Left-right commissural aortic root enlargement facilitates valve-in-valve transcatheter aortic valve implantation: A computed tomographic analysis
Bibliographic record
Abstract
Objective: Aortic root enlargement (ARE) at the left-right (LR) commissure may mitigate risk of coronary obstruction during future valve-in-valve (VinV) transcatheter aortic valve implantation (TAVI) by creating space for blood flow behind the LR surgical valve strut into the adjacent sinuses. We analyzed computed tomography (CT) scans after LR ARE to determine theoretical candidacy for future VinV TAVI. Methods: All patients undergoing LR ARE and bioprosthetic surgical aortic valve replacement (SAVR) between February 2023 and November 2024 were reviewed retrospectively. Postoperative CT scans were analyzed, modeling for both balloon-expandable (BEV) and self-expanding (SEV) valves. Risk of coronary obstruction was based on virtual transcatheter valve to coronary (VTC) and sinotubular junction (VTSTJ) distances, and measurements of the LR ARE patch. Results: There were 32 patients (62% female, 44% inpatient) who had LR ARE with bioprosthetic SAVR, including 22% with a concomitant Y ARE. There was no 30-day mortality or stroke. Postoperative mean gradient was 5.5 mm Hg. Overall, 85% of valves were 23 or 25 mm, representing upsizing by 1.7 ± 0.7 sizes. The patch was 26.2 ± 4.7 mm tall, with 6.2 ± 2.4 mm of space behind the LR strut. If a SEV were used, 94% would be safe for VinV TAVI with low risk of coronary obstruction; if balloon inflation were needed during TAVI (such as for BEV), 77% could have safe VinV TAVI. Conclusions: In this CT analysis, LR ARE carried low risk of coronary obstruction for future VinV TAVI and may benefit patients undergoing bioprosthetic SAVR.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".