Clinical and Angiographic Evaluation of the Resolute Zotarolimus-Eluting Coronary Stent in Japanese Patients
Bibliographic record
Abstract
BACKGROUND: This study evaluated the safety and efficacy of the RESOLUTE(TM)zotarolimus-eluting stent (R-ZES; Medtronic, Inc, Santa Rosa, CA, USA) in Japanese patients for the treatment of de novo native coronary lesions. METHODS AND RESULTS: Both RESOLUTE Japan (R-Japan) and RESOLUTE Japan Small Vessel Study (R-Japan SVS) were prospective, multicenter, single-arm observational studies. R-Japan enrolled 100 patients (reference vessel diameter, 2.5-3.5 mm) and R-Japan SVS enrolled 65 patients (at least 1 lesion suitable for 2.25-mm stent) treated with R-ZES. In R-Japan, in-stent late lumen loss (LLL; the primary endpoint) at 8 months was 0.12 ± 0.22 mm and volume obstruction on intravascular ultrasound was 2.33 ± 3.51%. At 4 years, there were no cases of clinically driven target lesion revascularization (TLR); the target lesion failure (TLF; composite of cardiac death, target vessel myocardial infarction, and clinically driven TLR) was 5.6% (5/90). In R-Japan SVS, in-stent LLL at 9 months was 0.27 ± 0.33 mm, TLF (primary endpoint) was 4.6% (3/65), without incidence of TLR. At 3 years, TLF was 7.9% (5/63) and clinically driven TLR, 3.2% (2/63). CONCLUSIONS: R-Japan and R-Japan SVS demonstrate substantial suppression of neointimal hyperplasia, low LLL, and excellent and sustained long-term clinical outcome with R-ZES in Japanese patients.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".