The intravesical injection of highly purified botulinum toxin for the treatment of neurogenic detrusor overactivity
Bibliographic record
Abstract
INTRODUCTION: We aimed to assess safety and efficacy of incobotulinumtoxinA for the treatment of neurogenic detrusor overactivity (NDO). METHODS: We identified patients with NDO confirmed on urodynamics (UDS) and reported urgency incontinence (UI) in those who received intravesical incobotulinumtoxin A injection for neurogenic bladder between November 2013 and May 2017. Parameters studied were daytime frequency, daily incontinence episodes, daily pad use, clean intermittent catheterization (CIC) volumes, symptom scores (UDI6, IIQ7, PGII), and complications. RESULTS: We examined 17 male patients who met inclusion criteria and underwent incobotulinumtoxinA injection. Mean age was 61.2±15.4 years. Fourteen patients (82%) were taking oral antimuscarinics prior to the incobotulinumtoxin A injection. There were improvements in the following parameters: average daily pads (4.5 to 3.3, p=0.465), daily urinary frequency (9.4 to 4.6, p=0.048), daily incontinent episodes (2.5 to 0.4, p=0.033), CIC volumes (400 to 550 mL, p=0.356), hours in between CIC (3.6 to 5.2, p=0.127), and the validated questionnaires UDI6 (30.6 to 7.4, p=0.543) and IIQ7 (52.4 to 6.8, p=0.029). There were no documented symptomatic urinary tract infections (UTIs) within 30 days of injection or reports of de novo urinary retention. Nine of 17 patients (53%) reported being dry at their first postoperative visit. CONCLUSIONS: In this preliminary pilot study of a small cohort of males with NDO and UI, significant improvements were seen following incobotulinumtoxinA injection in daily frequency, incontinence episodes, hours in between CIC, and quality of life. Larger-scale and long-term studies are required to confirm these results, but initial findings are promising for wider use of this formulation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".