Effects of transcatheter aortic valve implantation on ascending aorta wall elastic properties: Tissue Doppler imaging and strain Doppler echocardiography study
Bibliographic record
Abstract
BACKGROUND: Aortic elastic properties are determinants of left ventricular function by means of ventriculo-arterial coupling and indicators of cardiovascular risk. Aortic valve stenosis surgical replacement temporary reduces aortic function damaging vasa vasorum, while transcatheter aortic valve implantation (TAVI) does not influence it in the short term. We studied aortic distensibility, stiffness, M-mode strain and tissue strain after 6 and 12 months from TAVI. METHODS: We enrolled 15 patients with symptomatic severe aortic stenosis who underwent CoreValve prosthesis (Medtronic, Minneapolis, MN) implantation. Everyone had blood pressure measurement and echocardiography registration before TAVI and after 6 and 12 months. RESULTS: After TAVI NYHA class (p = 0.016), peak and mean aortic valve gradients (p < 0.001 for both) improved. Aortic distensibility increased (p = 0.032 in the first 6 months, p = 0.005 in the second 6 months, and p = 0.003 from baseline to 12 months), as well as stiffness decreased (p = 0.034; 0.090; 0.001), M-mode strain and tissue strain ameliorated (p = 0.041; 0.004; 0.004; and p = 0.013; 0.002; 0.001, respectively), tissue Doppler imaging improved (S' wave: p = 0.289; 0.347; 0.018. E' wave: p = 0.018; 0.113; 0.007. A' wave: p = 0.002; 0.532; 0.001). Moreover, some left ventricular parameters improved at 6 months, such as ejection fraction (from 49 ± 16 to 57 ± 11%; p = 0.044) and diastolic interventricular septum thickness (from 14 ± 2 to 12 ± 2 mm; p = 0.010). Even systolic pulmonary artery pressure (p = 0.019) and left diastolic dysfunction grade ameliorated (p = 0.042). CONCLUSIONS: For the first time we demonstrated that aortic elastic properties improve at 6 and 12 months after TAVI, thus influencing ventriculo-arterial coupling and ameliorating left ventricular function.
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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 | 0.001 |
| 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".