Symptoms of urinary incontinence and pelvic organ prolapse and physical performance in middle-aged women from Northeast Brazil: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Reproductive history and urogynecological disorders have been associated with limitations in physical function. However, little is known about the relationship between symptoms of urinary incontinence and pelvic organ prolapse, and physical performance. Therefore, the purpose of this study was to examine whether symptoms of urinary incontinence and pelvic organ prolapse are independently associated factors with indicators of lower physical performance in middle-aged women from Northeast Brazil. METHODS: This is a cross-sectional study of 381 women between 40 to 65 years old living in Parnamirim, Northeast Brazil. Physical performance was assessed by gait speed, chair stand and standing balance tests. Urinary incontinence and pelvic organ prolapse were self-reported. Multiple linear regression analyses were performed to model the effect of self-reported urinary incontinence and pelvic organ prolapse on each physical performance measure, adjusted for covariates (age, family income, education, body mass index, parity). RESULTS: In the analysis adjusted for confounders, women reporting urinary incontinence spent, on average, half a second longer to perform the chair stand test (β = 0.505 95% CI: 0.034: 0.976). Those reporting pelvic organ prolapse shortened the balance time with eyes open by 2.5 s on average (β = - 2.556; CI: - 4.769: - 0.343). CONCLUSIONS: Symptoms of pelvic organ prolapse and urinary incontinence are associated to worse physical performance in middle-aged women. These seemingly small changes in physical performance levels are of clinical importance, since these conditions may influence women's physical ability, with implications for other tasks important to daily functioning and should be addressed by health policies targeting women's health and functionality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".