Bibliographic record
Abstract
Overactive bladder (OAB) is a symptom-based syndrome characterized by the presence of urgency, which is defined as a sudden and compelling desire to void that cannot be postponed. OAB may significantly impact of quality of life. Numerous treatment options exist for OAB, including behavioral therapies such as pelvic floor muscle rehabilitation, bladder training, and dietary modification, as well as traditional therapies such as pharmacological therapy and neuromodulation. Behavioral therapies are considered the mainstay of treatment for urinary incontinence in general. However the efficacy of these noninvasive strategies for OAB treatment has not been well addressed in the literature. This article presents an overview of current evidence with attention to the clinical relevance of findings related to lifestyle modification, bladder training, and pelvic floor muscle training. Initial evidence suggests that obesity, smoking, and consumption of carbonated drinks are risk factors for OAB but there is less support for the contributory role of caffeine or the impact of caffeine reduction. The evidence supporting bladder training and pelvic floor muscle training is more consistent and a trend towards combining these therapies to treat OAB appears positive. Given the prevalence of OAB and growing support for the efficacy of behavioral treatments it is important and timely to augment existing evidence with well-designed multicenter trials.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".