Computed tomography-based oversizing and incidence of paravalvular aortic regurgitation and permanent pacemaker implantation with a new-generation self-expanding transcatheter heart valve
Bibliographic record
Abstract
AIMS: We aimed to evaluate the relationship between CT-based annular perimeter oversizing and the incidence of paravalvular aortic regurgitation (PAR) and permanent pacemaker (PPM) implantation in patients treated with the new self-expanding CENTERA transcatheter heart valve (THV) for severe aortic stenosis. METHODS AND RESULTS: One hundred and ninety-eight patients in the CENTERA-EU trial were stratified a priori into four groups based on the perimeter oversizing (2.5-10%, 10-15%, 15-20% and >20%). PAR at 30 days was moderate or higher in 0.6% of patients. The frequency of PPM implantation was 4.9%. The mean perimeter oversizing was 16.2±5.6%. For patients with a perimeter oversizing >10%, an inverse relationship between oversizing and ≥mild PAR was observed (43.3% for 10-15% oversizing; 37.7%, 15-20%; 33.3%, >20%). No association between oversizing and effective orifice area was observed. The optimal cut-off value of perimeter oversizing for the prediction of ≥mild PAR was 15.9% (AUC 0.718, 95% CI: 0.576, 0.860). No annular ruptures were observed. CONCLUSIONS: The CENTERA THV appears to have a wide range of sizing tolerance. The degree of oversizing to mitigate PAR is relatively low compared to other self-expanding transcatheter devices. There appears to be no compromise between occurrence of PAR and PPM across this wide range of oversizing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".