A279 EUS-GUIDED BILIARY DRAINAGE IN MALIGNANT DISTAL BILIARY OBSTRUCTION: AN INTERNATIONAL SURVEY TO IDENTIFY BARRIERS OF TECHNOLOGY IMPLEMENTATION
Bibliographic record
Abstract
Abstract Background Endoscopic ultrasound-guided biliary drainage (EUS-BD) is a promising alternative to endoscopic retrograde cholangiopancreatography (ERCP) in malignant distal biliary obstruction (MDBO). Recent small randomized controlled trials comparing EUS-BD with ERCP suggest that EUS-BD achieves a similar technical success rate and safety profile while potentially being associated with lower rates of stent dysfunction However, its application in clinical practice has been impeded by various undefined barriers. Aims To evaluate the current practice of EUS-BD and the determinants for its clinical implementation in MDBO. Methods An online survey was generated using Google Forms. Five endoscopy societies have distributed the survey as of October 10th, 2019. Survey questions measured participant characteristics, EUS-BD in different clinical scenarios, and potential barriers to implementation. Descriptive statistics were calculated using frequencies, chi-square statistics were used for inferential analysis, and a standard step-wise multivariable analysis was performed to identify independent variables for and against the use of EUS-BD. Results To date, 102 physicians have participated in the survey (response rate 7.97%). The majority of participants are from North America (39.2%), Asia (31.4%), and Europe (19.6%). Most participants are gastroenterologists with formal therapeutic endoscopy training (66.7%), though only 28.4% have received EUS-BD training. In unresectable cancer, 85.1% of respondents favoured EUS-BD over percutaneous biliary drainage following ERCP failure (p<0.0001), while in borderline resectable disease, 72.3% preferred EUS-BD. On multivariable analysis, male gender, formal training in EUS-BD, and unresectable cancer were independent variables for the use of EUS-BD. Conversely, independent discouraging factors for EUS-BD included fear of adverse events, limited high-quality data, lack of local expertise, and inadequate access to EUS technology. Conclusions In this international survey, it appears that EUS-BD is gaining traction, especially in the setting of unresectable disease following ERCP failure. However, barriers to implementation include the lack of high-quality data, fear for adverse events, limited experts in the field, and inadequate access to EUS technology. This suggest the need for high-quality clinical trials, increased endoscopist training in this field, and further technology development in EUS-BD in order to increase its uptake in clinical practice. Funding Agencies None
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".