Speckle tracking carotid artery circumferential strain is a marker of arterial sclerosis but not coronary atherosis
Bibliographic record
Abstract
PURPOSE: Circumferential speckle tracking carotid artery strain is a novel method of quantifying vessel wall stiffness. We hypothesized that carotid wall stiffness would be associated with carotid intimal medial thickening (a medial process associated with risk factors), but not coronary artery disease (an intimal process). METHODS: Bilateral carotid artery ultrasound was conducted on outpatients who had previously undergone elective coronary angiography. Mean carotid artery far wall circumferential strain (FWCS) was assessed for correlations with coronary angiographic stenosis, cardiac risk factors, carotid intima-media thickness (CIMT), and carotid plaque. RESULTS: One hundred and sixty five (165) patients were studied. No significant association was found between the presence of coronary artery disease on angiography and mean FWCS. FWCS was higher in current tobacco smokers. In addition, carotid strain was found to decrease with increased age (r = -0.33, P < 0.001). When adjusted for pulse pressure (PP), FWCS/PP was negatively correlated with mean CIMT (r = -0.29, P = 0.002) and bulb maximum plaque height (r = -0.27, P = 0.004). Hypertension and diabetes were associated with decreased FWCS/PP (increased wall stiffness). CONCLUSIONS: While no clear relationship between carotid strain and coronary artery disease was observed, increased CIMT, carotid plaque, and cardiac risk factors were associated with decreased carotid strain. Further work is required to explore the relationship between carotid strain and cardiovascular events.
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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 | 0.001 | 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) | 0.001 | 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".