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Analysis of Predictive Model of Coronary Vulnerable Plaque under Hemodynamic Numerical Simulation
Qiang Song1, Mingwei Chen2, Jin Shang3
1Department of Structural Heart Disease, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China.
Insights
Predicting vulnerable plaque, a cause of coronary events, can be improved by combining serum biochemical markers. This noninvasive method shows high diagnostic value for cardiovascular disease treatment.
Area of Science:
- Cardiovascular Medicine
- Biochemistry
- Biomedical Engineering
Background:
- Vulnerable plaque is a primary cause of clinical coronary events.
- Cytokines contribute to plaque instability, necessitating early prediction for effective cardiovascular disease management.
Purpose of the Study:
- To investigate the predictive value of serum biochemical markers for vulnerable plaque in patients with acute coronary syndrome (ACS).
- To assess the efficacy of combining multiple biochemical markers for noninvasive vulnerable plaque detection.
Main Methods:
- Computational fluid dynamics (CFD) simulated hemodynamics around plaques.
- Serum biochemical markers were analyzed in 224 low-risk ACS patients.
- Vulnerable plaques were identified based on serum marker distribution.
Main Results:
- CFD accurately characterized plaque hemodynamics.
- Age, hyperlipidemia history, apolipoprotein B (apoB), adiponectin (ADP), and sE-Selection were identified as risk factors.
- Combining five markers yielded a high area under the curve (AUC) of 0.826 for prediction.
Conclusions:
- A combination of multiple serum biochemical markers offers high diagnostic value for predicting vulnerable plaque.
- This noninvasive approach is convenient and suitable for clinical application in cardiovascular disease management.
Objective:
Vulnerable plaque is considered to be the cause of most clinical coronary arteries, and linear cytokines are an important factor causing plaque instability. Early prediction of vulnerable plaque is of great significance in the treatment of cardiovascular diseases.
Methods:
Computational fluid dynamics (CFD) was used to simulate the hemodynamics around plaques, and the serum biochemical markers in 224 patients with low-risk acute coronary syndrome (ACS) were analyzed. Vulnerable plaques were predicted according to the distribution of biochemical markers in serum.
Results:
CFD can accurately capture the hemodynamic characteristics around the plaque. The patient's age, history of hyperlipidemia, apolipoprotein B (apoB), adiponectin (ADP), and sE-Selection were risk factors for vulnerable plaque. Area under curve (AUC) values corresponding to the five biochemical markers were 0.601, 0.523, 0.562, 0.519, 0.539, and the AUC value after the combination of the five indicators was 0.826.
Conclusion:
The combination of multiple biochemical markers to predict vulnerable plaque was of high diagnostic value, and this method was convenient and noninvasive, which was worthy of clinical promotion.
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