Three‐year clinical outcomes of patients treated with everolimus‐eluting bioresorbable vascular scaffolds: Final results of the ABSORB EXTEND trial
Bibliographic record
Abstract
BACKGROUND: There is still limited data on the very long term clinical outcomes after ABSORB BRS in daily practice. We sought to evaluate the 3 year-performance of the Absorb bioresorbable vascular scaffolds for the treatment of low/moderate complexity patients enrolled in the ABSORB EXTEND trial. METHODS: ABSORB EXTEND is a prospective, single-arm, open-label clinical study in which 812 patients were enrolled at 56 sites. This study allowed the treatment of lesions ≤28 mm in length and reference vessel diameter of 2.0-3.8 mm (as assessed by on-line QCA). To determine the independent predictors of MACE, a multivariable logistic regression model was built using a stepwise (forward/backward) procedure. RESULTS: Average population age was 61 years and 26.5% had diabetes. Most patients had single target lesion (92.4%). Adequate scaffold deployment (PSP) was achieved in 14.2% of the cases. At three years, the composite endpoints of MACE and ischemia-driven target vessel failure were 9.2% and 10.6%, respectively. The cumulative rate of ARC definite/probable thrombosis was 2.2%, with 1.2% of the cases occurring after the 1st year. Independent predictors of MACE were hypertension and the need for "bail out" stent. CONCLUSION: At three-year follow-up, the use of ABSORB in low/moderate complex PCI was associated with low and acceptable rates of major adverse clinical events, despite the infrequent use of the recommended contemporary scaffold deployment technique. However, scaffold thrombosis rate was higher than reported with current generation of metallic DES. The study is registered on clinicaltrials.gov (unique identifier NCT01023789).
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".