Gender differences in carotid imaging and revascularization following stroke
Bibliographic record
Abstract
BACKGROUND: Carotid endarterectomy is performed less often in women than in men, but it is unknown whether this reflects differences in screening rates, disease prevalence, or other factors. METHODS: This was a cohort study of consecutive patients with acute stroke or TIA admitted to 11 Ontario stroke centers participating in the Registry of the Canadian Stroke Network between July 1, 2003, and September 30, 2007. We compared rates of carotid imaging, the severity of carotid stenosis, and rates of carotid endarterectomy or angioplasty within 6 months of the index event in women vs men. RESULTS: We studied 6,389 patients (48% women) with ischemic stroke or TIA. Women were less likely than men to undergo carotid imaging (81% vs 86%, p < 0.0001); however, when the analysis was limited to patients without apparent contraindications to surgery, 92% received carotid imaging, with no difference between women and men. Women were less likely than men to have severe carotid stenosis (7.4% vs 11.5%, p < 0.0001). Women were half as likely as men to undergo carotid revascularization within 6 months of the index event (odds ratio 0.51, 95% confidence interval 0.37 to 0.70), but this gender difference was no longer significant in the subgroup with severe carotid stenosis (odds ratio 0.75, 95% confidence interval 0.49 to 1.15). CONCLUSIONS: Although women with ischemic stroke or TIA are less likely than men to undergo carotid screening and revascularization, this difference is largely explained by potential contraindications to surgery and by sex differences in the severity of carotid disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".