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首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >Subclinical atherosclerosis modeling: integration of coronary artery calcium score to Framingham equation
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Subclinical atherosclerosis modeling: integration of coronary artery calcium score to Framingham equation

机译：亚临床动脉粥样硬化模型：冠状动脉钙分数与Framingham方程的整合

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Medical prevention consists to identify as soon as possible apparently healthy individuals who develop a disease and to engage them for active preventive treatment. Several cross-sectional studies of general populations or high cardiovascular risk have shown that coronary calcium score (coronary artery calcium, CAC) was positively associated with traditional risk factors (hypertension, dyslipidemia, diabetes, and smoking) and some new risk factors (fibrinogen). In this work, we first calculated, among 618 men, the risk of 10-years cardiovascular heart disease (CHD) according to the Framingham risk model, and then we calculated the probability that the CAC score of an individual falls in all four CAC categories (0, 1-100, 101-400 and > 400). We obtained risk factors adjusted relative risk (RR) estimates from a meta-analysis comparing the risk of coronary heart disease in individuals with CAC scores of 1-100 (RR = 1.7), 101 - 400 (RR = 3.0) and> 400 (RR = 4.3) with the risk of a person with a CAC score zero. The new model for the risk of CHD for each CAC score category were then calculated assuming an average 1-year risk of CHD and risk assessment of the four CAC score categories, weighted by the probability that scores fall into each category. The combination of modeling the CCA with the modeling of conventional risk factors allows obtaining a remarkable predictive value that can improve the assessment of overall risk Framingham through the reclassification of the risk of CHD to an extent which may be clinically important.
机译：医疗预防由以尽快看起来健康的人谁开发的疾病，并让他们参与主动预防性治疗识别。普通人群或高心血管风险的几个横断面研究表明，冠状动脉钙化评分（冠状动脉钙化，CAC）呈正与传统危险因素（高血压，血脂异常，糖尿病，吸烟）和一些新的风险因素（纤维蛋白原）关联。在这项工作中，我们首先根据Framingham风险模型计算，当中618人，10年风险心血管心脏疾病（CHD），然后我们计算出一个人的CAC得分落在所有四个CAC类别的概率（0，1-100，101-400和> 400）。我们得到调整相对危险度（RR），风险因素的估计从荟萃分析比较冠状动脉心脏疾病的风险与1-100（RR = 1.7），101 CAC评分个人 - 400（RR = 3.0）和“400（ RR = 4.3）与CAC中的人的风险评分为零。冠心病的每个CAC评分类别风险的新模式，然后计算假设CHD和四个CAC评分类别的风险评估的平均1年的风险，由分数落入每个类别的概率加权。该CCA与常规风险因子的模型建模的组合允许获得可改善总体风险弗雷明汉通过CHD的风险的重新分类的评估可能是临床上重要的程度显着的预测值。

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