Optimal Oversizing in Transcatheter Aortic Valve Replacement with the Self-Expanding Evolut Valve System
Bibliographic record
Abstract
OBJECTIVES: Valve oversizing has been associated with reduced paravalvular leaks (PVL) and valve migration risk. However, no optimal cut-off oversizing value has been defined for the Evolut system (Medtronic). The aim of this study was to assess the relationship between the degree of oversizing and moderate-to-severe PVL and determine the optimal oversizing cut-off value. METHODS: We conducted a multicenter study that included 740 consecutive patients with multidetector computed tomography (CT) data. Valve size was selected according to manufacturer recommendations, with oversizing ranging from 10% to 30%. The primary endpoint was moderate-to-severe PVL. RESULTS: The median age was 84 years (79-87 years), with 58.4% women, and a median EuroSCORE II of 4.1% (2.4-7.3%). Moderate-to-severe PVL was observed in 7.0% of the patients. An inverse relationship was found between oversizing and both PVL (11.3%, 8.6%, 5.4%, and 2.7% for quartiles Q1 to Q4; P = .007) and the need for post-dilation (P = .016). The multivariable analysis showed an association between oversizing and PVL (OR: 0.915 for each 1%-increase, P = .002). The optimal oversizing cut-off value to predict PVL was 20%, and PVL was significantly higher in patients with oversizing less than 20% (10.5% vs.4.2%, P less than .001). There were no differences in major clinical events according to the degree of oversizing, and a higher oversizing did not translate into an increased risk of permanent pacemaker (18.4% vs18.3%, P = .976). CONCLUSIONS: In TAVR with the Evolut valve, a higher oversizing was associated with lower rates of moderate-to-severe PVL and a lower need for post-dilation, with no negative impact on procedural and early clinical outcomes. A 20% oversizing threshold could be suggested to reduce PVLs. Further prospective studies are warranted to validate optimal oversizing for this valve system.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".