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Record W2152092971 · doi:10.3810/pgm.2012.05.2547

Stress Urinary Incontinence and Overactive Bladder Syndrome: Current Options and New Targets for Management

2012· review· en· W2152092971 on OpenAlexaff
Denise M. Elser

Bibliographic record

VenuePostgraduate Medicine · 2012
Typereview
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsMedicineUrinary incontinenceOveractive bladderAnticholinergicUrologyUrinary systemSurgeryInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

In the United States, office visits for women seeking treatment for urinary incontinence more than doubled between 1994 and 2000, from 1845 per 100 000 women. This review article addresses treatment options for 2 common types of incontinence in women: stress urinary incontinence (SUI) and detrusor overactivity (DO), commonly referred to as urge urinary incontinence (UUI). In the past, those with SUI typically faced limited treatment options, such as Kegel exercises, pessaries, or major surgery (Burch or Marshall-Marchetti-Krantz operations). However, treatment options for women also included anticholinergic medications, behavioral therapy, and implantable neuromodulation. In recent years, more options have become available. For women with SUI, a variety of minimally invasive synthetic midurethral sling approaches (eg, retropubic, transobturator, and single incision) and office-based procedures (eg, periurethral injection of bulking agents and radiofrequency collagen denaturation [Renessa®; Novasys Medical]) are now offered. More outpatient options will hopefully be available soon, including an inflatable, free-floating balloon to act as a shock absorber, and injection of muscle-derived stem cells into the periurethral tissue. Women with UUI now have targeted options, such as posterior tibial nerve stimulation (PTNS) and intravesical injections of onabotulinumtoxinA (Botox®; Allergan, Inc.), in addition to nonoral systemic medications.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.083
GPT teacher head0.370
Teacher spread0.288 · 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 designOther design
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

Citations9
Published2012
Admission routes1
Has abstractyes

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