospective analysis (Canadian Task Force classification II-1) was conducted at a university-affiliated hospital. A total of 42 patients who underwent LM underwent contact ultrasonography (CUS) and transvaginal ultrasonography (TVUS) to detect residual fibroids. After LM, additional enucleation guided by CUS was performed, and then the final residual fibroids were detected using TVUS. The frequency of postoperative residual fibroids and their characteristics were evaluated. All cases were followed for > 6 months postoperatively to assess recurrence. RESULTS: The total number of fibroids enucleated in the initial enucleation was 201, or 4.8 per patient. Median diameter of the largest fibroids for each patient was 60 mm. There were 25 additional fibroids enucleated with CUS guidance. Their median diameter was 12.1 mm. After the additional enucleation, 33 final residual fibroids were identified by TVUS. Their median diameter was 9.0 mm, which was significantly smaller than those of the additionally enucleated fibroids (p = 0.002). The frequency of patients with residual fibroids was calculated in relation to the number of enucleated fibroids. The results showed that the frequency tended to increase as the number of fibroids increased and that almost all the patients (7 of 8 cases, 87.5%) with > or = 10 fibroids had residual ones. The median follow-up period was 31 months (range, 6-37), and 8 cases (19.0%) had recurrent fibroids. The recurrence rate in patients with > or = 10 fibroids was 50%. CONCLUSION: Intraoperative CUS was useful in detecting and enucleating residualfibroids. As the number of enucleated fibroids increased, the risk of residual fibroids and recurrence tended to increase.
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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 | 0.003 |
| 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) | 0.000 | 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".