Bibliographic record
Abstract
Carotid endarterectomy is the standard of care for people with severe symptomatic carotid stenosis. We analyzed population administrative data and clinical trial data to determine whether sex differences exist in the use and outcomes of this surgical procedure. We studied patients in Ontario who underwent carotid endarterectomy between 1982 and 1994 (n = 12,949) and patients with severe carotid stenosis who were enrolled in two randomized trials of endarterectomy (n = 1646). We compared the proportion of men and women who underwent carotid endarterectomy in each group, over time, and after adjustment for demographic factors. Men were twice as likely as women to receive carotid endarterectomy in the administrative analysis (65% versus 35%, p < 0.001) and in the clinical trial analysis (70% versus 30%, p < 0.001). The relatively lower use in women was consistent in every age group and in every year studied. Men in the administrative database were somewhat less likely than women to die or be institutionalized after surgery (5% versus 6%, p = 0.007). Men in the clinical trial database were also less likely than women to experience perioperative stroke or death, although the results were not statistically significant (6% versus 7%, p = 0.32). Patients who were assigned to surgical therapy, compared with those assigned to medical therapy, had a significant decrease in the risk of adverse events at 1 year, and the net benefit appeared similar in women and men. Carotid endarterectomy is performed relatively infrequently on women despite their similar lifetime burden of disease and similar short-term perioperative risks compared with men.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".