EUS-guided drainage of large walled-off pancreatic necroses using plastic versus lumen-apposing metal stents: a single-centre randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE: In treating pancreatic walled-off necrosis (WON), lumen-apposing metal stents (LAMS) have not proven superior to the traditional double pigtail technique (DPT). Among patients with large WON (>15 cm) and their associated substantial risk of treatment failure, the increased drainage capacity of a novel 20-mm LAMS might improve clinical outcomes. Hence, we conducted a study comparing the DPT and 20-mm LAMS in patients with large WON. DESIGN: A single-centre, open-label, randomised, controlled superiority trial using an endoscopic step-up approach in patients with WON exceeding 15 cm in size. The primary endpoint was the number of necrosectomies needed to achieve clinical success (clinical and CT resolution), while the secondary endpoints included technical success, adverse events, length of stay and mortality. RESULTS: Twenty-two patients were included in the DPT group and 20 in the LAMS group, with no significant differences in patient characteristics. The median size of WON was 24.1 cm (P25-P75: 19.6-31.1). The technical success rates were 100% for DPT and 95% for LAMS (p=0.48), while clinical success rates were 95.5% and 94.7%, respectively (p=1.0). The mean number of necrosectomies was 2.2 for DPT and 3.2 for LAMS (p=0.42). Five patients (12%) developed procedure-related serious adverse events (DPT=4, LAMS=1, p=0.35). The median length of stay was 43 (P25-P75: 40-67) and 58 days (P25-P75: 40-86) in the DPT and LAMS groups (p=0.71), respectively, with an overall mortality of 4.8%. CONCLUSIONS: For treating large WON, LAMS are not superior to DPT. The techniques are associated with comparable needs for necrosectomy and hospital stay, and no gross difference in adverse events. TRIAL REGISTRATION NUMBER: NCT04057846.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".