Endoscopic Ultrasound-Guided Vascular Therapy: The Present and the Future
Bibliographic record
Abstract
Endoscopic ultrasound (EUS) offers access to many intra-abdominal vessels that until now have only been accessible to the surgeon and interventional radiologist. In addition to assisting with diagnostics, this unique access offers the potential for therapeutic intervention for a host of indications. To date, this has had the most clinical impact in the treatment of gastroesophageal varices, with EUS-guided coil and glue application growing in use worldwide. Although randomised controlled trial data is lacking, we discuss the growing body of literature behind EUS-guided therapy in the management of varices. EUS has also been used in specialized centres to assist in non-variceal gastrointestinal bleeding. The treatment of bleeding from Dieulafoy lesions, tumours and pancreatic pseudoaneurysms has all been described. The potential applications of EUS have also extended to the placement of portal vein stents and porto-systemic shunts in animal models. As medicine continues to move to increasingly less invasive interventions, EUS-guided therapies offer substantial promise for the safe and effective delivery of targeted treatment for a widening array of vascular disorders.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".