An in vitro comparison of internally versus externally mounted leaflets in surgical aortic bioprostheses
Bibliographic record
Abstract
OBJECTIVES: To improve haemodynamic performance, design modifications of prosthetic valves have been proposed with each new generation of valves. These different designs also impact the amount of mechanical wear, because mechanical stresses are distributed differently. Because long-term evidence for new prosthetic valves is lacking, this in vitro study compared hydrodynamic performance and durability among 3 currently available bioprosthetic valves with internally (IMLV) or externally mounted leaflets (EMLV). METHODS: Prostheses of the internally mounted Medtronic Avalus and Carpentier-Edwards Perimount Magna Ease valves were compared to prostheses of the externally mounted Abbott Trifecta valve. For each labelled size (e.g. 19, 21 and 23) of the 3 types, 3 valves underwent accelerated wear testing for up to 600 million cycles, corresponding to ∼15 years of simulated wear. The valves underwent hydrodynamic testing and visual inspection. RESULTS: EMLV had the largest effective orifice area and lowest pressure gradient for each labelled size at baseline and 600 million cycles; the effective orifice area and the pressure gradient were equivalent for the 2 types of IMLV. Five of 9 EMLVs had at least 1 hole or tear in the leaflet tissue around the stent posts, which resulted in severe regurgitation at 500 million cycles in 2 cases. All IMLVs were intact at 600 million cycles with minimal tissue wear. CONCLUSIONS: EMLV showed superior hydrodynamic performance but inferior mechanical durability compared to IMLV after 600 million cycles of testing. The primary failures were because of significant mechanical abrasion in the commissural region, which may warrant close monitoring of EMLV during long-term follow-up.
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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 | 0.001 |
| 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) | 0.001 | 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".