Evaluation of Uterine Volume in Total Laparoscopic Hysterectomy for Uterine Leiomyomas
Bibliographic record
Abstract
Background: The aim of this retrospective study was to evaluate uterine volume in patients who underwent transabdominal hysterectomy (TAH) or total laparoscopic hysterectomy (TLH) for uterine leiomyomas in our teaching hospital and to determine the appropriate uterine volume in patients who could undergo TLH. Methods: This retrospective study was based on a cohort 47 consecutive cases that underwent TLH for uterine leiomyomas in our institution between April 2008 and April 2012 (TLH group). Controls were defined as 134 patients who underwent TAH for uterine leiomyomas in our institution between April 2008 and April 2012 (TAH group). Results: The TLH group comprised 45 cases because two surgeries in the TLH group were converted to TAH. Uterine volume was significantly smaller in the TLH group than in the TAH group (median 342 g vs. 788 g). Surgical duration was significantly longer in the TLH group than in the TAH group (median 214 minutes vs. 152 minutes). Blood loss was significantly lower in the TLH group than in the TAH group (median 0 mL vs. 250 mL). The incidence of postoperative complications was lower in the TLH group than in the TAH group (0/45 vs. 15/134). The hospital stay was significantly shorter for the TLH group than for the TAH group. In the TLH group, surgical duration correlated with uterine volume (regression coefficient = 1.6598, P = 0.0 014). Conclusion: There seems to be no limitation of uterine volume in TLH for uterine leiomyomas because TLH is safer than TAH except for the longer surgical duration. doi: http://dx.doi.org/10.4021/jcgo179w
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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 | 0.003 |
| 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) | 0.001 | 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".