Transcatheter Aortic Valve Implantation with ACURATE neo: Results from the PROGRESS PVL Registry
Bibliographic record
Abstract
Objectives. The PROGRESS PVL registry evaluated transcatheter aortic valve implantation (TAVI) in patients treated with ACURATE neo, a supra-annular self-expanding bioprosthetic aortic valve. Background. While clinical outcomes with TAVI are comparable with those achieved with surgery, residual aortic regurgitation (AR) and paravalvular leak (PVL) are common complications. The ACURATE neo valve has a pericardial sealing skirt designed to minimize PVL. Methods. The primary endpoint was the rate of total AR over time, as assessed by a core echocardiographic laboratory. The study enrolled 500 patients (mean age: 81.8 +/- 5.1 years; 61% female; mean baseline STS score: 6.0 +/- 4.5%) from 22 centers in Europe and Canada; 498 patients were treated with ACURATE neo. Results. The rate of >= moderate AR was 4.6% at discharge and 3.1% at 12 months; the rate of >= moderate PVL was 4.6% at discharge and 2.6% at 12 months. Paired analyses showed significant improvement in overall PVL between discharge and 12 months (P < 0.001); 64.6% of patients had no change in PVL grade, 24.9% improved, and 10.5% worsened. Patients also exhibited significant improvement in transvalvular gradient (P < 0.001) and effective orifice area (P=0.01). The mortality rate was 2.2% at 30 days and 11.3% at 12 months. The permanent pacemaker implantation (PPI) rate was 10.2% at 30 days and 12.2% at 12 months. Conclusions. Results from PROGRESS PVL support the sustained safety and performance of TAVI with the ACURATE neo valve, showing excellent valve hemodynamics, good clinical outcomes, and significant interindividual improvement in PVL from discharge to 12-month 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".