Ultrasound measurement of bladder wall thickness is associated with the overactive bladder syndrome
Bibliographic record
Abstract
AIMS: To assess the relationship between mean bladder wall thickness and components of the overactive bladder (OAB syndrome). METHODS: Women attending urogynaecology clinic was categorized into overactive bladder syndrome, stress urinary incontinence (SUI), and mixed urinary continence (MUI) according to International Continence Society (ICS) definitions based on symptom history. Women completed a bladder diary, visual analog score (VAS) for urgency, and the mean bladder wall thickness (BWT) was determined. Comparison was made between the mean BWT and symptom history, daytime frequency, nocturia, VAS scores. RESULTS: Three hundred seventy-nine women were recruited to the study with a mean age of 56 years (range: 24-92 years). The mean bladder wall thickness did not show any age-related difference. Of these women 138/379 (36%) reported overactive bladder symptoms (mean BWT = 5.6 mm) 75/379 (20%) gave a history of stress urinary incontinence (mean BWT = 4.7 mm), and 166/379 (44%) had mixed urinary incontinence (mean BWT = 5.4). Women with nocturia >1 had mean BWT 5.6 mm, with nocturia <1 a mean BWT 4.9 mm. Women with daytime frequency >7 had mean BWT 5.7 mm and those <7 had mean BWT 5.1 (P < 0.001). Women with a mean BWT of ≤5 mm had a mean VAS score lower than women with a BWT >5 mm (P < 0.001). CONCLUSIONS: Mean BWT is associated with a symptom history of OAB and MUI, higher daytime and nightime frequency, and higher VAS scores.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".