Safety and Efficacy of Embolic Protection Devices in Saphenous Vein Graft Interventions: A Propensity Score Analysis—Multicenter SVG PCI PROTECTA Study
Bibliographic record
Abstract
Background: Evidence concerning the efficacy of the embolic protection devices (EPDs) in saphenous vein graft (SVG) percutaneous coronary intervention (PCI) is sparse. The study was designed to compare major cardiovascular events of all-comer population of SVG PCI with and without EPDs at one year of follow-up. Methods and results: A multi-center registry comparing PCI with and without EPDs in consecutive patients undergoing PCI of SVG. The group comprised 792 patients, among which 266 (33.6%) had myocardial infarction (MI). The primary composite endpoint was major adverse cardiac and cerebrovascular event (MACCE) defined as death, MI, target vessel revascularization (TVR), and stroke assessed at one year. After propensity score analysis, there were no differences in MACCE (21.9% vs. 23.9%; HR 0.91, 95% CI 0.57–1.45, p = 0.681, respectively) nor in secondary endpoints of death, MI, TVR, target lesion revascularization (TLR) and stroke at one year in EPDs PCI group vs. no-EPDs PCI group. Similarly, there were no differences between groups in the study endpoints at 30 days follow-up. Conclusions: There were no clinical benefit for routine use of EPDs during SVG PCI in short and long-term follow-up. Further studies are warranted to explore the effect of individual types of EPDs on clinical outcomes.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".