One-year clinical outcomes of patients treated with everolimus-eluting bioresorbable vascular scaffolds versus everolimus-eluting metallic stents: a propensity score comparison of patients enrolled in the ABSORB EXTEND and SPIRIT trials
Bibliographic record
Abstract
AIMS: We sought to compare the outcomes of low/moderate complexity patients treated with the Absorb BVS from the ABSORB EXTEND trial with patients treated with the XIENCE everolimus-eluting stent (EES), using propensity score (PS) matching of pooled data from the SPIRIT trials (SPIRIT II, SPIRIT III, SPIRIT IV) and the XIENCE V USA trial. METHODS AND RESULTS: ABSORB EXTEND was 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 with a reference vessel diameter of 2.0-3.8 mm (as assessed by online QCA). The propensity score was obtained by fitting a logistic regression model with the cohort indicator as the binary outcome and other variables as the predictor variables. At one-year clinical follow-up, there was no statistical difference between groups with regard to MACE (5.0% vs. 4.8%, p=0.83), target lesion failure (5.0% vs. 4.7%, p=0.74), ischaemia-driven target vessel revascularisation (2.3% vs. 3.0%, p=0.38) and device thrombosis (1.0% vs. 0.3%, p=0.11). Myocardial infarction was higher with Absorb (3.3% vs. 1.5%, p=0.02), at the expense of periprocedural CK-MB elevation. Independent predictors of MACE among patients receiving Absorb BVS were treatment of multivessel disease, insulin-dependent diabetes and performance of post-dilation. CONCLUSIONS: At one-year follow-up, propensity score-matched analysis demonstrated that the clinical safety and effectiveness of Absorb are comparable to those of XIENCE EES among non-complex patients treated with PCI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".