Patients and methods: A total of 243 patients (210 males, 33 females; mean age: 63.3±11.5; range, 51 to 76 years) who underwent coronary angiography due to typical chest pain or myocardial ischemia detected in noninvasive stress tests and diagnosed with ≥1 major coronary artery occlusion between January and September 2020 were included in the cross-sectional observational study. The angiographic collateral index was determined according to the Cohen-Rentrop classification. The patients were divided into two groups according to the sufficiency of collateral development: the well-developed collaterals group (n=155) and the poor-developed collaterals group (n=88).

Results: Statistically significant parameters in univariate logistic regression analysis were evaluated with multivariate (stepwise) logistic regression analysis; as a result, presence of chronic total occlusion in left anterior descending artery (odds ratio [OR]=2.447; 95% confidence interval [CI], 1.160-5.162; p=0.019), total number of occlusions (OR=3.503; 95% CI, 1.445-8.494; p=0.006), left ventricular ejection fraction (OR=1.056; 95% CI, 1.022-1.091; p=0.001), and the atherogenic index of plasma (OR=0.017; 95% CI, 1.022-1.091; p<0.001) were independently associated with well-developed collaterals. Although the triglyceride-glucose index had statistical significance in the univariate analysis, it was not detected as an independent variable in the multivariate analysis. The monocyte-lymphocyte ratio was not significant in the univariate analysis.

Conclusion: Of the new atherosclerosis markers, only the atherogenic index of plasma had an independent association with poor collateral development.

Dyslipidemia is a crucial factor contributing to vascular endothelial dysfunction.[2] Intact vascular endothelium is essential for coronary collateral development. Therefore, vascular endothelial dysfunction may disrupt collateral development. The fact that collateral development is impaired in diabetes mellitus and metabolic syndrome that causes vascular endothelial dysfunction supports this theory.[3-5]

Inflammation and abnormal glucose and lipid metabolisms are critical in atherogenesis and substantial risk factors for cardiovascular diseases.[6,7] Studies have shown that atherogenic index of plasma (AIP), triglyceride-glucose (TyG) index, and monocytelymphocyte ratio (MLR) are novel markers for atherosclerosis, insulin resistance, and inflammation, respectively.[8-10] Endothelial dysfunction plays a significant role in initiating the atherosclerosis process; in addition, it is the common ground of atherosclerosis risk factors. Considering the relationship between coronary collateral development and endothelial dysfunction, new biochemical markers indicate atherosclerosis may be associated with collateral development. In the present study, we aimed to evaluate the relationship of new atherosclerosis-related biochemical markers (AIP, TyG index, and MLR) with the coronary collateral development in chronic total occlusion (CTO) patients.

The presence of classical cardiovascular risk factors, such as age, sex, diabetes mellitus, hypertension, dyslipidemia, and smoking, was questioned. Patients underwent a transthoracic echocardiographic examination. Hypertension was defined as systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg on repeat measurements or use of any antihypertensive drug. Diabetes mellitus was defined as a fasting plasma glucose level of ≥126 or ≥200 mg/dL at any measurement or use of any antidiabetic drug.

Peripheral venous blood samples were obtained from the patients on the day of hospitalization. The levels of blood biochemical parameters, including a lipid panel, fasting glucose, creatinine, and C-reactive protein levels, were measured. The TyG index was calculated as ln[fasting triglycerides (mg/dL) ¥ fasting plasma glucose (mg/dL)/2]. The AIP was calculated by using the following formula: log10 (TG/HDL-C).[7,12] It can be classified according to the values obtained: −0.3 to 0.1 for low risk, 0.1 to 0.24 for medium, and more than 0.24 for high risk of CVD.[13] The MLR was calculated by dividing monocyte count by lymphocyte count.

Standard selective CAG was performed on all patients using the Judkins technique with at least four images for the left coronary system and at least two images for the right coronary artery. Images of CAG were reevaluated for analyzing collateral development by two experienced interventional cardiologists who were blinded to the study. Collateral grading was assessed concerning the vessel with the highest Rentrop grade in case of having more than one CTO-containing vessel. The degree of coronary collateral development was determined according to the Cohen–Rentrop method: Grade 0, no filling of any collateral vessels; Grade 1, side branch filling of the recipient artery without filling of the main artery; Grade 2, partial filling of the main epicardial artery by collaterals; Grade 3, complete filling of the main epicardial artery by collaterals.[14]

The patients were divided into two groups according to collateral development. Patients with Grade 0 to 1 Rentrope were included in the poor-developed collateral group, and patients with Grade 2 to 3 Rentrope were included in the well-developed collateral group. Coronary angiograms of 243 patients were analyzed, and according to the Cohen-Rentrop method, welldeveloped collaterals were observed in 155 (63.7%) patients, while poor-developed collaterals were observed in 88 (36.2%) patients.

