Relationship Between Nonobstructive Coronary Arteries and Metabolic Parameters

Year 2024, Volume: 14 Issue: 2, 138 - 143, 29.08.2024

Muammer Karakayalı , Mehmet Altunova Turab Yakışan , Serkan Aslan İnanç Artaç , Timor Omar , Ayça Arslan , Doğan İliş , Ezgi Güzel , İbrahim Rencüzoğulları , Yavuz Karabağ

Abstract

Aim: The atherogenic index of plasma (AIP) and triglyceride-glucose (TyG) index are strongly associated with atherogenesis of the coronary artery. However, the relationship between these metabolic parameters and ischaemia with nonobstructive coronary artery diseases (INOCA) is unknown. Therefore, we aimed to investigate the relationship between AIP and TyG index and INOCA patients.
Material and Method: A total of 529 patients were enrolled in this study and assigned to the INOCA group (n=264) and control group (n=265). The clinical data and calculated AIP, TyG index, were collected. Multivariate logistic regression was set up to assess the AIP and TyG indices for INOCA.
Results: The optimal cut-off value of TyG for predicting INOCA was 8.87 with a sensitivity of 52.24% and a specificity of 70% ([AUC]: 0.634 [95% CI: 0.592–0.675, p=0.023]). The optimal cutoff value of AIP for predicting INOCA was 0.54 with a sensitivity of 45.15% and a specificity of 70.57% ([AUC]: 0.590 [95% CI: 0.547–0.632, p=0.025]). When the ROC curves of TyG and AIP are compared, it is seen that TyG is a better predictor ([Difference between areas]: 0.045 [95% CI: 0.0180–0.0711, p=0.001]).
Conclusion: AIP and TyG index were significantly higher in the INOCA group when compared to the control group. In addition, the main finding was that when the metabolic parameters TyG index and AIP were compared with each other, the TyG index provided a stronger prediction and was found to be an independent risk factor for INOCA.

Keywords

atherogenic index of plasma, triglyceride-glucose index; ischaemia with no obstructive coronary arteries (INOCA);, coronary artery disease

References

• 1. Knuuti J, Wijns W, Saraste A, Capodanno D, Barbato E, FunckBrentano C, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. 2020;41(3):407–77.
• 2. Taqueti VR. Coronary Microvascular Dysfunction in Vasospastic Angina: Provocative Role for the Microcirculation in Macrovessel Disease Prognosis. J Am Coll Cardiol. 2019;74(19):2361–4.
• 3. Ong P, Camici PG, Beltrame JF, Crea F, Shimokawa H, Sechtem U, et al. International standardization of diagnostic criteria for microvascular angina. Int J Cardiol. 2018;250:16–20.
• 4. Agrawal S, Mehta PK, Bairey Merz CN. Cardiac Syndrome X. update 2014. Cardiol Clin. 2014;32(3):463–78.
• 5. Weber C, Noels H. Atherosclerosis: current pathogenesis and therapeutic options. Nat Med. 2011;17(11):1410–22.
• 6. Emamalipour M, Seidi K, Jahanban-Esfahlan A JahanbanEsfahlan R. Implications of resistin in type 2 diabetes mellitus and coronary artery disease: Impairing insulin function and inducing pro-inflammatory cytokines. J Cell Physiol. 2019;234(12):21758–769.
• 7. Cai G, Liu W, Lv S, Wang X, Guo Y, Yan Z, et al. Genderspecific associations between atherogenic index of plasma and the presence and severity of acute coronary syndrome in very young adults: a hospital based observational study[J]. Lipids Health Dis. 2019;18(1):99.
• 8. Alizargar J, Bai CH, Hsieh NC, Wu SV. Use of the triglycerideglucose index (TyG) in cardiovascular disease patients[J]. Cardiovasc Diabetol. 2020;19(1):8.
• 9. Niroumand S, Khajedaluee M, Khadem-Rezaiyan M, Abrishami M, Juya M, Khodaee G, et al. Atherogenic Index of Plasma (AIP): A marker of cardiovascular disease. Med. J. Islam. Repub. Iran. 2015;29:240.
• 10. Lee BK, Lim HS, Fearon WF, Yong AS, Yamada R, Tanaka S, et al. Invasive evaluation of patients with angina in the absence of obstructive coronary artery disease. Circulation. 2015;131(12):1054–60.
• 11. Camici PG, Crea F. Coronary microvascular dysfunction. N Engl J Med. 2007;356(8):830–40.
• 12. Hagemann CE, Ghotbi AA, Kjaer A, Hasbak P. Quantitative myocardial blood flow with Rubidium-82 PET. a clinical perspective. Am J Nucl Med Mol Imaging. 2015;5(5):457–68.
• 13. Stein R, Ferrari F, Scolari F. Genetics, dyslipidemia, and cardiovascular disease: new insights. Curr Cardiol Rep. 2019;21(8):68.
• 14. Dobiásová M. AIPeatherogenic index of plasma as a significant predictor of cardiovascular risk: from research to practice [in Czech]. Vnitr Lek. 2006;52:64–71.
• 15. Quispe R, Manalac RJ, Faridi KF, Blaha MJ, Toth PP, Kulkarni KR, et al. Relationship of the triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio to the remainder of the lipid profile: the very large database of Lipids-4 (VLDL-4) study. Atherosclerosis. 2015;242:243–50.
• 16. Wu TT, Gao Y, Zheng YY, Ma YT, Xie X. Atherogenic index of plasma (AIP): a novel predictive indicator for the coronary artery disease in postmenopausal women. Lipids Health Dis. 2018;17(1):197.
• 17. Shen S, Lu Y, Qi H, Li F, Shen Z, Wu L, et al. Association between ideal cardiovascular health and the atherogenic index of plasma. Med (Baltimore). 2016;95:e3866.
• 18. Edwards MK, Blaha MJ, Loprinzi PD. Atherogenic index of plasma and triglyceride/high-density lipoprotein cholesterol ratio predict mortality risk better than individual cholesterol risk factors, among an older adult population. Mayo Clin Proc. 2017;92:680–81.
• 19. Cure E, Cumhur Cure M. Comment on the relationship between atherogenic index of plasma and noreflow in patients with acute STsegment elevation myocardial infarction who underwent primary percutaneous coronary intervention. Int J Cardiovasc Imaging. 2020;36(5):797–98.
• 20. Cho YR, Ann SH, Won KB, Park GM, Kim YG, Yang DH, et al. Association between insulin resistance, hyperglycemia, and coronary artery disease according to the presence of diabetes. Sci Rep. 2019;9(1):6129.
• 21. da Silva A, Caldas APS, Hermsdorff HHM, Bersch-Ferreira ÂC, Torreglosa CR, Weber B, et al. Triglyceride-glucose index is associated with symptomatic coronary artery disease in patients in secondary care. Cardiovasc Diabetol. 2019;18(1):89.
• 22. Won KB, Kim YS, Lee BK, Heo R, Han D, Lee JH, et al. The relationship of insulin resistance estimated by triglyceride glucose index and coronary plaque characteristics. Medicine (Baltimore) . 2018;97(21):e10726.
• 23. Ormazabal V, Nair S, Elfeky O, Aguayo C, Salomon C, Zuñiga FA. Association between insulin resistance and the development of cardiovascular disease. Cardiovasc Diabetol. 2018;17(1):122.
• 24. Ong P, Athanasiadis A, Sechtem U. Patterns of coronary vasomotor responses to intracoronary acetylcholine provocation. Heart. 2013;99(17):1288–95.