Valve hemodynamic performance and myocardial strain after implantation of a third-generation, balloon-expandable, transcatheter aortic valve
Bibliographic record
Abstract
BACKGROUND: Left ventricular (LV) mechanics are impaired in patients with severe aortic stenosis (AS); however, transcatheter aortic valve implantation (TAVI) may positively affect LV mechanics. Assessed herein is the performance of the SAPIEN 3 transcatheter heart valve (THV) and the effect of TAVI on LV function recovery, as assessed by global longitudinal strain (GLS). METHODS: A subset of patients from the SOURCE 3 registry (n = 276) from 16 European centers received SAPIEN 3 balloon-expandable THV. Echocardiography was performed at baseline, postprocedure, and at 1 year, including assessment of GLS using standard two-dimensional images, and was analyzed in a core laboratory. Paired analyses between baseline and discharge, baseline and at 1 year were conducted. RESULTS: Hemodynamic parameters were improved after TAVI and sustained to 1 year. At 1 year, the rate of moderate to severe paravalvular leaks (PVL), and moderate to severe mitral and tricuspid regurgitations were 1.8%, 1.7%, and 8.0%, respectively. The discharge GLS (-15.6 ± 5.1; p = 0.004; n = 149) improved significantly from baseline (-15.1 ± 4.8) following TAVI. This improvement was sustained at 1 year compared with baseline (-17.0 ± 4.6, p < 0.001; n = 100). Conversely, LV ejection fraction (LVEF) did not significantly change following TAVI (p = 0.47). CONCLUSIONS: Following TAVI with a third-generation THV, valve performances were good at 1 year with low PVL rate. The LV mechanics improved immediately after the procedure and were maintained at 1 year. These findings demonstrate the benefit of TAVI on LV mechanics, and suggests that GLS may be superior to LVEF in assessing this benefit. Clinicaltrial.gov number: NCT02698956.
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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 | 0.001 |
| 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".