Factors Affecting Conversion of Laparoscopic Myomectomy to Laparotomy
Bibliographic record
Abstract
Objectives: The purpose of our study was to evaluate cases that required conversion to laparotomy and its predisposing factors. Design: This was a retrospective study. Methods: We examined the medical records of women who underwent laparoscopic myomectomy during the period 2000–2008. Results: Of 67 patients, 9 required conversion of laparoscopy to laparotomy (conversion rate of 13.4%). The median diameter of the dominant myoma in the conversion group (group I) was 9 cm (range 6–17 cm) and in the laparoscopic myomectomy group (group II was 7.4 cm [range 4–21 cm; p: 0.03, CI 0–4.5]). Group I had more intramural myoma (n = 8; 88.9%) than group II (n = 28, 48.3%; p < 0.03), and two thirds of patients in group I had had posterior intramural myoma. Preoperative gonadotropin-releasing hormone analog (GnRHa) was used by all patients in group I and by 67.2% of patients in group II. There was no difference in the blood loss between both groups. The weight of myomas in group I (387.1 ± 86.0 g) was higher than in group II (196.7 ± 33.9 g, p < 0.04). Conclusions: Factors related to conversion of laparoscopic myomectomy to laparotomy are posterior intramural location, the use of preoperative GnRHa, the diameter of the dominant myoma, and the weight of the myoma. (J GYNECOL SURG 26:115)
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".