Bespoke valve sizing avoids annular rupture in patients treated with a balloon‐expandable transcatheter heart valve
Bibliographic record
Abstract
BACKGROUND: Annular and left ventricular outflow tract (LVOT) calcification increase the risk of annular rupture following transcatheter aortic valve replacement (TAVR). The outcomes of a strategy of routine use of a balloon-expandable valve (BEV) for all patients irrespective of annular or LVOT calcium is unknown. OBJECTIVES: We evaluated the impact of bespoke sizing on annular rupture in patients treated with a BEV. METHODS: All consecutive patients undergoing TAVR at a single centre (February 2020-February 2022) were treated only with a BEV. No other valve design was used. Annular/LVOT calcification was assessed using a standardized grading system. For each annular area, we determined the percentage valve oversizing with nominal deployment. The balloon deployment volume was then adjusted when required (over-/underfilled) to achieve over-sizing of approximately 5% in the presence of annular/LVOT calcium and 5%-10% in the absence of annular/LVOT calcium. Adjusted valve areas were assumed to change proportionately to the change in balloon deployment volume. RESULTS: Among 533 TAVR treated patients, annular/LVOT calcification was present in 166 (31.1%) and moderate or severe in 90 (16.9%). In patients with annular/LVOT calcification, the adjusted oversizing was 3.5 ± 3.6% and in patients without annular/LVOT calcification, the adjusted oversizing was 6.8 ± 4.7% (p < 0.001). There were no cases of annular rupture and no cases with more than mild paravalvular leak (PVL). Mild PVL was more frequent in patients with annular/LVOT calcium (10.8% vs 4.6%, p = 0.01). CONCLUSION: Bespoke BEV sizing by adjustment of balloon deployment volume avoided annular rupture in patients undergoing TAVR.
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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) | 0.001 | 0.008 |
| 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".