Non-traditional Lipid Profile and Obstructive Coronary Artery Disease Based On CAD-RADS Score
Abstract
Background: The association between dyslipidemia and coronary artery disease (CAD) is undisputable. Current evidence suggests that, in comparison to conventional lipid parameters, a comprehensive non-traditional lipid profile serves as a more robust predictor of CAD. The evidence regarding the correlation between nontraditional lipid profile and severity of coronary lesions, as measured by the coronary artery disease-reporting and data system (CAD-RADS) score by Coronary Computed Tomography Angiography (CCTA), is still scarce. This study aimed to elaborate on the association between those parameters. Understanding these associations may improve risk stratification and management in CAD patients.
Methods: A cross-sectional single-center study was conducted in a large population of patients with suspected CAD. Data were obtained from medical records between January 2020 and February 2024. The CAD-RADS score was stratified into three groups: CAD-RADS 0 (no CAD), CAD-RADS 1-2 (stenosis <50%, classified as non-obstructive CAD), and CAD-RADS ≥3 (stenosis ≥50% in ≥1 coronary segment, classified as obstructive CAD). Logistic regression analysis analyzes the association between patients' lipid profiles and CAD-RADS scores. P-value <0.05 was considered statistically significant.
Results: A total of 543 (274 female) patients were included in this study. In the univariate analysis, the LDL/HDL ratio was significantly associated with the severity of CAD based on CAD-RADS scores. The multivariate analysis revealed that the LDL/HDL ratio was the most significant lipid parameter across all models (Adj OR: 9.728, 95% CI: 2.078-45.649, P = 0.004), with the highest adjusted odds ratio observed after adjustments for age, gender, family history, history of hypertension, diabetes mellitus, and chronic kidney disease, and also smoking status. The LDL/HDL ratio cut-off value was 2.82 with a sensitivity of 83.95% and a specificity of 21.05%. Other non-traditional lipid profiles lost their significance in the multivariate models.
Conclusions: The LDL/HDL ratio was significantly associated with obstructive CAD, as assessed by the CAD-RADS score, even after adjustment for other cardiovascular risk factors
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References
2. Chen, S., Li, Z., Li, H., Zeng, X., Yuan, H., & Li, Y. (2023). Novel lipid biomarkers and ratios as risk predictors for premature coronary artery disease: A retrospective analysis of 2952 patients. Journal of clinical hypertension (Greenwich, Conn.), 25(12), 1172–1184. https://doi.org/10.1111/jch.14751
3. Alloubani, A., Nimer, R., & Samara, R. (2021). Relationship between Hyperlipidemia, Cardiovascular Disease and Stroke: A Systematic Review. Current cardiology reviews, 17(6), e051121189015. https://doi.org/10.2174/1573403X16999201210200342
4. Zheng, J., Sun, Z., Zhang, X., Li, Z., Guo, X., Xie, Y., Sun, Y., & Zheng, L. (2019). Non-traditional lipid profiles associated with ischemic stroke not hemorrhagic stroke in hypertensive patients: results from an 8.4 years follow-up study. Lipids in health and disease, 18(1), 9. https://doi.org/10.1186/s12944-019-0958-y
5. Okan, T., Doruk, M., Ozturk, A., Topaloglu, C., Dogdus, M., & Yilmaz, M. B. (2024). Evaluation of Plasma Atherogenic Index, Triglyceride-Glucose Index and Other Lipid Ratios as Predictive Biomarkers of Coronary Artery Disease in Different Age Groups. Diagnostics (Basel, Switzerland), 14(14), 1495. https://doi.org/10.3390/diagnostics14141495
6. Zhao, X., Wang, D., & Qin, L. (2021). Lipid profile and prognosis in patients with coronary heart disease: a meta-analysis of prospective cohort studies. BMC cardiovascular disorders, 21(1), 69. https://doi.org/10.1186/s12872-020-01835-0
7. Aggarwal, D. J., Kathariya, M. G., & Verma, D. P. K. (2021). LDL-C, NON-HDL-C and APO-B for cardiovascular risk assessment: Looking for the ideal marker. Indian heart journal, 73(5), 544–548. https://doi.org/10.1016/j.ihj.2021.07.013
8. Li, Y., Feng, Y., Li, S., Ma, Y., Lin, J., Wan, J., & Zhao, M. (2023). The atherogenic index of plasma (AIP) is a predictor for the severity of coronary artery disease. Frontiers in cardiovascular medicine, 10, 1140215. https://doi.org/10.3389/fcvm.2023.1140215
9. Knuuti J, Wijns W, Saraste A, et all. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. 2020 Jan 14;41(3):407-477. doi: 10.1093/eurheartj/ehz425. Erratum in: Eur Heart J. 2020 Nov 21;41(44):4242. PMID: 31504439
10. Cury RC, Leipsic J, Abbara S, Achenbach S, Berman D, Bittencourt M. CAD-RADSTM 2.0 – 2022 Coronary Artery Disease – Reporting and Data System An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR) and the North America Society of Cardiovascular Imaging (NASCI). Radiol Cardiothorac Imaging. 2022 Oct 1;4(4)
11. Wang Z, Sun Z, Yu L, Wang Z, Li L, Lu X. Machine learning-based prediction of composite risk of cardiovascular events in patients with stable angina pectoris combined with coronary heart disease: development and validation of a clinical prediction model for Chinese patients. Front Pharmacol. 2024 Jan 10;14:1334439. doi: 10.3389/fphar.2023.1334439.
