Comparison of a polymer‐free rapamycin‐eluting stent (YUKON) with a polymer‐based paclitaxel‐eluting stent (TAXUS) in real‐world coronary artery lesions
Bibliographic record
Abstract
BACKGROUND: In selected patient cohorts the polymer-free rapamycin-eluting YUKON stent (A) has demonstrated noninferiority compared with the polymer-based paclitaxel-eluting TAXUS stent (B). To test for equivalency in unselected real-world patients with coronary lesions of various complexities, we retrospectively compared both stent designs. METHODS: A total of 410 patients with symptomatic CAD were successfully treated with A (n = 205) or with B (n = 205). Baseline clinical characteristics, coronary lesion location, lesion length, and the number of stents implanted per lesion were equally distributed between the treatment groups. All patients underwent QCA-analysis at baseline. Clinical follow-up with assessment of MACE and noncardiac deaths was obtained at 30 days and 6 months. RESULTS: Nominal stent diameter was 2.96 +/- 0.38 mm in Group A vs. 3.05 +/- 0.42 mm in Group B (P = 0.2); nominal length of stented segmentwas 22.97 +/-13.0 mm vs. 23.63 +/- 10.0 (P = 0.56). Analysis of MACE after 6 months resulted in one angiographically documented stent thrombosis causing MI in B (0.2%) vs. none in A. No other MI or cardiac deaths occurred in either group, while two noncardiac deaths in A (1.0%) were reported. Fifteen target lesion revascularizations (7.3%) were performed in A vs. 7 (3.4%) in B. Differences in study endpoints at 6 months did not reach statistical significance (P > 0.05). CONCLUSIONS: Up to 6 months after PCI of real-world coronary lesions, there were no statistically significant differences in MACE between patients treated with the polymer-free rapamycin-eluting YUKON stent and the polymer-based paclitaxel-eluting TAXUS stent.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".