Impact of Coronary Artery Disease Severity Assessed With the SYNTAX Score on Outcomes Following Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
BACKGROUND: The influence of coronary artery disease (CAD) on clinical and echocardiographic outcomes after transcatheter aortic valve replacement (TAVR) is still controversial. We sought to evaluate the impact of CAD severity as measured by the SYNTAX score (SS) on patients undergoing TAVR. METHODS AND RESULTS: A total of 377 patients who underwent TAVR in 2 high-volume centers in North America were included in our retrospective analysis. A blinded angiographic core laboratory calculated the SS on all available coronary angiograms with the use of quantitative coronary analysis. Patients were stratified into 4 groups: (1) no CAD (SS=0); (2) low SS (SS between 1 and 22); (3) intermediate SS (SS between 23 and 32); and (4) high SS (SS ≥33). Patients who had undergone percutaneous coronary intervention within 6 months prior to TAVR were separated into 2 categories based on their residual SS (<8 and ≥8). Patients with previous coronary artery bypass grafting (CABG) were divided into 2 groups: (1) low CABG SS and (2) high CABG SS. The primary end point was a composite of all-cause mortality, myocardial infarction, and stroke. At 30 days and 1 year, both the presence and the severity of CAD had no impact on the rate of the combined primary end point and on all-cause mortality, cardiovascular mortality, and myocardial infarction. Patients with less complete revascularization (residual SS ≥8 versus residual SS <8 and low CABG SS versus high CABG SS, had similar rates of the combined primary end point, all-cause mortality, cardiovascular mortality, MI, and stroke, at both 30 days and 1 year. CONCLUSIONS: In our core laboratory-validated study, neither the severity of CAD nor completeness of revascularization after percutaneous coronary intervention or CABG were associated with clinical outcomes after TAVR, at both 30 days and 1 year.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".