A randomized, controlled trial of transcutaneous tibial nerve stimulation to treat overactive bladder and neurogenic bladder patients
Bibliographic record
Abstract
INTRODUCTION: We aimed to determine if transcutaneous tibial nerve stimulation (TTNS) is effective at treating overactive bladder (OAB) symptoms among neurogenic and non-neurogenic patients. METHODS: We conducted a randomized, double-blind, sham-controlled study. Adult patients were recruited from one of two groups: 1) women with OAB; and 2) patients with neurogenic disease and bladder symptoms. The intervention was stimulation of the posterior tibial nerve, for 30 minutes, three times per week for 12 weeks at home using transcutaneous patch electrodes. The primary outcome was improvement of the patient perception of bladder condition (PPBC). We used ANCOVA (with adjustment for baseline values) and followed the intention-to-treat principle; we reported marginal means (MM) and a p<0.05 was considered significant. RESULTS: We recruited 50 patients (OAB n=20, neurogenic bladder n=30); 24 were allocated to the sham group and 26 to the active TTNS group. Baseline characteristics in both groups were similar. At the end of the study, there was no significant difference in the PPBC between sham or active groups: 13% (3/24) of sham patients and 15% (4/26) of active TTNS patients were responders (p=0.77), and the MM of the end-of-study PPBC score was 3.3 (95% confidence interval [CI] 2.8-3.7) vs. 2.9 (95% CI 2.5-3.4), respectively (p=0.30). Similarly, there were no significant differences in secondary outcomes (24-hour pad weight, voiding diary parameters, or condition-specific patient-reported outcomes). The results were similar within the OAB and neurogenic bladder subgroups. CONCLUSIONS: TTNS does not appear to be effective for treating urinary symptoms of people with OAB or neurogenic bladder dysfunction.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".