Severe CAD was defined as stenosis of more than 50% in vessels greater than 1.5 mm in diameter. Coronary total occlusion was defined as lesions present for more than three months, in which the artery shows either the complete interruption of antegrade blood flow on angiography or minimal contrast penetration through the lesion without distal vessel opacification.[15]

Statistical analysis
Statistical analysis was performed using IBM SPSS version 20.0 (IBM Corp., Armonk, NY, USA). Continuous variables were tested for normal distribution using the Kolmogorov-Smirnov test, the Shapiro-Wilk test, and visualization methods (histograms and probability plots). Data were expressed as mean±standard deviation (SD) for normally distributed continuous variables and median (interquartile range) for categorical variables. Variables of both groups were compared by the chi-square test, Mann-Whitney U test, and independent samples t-test, where appropriate. Univariate and backward multivariate logistic regression analysis was performed to identify independent predictors for well-developed collaterals. A two-tailed p value of <0.05 was considered statistically significant.

Table 1: Baseline characteristics of the groups

The parameters that reached statistical significance were tested with univariate logistic regression analysis, and factors other than smoking were found to be significant (Table 2). All statistically significant parameters in univariate logistic regression analysis were evaluated with multivariate (stepwise) logistic regression analysis; eventually, the presence of CTO in the LAD artery (odds ratio [OR]=2.447; 95% confidence interval [CI], 1.160-5.162; p=0.019), total number of occlusions (OR=3.503; 95% CI, 1.445-8.494; p=0.006), left ventricular ejection fraction (OR=1.056; 95% CI, 1.022-1.091; p=0.001) and AIP (OR=0.017; 95% CI, 1.022-1.091; p<0.001) were independently associated with good collateral development.

Table 2: Multivariate binary logistic regression analysis

The AIP is a new lipid index superior to low-density lipoprotein (LDL)-cholesterol (LDL-C), HDL-C, total cholesterol, and triglyceride in predicting CAD.[24] Atherogenic index of plasma is a substitute for small dense (sd) LDL particles and is inversely proportional to LDL-C particle size.[25] The rise in AIP indicates a decrease in LDL particle diameter and an increase in sdLDL, which favors the formation of foam cells and atherosclerotic plaque development.[26] Atherogenic index of plasma is independently associated with CTO and is thought to predict the presence and severity of CTO.[27]

High-density lipoprotein cholesterol has cardioprotective effects and improves endothelial function through its anti-inflammatory and antioxidative effects; in addition, it modulates monocyte activation, adhesion, and migration.[28,29] In the present study, HDL-C level was found close to statistical significance in the well-developed collateral group. The HDL-C level might have contributed to well collateral development.

Studies have shown that the TyG index is superior to HOMA-IR (homeostatic model assessment for insulin resistance) in assessing insulin resistance and can be used to predict CAD and adverse cardiovascular events.[30-32] Insulin resistance can directly or indirectly contribute to ventricular and vascular dysfunction due to attenuated proinf lammatory response and aggravated atherosclerotic plaque.[33,34] Furthermore, insulin resistance can alter systemic lipid metabolism, leading to dyslipidemia and even accelerating the rupture of fragile plaques by aggravating vascular endothelial damage and inflammation.[35] However, in the current study, although its relationship with collateral development was significant, it was not detected as an independent variable.

Monocyte-lymphocyte ratio, a novel marker of systemic inflammation, is an independent risk factor for CAD and predicts lesion severity.[36] Increased MLR favors body inflammation and oxidative stress, accelerates the formation of foam cells and endothelial damage, suppresses immune responses, and aggregates coronary plaque development.[37,38] In the present study, its relationship with collateral development had no statistical significance.

Melidonis et al.[39] more frequently detected thirddegree collateral circulation following complete occlusion of the LAD and right coronary arteries. In the current study, well-developed collaterals were observed much more in the LAD artery CTO cases. We thought that this might be due to the size of the myocardial jeopardy area, which is influential in collateral development, and the ischemic stimulus that it created. We considered that the higher the total number of occlusions and the number of lesions above 50%, the greater the collateral development as a factor affecting the size of the myocardial jeopardy area.

