Long‐term outcomes after seton placement for perianal fistulas with and without Crohn’s disease
Bibliographic record
Abstract
AIM: Perianal sepsis in Crohn's disease (CD) fistulas is managed with antibiotics and surgical drainage; a noncutting seton is used for an identified transsphincteric fistula tract. The optimal management following seton placement for initial control of perianal sepsis remains to be determined. Our main aim was to assess the success rates of curative surgery, seton removal or long-term indwelling seton in patients with and without CD. METHOD: This was a retrospective cohort of consecutive patients with a perianal fistula treated with a noncutting seton between 2010 and 2019, including 83 CD patients and 94 patients without CD. Initial control of symptomatic perianal infection with a seton and subsequent healing and reintervention rates were compared between the three postseton management strategies. RESULTS: A total of 177 patients, 61% male and 83.1% with complex fistulas, were followed for a median of 23 months (interquartile range 11-40 months). Immunomodulatory treatment was used in 90.4% of CD patients after seton placement. Good initial control of perianal infection was achieved with a seton in CD and non-CD patients, at 92.9% and 96.7%, respectively (p = 0.11). Overall fistula healing or control for CD and non-CD patients was, respectively, 64% and 86% (p = 0.1) after curative surgery, 49% and 71% after seton removal (p = 0.21) and 58% and 50% with long-term seton placement (p = 0.72). Overall reintervention for recurrence was 83% in CD versus 53.1% in non-CD patients during the follow-up period (p = 0.002). CONCLUSION: Definitive surgery was possible in only a minority of CD patients. Long-term seton management was an effective option in patients with CD with acceptable improvement and recurrence rates.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".