Draining Setons as Definitive Management of Fistula-in-Ano
Bibliographic record
Abstract
BACKGROUND: The ideal management for fistula-in-ano would resolve the disease while preserving anal continence. OBJECTIVE: The purpose of this study was to determine the efficacy of draining seton alone in achieving resolution or significant amelioration of symptoms for patients with fistula-in-ano. DESIGN: This was a retrospective case series involving chart review and telephone interviews. A single colorectal surgeon performed surgeries between June 1, 2005, and June 30, 2014. SETTINGS: The study was conducted by a single surgeon in a large urban city. PATIENTS: Patient ≥18 years of age presenting with fistula-in-ano of cryptoglandular origin were included. MAIN OUTCOME MEASURES: Resolution of symptoms or significant symptom improvement requiring no additional surgical management and rate of recurrence were measured. RESULTS: A total of 76 patients (53 men) met the inclusion criteria. Mean age was 45 years (range, 19-73 y). The average time to seton removal was 36.6 weeks (range, 6.0-188.0 wk). Mean follow-up was 63 months (range, 7-121 mo). Fifty-seven patients (75%) were reached for telephone interview. Fifty-six patients (73.7%) had complete symptom resolution, and 14 (18.4%) had significant amelioration of symptoms with no additional surgical management required. Six (7.9%) had persistent severe symptoms. Five (7.1%) had a recurrence after seton removal. Rates of symptom resolution and recurrence were similar between patients whose setons were removed before or after 26 weeks (median time of seton removal) from the time of placement. Twenty-one patients (27.6%) required 1 or more additional operative procedures before planned seton removal to unroof a collection and/or replace the seton, and this represented the most significant risk factor for failure of resolution or improvement or recurrence (relative risk = 7.0). LIMITATIONS: This study was retrospective and represents a single surgeon experience. CONCLUSIONS: Placement of draining seton alone is a viable treatment option for definitive symptomatic management of fistula-in-ano. Because draining setons are sphincter and function preserving, their use should be considered as primary management for fistula-in-ano. See Video Abstract at http://links.lww.com/DCR/A552.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".