Sacral nerve stimulation can be an effective treatment for low anterior resection syndrome
Bibliographic record
Abstract
AIM: Sacral nerve stimulation has become a preferred method for the treatment of faecal incontinence in patients who fail conservative (non-operative) therapy. In previous small studies, sacral nerve stimulation has demonstrated improvement of faecal incontinence and quality of life in a majority of patients with low anterior resection syndrome. We evaluated the efficacy of sacral nerve stimulation in the treatment of low anterior resection syndrome using a recently developed and validated low anterior resection syndrome instrument to quantify symptoms. METHOD: A retrospective review of consecutive patients undergoing sacral nerve stimulation for the treatment of low anterior resection syndrome was performed. Procedures took place in the Division of Colon and Rectal Surgery at two academic tertiary medical centres. Pre- and post-treatment Cleveland Clinic Incontinence Scores and Low Anterior Resection Syndrome scores were assessed. RESULTS: Twelve patients (50% men) suffering from low anterior resection syndrome with a mean age of 67.8 (±10.8) years underwent sacral nerve test stimulation. Ten patients (83%) proceeded to permanent implantation. Median time from anterior resection to stimulator implant was 16 (range 5-108) months. At a median follow-up of 19.5 (range 4-42) months, there were significant improvements in Cleveland Clinic Incontinence Scores and Low Anterior Resection Syndrome scores (P < 0.001). CONCLUSION: Sacral nerve stimulation improved symptoms in patients suffering from low anterior resection syndrome and may therefore be a viable treatment option.
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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 | 0.000 | 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) | 0.004 | 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".