Dual Stent Migration to the Heart and Pulmonary Artery
Bibliographic record
Abstract
The practice of intravascular stenting largely grew out of the concept of stenting the coronaries in acute myocardial infarction. According to the recent United States Renal Data System data registry, there has been a significant increase in endovascular intervention (1.8-fold increase-from 52,380 to 98,148) with a 2.2-fold increase in stent deployment in hemodialysis access (3792-8514). With the increasing use of endovascular stents in the management of dialysis access stenosis, the incidence of stent-related complications has increased significantly. Stent-related complications include stent restenosis, thrombosis (narrowing of the vessel lumen and being a nidus for thombus formation), stent shortening, stent fracture, stent infection, and stent migration. Physiologic variation in the diameter of veins due to respiration, which along with the geometry of the stent, can lead to a shortening lengthening of the stent-resulting in poor wall contact or high-speed impact of shock; in the case of trauma, mechanical bucking can result in tortuous blood vessels thereby resulting in stent migration (however proving this association was not the aim of this article). We report a case of a 44-year-old female with end-stage renal disease on hemodialysis, with stent placement to treat a compromised arteriovenous graft. There have been many cases of stent migration in the past; however, this is the first case of dual stent migration to the heart and pulmonary artery from an unusual (lower extremity) arteriovenous graft location.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".