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Record W2625190228 · doi:10.5489/cuaj.4584

The management of mixed urinary incontinence in women

2017· review· en· W2625190228 on OpenAlexaffvenue
Blayne Welk, Richard Baverstock

Bibliographic record

VenueCanadian Urological Association Journal · 2017
Typereview
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of CalgaryWestern University
Fundersnot available
KeywordsMedicineUrinary incontinenceStress incontinenceUrinary LeakageGynecologyPelvic Floor MusclePopulationPhysical therapyUrologyObstetrics

Abstract

fetched live from OpenAlex

Mixed urinary incontinence is a common diagnosis among women with urinary leakage and is often present in women who are unable to characterize their incontinence. Research and optimized clinical treatment of these patients is limited by the challenges in objectively defining and stratifying this population. The evaluation of these patients should follow the same general principles as any assessment of any women with incontinence; however, it is essential to define whether urge or stress incontinence is the predominant symptom. Urodynamics (UDS) may be helpful in this regard and may help predict surgical outcomes. Behavioural therapy, weight loss, and pelvic floor muscle therapy are usually appropriate initial management strategies. In postmenopausal women, vaginal estrogen can be considered, and in women with equal parts stress and urge incontinence or urge-predominant mixed incontinence, a trial of anticholinergics or beta-3 agonists is appropriate. In women with stress-predominant or equal parts stress and urge incontinence, stress incontinence surgery can be considered, with the caveat that outcomes are generally worse among women with more severe levels of urgency, success rates may not be as durable, and a significant proportion of women may need additional medical therapy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.035
GPT teacher head0.303
Teacher spread0.268 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations29
Published2017
Admission routes2
Has abstractyes

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