Sacral neuromodulation in the golden years
Bibliographic record
Abstract
INTRODUCTION: Despite high prevalence and increased severity and burden of overactive bladder (OAB) and fecal incontinence (FI) in the elderly, sacral neuromodulation (SNM) is often overlooked as a potential treatment option for this demographic. In this study, we report the outcomes of SNM in patients aged 75 years or older at the time of surgery. METHODS: We conducted a retrospective cohort study of patients who underwent SNM implantation between 2013 and 2022 performed by a single, high-volume urologist at a tertiary center. Success, complication, and adjunct therapy rates were analyzed by Fisher's or Wilcox rank-sum test as appropriate. We compared outcomes between patients aged 75-79 years and octogenarians. RESULTS: Of 632 patients, 50 were ≥75 years. Patients had a mean age of 78.4±2.6 years and were predominantly female (84%). The indications for SNM were 66% OAB, 16% FI, 16% non-obstructive urinary retention, and 4% pelvic pain. Within the first year, 94% of patients reported satisfaction and improvement in symptoms, while 76% continued to experience improvement beyond one year. SNM insertion led to reduced oral medication use from 68% to 24% (p<0.0001). The complication rate was 16% and mostly included device pain. No significant difference was observed in treatment success, complication, or adjunct therapy rate between age groups. CONCLUSIONS: SNM is a safe and effective option in well-selected patients over the age of 75 years. Treatment success rate is comparable to younger cohorts. Advanced age should not preclude third-line therapy options in this population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".