Feasibility of coronary access after transcatheter aortic valve implantation (TAVI): a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
INTRODUCTION: The expanding indications for transcatheter aortic valve implantation (TAVI) to younger, lower-risk patients, entails assessing not only the short-term clinical outcomes but also the long-term considerations for future interventions. The prevalence of coronary artery disease in TAVI patients is relevant, and the optimal timing of percutaneous coronary intervention remains a question. METHODS AND RESULTS: We conducted a systematic literature review and meta-analysis including 20 eligible studies involving 1660 patients who underwent coronary angiography after TAVI. The primary endpoint was the incidence of successful selective coronary re-access. Secondary endpoints included semi-selective and non-selective access rates. The analysis was stratified by balloon-expandable (BEVs) and self-expandable valve (SEVs) types. Successful coronary access after TAVI was feasible in the majority of patients, with a higher success rate observed for the left main (LM) compared to the right coronary artery (RCA). BEVs demonstrated the highest success rates in coronary ostia cannulation, achieving nearly 100% success for both LM and RCA. Among SEVs, the Acurate Neo and Evolut R/PRO showed superior success rates in selective coronary access (68 and 77% for LM; 57 and 72% for RCA, respectively) compared to the CoreValve (46% for LM and 49% for RCA). Notably, the majority of coronary angiograms were performed due to acute coronary syndrome, primarily non-ST-segment elevation myocardial infarction, and unstable angina. CONCLUSION: Selective coronary engagement after TAVI is generally achievable, with BEVs demonstrating superior success rates compared to SEVs. Among SEVs, the Acurate NEO showed better outcomes than the other types.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.028 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".