ISSN 1004-4140
CN 11-3017/P
朱娜君, 方欣欣, 尹伊君, 等. 心绞痛患者斑块进展危险因素与冠状动脉CT血管成像指标的关系研究[J]. CT理论与应用研究, 2023, 32(2): 217-222. DOI: 10.15953/j.ctta.2022.219.
引用本文: 朱娜君, 方欣欣, 尹伊君, 等. 心绞痛患者斑块进展危险因素与冠状动脉CT血管成像指标的关系研究[J]. CT理论与应用研究, 2023, 32(2): 217-222. DOI: 10.15953/j.ctta.2022.219.
ZHU N J, FANG X X, YIN Y J, et al. Risk Factors of Plaque Progression in Patients with Angina Pectoris and Their Relationships with Coronary CT Angiography[J]. CT Theory and Applications, 2023, 32(2): 217-222. DOI: 10.15953/j.ctta.2022.219. (in Chinese).
Citation: ZHU N J, FANG X X, YIN Y J, et al. Risk Factors of Plaque Progression in Patients with Angina Pectoris and Their Relationships with Coronary CT Angiography[J]. CT Theory and Applications, 2023, 32(2): 217-222. DOI: 10.15953/j.ctta.2022.219. (in Chinese).

心绞痛患者斑块进展危险因素与冠状动脉CT血管成像指标的关系研究

Risk Factors of Plaque Progression in Patients with Angina Pectoris and Their Relationships with Coronary CT Angiography

  • 摘要: 目的:探讨心绞痛患者斑块进展危险因素与冠状动脉CT血管成像指标的关系。方法:回顾性分析2017年1月至2020年1月我院收治心绞痛患者共236例临床资料,根据是否发生斑块进展分组,比较两组一般资料和冠状动脉CT血管成像指标,采用Logistic回归模型评价心绞痛患者斑块进展独立危险因素,描绘ROC曲线分析基于冠状动脉CT血管成像指标构建的预测模型在斑块进展风险预测中的价值。结果:两组性别、合并高血脂比例、服用他汀类药物比例、冠状动脉狭窄程度、最小管腔面积、斑块总体积、重塑指数(RI)及基于CT的血流储备分数(CT-FFR)水平比较差异有统计学意义;单因素分析结果显示,冠状动脉狭窄程度、最小管腔面积、斑块体积、非钙化斑块体积、RI及CT-FFR水平与心绞痛患者斑块进展有关;多因素分析结果显示,RI和CT-FFR水平是心绞痛患者斑块进展的独立影响因素;ROC曲线分析结果显示,冠状动脉狭窄程度+RI+CT-FFR联合用于斑块进展预测AUC优于单纯狭窄程度、狭窄程度+RI。结论:RI和CT-FFR水平是导致心绞痛患者斑块进展的重要影响因素,基于两者的预测模型可更为准确识别斑块进展。

     

    Abstract: Objective: To investigate the risk factors of plaque progression in patients with angina pectoris and their relationships with coronary computed tomography (CT) angiography. Methods: Clinical data of 236 patients with angina pectoris were retrospectively analyzed from January 2017 to January 2020. All patients were grouped according to whether plaque progression occurred, and the general information and coronary CT angiography indexes were compared between the two groups. A logistic regression model was used to evaluate the independent risk factors of plaque progression in patients with angina pectoris. The receiver operating characteristic (ROC) curve was delineated to analyze the clinical value of the prediction model based on coronary CT angiography indicators in predicting plaque progression risk. Results: There were significant differences in sex, the proportion of hyperlipidemia, proportion of statins, degree of stenosis, minimum lumen area, total plaque volume, RI, and CT-derived fractional flow reserve (FFR) between the two groups. The results of single factor analysis showed that the degree of stenosis, the minimum lumen area, plaque volume, the volume of non-calcified plaque, RI, and CT-FFR levels were related to the plaque progression in patients with angina pectoris. Univariate analysis showed that the degree of stenosis, minimum lumen area, plaque volume, non-calcified plaque volume, RI, and CT-FFR levels were associated with plaque progression in patients with angina pectoris. Multivariate analysis showed that RI and CT-FFR levels were independent factors of plaque progression in patients with angina pectoris. ROC curve analysis showed that the combination of stenosis degree + RI + CT-FFR was better than that of simple stenosis degree and stenosis degree + RI in predicting the area under the curve of plaque progression. Conclusion: RI and CT-FFR levels are important factors leading to plaque progression in patients with angina pectoris. The prediction model based on RI and CT-FFR can more accurately identify plaque progression.

     

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