The relatively small study population and the single-center design may limit the interpretation of results. The study’s cross-sectional nature limits the direct relationship between cause and effect. More extensive and prospective studies are needed to confirm this relationship.

In conclusion, the use of AIP, one of the new biochemical markers associated with atherosclerosis in patients with CTO, should be at the forefront in predicting poor collateral development. Furthermore, the use of TyG would be beneficial, but MLR was not appropriate. Compared to these parameters, the AIP, which is noninvasive and easily accessible, can help predict the degree of collateral development the best, but more comprehensive randomized controlled studies are needed.

Ethics Committee Approval: The study protocol was approved by the Recep Tayyip Erdoğan University Faculty of Medicine Ethics Committee (Date/no: 18.05.2022/40465587- 050.01.04-443). The study was conducted in accordance with the principles of the Declaration of Helsinki.

Patient Consent for Publication: A written informed consent was obtained from each patient.

Data Sharing Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.

Author Contributions: Idea/concept: N.E.; Literature review: A.G.Ö.; Analysis and interpretation: A.E.; Data collection: M.M.Ö.; Materials: M.Ö.; Design/control: C.A.

Conflict of Interest: The authors declared no conflicts of interest with respect to the authorship and/or publication of this article.

Funding: The authors received no financial support for the research and/or authorship of this article.

1) Hansen JF. Coronary collateral circulation: Clinical significance and influence on survival in patients with coronary artery occlusion. Am Heart J 1989;117:290-5.

2) Habib GB, Heibig J, Forman SA, Brown BG, Roberts R, Terrin ML, et al. Influence of coronary collateral vessels on myocardial infarct size in humans. Results of phase I thrombolysis in myocardial infarction (TIMI) trial. The TIMI Investigators. Circulation 1991;83:739-46.

3) Glasser SP, Selwyn AP, Ganz P. Atherosclerosis: Risk factors and the vascular endothelium. Am Heart J 1996;131:379-84.

4) Abaci A, Oğuzhan A, Kahraman S, Eryol NK, Unal S, Arinç H, et al. Effect of diabetes mellitus on formation of coronary collateral vessels. Circulation 1999;99:2239-42.

5) Turhan H, Erbay AR, Yasar AS, Bicer A, Sasmaz H, Yetkin E. Impaired coronary blood flow in patients with metabolic syndrome: Documented by Thrombolysis in Myocardial Infarction (TIMI) frame count method. Am Heart J 2004;148:789-94.

6) Weber C, Noels H. Atherosclerosis: Current pathogenesis and therapeutic options. Nat Med 2011;17:1410-22.

7) Emamalipour M, Seidi K, Jahanban-Esfahlan A, Jahanban- Esfahlan 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;234:21758-69.

8) 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. Lipids Health Dis 2019;18:99.

9) Alizargar J, Bai CH, Hsieh NC, Wu SV. Use of the triglyceride-glucose index (TyG) in cardiovascular disease patients. Cardiovasc Diabetol 2020;19:8.

10) Xiang F, Chen R, Cao X, Shen B, Liu Z, Tan X, et al. Monocyte/lymphocyte ratio as a better predictor of cardiovascular and all-cause mortality in hemodialysis patients: A prospective cohort study. Hemodial Int 2018;22:82-92.

11) Knuuti J, Wijns W, Saraste A, Capodanno D, Barbato E, Funck-Brentano C, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J 2020;41:407-77.

12) Nwagha UI, Ikekpeazu EJ, Ejezie FE, Neboh EE, Maduka IC. Atherogenic index of plasma as useful predictor of cardiovascular risk among postmenopausal women in Enugu, Nigeria. Afr Health Sci 2010;10:248-52.

13) Dobiásová M. AIP--atherogenic index of plasma as a significant predictor of cardiovascular risk: From research to practice. Vnitr Lek 2006;52:64-71.

14) Schiller NB, Shah PM, Crawford M, DeMaria A, Devereux R, Feigenbaum H, et al. Recommendations for quantitation of the left ventricle by two-dimensional echocardiography. American Society of Echocardiography Committee on Standards, Subcommittee on Quantitation of Two- Dimensional Echocardiograms. J Am Soc Echocardiogr 1989;2:358-67.

15) van Royen N, Piek JJ, Buschmann I, Hoefer I, Voskuil M, Schaper W. Stimulation of arteriogenesis; A new concept for the treatment of arterial occlusive disease. Cardiovasc Res 2001;49:543-53.

16) Sasmaz H, Yilmaz MB. Coronary collaterals in obese patients: Impact of metabolic syndrome. Angiology 2009;60:164-8.

