Pre- and Post-Implant Endoscopy in Left Ventricular Assist Device Recipients: A Single-Center Experience
Bibliographic record
Abstract
Background: Gastrointestinal bleeding (GIB) is common in left ventricular assist devices (LVADs) patients, but the optimal screening approach before LVAD implantation is still unclear. The aim of the study was to describe our experience with pre- and post-LVAD implantation endoscopic screening and subsequent GI bleeding in this cohort. Methods: A retrospective review was conducted among all patients who underwent LVAD implantation at Saint Luke's Hospital, between 2010 and 2020. The data were reviewed to determine the yield and safety of endoscopic procedures performed within 1 month before LVAD placement and the incidence of GIB within 1 year after implantation. Results: A total of 167 LVAD patients met the inclusion criteria, and 23 underwent pre-implantation endoscopic evaluation. Angiodysplasia had a significantly higher odds ratio (OR) of 9.41 (95% confidence interval (CI): 2.01 - 44.09) in post-LVAD endoscopy, while there was no significant difference in bleeding from other sources such as peptic ulcer disease or diverticular bleeding. There was no difference in the incidence of GIB in patients who underwent endoscopic evaluation pre-LVAD compared to post-LVAD GIB (32.6% vs. 39.1%, P = 0.64). Endoscopy was well-tolerated in this cohort, and argon plasma coagulation was the most commonly used intervention to achieve hemostasis. Conclusions: According to our results, we recommend against routine pre-LVAD endoscopic screening. Instead, we suggest an individualized approach, where decisions are made on a case-by-case basis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".