Feasibility of Coronary Access Following Redo-TAVR for Evolut Failure: A Computed Tomography Simulation Study
Bibliographic record
Abstract
BACKGROUND: Coronary accessibility following redo–transcatheter aortic valve replacement (redo-TAVR) is increasingly important, particularly in younger low-risk patients. This study aimed to predict coronary accessibility after simulated Sapien-3 balloon-expandable valve implantation within an Evolut supra-annular, self-expanding valve using pre-TAVR computed tomography (CT) imaging. METHODS: A total of 219 pre-TAVR CT scans from the Evolut Low-Risk CT substudy were analyzed. Virtual Evolut and Sapien-3 valves were sized using CT-based diameters. Two initial Evolut implant depths were analyzed, 3 and 5 mm. Coronary accessibility was evaluated for 2 Sapien-3 in Evolut implant positions: Sapien-3 outflow at Evolut node 4 and Evolut node 5. RESULTS: With a 3-mm initial Evolut implant depth, suitable coronary access was predicted in 84% of patients with the Sapien-3 outflow at Evolut node 4, and in 31% of cases with the Sapien-3 outflow at Evolut node 5 ( P <0.001). Coronary accessibility improved with a 5-mm Evolut implant depth: 97% at node 4 and 65% at node 5 ( P <0.001). When comparing 3- to 5-mm Evolut implant depth, sinus sequestration was the lowest with Sapien-3 outflow at Evolut node 4 (13% versus 2%; P <0.001), and the highest at Evolut node 5 (61% versus 32%; P <0.001). CONCLUSIONS: Coronary accessibility after Sapien-3 in Evolut redo-TAVR relates to the initial Evolut implant depth, the Sapien-3 outflow position within the Evolut, and the native annular anatomy. This CT-based quantitative analysis may provide useful information to inform and refine individualized preprocedural CT planning of the initial TAVR and guide lifetime management for future coronary access after redo-TAVR. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02701283.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".