Sex Differences in Thoracic Aortic Aneurysm Growth
Bibliographic record
Abstract
Women with thoracic aortic aneurysms (TAAs) have higher risk of acute aortic syndromes and death than men. We have shown that TAA growth is accelerated in women, helping explain the sex differences in TAA outcomes. Since aortic stiffness reflects the health of the aorta, we sought to determine the sex-specific role of aortic stiffness on TAA growth. One hundred thirty unoperated people with TAA were recruited. Maximal aneurysm size at the oldest and latest imaging studies was measured to calculate TAA growth rate. Aortic stiffness was assessed by carotid-femoral pulse wave velocity (cfPWV) using applanation tonometry. Multivariable linear regression adjusted for confounders assessed the association of cfPWV with TAA growth. Seventy-three percent of subjects were men. Mean±SD age, baseline aneurysm size, follow-up time, and cfPWV were 62.5±11.5 years, 45.3±4.0 mm, 3.3±3.0 years and 9.6±3.5 m/s, and not different based on sex. TAA growth rate was 0.96±1.00 mm/y in women and 0.45±0.58 mm/y in men ( P=0.006). In the whole group, cfPWV was independently associated with TAA growth (β±SE: 0.06±0.02, P=0.02). However, in sex-specific analyses cfPWV was independently associated with faster aneurysm growth in women (β±SE: 0.21±0.09, P=0.03), but not in men (β±SE: -0.002±0.02, P=0.94), with a significant sex×cfPWV interaction ( P<0.0001). In patients with TAA, aneurysm growth is more than twice as fast in women than men, and aortic stiffness is associated with greater TAA growth in women, but not in men. Our findings highlight greater aortic stiffness as an important correlate of TAA expansion in women.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".