17) Liu T, Wu Z, Liu J, Lv Y, Li W. Metabolic syndrome and its components reduce coronary collateralization in chronic total occlusion: An observational study. Cardiovasc Diabetol 2021;20:104.

18) Kaur R, Kaur M, Singh J. Endothelial dysfunction and platelet hyperactivity in type 2 diabetes mellitus: molecular insights and therapeutic strategies. Cardiovasc Diabetol 2018;17:121.

19) Allahwala UK, Khachigian LM, Nour D, Ridiandres A, Billah M, Ward M, et al. Recruitment and maturation of the coronary collateral circulation: Current understanding and perspectives in arteriogenesis. Microvasc Res 2020;132:104058.

20) Liu Z, Pericak-Vance MA, Goldschmidt-Clermont P, Seo D, Wang L, Rundek T, et al. Coronary collateralization shows sex and racial-ethnic differences in obstructive artery disease patients. PLoS One 2017;12:e0183836.

21) Ross R. Atherosclerosis--an inflammatory disease. N Engl J Med 1999;340:115-26.

22) Shu W, Jing J, Fu LC, Min JT, Bo YX, Ying Z, et al. The relationship between diastolic pressure and coronary collateral circulation in patients with stable angina pectoris and chronic total occlusion. Am J Hypertens 2013;26:630-5.

23) Schaper W, Sharma HS, Quinkler W, Markert T, Wünsch M, Schaper J. Molecular biologic concepts of coronary anastomoses. J Am Coll Cardiol 1990;15:513-8.

24) 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;17:197.

25) Guo Q, Zhou S, Feng X, Yang J, Qiao J, Zhao Y, et al. The sensibility of the new blood lipid indicator--atherogenic index of plasma (AIP) in menopausal women with coronary artery disease. Lipids Health Dis 2020;19:27.

26) Süleymanoğlu M, Rencüzoğulları İ, Karabağ Y, Çağdaş M, Yesin M, Gümüşdağ A, et al. The relationship between atherogenic index of plasma and no-reflow in patients with acute ST-segment elevation myocardial infarction who underwent primary percutaneous coronary intervention. Int J Cardiovasc Imaging 2020;36:789-96.

27) Liu T, Liu J, Wu Z, Lv Y, Li W. Predictive value of the atherogenic index of plasma for chronic total occlusion before coronary angiography. Clin Cardiol 2021;44:518-

25)

28) Murphy AJ, Chin-Dusting JP, Sviridov D, Woollard KJ. The anti inflammatory effects of high density lipoproteins. Curr Med Chem 2009;16:667-75.

29) Murphy AJ, Woollard KJ. High-density lipoprotein: A potent inhibitor of inflammation. Clin Exp Pharmacol Physiol 2010;37:710-8.

30) 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;9:6129.

31) 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;18:89.

32) Jin JL, Cao YX, Wu LG, You XD, Guo YL, Wu NQ, et al. Triglyceride glucose index for predicting cardiovascular outcomes in patients with coronary artery disease. J Thorac Dis 2018;10:6137-46.

33) Novo G, Manno G, Russo R, Buccheri D, Dell'Oglio S, Morreale P, et al. Impact of insulin resistance on cardiac and vascular function. Int J Cardiol 2016;221:1095-9.

34) Montecucco F, Steffens S, Mach F. Insulin resistance: A proinf lammatory state mediated by lipidinduced signaling dysfunction and involved in atherosclerotic plaque instability. Mediators Inf lamm 2008;2008:767623.

35) 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;17:122.

36) Wen Y, Zhan X, Wang N, Peng F, Feng X, Wu X. Monocyte/ lymphocyte ratio and cardiovascular disease mortality in peritoneal dialysis patients. Mediators Inflamm 2020;2020:9852507.

37) Shaw DM, Merien F, Braakhuis A, Dulson D. T-cells and their cytokine production: The anti-inflammatory and immunosuppressive effects of strenuous exercise. Cytokine 2018;104:136-42.

38) Register TC, Appt SE, Clarkson TB. Atherosclerosis and vascular biologic responses to estrogens: Histologic, immunohistochemical, biochemical, and molecular methods. Methods Mol Biol 2016;1366:517-32.

39) Melidonis A, Tournis S, Kouvaras G, Baltaretsou E, Hadanis S, Hajissavas I, et al. Comparison of coronary collateral circulation in diabetic and nondiabetic patients suffering from coronary artery disease. Clin Cardiol 1999;22:465-71.