Techniques – Robotic-assisted laparoscopic implantation of artificial urinary sphincter with concomitant hysterectomy and sacrocolpopexy
Bibliographic record
Abstract
The artificial urinary sphincter (AUS) was first described by Foley in 1943.1 The current generation model of AMS 800 (American Medical Systems, MN, U.S.) has been implanted since 1982. Indications for implantation of an AUS include post-prostatectomy incontinence, neurogenic bladder dysfunction, intrinsic sphincter deficiency (ISD), and rare congenital causes of incontinence.2 When looking specifically at female non-neurogenic stress urinary incontinence, recent studies demonstrate good long-term functional outcomes from the abdominal approach, with success rates of up to 94.4%.3 Recent advances in minimally invasive surgery have mitigated the risks of abdominal surgery, with the first laparoscopic implantation of AUS published in 2005.4 The introduction of robotic-assisted laparoscopic (RAL) surgery brings distinct benefits of superior visualization, improved dexterity, and minimization of blood loss during deep pelvic dissection.5 Hence, we set out to evaluate the role of robotic assistance in AUS implantation in a neurogenic bladder patient with concomitant surgery for pelvic organ prolapse (POP).
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".