Effect of size and position of self-expanding transcatheter valve on haemodynamics following valve-in-valve procedure in small surgical bioprostheses: an in vitro study
Bibliographic record
Abstract
AIMS: The valve-in-valve (ViV) procedure has become a valuable alternative for the treatment of failed surgical bioprostheses (BP) in high-risk patients. However, in small BP, the clinical outcomes have been suboptimal due to high post-procedural gradients. We aimed to examine the effect of size and position of the self-expanding transcatheter heart valve (THV) CoreValve on the haemodynamics of ViV within small BP. METHODS AND RESULTS: Sizes 23 and 26 mm of the CoreValve were implanted in sizes 19 and 21 mm of three BP models: Trifecta, Mitroflow and Epic Supra. The THV was tested in three positions -normal (manufacturer recommendation), low (4 mm below normal) and high (4 mm above normal)- using a pulse duplicator. Haemodynamics were assessed by Doppler echocardiography and flowmeter, and GOA with a high-speed camera. Higher implantation was associated with lower residual gradients (normal position: -9%, high: -25% versus low). High position was, however, associated with increased risk of regurgitation in the Mitroflow and embolisation in the Epic Supra. Using a 26 mm THV instead of a 23 mm was associated with larger EOAs in the Trifecta, smaller in the Mitroflow, and increased risk of embolisation in the Epic Supra. CONCLUSIONS: Supra-annular positioning of the CoreValve THV is associated with improved post-ViV haemodynamics in small surgical BP. The haemodynamic outcomes are highly dependent on the model and size of surgical BP.
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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 | 0.000 | 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) | 0.002 | 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".