The role of urgency, frequency, and nocturia in defining overactive bladder adaptive behavior
Bibliographic record
Abstract
AIM: To determine the relation between urgency alone, or in combination with frequency and nocturia, and adaptive behavior in overactive bladder (OAB) syndrome. METHODS: We used survey data from the General Longitudinal Overactive Bladder Evaluation (GLOBE) of primary care patients over 40. Participants (n=2,752: 1,557 females; 1,195 males) completed the same survey at two time points, 6 months apart. Questions assessed OAB symptoms and adaptive behavior. We estimated correlation coefficients (R(2)) between urgency, frequency, and nocturia symptom scores (alone and in combination) and adaptive behavior measures at baseline and change in symptom scores and behavioral measures from baseline to 6 months. RESULTS: At baseline, urgency was the dominant predictor of all behavioral measures for females (R(2)=0.19-0.48) and males (R(2)=0.15-0.39). Lower R(2) values were observed for the change in measures from baseline to 6 months, but again change in urgency was the strongest predictor of change in adaptive behavior (R(2)=0.04-0.13 in females, and 0.02-0.08 in males). The correlation between symptoms and measures of adaptive behavior was almost completely explained by the urgency score. Frequency and nocturia did not substantially improve the overall correlation. CONCLUSION: The relation between measures of OAB symptoms and adaptive behavior at baseline and over time are largely explained by urgency, not by frequency and nocturia.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".