Rapid Deployment Aortic Valves Deliver Superior Hemodynamic Performance in Vitro
Bibliographic record
Abstract
OBJECTIVE: Clinical studies have demonstrated excellent hemodynamic performance of rapid deployment aortic valves; however, few studies have directly compared the performance of these valves with conventional bioprosthetic valves. Thus, the hemodynamic function of the EDWARDS INTUITY valve (rapid deployment valve) was compared with the Edwards Magna Ease valve in vitro (Edwards Lifesciences Corp, Irvine, CA USA). METHODS: Elastomeric material was used to create an aortic root model that included a left ventricular outflow tract and aortic annulus. The model was based on reconstructions from 3-dimensional multislice computed tomography images in patients with aortic stenosis; the aortic root was scaled to a 21-mm effective annulus diameter. EDWARDS INTUITY valves (21-mm diameter) were deployed by stent frame expansion within the aortic root; Edwards Magna Ease valves (21-mm diameter) were sutured to the annulus. The left ventricular outflow tract area index (left ventricular outflow tract area/baseline area) and ellipticity or noncircularity as indexed by Dmax/Dmin were measured under a video microscope after valve placement. Hemodynamic data were collected under pulsatile flow with saline (70 beats per minute, 5 L/min, 100 mm Hg aortic pressure). RESULTS: Compared with the Edwards Magna Ease valve (n = 4), the EDWARDS INTUITY valve (n = 4) had a greater effective orifice area (1.56 ± 0.01 vs 1.85 ± 0.06 cm, P < 0.001) and a lower transvalvular pressure gradient (23.4 ± 0.51 vs 16.8 ± 1.3 mm Hg, P < 0.001). Multiple regression analysis showed that 93% of the variation in the effective orifice area and transvalvular pressure gradient was due to variation in the left ventricular outflow tract area index and ellipticity index. CONCLUSIONS: A clinically relevant aortic root model was developed to evaluate aortic valve performance. The superior performance of the EDWARDS INTUITY valve seemed to be related to both a greater inflow area and a more circular left ventricular outflow tract.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".