Safety and efficacy of early versus late removal of LAMS for pancreatic fluid collections
Bibliographic record
Abstract
Abstract Background and study aims Optimal timing for removal of lumen-apposing metal stents (LAMS) for effective drainage of pancreatic fluid collections (PFC) while minimizing adverse events (AE) is unknown. Outcomes of early (≤ 4 weeks) or delayed (> 4 weeks) LAMS removal on both clinical efficacy and the incidence of AE were assessed. Patients and methods This was a retrospective analysis of a prospectively maintained registry of PFC drainage between November 2016 and September 2021. Clinical success was defined as a 75% decrease in fluid collection volume with no need for reintervention at 6 months. AE were defined using the American Society for Gastrointestinal Endoscopy lexicon. Multiple logistic regression analysis was performed to determine variables associated with clinical success and AE. Results A total of 108 consecutive PFCs were included. LAMS deployment was technically successful in 103 of 108 cases (95.4%). Failure was associated with collection diameter ≤ 4 cm (odds ratio [OR] 24.0, P = 0.005) and presence of more than 50% necrotic material (OR 20.1, P = 0.01). Stents were left in place for a median of 48 days. Patients with early stent removal (< 4 weeks) had clinical success in 70.0% of cases, which was significantly less than in the group with delayed stent removal (96.4%, P = 0.03). On multiple regression analysis, clinical failure was associated with early stent removal (OR 25.5, P = 0.003). AEs occurred in 8.7% of cases (9/103). There were no predictors of AE. Notably, delayed stent removal did not predict the occurrence of AE. Conclusions Early LAMS removal (< 4 weeks) did not prevent AEs but did lead to increased clinical failure.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".