A38 OVER-THE-SCOPE AND THROUGH-THE-SCOPE SUTURING OUTCOMES FOR ENDOSCOPIC LEAK AND FISTULA MANAGEMENT: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Abstract Background Leaks and fistulae are well-recognized sequelae arising from gastrointestinal surgeries, inflammatory bowel disease, malignancy, and traumatic injury; reflecting significant morbidity, mortality and resource utilization. Endoscopic management has gained traction as a minimally invasive alternative to surgery including both over-the-scope suturing (OTSS) and through-the-scope suturing (TTSS). Aims We aimed to systematically evaluate available evidence for OTSS and TTSS outcomes for leak and fistula management. Methods From inception to July 1st, 2024, MEDLINE, EMBASE and Cochrane Library were searched for relevant citations. Full-text citations were included if they evaluated both technical success (endoscopic closure of leak or fistula) and clinical success (technical success with avoidance of further intervention) for leak or fistulae management with OTSS or TTSS. In this preliminary analysis, outcomes were reported as ranges. Results A total of 11 studies including 185 defects were included for analysis. For fistulae, technical success for OTSS and TTSS ranged from 83-100% and 82-100%, respectively. Clinical success for OTSS and TTSS ranged from 0-80% and 55-100% respectively. For leaks, technical success for OTSS and TTSS ranged from 90-100% and 0-57%, respectively. Clinical success for OTSS and TTTS ranged from 25-100% and 29%, respectively. Conclusions OTSS and TTSS are new interventions for leak and fistulae management with varying performance outcomes. Further research is required to delineate optimal candidates for OTSS/TTSS closure and treatment algorithms after technical/clinical failure. Funding Agencies None
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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".