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Record W1986715673 · doi:10.1310/enmx-ruv5-15wl-vna2

Urinary Incontinence After Stroke: Does Rehabilitation Make a Difference? A Systematic Review of the Effectiveness of Behavioral Therapy

2005· review· en· W1986715673 on OpenAlexafffund
Chantale Dumoulin, Nicol Korner‐Bitensky, Cara Tannenbaum

Bibliographic record

VenueTopics in Stroke Rehabilitation · 2005
Typereview
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsMcGill UniversityUniversité de MontréalMcGill University Health CentreCentre for Interdisciplinary Research in Rehabilitation
FundersCanadian Stroke NetworkCentre for Interdisciplinary Research in RehabilitationU.S. Department of Defense
KeywordsMedicineUrinary incontinencePhysical therapyRehabilitationStroke (engine)Randomized controlled trialPhysical medicine and rehabilitationEvidence-based practiceAlternative medicineSurgery

Abstract

fetched live from OpenAlex

This study uses a comprehensive review of the literature to assess the scientific evidence for the effectiveness of behavioral therapies to treat urinary incontinence (UI) post stroke. Evidence for the different behavioral therapies was critically appraised to achieve a level of evidence based on Foley's classification of levels of evidence. Only four randomized clinical trials (RCTs), one cohort study, and recommendations from three clinical practice guidelines were found. There is limited evidence that bladder retraining with urge suppression in combination with pelvic floor exercises results in reduction of UI in male individuals with stroke. Further research is urgently needed to elucidate clinical recommendations about the efficacy of behavioral approaches.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.036
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.005
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.338
Teacher spread0.321 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations45
Published2005
Admission routes2
Has abstractyes

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