Biomechanical Properties of Common Carotid Arteries Assessed by Circumferential 2D Strain and β Stiffness Index in Patients With Ankylosing Spondylitis
Bibliographic record
Abstract
Objective. Ankylosing spondylitis (AS) is associated with an elevated risk of cardiovascular disease (CVD) related to atherosclerosis, preceded by arterial stiffness. We aimed to examine common carotid artery (CCA) biomechanical properties using ultrasound to calculate β stiffness index (indicating arterial stiffness) and, a more recently developed technique, 2-dimensional (2D) speckle tracking strain (indicating arterial motion and deformation, strain) to (1) compare with age- and sex-matched controls, and (2) analyze relationships between strain and stiffness with disease characteristics and traditional risk factors for CVD in patients with AS. Methods. In this cross-sectional study, a cohort of 149 patients with AS, mean age 55.3 ± 11.2 years, 102 (68.5%) men, and 146 (98%) HLA-B27–positive, were examined. Bilateral CCA were examined for circumferential 2D strain and β stiffness index. A subgroup of 46 patients was compared with 46 age- and sex-matched controls, both groups without hypertensive disease, diabetes, myocardial infarction, or stroke. Results. Mean bilateral circumferential 2D strain was lower in AS patients compared with controls (7.9 ± 2.6% vs 10.3 ± 1.9%, P < 0.001), whereas mean bilateral β stiffness index was higher (13.1 ± 1.7 mmHg/mm vs 12.3 ± 1.3 mmHg/mm, P = 0.02). In multivariable linear regression analyses, strain was associated with age, erythrocyte sedimentation rate, history of anterior uveitis, and treatment with conventional synthetic disease-modifying antirheumatic drugs (DMARD) and/or biological DMARD (R2 0.33), while stiffness was associated with age (R2 0.19). Conclusion. Both CCA circumferential 2D strain and β stiffness index differed between patients with AS and controls. Strain was associated with AS-related factors and age, whereas only age was associated with stiffness, suggesting that the obtained results reflect different pathogenic vascular processes.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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".