Carotid Artery Atherosclerosis: What is the Evidence for Drug Action?
Bibliographic record
Abstract
Carotid artery disease is a well-established cause of cerebrovascular events. This risk is predicted by the severity of stenosis and other plaque characteristics that can be documented using imaging techniques. Among these techniques, ultrasound is the most widely available. Increased carotid intima-media thickness (IMT) measured ultrasonically is associated with a higher risk for cerebrovascular as well as coronary heart disease. Furthermore, it is increasingly recognized that echolucent and heterogeneous carotid plaques in patients with high-grade carotid stenosis are associated with a greater risk for cerebrovascular events. Several local and systemic factors can influence plaque stability. Identifying the high-risk carotid plaque could improve selection for vascular intervention (surgery/angioplasty) and increase cost-effectiveness. Aggressive medical treatment should always be provided for these high-risk patients. For example, lipid-lowering, anthihypertensive and antiplatelet drugs decrease the carotid IMT, stabilize carotid plaques or reduce the risk of cerebrovascular and systemic events. Continuously evolving technology will lead to more accurate identification of high-risk carotid plaques. A combination of comprehensive non- or minimally-invasive imaging techniques together with measuring clinical and systemic biochemical markers of risk may facilitate the identification of the vulnerable plaque in the vulnerable patient, and help select the best treatment options.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".