AUTHOR=Yu Bingyan , Wu Ying , Li Wei , Zhou Langping , Lin Yan , Wang Weimian , Li Guang , Zhou Yingling , Hu Xiangming , Li Xiaohong TITLE=Predictive effect of different blood lipid parameters combined with carotid intima-media thickness on coronary artery disease JOURNAL=Frontiers in Cardiovascular Medicine VOLUME=9 YEAR=2023 URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2022.1105413 DOI=10.3389/fcvm.2022.1105413 ISSN=2297-055X ABSTRACT=Background

Blood lipids disorder and atherosclerosis are closely related to coronary artery disease (CAD). This study aims to compare different blood lipid parameters combined with carotid intima-media thickness (cIMT) in predicting CAD.

Methods

This was a retrospective study including patients who underwent coronary angiography for highly suspected CAD. Blood samples were taken for lipid profile analysis and cIMT was evaluated by carotid ultrasound. Logistic analysis was used to establish different models of different lipid parameters in predicting CAD. The area under the receiver operating characteristic curve (AUC) was used to examine the predictive value. The optimal lipid parameter was also used to explore the relationship with multi-vessel CAD.

Results

Patients were classified into two groups based on whether CAD existed. Compared with non-CAD patients, the CAD group had higher lipoprotein (a) [Lp (a)], apolipoprotein B/apolipoprotein A, total cholesterol/high-density lipoprotein cholesterol (HDL-C), triglyceride/HDL-C and LDL-C/HDL-C. According to the AUCs, Lp (a) combined with cIMT (AUC: 0.713, P < 0.001) had the best performance in predicting CAD compared to other lipid parameters. High level of Lp (a) was also associated with multi-vessel CAD (odds ratio: 1.41, 95% confidence interval: 1.02–1.95, P = 0.036).

Conclusion

For patients with highly suspected CAD, Lp (a) better improved the predictive value of CAD rather than most of blood lipid indices, especially in the absence of high levels of LDL-C. Lp (a) also can be used to predict the multi-vessel CAD.