OnabotulinumtoxinA for the treatment of idiopathic overactive bladder is effective and safe for repeated use
Bibliographic record
Abstract
INTRODUCTION: The objective of this study was to compare efficacy and safety outcomes between patients receiving onabotulinum-toxinA (OnabotA) for the first time and those receiving a repeat injection. METHODS: Data collected before and after OnabotA injection were extracted from a clinical registry. Patients were classified into either first or repeat injection subgroups. Efficacy was measured by the change in use of oral bladder medications, the number of voids per day or night, the frequency of urinary incontinence (UI) episodes, and patient-reported outcomes. Safety was measured by the number of self-reported complications. Differences in safety measures between the subgroups were tested. RESULTS: The analysis included complete data from 81 patients; 30 (37%) receiving OnabotA for the first time, 51 (63%) receiving a repeat injection. Both subgroups reported significant reductions in the use of anticholinergics, more tolerable bladder symptoms, and improvements in patient-reported outcomes. Dry rates were similarly high in both groups (50% and 43%, respectively). There were no statistically significant differences between the subgroups in terms of their safety outcomes. CONCLUSIONS: OnabotA is equally as efficacious and safe for patients with overactive bladder receiving a repeat injection as it is for those receiving their first injection.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".