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Metabolic, Inflammatory and Imaging Biomarkers in Evaluation of Coronary Arteries Anatomical Stenosis in Patients with Stable Coronary Artery Disease

https://doi.org/10.20996/1819-6446-2020-01-01

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Abstract

Aim. To reveal the statistically significant determinants of the coronary artery (CA) stenosis ≥70% in patients with chronic stable CA disease receiving drug therapy.

Material and methods. The study included 68 patients (aged 59.6±6.4 years) with stable CA disease and optimal cardioactive therapy. Coronary angiography was performed in all patients. Basic serum parameters of carbohydrate and lipid metabolism were evaluated; serum concentration of cytokines, adipokines and high sensitive C-reactive protein (hsCRP) were determined by ELISA. The epicardial adipose tissue (EAT) thickness was measured by B-mode echocardiography.

Results. The patients’ classification model was created. It allowed to determine probability P for CA stenosis of 70% or more for each patient using formula Р, where L=0.89-1.09×gender+ 0.51×triglycerides–0.28×HDL+0.24×hsCRP (HDL – high density lipoproteins). If calculated P value falls into interval (0; 0.228) the patient should be classified into the group with the risk of CA stenosis ≥70%, while if calculated P value falls into interval (0.228; 1), the patient should be classified into group with CA stenosis below 70%. Even though EAT thickness was indistinguishable determinant of CA stenosis ≥70% in our study, its inclusion into the model as a fifth variable allowed to increase the model quality: area under ROC-curve (AUC) in the model without EAT thickness constituted 0.708 (p=0.009), and increased up to 0.879 (p=0.011) after EAT thickness inclusion.

Conclusions. Male sex, level of triglycerides, HDL and hsCRP are statistically significant determinants of CA stenosis ≥70%. The presence of the triglycerides level in the created model underscores an important contribution of this lipid fraction, even when elevated only up to the moderate values, into modulation of the residual cardiovascular risk in patients receiving statins.

About the Authors

O. A. Koshelskaya
Tomsk National Research Medical Center, Russian Academy of Science, Cardiology Research Institute
Russian Federation

Olga A. Koshelskaya – MD, PhD, Professor, Leading Researcher, Department of Atherosclerosis and Coronary Artery Disease

Kievskaya ul. 111a, Tomsk, 634012



T. E. Suslova
Tomsk National Research Medical Center, Russian Academy of Science, Cardiology Research Institute
Russian Federation

Tatiana E. Suslova – MD, PhD, Leading Researcher, Department of Laboratory and Functional Diagnostics

Kievskaya ul. 111a, Tomsk, 634012



I. V. Kologrivova
Tomsk National Research Medical Center, Russian Academy of Science, Cardiology Research Institute
Russian Federation

Irina V. Kologrivova – MD, PhD, Researcher, Department of Laboratory and Functional Diagnostics

Kievskaya ul. 111a, Tomsk, 634012



N. Y. Margolis
Tomsk State University
Russian Federation

Natalia Y. Margolis – PhD (Technology), Associate Professor, Chair of Probability Theory and Mathematical Statistics

Lenina prospect 36, Tomsk, 634050



O. A. Zhuravleva
Tomsk National Research Medical Center, Russian Academy of Science, Cardiology Research Institute
Russian Federation

Olga A. Zhuravleva – MD, PhD, Researcher, Department of Atherosclerosis and Coronary Artery Disease

Kievskaya ul. 111a, Tomsk, 634012



O. A. Kharitonova
Tomsk National Research Medical Center, Russian Academy of Science, Cardiology Research Institute
Russian Federation

Olga A. Kharitonova – Research Assistant, Department of Atherosclerosis and Coronary Artery Disease

Kievskaya ul. 111a, Tomsk, 634012



I. V. Vinnitskaya
Tomsk National Research Medical Center, Russian Academy of Science, Cardiology Research Institute
Russian Federation

Irina V. Vinnitskaya – MD, Cardiologist, Diagnostic and Consultation Center

Kievskaya ul. 111a, Tomsk, 634012



References

1. Metelskaya V.A., Gavrilova N.E., Yarovaya E.A., Boytsov S.A. An integrative biomarker: opportunities for non-invasive diagnostics of coronary atherosclerosis. Russian Journal of Cardiology 2017;146(6):132-8 (In Russ.). DOI:10.15829/1560-4071-2017-6-132-138.

