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Record W2026083305 · doi:10.1136/ebn.12.4.110

A behavioural weight-loss programme reduced urinary incontinence more than an education programme in overweight and obese womenCommentary

2009· letter· en· W2026083305 on OpenAlexaff
Jennifer Skelly

Bibliographic record

VenueEvidence-Based Nursing · 2009
Typeletter
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineOverweightUrinary incontinenceWeight lossBlindingBody mass indexPhysical therapyObesityRandomized controlled trialInternal medicineSurgery

Abstract

fetched live from OpenAlex

In overweight and obese women, does a behavioural weight-loss programme reduce incontinence more than an education programme? ### Design: randomised controlled trial (Program to Reduce Incontinence by Diet and Exercise [PRIDE]). ClinicalTrials.gov NCT00091988. ### Allocation: {concealed}.* ### Blinding: blinded (outcome assessors). ### Follow-up period: 6 months. ### Setting: Providence, Rhode Island and Birmingham, Alabama, USA. ### Patients: 338 women ⩾30 years of age (mean age 53 y) who had a body mass index of 25–50 and ⩾10 episodes of urinary incontinence over 1 week, monitored food intake and physical activity for 1 week, could walk unassisted for 2 blocks without stopping, and agreed to not begin new treatments for incontinence or weight reduction during the study. Exclusion criteria included use of medications for incontinence or weight loss in the past month, current urinary tract infection or ⩾4 in the past year, neurological or functional incontinence, …

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)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.042
GPT teacher head0.323
Teacher spread0.282 · 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 designNon-randomized trial
Domainnot available
GenreCommentary

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

Citations1
Published2009
Admission routes1
Has abstractyes

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