Bibliographic record
Abstract
Dr. Steele succinctly summarizes the efficacy and safety of Botulinum toxin A (BTX A) – a point which is not in debate.1 However, the use of BTX A as a primary modality of treatment for OAB has never been reported. While it is likely that BTX A will be able to control overactivity in anticholinergic naive patients, it is unclear what side effects, such as urinary retention, will be seen in such a group. Research into patient preferences and decision-making as it relates to the weighted value of the invasiveness of intervention and side effects balanced with overall levels of improvement in symptoms would yield insight. A randomized trial between BTX A and an anti-cholinergic medication in patients with moderate to severe OAB with detrusor overactivity who are naive to treatment may be reasonable to address this issue, especially in the subset of neurogenic OAB who are already intermittently catheterizing. For the time being, there is no data to support the use of BTX A as a primary treatment for OAB. The long-term success beyond 10 years of BTX A for OAB is unknown. Thus, patients should continue to be treated in a stepwise fashion beginning with lifestyle and behavioural changes, and oral pharmacotherapy.
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 | 0.021 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.129 | 0.022 |
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".