Membranous septum morphology and risk of conduction abnormalities after transcatheter aortic valve implantation
Bibliographic record
Abstract
BACKGROUND: There are limited data on the association of membranous septum (MS) morphology and transcatheter heart valve (THV) implantation depth, and the development of new conduction abnormalities (CA) after transcatheter aortic valve implantation (TAVI). AIMS: The aim of this study was to describe the morphology of the MS and predict the risk of new CA after TAVI based on the MS morphology and THV implantation depth. METHODS: Based on preprocedural CT scans, the MS depth was measured for every 25% of the entire MS width in 272 TAVI patients without preprocedural bundle branch block (BBB) or pacemaker. Post-procedural CT scans for THV implantation depth assessment were available in 130 of these patients. RESULTS: The MS depth was a median of 2.5 mm (IQR 1.4-3.8) deeper at the posterior edge when compared to the anterior edge of the MS. New CA developed in 7.1% of patients in whom the THV did not cross the lower MS border at its anterior edge (3.6% with new BBB and high degree CA, respectively), in 18.8% of patients (15.6% with new BBB and 3.1% with new high-degree CA) where the THV overlapped the lower MS border by <2.5 mm and in 47.1% of patients (24.3% with new BBB and 22.9% with new high-degree CA) with THV overlap of the lower MS border by ≥2.5 mm. CONCLUSIONS: The difference of the MS depth and THV implantation depth measured at the anterior edge of the MS predicted new CA after TAVI.
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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 | 0.000 | 0.003 |
| 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 | 0.001 |
| 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".