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Background <p>This study aimed to investigate the ability of an ultrasound-based risk stratification model integrating carotid intima thickness (CIT) and carotid-femoral pulse wave velocity (cfPWV) to aid in risk stratification and assessment of atherosclerotic cardiovascular disease (ASCVD) in patients with type 2 diabetes mellitus (T2DM), thereby providing an objective basis for identifying high-risk individuals and informing individualized management strategies.</p> Methods <p>A total of 105 patients with T2DM were enrolled in this study. According to the 10-year ASCVD risk score, patients were further classified into T2DM patients with low-to-moderate burden of other cardiovascular risk factors and T2DM patients with high burden of other cardiovascular risk factors. CIT was measured using high-resolution ultrasound to assess vascular structure, while cfPWV was evaluated using the automatic measurement of arterial stiffness (AMAS) system to assess vascular function. Logistic regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to identify independent risk factors of high ASCVD risk. Based on these risk factors, individual discriminative models and a nomogram were constructed. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to evaluate model performance, and differences among models were assessed using the DeLong test.</p> Results <p>CIT, cfPWV, and estimated glomerular filtration rate (eGFR) were identified as independent risk factors of high 10-year ASCVD risk in patients with T2DM. The areas under the curve (AUCs) for the CIT model, cfPWV model, eGFR model, combined CIT–cfPWV model, and the nomogram were approximately 0.781, 0.808, 0.797, 0.831, and 0.875, respectively. The constructed nomogram demonstrated excellent discrimination, calibration, and clinical applicability.</p> Conclusions <p>CIT and cfPWV show strong potential for identifying T2DM patients at high ASCVD risk as estimated by the China-PAR model. Incorporating these parameters into vascular evaluation may aid in risk stratification and provide a robust basis for individualized clinical intervention strategies. Prospective studies are needed to validate their prognostic value for future ASCVD events.</p>

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Vascular ultrasound-based risk stratification model for atherosclerotic cardiovascular disease in patients with type 2 diabetes mellitus

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月2日

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  • Cuie Chen,
  • Qiuxiao Xu,
  • Hong Xu,
  • Yiyun Xu,
  • Xueling He,
  • Minhao Lin,
  • Yuan Li,
  • Yinhua Li,
  • Lijuan Liu

摘要

Background

This study aimed to investigate the ability of an ultrasound-based risk stratification model integrating carotid intima thickness (CIT) and carotid-femoral pulse wave velocity (cfPWV) to aid in risk stratification and assessment of atherosclerotic cardiovascular disease (ASCVD) in patients with type 2 diabetes mellitus (T2DM), thereby providing an objective basis for identifying high-risk individuals and informing individualized management strategies.

Methods

A total of 105 patients with T2DM were enrolled in this study. According to the 10-year ASCVD risk score, patients were further classified into T2DM patients with low-to-moderate burden of other cardiovascular risk factors and T2DM patients with high burden of other cardiovascular risk factors. CIT was measured using high-resolution ultrasound to assess vascular structure, while cfPWV was evaluated using the automatic measurement of arterial stiffness (AMAS) system to assess vascular function. Logistic regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to identify independent risk factors of high ASCVD risk. Based on these risk factors, individual discriminative models and a nomogram were constructed. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to evaluate model performance, and differences among models were assessed using the DeLong test.

Results

CIT, cfPWV, and estimated glomerular filtration rate (eGFR) were identified as independent risk factors of high 10-year ASCVD risk in patients with T2DM. The areas under the curve (AUCs) for the CIT model, cfPWV model, eGFR model, combined CIT–cfPWV model, and the nomogram were approximately 0.781, 0.808, 0.797, 0.831, and 0.875, respectively. The constructed nomogram demonstrated excellent discrimination, calibration, and clinical applicability.

Conclusions

CIT and cfPWV show strong potential for identifying T2DM patients at high ASCVD risk as estimated by the China-PAR model. Incorporating these parameters into vascular evaluation may aid in risk stratification and provide a robust basis for individualized clinical intervention strategies. Prospective studies are needed to validate their prognostic value for future ASCVD events.