Predictors for coronary artery calcium score and differences in its distributions between populations with and without diabetes

Cyc Guo, A. Kinninger, S. Roy, I. Golub, VR Muller, A. Johanis, J. Luce, M. Budoff
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Abstract

Background and aims Coronary artery calcium (CAC) scoring is a method of measure coronary plaque burden and has been shown as an excellent predictor for atherosclerotic cardiovascular disease (ASCVD). Diabetes mellitus (DM) is an established risk factor for ASCVD, but a certain portion of patients with DM do not have CAC (score = 0). We conducted a study to identify predictors of the CAC score other than DM and to compare distributions of the score between populations with and without DM. Methods We included participants who were referred to receive CAC scanning at a large imaging center from July 1992 to July 2020. The distribution of the CAC scores and baseline characteristics were compared between participants with and without DM. Univariate logistic regressions followed by multivariate analysis were performed using CAC score > 0 as outcome to identify independent factors contributing to the score. Results A total of 35,086 participants (mean age 58.9 ± 11.9 years, 63% male, 69% white) were included in the analysis. Of them, 11.8% had DM, 56% had hyperlipidemia, 38% had hypertension, and 7% were current smokers. A higher proportion of participants in the DM group had CAC score > 0 (82% vs 62%, p <0.01), but a substantial portion (18%) of DM patients had no CAC. Distribution of CAC score was also variable among participants with and without DM. Multivariate analysis showed that DM, age, male, hyperlipidemia, hypertension, and smoking were all independent predictors of CAC, and DM was associated with the second highest odds ratio (2.05, 95% confidence interval 1.87- 2.25) behind male (4.55, 95% confidence interval 4.17-4.76). Conclusions While DM was the second strongest predictor of CAC, nearly one fifth of persons with DM had no detectable CAC. Among DM patients, there is significant heterogeneity of scores, so an individualized approach to primary prevention for these patients is warranted.
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冠状动脉钙评分的预测因子及其在糖尿病和非糖尿病人群中的分布差异
背景和目的冠状动脉钙(CAC)评分是一种测量冠状动脉斑块负荷的方法,已被证明是动脉粥样硬化性心血管疾病(ASCVD)的良好预测指标。糖尿病(DM)是ASCVD的一个确定的危险因素,但一部分DM患者没有CAC(评分= 0)。我们进行了一项研究,以确定除DM以外的CAC评分的预测因素,并比较有和没有DM的人群之间的评分分布。方法我们纳入了1992年7月至2020年7月在一家大型成像中心接受CAC扫描的参与者。比较患有和不患有糖尿病的参与者的CAC评分和基线特征的分布。以CAC评分> 0为结果进行单因素logistic回归,然后进行多因素分析,以确定影响评分的独立因素。结果共纳入35086例患者,平均年龄58.9±11.9岁,男性63%,白人69%。其中,11.8%患有糖尿病,56%患有高脂血症,38%患有高血压,7%目前是吸烟者。DM组中CAC评分> 0的参与者比例较高(82% vs 62%, p <0.01),但相当一部分(18%)DM患者没有CAC。多因素分析显示,糖尿病、年龄、男性、高脂血症、高血压和吸烟都是CAC的独立预测因素,糖尿病的比值比(2.05,95%可信区间1.87- 2.25)仅次于男性(4.55,95%可信区间4.17-4.76)。结论:虽然糖尿病是CAC的第二大预测因子,但近五分之一的糖尿病患者没有检测到CAC。在糖尿病患者中,得分存在显著的异质性,因此对这些患者采取个体化的一级预防方法是有必要的。
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