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Record W2126316077 · doi:10.1353/cja.2005.0024

A 10-Year Follow-Up of Urinary and Fecal Incontinence among the Oldest Old in the Community: The Canadian Study of Health and Aging

2004· article· en· W2126316077 on OpenAlexaffabout
Truls Østbye, Arnfinn Seim, Katrina M. Krause, John Feightner, Vladimir Hachinski, Elizabeth A. Sykes, Steinar Hunskaar

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2004
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of OttawaWestern University
Fundersnot available
KeywordsFecal incontinenceUrinary incontinenceMedicineIncidence (geometry)Urinary systemEpidemiologyUrineInternal medicineUrologySurgery

Abstract

fetched live from OpenAlex

Urinary incontinence is common in the elderly. The epidemiology of fecal and double (urinary and fecal) incontinence is less known. The Canadian Study of Health and Aging (CSHA) is a national study of elderly living in the community at baseline (n = 8,949) and interviewed in 1991-1992, 1996, and 2001. Using data from the CSHA, we report the prevalence of urinary, fecal, and double incontinence in each wave and the cumulative incidence between waves and investigate the predictors of urinary and fecal incontinence. Urinary incontinence increased rapidly in old age, being almost twice as high in women as in men. Fecal and double incontinence were less common, but also increased rapidly with age. In women, parity showed a positive relationship with (prevalent) urinary incontinence. In men, diabetes was a risk factor for urinary and fecal incontinence. We conclude that urinary, fecal, and double incontinence increase rapidly with age and that inquiry about incontinence should be part of routine medical and nursing assessment of all elderly.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.243
Teacher spread0.226 · 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 designObservational
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

Citations46
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicPelvic floor disorders treatmentsFrench-language works237,207