Utility of endoscopic ultrasound-guided hepaticoduodenostomy for intrahepatic bile duct drainage: a multicenter retrospective study in Western Japan
Bibliographic record
Abstract
Abstract Background : There are several biliary drainage procedures for biliary strictures, including endoscopic ultrasound-guided hepaticoduodenostomy (EUS-HDS). However, only a few studies have investigated the technical and clinical success of this procedure with a small number of cases at single high-volume centers. Objective: This multicenter, non-controlled, retrospective study evaluated the safety and efficacy of EUS-HDS for intrahepatic bile duct drainage. Methods : Consecutive patients who underwent EUS-HDS at one of 12 Japanese referral centers between January 2010 and December 2024 were enrolled. The primary endpoint was clinical success. The secondary endpoints were technical success, stent patency, and complications. Results : A total of 35 eligible patients were analyzed. Perihilar biliary stenosis was observed in 32 of 35 patients (91.4%) and right posterior sectoral bile ducts were targeted by EUS-HDS in 28 of 35 patients (80.0%). Technical success was achieved in 31 of 35 patients (88.6%) and clinical success was achieved in 24 of 31 patients (77.4%) according to per-protocol analysis. Median stent patency was 285 (6–999) days. An early procedural adverse event (mild peritonitis) occurred in one case. Patency did not significantly differ between plastic and metal stents (P=0.117). In multivariable analysis, less severe than mild cholangitis (P=0.073) and biliary stent deployment before EUS-HDS (P=0.065) tended to predict clinical effectiveness. Conclusions : EUS-HDS may be a feasible and effective treatment, especially for cases with some degree of controlled cholangitis achieved by adequate biliary drainage other than bile ducts targeted by EUS-HDS.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".