Purpose <p>Analyzing the correlation between carotid stiffness and atherosclerotic cardiovascular disease (ASCVD) risk, and determine elastic modulus (EM) threshold.</p> Methods <p>In this single-center, cross-sectional retrospective observational study, 229 patients without carotid plaque were consecutively enrolled between July 2021 and August 2022. ASCVD risk was calculated by simpler Framingham model and categorized into low (<i>N</i> = 108), moderate (<i>N</i> = 58) and high risk groups (<i>N</i> = 63). Shear-wave elastography was used to quantify carotid stiffness, and the resulting values were analyzed for their association with ASCVD risk.</p> Results <p>Among 229 participants without carotid plaque, 108 (47.2%), 58 (25.3%), and 63 (27.5%) were categorized as low, moderate, and high ASCVD risk, respectively. Carotid stiffness parameters (Emean and Emax) were significantly lower in the low-risk group compared with moderate- and high-risk groups (<i>p</i> &lt; 0.05), with no significant differences between the latter two groups. Multivariable linear regression revealed that each one-level increase in ASCVD risk category was independently associated with increased Emean (β = 0.933&#xa0;kPa, <i>p</i> &lt; 0.001), Emax (β = 1.222&#xa0;kPa, <i>p</i> = 0.005), and Emin (β = 0.564&#xa0;kPa, <i>p</i> = 0.011). All three stiffness parameters independently predicted cardiovascular events: Emean (OR = 1.105, 95%CI:1.009–1.211), Emax (OR = 1.067, 95%CI:1.002–1.136), and Emin (OR = 1.129, 95%CI:1.005–1.267). For CVD detection, Emean demonstrated optimal specificity (0.795) at a cutoff of 8.177&#xa0;kPa (AUC = 0.629), whereas ASCVD risk category alone achieved an AUC of 0.644 (sensitivity 0.717, specificity 0.528). Combined models improved specificity but reduced sensitivity without significantly enhancing AUC values.</p> Conclusion <p>EM was associated with ASCVD risk in this exploratory cohort; whether it can reliably distinguish risk categories awaits prospective validation.</p>

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A cross-sectional study: carotid artery stiffness in individuals with varying cardiovascular disease risk using shear wave elasticity

  • Chuanjian Chen,
  • Junni Shi,
  • Yanchun Xie,
  • Lixia Zhang,
  • Shengnan Li,
  • Yunqian Huang,
  • Man Chen

摘要

Purpose

Analyzing the correlation between carotid stiffness and atherosclerotic cardiovascular disease (ASCVD) risk, and determine elastic modulus (EM) threshold.

Methods

In this single-center, cross-sectional retrospective observational study, 229 patients without carotid plaque were consecutively enrolled between July 2021 and August 2022. ASCVD risk was calculated by simpler Framingham model and categorized into low (N = 108), moderate (N = 58) and high risk groups (N = 63). Shear-wave elastography was used to quantify carotid stiffness, and the resulting values were analyzed for their association with ASCVD risk.

Results

Among 229 participants without carotid plaque, 108 (47.2%), 58 (25.3%), and 63 (27.5%) were categorized as low, moderate, and high ASCVD risk, respectively. Carotid stiffness parameters (Emean and Emax) were significantly lower in the low-risk group compared with moderate- and high-risk groups (p < 0.05), with no significant differences between the latter two groups. Multivariable linear regression revealed that each one-level increase in ASCVD risk category was independently associated with increased Emean (β = 0.933 kPa, p < 0.001), Emax (β = 1.222 kPa, p = 0.005), and Emin (β = 0.564 kPa, p = 0.011). All three stiffness parameters independently predicted cardiovascular events: Emean (OR = 1.105, 95%CI:1.009–1.211), Emax (OR = 1.067, 95%CI:1.002–1.136), and Emin (OR = 1.129, 95%CI:1.005–1.267). For CVD detection, Emean demonstrated optimal specificity (0.795) at a cutoff of 8.177 kPa (AUC = 0.629), whereas ASCVD risk category alone achieved an AUC of 0.644 (sensitivity 0.717, specificity 0.528). Combined models improved specificity but reduced sensitivity without significantly enhancing AUC values.

Conclusion

EM was associated with ASCVD risk in this exploratory cohort; whether it can reliably distinguish risk categories awaits prospective validation.