Abstract 13173: Impact of Bicuspid Aortic Valve Morphology on Computed Tomography Valvular Calcification in Aortic Stenosis and Sex Differences
Bibliographic record
Abstract
Introduction: Aortic valve calcification (AVC) is the key pathophysiology underlying aortic stenosis (AS). We aimed to assess computed tomography AVC in AS by valve morphology (bicuspid [BAV] vs. tricuspid aortic valve[TAV]) and sex. Methods: Retrospective study of patients with echocardiographic AS severity and AVC assessments within six months. Patients with > moderate aortic regurgitation, prosthetic aortic valve, or indeterminate aortic valve morphology were excluded. Severe AS with high mean gradient (MG) was defined as aortic valve area (AVA)≤1cm2 or indexed AVA≤0.6 cm2/m2 + MG≥40 mmHg. Results: Of 2647 patients, 361(65% men) had BAV and 2286(59% men) had TAV, age 65±11 vs. 80±9 years(p<0.001), AVA 1.07±0.42 vs. 0.90±0.25 cm2(p<0.001), MG 41±16 vs.42±14 mmHg(p=0.4) for BAV and TAV, respectively. For both BAV and TAV groups, age, MG, and severe AS frequency were similar between women and men(all p≥0.06). BAV morphology affected AVC-AS severity and AVC-sex associations (p for interactions <0.001): as AS severity increased, mean AVC difference became larger between BAV-men and TAV-men, but smaller between BAV-women and TAV-women. Similar patterns were observed in AVC density (AVCd, AVC divided by left ventricular outflow tract diameter)-AS severity and AVCd-sex associations (p for interactions < 0.001). In patients with concordant AS severity and MG levels, the best BAV AVC-cutoff for detecting severe AS + high MG by area-under-the-curve analysis was 924 AU for BAV-women and 2851 AU for BAV-men, different from guideline-recommended AVC-thresholds (1200 for women and 2000 for men). The best BAV AVCd cutoff was 289 for BAV-women and 476 for BAV-men, similar to the cutoffs for patients predominantly with TAV (292 for women and 476 for men from Clavel MA JACC 2013). The BAV-AVC threshold identified more patients with severe AS than guideline-recommended threshold in BAV-women (84% vs 74%, p<0.001), but not in BAV-men. Conclusions: Valvular calcium accretion in AS was different by valve morphology and sex. As compared to TAV, BAV-women exhibited the least calcification while BAV-men exhibited the highest. Such patterns may impact the sensitivity of guideline-recommended AVC thresholds for detecting severe AS in BAV patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.007 | 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".