Microlaparoscopic-assisted vaginal hysterectomy in the morbidly obese patient.
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to demonstrate a minimally invasive, novel variation, microlaparoscopic-assisted vaginal hysterectomy (MAVH) of a previously established technique, laparoscopic-assisted vaginal hysterectomy (LAVH), in the morbidly obese patient. METHODS: This was a prospective, descriptive feasibility study (Canadian Task Force classification 11-2) conducted at a university-affiliated hospital and private community hospital. Seven morbidly obese women with an average body mass index of 45.8 kg/m2 (range, 40.6 to 51.5) underwent microlaparoscopic-assisted vaginal hysterectomy (MAVH). Microlaparoscopic-assisted vaginal hysterectomy (MAVH), classified as Type 1B, including unilateral or bilateral occlusion and division of the ovarian artery(ies), either medial or lateral to the ovary(ies), with or without dissection of the adjacent broad ligament under microlaparoscopic guidance, in addition to incision of the vesicouterine peritoneum. RESULTS: The median duration of surgery was 109.1 minutes (range, 86 to 134), median blood loss was 207 mL (range, 100 to 350), and average length of stay in the hospital was 33.7 hours (range, 23 to 48). The complication rate was 0%. CONCLUSION: Microlaparoscopic-assisted vaginal hysterectomy (MAVH) is a safe and effective, more minimally invasive method of performing laparoscopic hysterectomies in select morbidly obese patients.
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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 | 0.001 |
| 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) | 0.001 | 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".