Absorb Bioresorbable Scaffold Versus Xience Metallic Stent for Prevention of Restenosis Following Percutaneous Coronary Intervention in Patients at High Risk of Restenosis: Rationale and Design of the COMPARE ABSORB Trial
Bibliographic record
Abstract
BACKGROUND: The advent of bioresorbable vascular scaffolds (BVS) was considered as a potential improvement in percutaneous coronary intervention (PCI) after the groundbreaking development of drug eluting stents (DES). However, the clinical performance, long-term safety and efficacy of BVS in complex coronary lesions remain uncertain. COMPARE ABSORB, a multicenter, single blind, prospective randomized trial, aims to compare the clinical outcomes between the Absorb BVS and Xience everolimus-eluting metallic stent (EES) in patients with coronary artery disease and a high risk of restenosis. DESIGN: COMPARE ABSORB is designed to enroll 2100 patients at up to 45 European sites. Enrolled patients will possess high risk for restenosis due to clinical profile or coronary lesion complexity and will undergo elective or emergent PCI. Once included in the study, patients will receive either Absorb BVS or Xience EES. Specific advice on implantation technique including mandatory pre-dilatation, sizing and post-dilatation (PSP), will be used in the Absorb BVS arm. The primary endpoint is target lesion failure (TLF), a device-oriented composite endpoint (cardiac death, target vessel myocardial infarction and clinically-indicated target lesion revascularization). The trial is powered to assess non-inferiority of Absorb BVS compared with Xience EES with a predetermined non-inferiority margin of 4.5% at 1 year after index procedure. The clinical follow-up will continue for 7 years. CONCLUSIONS: The prospective COMPARE ABSORB randomized trial (ClinicalTrials.govNCT02486068) will help to assess the long-term safety and efficacy of Absorb BVS compared with Xience EES in the treatments of patients with complex coronary artery disease and a high attendant risk of restenosis.
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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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".