A multi-institution consensus on how to perform EUS-guided biliary drainage for malignant biliary obstruction
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: EUS-guided biliary drainage (EUS-BD) was shown to be useful for malignant biliary obstruction (MBO). However, there is lack of consensus on how EUS-BD should be performed. METHODS: This was a worldwide multi-institutional survey among members of the International Society of EUS conducted in February 2018. The survey consisted of 10 questions related to the practice of EUS-BD. RESULTS: Forty-six endoscopists of them completed the survey. The majority of endoscopists felt that EUS-BD could replace percutaneous transhepatic biliary drainage after failure of ERCP. Among all EUS-BD methods, the rendezvous stenting technique should be the first choice. Self-expandable metal stents (SEMSs) were recommended by most endoscopists. For EUS-guided hepaticogastrostomy (HGS), superiority of partially-covered SEMS over fully-covered SEMS was not in agreement. 6-Fr cystotomes were recommended for fistula creation. During the HGS approach, longer SEMS (8 or 10 cm) was recommended. During the choledochoduodenostomy approach, 6-cm SEMS was recommended. During the intrahepatic (IH) approach, the IH segment 3 was recommended. CONCLUSION: This is the first worldwide survey on the practice of EUS-BD for MBO. There were wide variations in practice, and randomized studies are urgently needed to establish the best approach for the management of this condition.
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 | 0.046 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".