Bioprosthetic Valve Fracture Improves the Hemodynamic Results of Valve-in-Valve Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
Background— Valve-in-valve (VIV) transcatheter aortic valve replacement (TAVR) may be less effective in small surgical valves because of patient/prosthesis mismatch. Bioprosthetic valve fracture (BVF) using a high-pressure balloon can be performed to facilitate VIV TAVR. Methods and Results— We report data from 20 consecutive clinical cases in which BVF was successfully performed before or after VIV TAVR by inflation of a high-pressure balloon positioned across the valve ring during rapid ventricular pacing. Hemodynamic measurements and calculation of the valve effective orifice area were performed at baseline, immediately after VIV TAVR, and after BVF. BVF was successfully performed in 20 patients undergoing VIV TAVR with balloon-expandable (n=8) or self-expanding (n=12) transcatheter valves in Mitroflow, Carpentier-Edwards Perimount, Magna and Magna Ease, Biocor Epic and Biocor Epic Supra, and Mosaic surgical valves. Successful fracture was noted fluoroscopically when the waist of the balloon released and by a sudden drop in inflation pressure, often accompanied by an audible snap. BVF resulted in a reduction in the mean transvalvular gradient (from 20.5±7.4 to 6.7±3.7 mm Hg, P <0.001) and an increase in valve effective orifice area (from 1.0±0.4 to 1.8±0.6 cm 2 , P <0.001). No procedural complications were reported. Conclusions— BVF can be performed safely in small surgical valves to facilitate VIV TAVR with either balloon-expandable or self-expanding transcatheter valves and results in reduced residual transvalvular gradients and increased valve effective orifice area.
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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 | 0.002 |
| 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".