Plaque sealing with drug-eluting stents versus medical therapy for treating intermediate non-obstructive saphenous vein graft lesions: A pooled analysis of the VELETI and VELETI II trials
Bibliographic record
Abstract
BACKGROUND: The presence of intermediate "non-obstructive" saphenous vein graft (SVG) lesions is a strong predictor of cardiac events. We wanted to assess the efficacy of sealing these SVG lesions with drug-eluting stent (DES) implantation for reducing major adverse cardiac event (MACE) rate. METHODS: The present analysis is based on the pooled data from the VELETI and VELETI II randomized trials. Patients with at least 1 intermediate SVG lesion (30%-60% diameter stenosis) were randomized to DES implantation (SVG-DES) or medical treatment (SVG-MT). The primary outcome was the first occurrence of MACE, defined as the composite of cardiac death, myocardial infarction, or coronary revascularization related to the target SVG. RESULTS: A total of 182 patients were included (mean age, 70 ± 9 years), with 90 and 92 patients allocated to the SVG-DES and SVG-MT groups, respectively. After a mean follow-up of 4 ± 1 years, patients in the SVG-MT group exhibited a higher rate of MACE related to the target SVG (23.9% vs 17.8% in the SVG-DES group; P=.04) and MACE related to the target SVG lesion (21.7% vs 12.2% in the SVG-DES group; P<.01). In the multivariable analysis, a higher total cholesterol value at baseline (P=.04) was the only independent predictor of SVG disease progression leading to clinical events. CONCLUSIONS: In patients with prior coronary artery bypass grafting and intermediate non-obstructive SVG lesions, plaque sealing with DES reduced the incidence of MACE related to SVG disease progression. A higher cholesterol level was the main predictor of SVG disease progression leading to clinical events in these patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".