2. Lotta L.A., Stewart I.D., Sharp S.J., et al. Association of genetically enhanced lipoprotein lipase-mediated lipolysis and low-density lipoprotein cholesterol-lowering alleles with risk of coronary disease and type 2 diabetes. JAMA Cardiology. 2018;3(10):957-66. DOI:10.1001/jamacardio.2018.2866.

3. Chistiakov D.A., Grechko A.V., Myasoedova V.A., et al. Impact of the cardiovascular system-associated adipose tissue on atherosclerotic pathology. Atherosclerosis. 2017;263:361-8. DOI:10.1016/j.atherosclerosis.2017.06.017.

4. Ansari A.M., Mohebati M., Pousadegh F., et al. Is echocardiographic epicardial fat thickness increased in patients with coronary artery disease? A systematic review and meta-analysis. Electronic Physician. 2018;10(9):7249-58. DOI:10.19082/7249.

5. Akhmedzhanov N.M., Dedov I.I., Zvenigorodskaya L.A., et al. Russian experts' consensus on metabolic syndrome problem in the Russian Federation: definition, diagnostic criteria, primary prevention, and treatment. Cardiovascular Therapy and Prevention. 2010;9(5):4-11. (In Russ.). DOI:10.15829/1728-8800-2010-5-4-11.

6. Jacobellis G., Assael F., Ribaudo M.C., et al. Epicardial fat from echocardiography: a new method for visceral adipose tissue prediction. Obes Res. 2003;11:304-10. DOI:10.1038/oby.2003.45.

7. Meenakshi K., Rajendran M., Srikumar S., Chidambaram S. Epicardial fat thickness: A surrogate marker of coronary artery disease – Assessment by echocardiography. Indian Heart J. 2016;68(3):336-41. DOI:10.1016/j.ihj.2015.08.005.

8. Habib S.S., Masri A.A.A. Relationship of high sensitivity C-reactive protein with presence and severity of coronary artery disease. J Clin Sci Res. 2012;3:126-30. DOI:10.12669/pjms.296.3302.

9. Belfort R., Berria R., Cornell J., et al. Fenofibrate reduces systemic inflammation markers independent of its effects on lipid and glucose metabolism in patients with metabolic syndrome. J Clin Endocrin Metab. 2010;95:829-36. DOI:10.1210/jc.2009-1487.

10. Diabetes Atherosclerosis Intervention Study Investigators. Effect of fenofibrate on progression of coronary-artery disease in type 2 diabetes: the Diabetes Atherosclerosis Intervention Study, a randomised study. Lancet. 2001;357(9260):905-10.

11. Chumakova G.A., Veselovskaya N.G. Clinical importance of epicardial fat thickness defining in obese patients. International Journal of Biomedicine. 2012;2(3):161-8.

12. Kologrivova I.V., Vinnitskaya I.V., Koshelskaya O.A., Suslova T.E. Visceral obesity and cardiometabolic risk: features of hormonal and immune regulation. Obesity and Metabolism. 2017;14(3): 3-10 (In Russ.) DOI:10.14341/OMET201733-10.


For citation:


Koshelskaya O.A., Suslova T.E., Kologrivova I.V., Margolis N.Y., Zhuravleva O.A., Kharitonova O.A., Vinnitskaya I.V. Metabolic, Inflammatory and Imaging Biomarkers in Evaluation of Coronary Arteries Anatomical Stenosis in Patients with Stable Coronary Artery Disease. Rational Pharmacotherapy in Cardiology. 2020;16(1):4-9. (In Russ.) https://doi.org/10.20996/1819-6446-2020-01-01

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ISSN 1819-6446 (Print)
ISSN 2225-3653 (Online)