DurAVR – a novel biomimetic balloon-expandable transcatheter valve for TAVI, valve-in-valve TAVI and redo-TAVI
Bibliographic record
Abstract
BACKGROUND: The DurAVR transcatheter heart valve (THV) is a novel biomimetic balloon-expandable valve with promising early clinical results. AIMS: We aimed to assess the hydrodynamic performance of the DurAVR THV in native, valve-in-valve (ViV), and redo-transcatheter aortic valve implantation (TAVI) procedures against commercially available THVs on the bench. METHODS: The hydrodynamic function of the DurAVR THV was assessed by simulating native valve deployments at 0 mm, 3 mm, and 6 mm depths, compared to SAPIEN 3 (S3), Evolut PRO, Navitor, and ACURATE neo2 (ACn2) valves. For ViV simulations, THVs were implanted in 21 mm and 23 mm Magna Ease, Mosaic, and Hancock bioprostheses. For redo-TAVI simulations, the DurAVR THV was assessed within S3, Evolut PRO, Navitor, and ACn2 valves. RESULTS: and a mean gradient (MG) <6 mmHg. The DurAVR THV had nil to mild pinwheeling (0-2%) at all depths, while the S3 and Evolut PRO showed moderate pinwheeling at 6 mm depth. For ViV simulations, the DurAVR THV exhibited larger EOAs and lower MGs than the comparator THVs and showed no more than mild pinwheeling in all ViV configurations. For redo-TAVI simulations, the DurAVR THV exhibited larger EOAs and lower MGs in each simulation compared to all other THVs tested, with no more than mild pinwheeling observed in all configurations except when implanted within the Evolut PRO. CONCLUSIONS: In this bench study, the DurAVR THV demonstrated excellent hydrodynamic performance in native, ViV, and redo-TAVI simulations. Future large-scale studies are needed to confirm these findings in clinical application and further characterise the valve's short- and long-term performance.
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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 | 0.000 |
| 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 | 0.000 | 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".