Randomized Controlled Trial Comparing Outcomes of Video Capsule Endoscopy with Push Enteroscopy in Obscure Gastrointestinal Bleeding
Bibliographic record
Abstract
BACKGROUND: Optimal management of obscure gastrointestinal bleeding (OGIB) remains unclear. OBJECTIVE: To evaluate diagnostic yields and downstream clinical outcomes comparing video capsule endoscopy (VCE) with push enteroscopy (PE). METHODS: Patients with OGIB and negative esophagogastroduodenoscopies and colonoscopies were randomly assigned to VCE or PE and followed for 12 months. End points included diagnostic yield, acute or chronic bleeding, health resource utilization and crossovers. RESULTS: Data from 79 patients were analyzed (VCE n=40; PE n=39; 82.3% overt OGIB). VCE had greater diagnostic yield (72.5% versus 48.7%; P<0.05), especially in the distal small bowel (58% versus 13%; P<0.01). More VCE-identified lesions were rated possible or certain causes of bleeding (79.3% versus 35.0%; P<0.05). During follow-up, there were no differences in the rates of ongoing bleeding (acute [40.0% versus 38.5%; P not significant], chronic [32.5% versus 45.6%; P not significant]), nor in health resource utilization. Fewer VCE-first patients crossed over due to ongoing bleeding (22.5% versus 48.7%; P<0.05). CONCLUSIONS: A VCE-first approach had a significant diagnostic advantage over PE-first in patients with OGIB, especially with regard to detecting small bowel lesions, affecting clinical certainty and subsequent further small bowel investigations, with no subsequent differences in bleeding or resource utilization outcomes in follow-up. These findings question the clinical relevance of many of the discovered endoscopic lesions or the ability to treat most of these effectively over time. Improved prognostication of both patient characteristics and endoscopic lesion appearance with regard to bleeding behaviour, coupled with the impact of therapeutic deep enteroscopy, is now required using adapted, high-quality study methodologies.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".