New Insights and Perspective on Bioprosthetic Valve Fracture From Bench Testing and Computed Tomography Analysis
Bibliographic record
Abstract
Background: Bioprosthetic valve fracture (BVF) during valve-in-valve TAVR (transcatheter aortic valve replacement) is a procedural adjunct designed to optimize the expansion of the transcatheter heart valve and reduce patient-prosthesis mismatch by using a high-pressure balloon to intentionally fracture the surgical heart valve (SHV). Methods: We performed bench testing on 15 bioprosthetic SHV to examine the optimal balloon size and pressure for BVF. We assessed morphological changes and expansion of SHV by computed tomography angiography. Successful BVF was defined as balloon waist disappearance on fluoroscopy and/or sudden pressure drop during balloon inflation. Results: Nine valves met the definition of BVF, 3 of which were confirmed by disruption of the stent frame. We classified surgical valves into 3 subsets: 1) fracturable with metal stent frame (MSF), 2) fracturable with polymer stent frame (PSF) and 3) nonfracturable. In general, valves with MSF were fractured using a balloon size = true internal diameter plus 3-5 mm inflated at high pressure (16-20 ATM) whereas valves with PSF could be fractured with a balloon size = true internal diameter plus 3-5 mm and lower balloon pressure (6-14 ATM). Gains in computed tomography angiography derived inflow area after BVF were 12.3% for MSF and 3.6% for PSF SHV. Conclusions: Gains in CT-determined valve area after BVF depend on the physical properties of the SHV, which in turn influences pressure thresholds and balloon sizing strategy for optimal BVF. Elastic recoil of PSF valves limits the gains in inflow area after BVF.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".