Thoracic Aortic Aneurysm Growth: Role of Sex and Aneurysm Etiology
Bibliographic record
Abstract
BACKGROUND: Thoracic aortic aneurysm (TAA) outcomes are worse in women than men, although reasons for sex differences are unknown. Because faster TAA growth is a risk factor for acute aortic syndromes, we sought to determine the role of sex and aneurysm etiology on TAA growth. METHODS AND RESULTS: Eighty-two consecutive unoperated subjects with TAA who had serial aneurysm measurements were recruited. In multivariable linear regression the association of female sex with aneurysm growth rate was assessed after adjustment for potential confounders. We also tested the interaction term sex×aneurysm etiology in the prediction of TAA growth. Seventy-four percent of subjects were men; mean±SD age was 62.4±11.9 years in men and 67.7±10.7 years in women (P=0.06). Forty-seven (57%) subjects had degenerative TAAs, and the remainder had heritable TAAs. Absolute baseline aneurysm size and follow-up time were not different between men and women. Aneurysm growth rate was 1.19±1.15 mm/y in women and 0.59±0.66 mm/y in men (P=0.02). Female sex remained significantly associated with greater aneurysm growth in multivariable analyses (β±SE: 0.35±0.12, P=0.005). In addition, female sex was associated with faster TAA growth only among those with degenerative TAA (β±SE: 0.33±0.08, P=0.0002) and not among those with heritable TAA (P=0.79), with a significant sex×etiology interaction (P=0.001). CONCLUSIONS: TAA growth rates are greater in women than men, and this difference is specific to women with degenerative TAAs. Our findings may explain sex differences in TAA outcomes and provide a foundation for future investigations of this topic.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".