The Evolution of EUS-Guided Transluminal Drainage for the Treatment of Pancreatic Fluid Collections: A Comparison of Clinical and Cost Outcomes with Double-Pigtail Plastic Stents, Conventional Metal Stents and Lumen-Apposing Metal Stents
Bibliographic record
Abstract
Abstract Background While most pancreatic fluid collections (PFCs) resolve spontaneously, endoscopic ultrasound-guided transluminal drainage (EUS-TD) may be necessary. EUS-TD has evolved from multiple double-pigtail plastic stents (DPPS) to fully covered self-expanding metal stents (FCSEMS) and lumen-apposing metal stents (LAMS). This study compares clinical attributes of DPPS, FCSEMS and LAMS. Methods This is a single-centre retrospective review of EUS-TD for PFCs. The primary outcome was clinical success. Secondary outcomes were technical success, procedure time, hospital length of stay (HLOS), number of endoscopies, need for necrosectomy, adverse events (AEs) and overall cost. Results Fifty-eight patients (37 male, average age 49 years) underwent a total of 60 EUS-TD procedures for PFCs (average size 11.2 cm with 29 pseudocysts and 29 walled-off necrosis). Ten patients (17%) underwent EUS-TD with DPPS and 48 patients (83%) with metal stents (32 FCSEMS, 16 LAMS). Overall technical and clinical success was 100% and 84%, respectively. Lumen-apposing metal stents had shorter procedure times (14.9 versus 63.6 DPPS, 39.1 min FCSEMS, P < 0.001), and no difference in AEs (3 of 16 versus 4 of 10 DPPS, 12 of 34 FCSEMS, ns). Double-pigtail plastic stents required more endoscopies (3.7 versus 2.3 LAMS, 2.3 FCSEMS, P = 0.013) and necrosectomies (4 of 10 [40%]) compared with 5 of 34 [15%] in the FCSEMS group and 3 of 16 [19%] in the LAMS group, respectively, P = 0.001) to achieve clinical resolution. The overall cost and HLOS was not significantly different between groups. Conclusion The use of LAMS for PFCs is not associated with any significant increase in cost despite technical (shorter procedure time) and clinical advantages (shorter indwell time, reduced need for necrosectomy and no increase in AEs).
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".