Robot-assisted artificial urinary sphincter implantation
Bibliographic record
Abstract
PURPOSE OF REVIEW: The aim of the present manuscript was to provide an overview on the current state of robotic artificial urinary sphincter (AUS) implantation in male and female patients. RECENT FINDINGS: Over the past few years, several series have been reported, with promising outcomes for the most part. This has contributed to expand the use of bladder neck AUS, especially in female patients, which was, until then, hampered by its perioperative morbidity. SUMMARY: Robotic AUS has been developed to overcome the technical challenge of bladder neck implantation in female patients and in specific male subgroups, especially self-catheterizing neurological patients. All the series of robotic AUS implantation published in the past few years reported much lower rates of cuff erosion and AUS explantation than the historical open cohorts suggesting that the robotic approach might become the standard for female AUS implantation. This less morbid approach along with technological improvement of the AUS device may contribute to make it a more popular option in the treatment of female stress urinary incontinence due to intrinsic sphincter deficiency. There are much less data available on robotic bladder neck AUS implantation in male 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".