Thoracic Aortic Aneurysm Growth in Bicuspid Aortic Valve Patients: Role of Aortic Stiffness and Pulsatile Hemodynamics
Bibliographic record
Abstract
Background Bicuspid aortic valve ( BAV ) is the most common congenital cardiac abnormality. A thoracic aortic aneurysm ( TAA ) is present in ≈50% of BAV patients, who also have an 8-fold higher risk of aortic dissection than the general population. Because the health of the aorta is directly reflected in its stiffness and pulsatile hemodynamics, we hypothesized that measures of aortic stiffness and arterial load would be associated with TAA growth in BAV . Methods and Results Twenty-nine unoperated participants with TAA due to BAV who had serial imaging were recruited. Aortic stiffness and steady and pulsatile arterial load were evaluated with validated methods that integrate arterial tonometry with echocardiography. TAA growth was assessed retrospectively based on available imaging, blinded to hemodynamic status. Multivariable linear regression assessed associations of aortic stiffness and hemodynamic variables with TAA growth, adjusting for potential confounders. Overall, 66% of participants were men. Mean±SD for age, baseline aneurysm size, growth rate, and follow-up time were 57.2±8.3 years, 46.9±3.6 mm, 0.75±0.81 mm/y, and 2.9±3.3 years, respectively. We found that greater aortic stiffness (β± SE for carotid-femoral pulse wave velocity: 0.30±0.13. P=0.03) and aortic characteristic impedance (β± SE : 0.46±0.18, P=0.02), as well as lower total arterial and proximal aortic compliance (β± SE : -0.44±0.21, P=0.05, and -0.63±0.16, P=0.001, respectively) were independently associated with faster aneurysm growth. Conclusions In patients with TAA due to BAV , measures of greater aortic stiffness and pulsatile arterial load indicate an association with accelerated aneurysm expansion. Assessing arterial hemodynamics may be useful for risk stratification and disease monitoring in TAA patients with BAV .
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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 | 0.004 |
| 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 | 0.001 |
| 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".