Urodynamic evaluation of sacral neuromodulation for urge urinary incontinence
Bibliographic record
Abstract
OBJECTIVE: To evaluate the urodynamic data before and 6 months after implantation of sacral neuromodulation (SNM, an established treatment for voiding dysfunction, including refractory urge urinary incontinence, UI) and to assess the correlation between the urodynamic data and clinical efficacy in patients with UI. PATIENTS AND METHODS: In all, 111 patients with a >50% reduction in UI symptoms during a percutaneous nerve evaluation test qualified for surgical implantation of SNM. Patients were categorized in two subgroups, i.e. those with UI with or without confirmed detrusor overactivity (DO) at baseline. At the 6-month follow-up all patients had a second urodynamic investigation, with the stimulator switched on. RESULTS: At baseline, there was urodynamically confirmed DO in 67 patients, while 44 showed no DO. A review of filling cystometry variables showed a statistically significant improvement in bladder volumes at first sensation of filling (FSF) and at maximum fill volume (MFV) before voiding for both UI subgroups, compared with baseline. In 51% of the patients with UI and DO at baseline, the DO resolved during the follow-up. However, those patients were no more clinically successful than those who still had DO (P = 0.73). At the 6-month follow-up, 55 of 84 implanted patients showed clinical benefit, having a >or=50% improvement in primary voiding diary variables. Patients with UI but no DO had a higher rate of clinical success (73%) than patients with UI and DO (61%), but the difference was not statistically significant. CONCLUSION: These urodynamic results show a statistically significant improvement in FSF and MFV in patients with UI with or with no DO after SNM. Although there was a urodynamic and clinical improvement in both groups, patients with UI but no DO are at least as successful as patients with UI and DO. Therefore in patients with UI, DO should not be a prerequisite selection criterion for using SNM.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".