Randomized Trial of a Nonpolymer-Based Rapamycin-Eluting Stent Versus a Polymer-Based Paclitaxel-Eluting Stent for the Reduction of Late Lumen Loss
Bibliographic record
Abstract
BACKGROUND: Although drug-eluting stents (DESs) constitute a major achievement in preventing restenosis, concerns remain regarding the increased inflammatory and thrombogenic responses associated with the polymers used. Recently, we showed that a nonpolymer on-site coating with rapamycin not only is feasible and safe but also leads to a dose-dependent reduction in restenosis. METHODS AND RESULTS: To assess whether polymer-free stents coated on-site with 2% rapamycin solution are inferior to polymer-based paclitaxel-eluting stents for the prevention of restenosis, we randomly assigned a total of 450 patients with de novo lesions in native coronary vessels, excluding the left main trunk, to either the polymer-free, rapamycin-coated Yukon DES (rapamycin stent) or the polymer-based, paclitaxel-eluting Taxus stent (paclitaxel stent). The primary end point was in-stent late lumen loss. Secondary end points were angiographic restenosis and target lesion revascularization. The study was designed to test the noninferiority of the rapamycin stent compared with the paclitaxel stent with respect to late lumen loss according to a noninferiority margin of 0.13 mm. Follow-up angiography was completed in 81% of the patients. The mean difference in in-stent late lumen loss between the rapamycin-stent group and the paclitaxel-stent group was 0.002 mm, and the upper limit of the 1-sided 95% confidence interval was 0.10 mm (P=0.02 from test for noninferiority). No significant differences were observed regarding angiographic restenosis rates (14.2% with the rapamycin stent and 15.5% with the paclitaxel stent) and target lesion revascularization rates due to restenosis (9.3% in both groups). CONCLUSIONS: The polymer-free, rapamycin-coated stent has an antirestenotic effect that is not inferior to that observed with the polymer-based paclitaxel-eluting 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".