Efficacy of Video Capsule Endoscopy in the Management of Suspected Small Bowel Bleeding in Patients With Continuous Flow Left Ventricular Assist Devices
Bibliographic record
Abstract
BACKGROUND: Continuous flow left ventricular assist device (CF-LVAD) patients have a high prevalence of gastrointestinal bleeding from the small bowel. Video capsule endoscopy (VCE) is often used for diagnosis in these patients, but efficacy has yet to be determined. In this study, we evaluated the efficacy of VCE in the management of CF-LVAD patients with suspected small bowel bleeding by comparing to a non-VCE CF-LVAD control group. METHODS: We retrospectively reviewed the charts of all patients with CF-LVADs implanted at Stanford Hospital from January 2010 to October 2015. Patients were included in the study if there was a clinical suspicion of small bowel bleeding and either a negative upper endoscopy or colonoscopy. RESULTS: A total of 26 patients met inclusion criteria for a total of 15 encounters where VCE was done, and 25 where VCE was not done. There were no statistical differences when comparing these groups in terms of medical therapy use (thalidomide or octreotide), enteroscopy use (double-balloon or push), intervention on lesions, or any 30-day outcomes. There was no advantage to VCE with regard to the composite endpoint time to re-bleed or death related to re-bleeding (median 114 vs. 161 days, P = 0.15) after removing patients who did not get a VCE due to death or critical illness. CONCLUSIONS: We did not find VCE changed management or outcomes in CF-LVAD patients with suspected small bowel bleeding at our institution when compared to a non-VCE control group. Our experience is small and single center, and larger, multi-center studies could further elucidate the utility of VCE in this patient population.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".