Long-Term Outcomes of Absorb Bioresorbable Vascular Scaffold vs. Everolimus-Eluting Metallic Stent ― A Randomized Comparison Through 5 Years in Japan ―
Bibliographic record
Abstract
BACKGROUND: Bioresorbable vascular scaffolds (BVS) are promising alternatives to metallic drug-eluting stents (DES) in percutaneous coronary interventions. Absorb BVS was comparable to XIENCE (DES) for patient- and device-oriented composite endpoints through 1 year post-procedure. Mid-term results showed increased rates of device-oriented events with Absorb. The objective of this study was to evaluate the long-term safety and effectiveness of Absorb BVS compared with XIENCE metallic DES when implanted in patients in Japan with de novo coronary artery lesions. METHODS AND RESULTS: ABSORB Japan randomized 400 patients into either Absorb (n=266) or XIENCE (n=134) treatment arm. Through 5-year follow-up, the composite endpoints of DMR (death, myocardial infarction [MI], and all revascularization), target vessel failure (TVF), major adverse cardiac events (MACE), target lesion failure (TLF), and cardiac death/all MI were evaluated. Individual endpoints included death, MI, coronary revascularization, and scaffold/stent thrombosis. There were no significant differences in the composite or individual endpoint outcomes between the Absorb and XIENCE arms through 5 years or between 3 and 5 years. Numerically lower TVF, MACE, and all MI rates were observed for the Absorb vs. XIENCE arm after 3 years. No scaffold/stent thrombosis was reported beyond 3 years. Post-procedure imaging subgroups showed comparable event rates. CONCLUSIONS: Following resorption of the scaffold, between 3 and 5 years post-procedure, the Absorb BVS performed comparably to XIENCE in all patient- and device-oriented endpoints (ClinicalTrials.gov, #NCT01844284).
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".