A47 LONG-TERM CLINICAL OUTCOMES AFTER ENDOSCOPIC TREATMENT FOR SMALL BOWEL VACULAR LESIONS BY DOUBLE BALLOON ENDOSCOPY
Bibliographic record
Abstract
Balloon-assisted endoscopy (BAE) has revolutionized the approach to obscure GI bleeding (OGIB) by enabling the diagnosis and treatment of bleeding sources from within the small bowel. The most common source of OGIB is small bowel vascular lesions (SBVL), and referring physicians and patients often anticipate a definitive cure once these have been endoscopically treated. The literature has predominantly focused on immediate diagnostic and therapeutic yields with relatively little attention paid to clinically meaningful outcomes. Therefore, the durability of endoscopic therapy to SBVL by BAE remains unclear. This meta-analysis aimed to address this question by determining the risk of rebleeding in long-term follow-up after endoscopic intervention to SBVL. A comprehensive literature search of PubMed, OVID, Medline and EMBASE was performed to identify studies reporting long-term clinical outcomes after endoscopic therapy for small bowel sources of OGIB via double balloon endoscopy, single balloon endoscopy or spiral enteroscopy. Original studies that identified patients receiving endoscopic treatment to SBVL and that reported objective measures of rebleeding such as overt bleeding signs, repeat hospitalization or intervention for OGIB and/or changes in hemoglobin levels or transfusion requirements were included. A minimum of 6 months follow up was required for study inclusion. Studies were selected using 2 independent and blinded reviewers followed by assessment of study quality. Data were extracted and then analyzed to determine the weighted pooled risk of rebleeding after successful endoscopic therapy. A literature search to April 1, 2016 yielded 1951 unique citations. After initial abstract screening, 30 articles were identified for full text review. Ultimately, 9 studies were selected for inclusion, comprising 565 patients who had received endoscopic therapy to SBVL. There was significant heterogeneity between studies and a random effects model was required. Rebleeding occurred in 242 patients, representing a pooled rebleeding risk of 42.8% after a median follow-up of 20 months. Patients with OGIB who have SBVL identified and successfully treated during BAE have significant rates of rebleeding. Therefore, ongoing clinical monitoring and consideration of repeat endoscopic investigations is recommended for these patients. None
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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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.019 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".