Laparoendoscopic Single-Site Surgery: Scarless Stitchless Hysterectomy
Bibliographic record
Abstract
Background: Hysterectomy is the most common gynecologic surgery. Approximately 600,000 hysterectomies are performed annually in the United States. Hysterectomy has increasingly been performed using minimally invasive approaches, which offer advantages, such as early recovery and return to routine activities, improved cosmesis, shorter length of hospital stay, and reduced pain, compared with laparotomy. Conventional laparoscopic hysterectomy consists of 3–4 incisions where separate ports are placed, one for laparoscope access and 2–3 for surgical instruments' access. One technique for reducing the invasiveness of conventional laparoscopy is laparoendoscopic single-site surgery—scarless stitchless hysterectomy (LESS-SSH). The technique involves no stitching of the skin incision, although there are vaginal stitches, and does not create scars. Objective: The aim of this study was to evaluate the feasibility of LESS-SSH and analyze its benefits. Materials and Methods: This was a prospective observational study of women undergoing LESS-SSH (Canadian Task Force classification II-3) at a tertiary-referral private hospital. Twenty seven patients who required hysterectomy underwent LESS-SSH between February 2012 and February 2014 in this study. The selected patients tolerated the surgery well and were followed-up at 1 week and at 3 months. Results: The operative time (mean 62.04±11.29 minutes), intraoperative blood loss (mean 34.44±6.98 mL), recovery time, and surgical outcomes for LESS-SSH were similar to those of conventional laparoscopic hysterectomies. However, the patients who underwent LESS-SSH patients had reduced visual analogue scale (VAS) pain scores on the day of surgery and on postoperative day 1. No patients had scars that were readily apparent at surgery or at 1- or 3-week follow-ups. Conclusions: As surgeons gain experience in performing LESS-SSH, this technique could be an alternative to conventional laparoscopic hysterectomy in selected patients in the future. (J GYNECOL SURG 31:144)
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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) | 0.002 | 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".