Trends and Clinical Practice Patterns of Sacral Neuromodulation for Overactive Bladder
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to investigate surgical practice patterns of American urologists treating refractory overactive bladder (OAB) over the past decade. Refractory OAB remains a management challenge to urologists. When multiple medical therapies have failed, treatment options may include sacral neuromodulation (SNM) or surgery such as augmentation cystoplasty (AC). METHODS: Data on SNM and AC performed between 2003 and 2012 by certifying and recertifying urologists were obtained in the form of annualized case logs from the American Board of Urology (ABU). Associations between surgeon characteristics (type of certification, annual volume, practice type, and location) and these procedures were evaluated. RESULTS: Over the past decade, 756 of 6355 urologists certified with the ABU performed SNM or AC for the treatment of refractory OAB. Forty-five (6%) of these surgeons completed fellowships in female urology and 71 surgeons (9%) completed another type of fellowship program. Surgeons recertifying with ABU performed 76% of all SNM procedures. Although SNM and AC have increased from 64 to 2086 between 2003 and 2012, however, this is mainly driven by the increase of SNM from 48 to 2068 cases. Rates of AC have remained stable with 14 to 38 cases reported annually. However, they have declined relative to the total, from 25% in 2003 to less than 1% in 2012. CONCLUSIONS: Sacral neuromodulation has increased dramatically over the past decade in surgeons certified with the ABU. This is in contrast to AC, which while remaining stable in number of procedures.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".