Age-Specific Sex Differences in Magnetic Resonance Imaging-Depicted Carotid Intraplaque Hemorrhage
Bibliographic record
Abstract
Background and Purpose— Stroke rates are higher in men compared with women in the fourth through seventh decades of life, and higher rates may result from differences in carotid intraplaque hemorrhage (IPH), an unstable atherosclerotic plaque component. We report age-specific sex differences in the presence of magnetic resonance imaging-depicted carotid IPH. Methods— Patients (n=1115) underwent magnetic resonance imaging for carotid IPH between 2005 and 2014. Low-grade carotid stenosis patients (n=906) without prior endarterectomy were eligible for this cross-sectional study. Results— Of the 906 patients included (mean age±SD in years, 66.98±15.15), 63 (6.95%) had carotid IPH. In men and women, carotid IPH was present in 11.43% (48 of 420) and 3.09% (15 of 486), respectively ( P <0.0001). Multivariable logistic regression analysis confirmed greater odds of carotid IPH in men for all ages: 45 to 54 (odds ratio=45.45; 95% confidence interval, 3.43–500), 55 to 64 years (odds ratio=21.74; 95% confidence interval, 3.21–142.86), 65 to 74 years (odds ratio=10.42; 95% confidence interval, 2.91–37.04), and ≥75 years (odds ratio=5.00; 95% confidence interval, 2.31–10.75). Male sex modified the effect of age on the presence of carotid IPH (β=0.074; SE=0.036; P =0.0411). Conclusions— Men have greater age-specific odds of magnetic resonance imaging-depicted carotid IPH compared with women. With increasing age post-menopause, the odds of carotid IPH in women becomes closer to that of men. Delayed onset of carotid IPH in women, an unstable plaque component, may partly explain differential stroke rates between sexes, and further studies are warranted.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 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".