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Pelvic Floor Muscle Training With Biofeedback and Bladder Training in Elderly Women

2005· article· en· W1968384368 on OpenAlexaff
Louise Perrin, Sharon Wood Dauphinée, Jacques Corcos, James A. Hanley, George A. Kuchel

Bibliographic record

VenueJournal of Wound Ostomy and Continence Nursing · 2005
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsBiofeedbackTraining (meteorology)Pelvic Floor MusclePelvic floorMedicinePhysical therapyPhysical medicine and rehabilitationSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: It is generally assumed that interventions used to treat urinary incontinence (UI) in young women could simply be applied to older competent and motivated women, but these assumptions have not been formally tested. The purpose of this study was to determine the feasibility of using physical therapies to treat UI in older women. DESIGN: Twelve-week time series. SETTINGS AND SUBJECTS: We recruited women older than 75 years with UI from an outpatient urology clinic and a waiting list for incontinence surgery. METHODS: After a baseline evaluation, the women collected data on their incontinence symptoms and bladder habits for 3 weeks using the 72-hour voiding diary and the 24-hour pad test. They then received 6 physical therapy treatments consisting of a combination of bladder training and pelvic floor muscle training assisted with biofeedback for 6 weeks. This was followed by another 3-week period of data collection and a final evaluation. RESULTS: Ten women participated in the study; 7 completed it. They were all comfortable with the treatment. They complied with the study demands in terms of attendance at treatment session (100%), data collection (96%), and completion of exercises at home (82%). The authors observed a decrease in the number of incontinent and urgency episodes. CONCLUSION: This preliminary study demonstrates that some women older than 75 years are good candidates to undertake physical therapies for UI and follow study demands. Random controlled studies that include this population will provide evidence regarding the effectiveness of these therapies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.016
GPT teacher head0.260
Teacher spread0.245 · 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
GenreEmpirical

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

Citations25
Published2005
Admission routes1
Has abstractyes

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