Bibliographic record
Abstract
Statins belong to a class of drugs known to inhibit 3-hydroxy 3-methylglutaryl coenzyme A (HMG CoA) reductase, and block hepatic cholesterol synthesis. Statins have been found to be highly effective in primary and secondary stroke prevention among medically managed patients with cardiovascular disease, and it appears that this benefit is largely owing to the non-cholesterol-lowering, so called pleiotropic, effects of statins. Over the past decade, agents such as beta-blockers, aspirin, or other antiplatelet medications have proven to reduce the incidence of adverse postoperative outcomes among vascular surgical patients and have rightfully assumed a place in our overall therapeutic armamentarium. There is growing evidence that statins may be especially effective in reducing cardiovascular morbidity and improving outcome following major vascular surgery. A recent study from Johns Hopkins Hospital demonstrated a threefold reduction in the rate of perioperative stroke (P < .05) and fivefold reduction of perioperative mortality (P < .05) among 1566 patients undergoing carotid endarterectomy (CEA). This benefit was confirmed in a series of 3360 CEAs performed at multiple hospitals throughout western Canada. Statin use was independently associated with a 75% reduction (OR: 0.25; 95%CI: 0.07-0.90) in the odds of death and a 45% reduction (OR: 0.55; 95% CI: 0.32-0.95) in the odds of ischemic stroke or death among patients with symptomatic carotid disease. A number of the pleiotropic effects of statin medications may be responsible for these clinical observations. Further work is necessary to better elucidate these mechanisms, as well as to determine the optimal agents, dosing, and timing of drug administration among patients undergoing carotid interventions. Nevertheless, in light of these data a strong case can be made to start patients on statin medications prior to CEA if time permits.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".