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Record W3108689923 · doi:10.1097/mou.0000000000000837

Robot-assisted artificial urinary sphincter implantation

2020· review· en· W3108689923 on OpenAlexaff
B. Peyronnet, Gary R. Gray, G. Capon, Jean‐Nicolas Cornu, Frank Van der Aa

Bibliographic record

VenueCurrent Opinion in Urology · 2020
Typereview
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsArtificial urinary sphincterMedicineUrinary incontinenceNeck of urinary bladderCuffPerioperativeSurgeryRobotic surgerySphincterUrinary bladder

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.146
GPT teacher head0.418
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations14
Published2020
Admission routes1
Has abstractyes

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