Angiographic complexity of coronary artery disease according to SYNTAX score and clinical outcomes after revascularisation with newer-generation drug-eluting stents: a substudy of the BIOSCIENCE trial
Bibliographic record
Abstract
AIMS: We sought to assess the performance of drug-eluting stents combining an ultrathin cobalt-chromium platform with a biodegradable polymer across categories of increasing SYNTAX score (SS). METHODS AND RESULTS: Patients included in the BIOSCIENCE trial and randomly allocated to treatment with biodegradable polymer sirolimus-eluting stents (BP-SES) or durable polymer everolimus-eluting stents (DP-EES) were categorised according to SS tertiles (low <8, medium 8-15, high >15). The primary endpoint, target lesion failure (TLF), was defined as a composite of cardiac death, target vessel myocardial infarction and clinically indicated target lesion revascularisation. The patient-oriented endpoint (POCE) included death, myocardial infarction, or any repeat revascularisation. The SS was available in 2,041 out of 2,119 patients (96.3%). At two-year follow-up, patients with an SS >15 experienced higher rates of both TLF and POCE as compared to patients with medium and low SS (14.5% vs. 8.1% and vs. 5.9%, p<0.001; 22.7% vs. 14.9% and vs. 12.4%; p<0.001), respectively. Comparable rates of the composite endpoints were documented for both stent types in each category of SS. CONCLUSIONS: Increasing lesion complexity as assessed by SS was associated with higher rates of TLF and POCE in a contemporary PCI population with minimal exclusion criteria. BP-SES and DP-EES showed comparable performance across the entire spectrum of CAD severity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".