The Role of Intraindividual Carotid Artery Variation in the Development of Atherosclerotic Carotid Artery Disease: A Literature Review
Bibliographic record
Abstract
Carotid artery disease (CAD) is associated with numerous risk factors, including hypertension, hyperlipidemia, hypercholesterolemia, diabetes mellitus, and smoking. These systemic risk factors do not affect the carotid arteries equally in most patients, resulting in asymmetrical bilateral and unilateral CAD. It is unclear if anatomic variations in the carotid arteries predispose an individual to formation of atherosclerotic CAD. We wanted to assess (1) the inter-individual or intra-individual anatomical variations in the carotid arteries and (2) whether anatomical variations predispose the development of atherosclerotic CAD. PubMed and Medline were utilized to identify relevant literature for critical appraisal, summarization and documentation. Inclusion and exclusion criteria were applied to narrow results and articles were critically appraised and analyzed. Evidence suggests that a low outflow/inflow ratio, elevated bifurcation height, and bifurcation angle are associated with increased risk for CAD. Sex and age demonstrated positive correlation with the disease. Additionally, tortuosity and kinking of the carotid arteries may affect the formation of CAD but coiling of the arteries is a natural age-dependent process and does not affect CAD development. This review suggests there are anatomic variations in the carotid arteries that increase the risk of developing carotid artery disease. The most significant risk factors include a low outflow/inflow ratio, increased internal carotid artery tortuosity, elevated bifurcation height, and bifurcation angle.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".