12. Graby J, Sellek J, Khavandi A, Loughborough W, Hudson B, Shirodaria C, et al. Coronary CT angiography derived pericoronary inflammation and bespoke cardiovascular risk prediction in the lipid clinic: beyond the calcium score. European Heart Journal. 2022.
13. Sun T, Chen M, Shen H, PingYin, Fan L, Chen X, Wu J, Xu Z, Zhang J. Predictive value of LDL/HDL ratio in coronary atherosclerotic heart disease. BMC Cardiovasc Disord. 2022 Jun 17;22(1):273. doi: 10.1186/s12872-022-02706-6. PMID: 35715736; PMCID: PMC9206383.
14. Hernáez Á, Soria-Florido MT, Schröder H, Ros E, Pintó X, Estruch R, Salas-Salvadó J, et al. Role of HDL function and LDL atherogenicity on cardiovascular risk: A comprehensive examination. PLoS One. 2019 Jun 27;14(6):e0218533. doi: 10.1371/journal.pone.0218533. PMID: 31246976; PMCID: PMC6597156.
15. Zhang S, Zhao Y, Li X, Dai W, Chen X, Yang G, Liu L, Su Q. The LDL-C/HDL-C ratio and 4-year risk of coronary artery disease: a retrospective study. 2020.
16. Sun, T., Chen, M., Shen, H., PingYin, Fan, L., Chen, X., Wu, J., Xu, Z., & Zhang, J. (2022). Predictive value of LDL/HDL ratio in coronary atherosclerotic heart disease. BMC cardiovascular disorders, 22(1), 273. https://doi.org/10.1186/s12872-022-02706-6
17. Zhang, R., Fan, Y., Xue, Y., Feng, Y., Dong, C., Wang, Y., Kou, P., Li, G., Ma, A., & Wang, T. (2022). The LDL/HDL ratio predicts long-term risk of coronary revascularization in ST-segment elevation myocardial infarction patients undergoing percutaneous coronary intervention: a cohort study. Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas, 55, e11850. https://doi.org/10.1590/1414-431X2021e11850
18. Ya Li, Yu-jiao Feng, Shu Li, Yulin Ma, Jiesheng Lin, J. Wan, Min Zhao. (2023). The atherogenic index of plasma (AIP) is a predictor for the severity of coronary artery disease. Frontiers in Cardiovascular Medicine, 10. DOI: 10.3389/fcvm.2023.1140215
19. Cai, G., Shi, G., Xue, S., & Lu, W. (2017). The atherogenic index of plasma is a strong and independent predictor for coronary artery disease in the Chinese Han population. Medicine, 96(37), e8058. https://doi.org/10.1097/MD.0000000000008058
20. Çelik, E., Çora, A. R., & Karadem, K. B. (2021). The Effect of Untraditional Lipid Parameters in the Development of Coronary Artery Disease: Atherogenic Index of Plasma, Atherogenic Coefficient and Lipoprotein Combined Index. Journal of the Saudi Heart Association, 33(3), 244–250. https://doi.org/10.37616/2212-5043.1266
21. Onat A, Can G, Kaya H, Hergenç G. "Atherogenic index of plasma" (log10 triglyceride/high-density lipoprotein-cholesterol) predicts high blood pressure, diabetes, and vascular events. J Clin Lipidol. 2010 Mar-Apr;4(2):89-98. doi: 10.1016/j.jacl.2010.02.005. Epub 2010 Feb 12. PMID: 21122635
22. Shui, X., Chen, Z., Wen, Z., Tang, L., Tang, W., Liao, Y., Wu, Z., & Chen, L. (2022). Association of Atherogenic Index of Plasma With Angiographic Progression in Patients With Suspected Coronary Artery Disease. Angiology, 73(10), 927–935. https://doi.org/10.1177/00033197221080911
23. Jung E, Kong SY, Ro YS, Ryu HH, Shin SD. Serum Cholesterol Levels and Risk of Cardiovascular Death: A Systematic Review and a Dose-Response Meta-Analysis of Prospective Cohort Studies. Int J Environ Res Public Health. 2022 Jul 6;19(14):8272. doi: 10.3390/ijerph19148272
24. Guo Y, Yin F, Fan Y, Liu C, Luo Y, Tang Q, et al. Influence of age and gender on the presence of comorbidities and reduced quality of life in patients with coronary artery disease. J Cardiovasc Transl Res. 2020;13(3):19-25
25. Otaki Y, Gransar H, Cheng VY, Dey D, Labounty, et all. Gender differences in the prevalence, severity, and composition of coronary artery disease in the young: a study of 1635 individuals undergoing coronary CT angiography from the prospective, multinational confirm registry. Eur Heart J Cardiovasc Imaging. 2015 May;16(5):490-9
26. Toupendi NZ, Tiam EM, Ngou MT, et all. Relationship between cardiovascular risk factors and coronary artery disease assessed by CAD-RADS. JESFC. 2024 Jan; 117(1): 26-27
27. Wang C, Cheng G, Duanmu Y, Zhu Y, Xu L. Correlation of coronary plaque characteristics and obstructive stenosis with chronic kidney disease by coronary CT angiography. Cardiovasc Diagn Ther. 2015 Dec;5(6):435-43
28. Deventer HE, Miller W, Myers G, Sakurabayashi I, Bachmann L, Caudill S, et al. Non-HDL cholesterol shows improved accuracy for cardiovascular risk score classification compared to direct or calculated LDL cholesterol in a dyslipidemic population. Clin Chem. 2011;57(3):490-501. doi: 10.1373/clinchem.2010.154773
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