Long‐term outcomes of sacral neuromodulation for lower urinary tract dysfunction: A 23‐year experience
Bibliographic record
Abstract
AIMS: To evaluate the long-term outcomes of sacral neuromodulation (SNM), and patient characteristics that may predict long-term success or complications. METHODS: A single-center retrospective cohort study was performed of all patients who underwent SNM testing and implantation. Outcome results, resolution of symptoms, and device removal were reported. Multivariable logistic regression was used to identify predictors of success. Cox proportional hazards model was used to identify predictors for device removal. RESULTS: Four hundred and thrity four patients underwent SNM test phase of which 241 (median age 48.0 years, 91.7% [221/241] female) had device implantation and were followed up for median [range] time of 4.0 (3 months-20.5 years) years. Multivariable logistic regression showed that male gender (odds ratio: 0.314; 95% confidence interval: 0.164-0.601, p = .0005) was independently associated with decreased peripheral nerve evaluation success. At final follow-up for patients who originally had device implantation, median (interquartile range) percent of symptoms resolution of all patients was 60.0% (0%-90%) and 69.3% (167/241) had SNM successful outcomes. Cox proportional hazards model showed no difference for time to SNM device removal with respect to patient age, gender, or diagnosis. 69.3% (167/241) patients had at least 1 surgical re-intervention. The most common reason at first surgical re-intervention was lead change only (26.3%, 44/167). CONCLUSION: SNM is a minimally invasive procedure with good long-term success rates. There is a high revision rate but overall, SNM has a good safety profile and excellent long-term outcomes.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".