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Published online: 2023-12-13

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Predictive role of monocyte count for significant coronary artery disease identification in patients with stable coronary artery disease

Tomasz Urbanowicz1, Anna Olasińska-Wiśniewska1, Michał Michalak2, Anna Komosa3, Krzysztof J. Filipiak34, Paweł Uruski3, Artur Radziemski3, Andrzej Tykarski3, Marek Jemielity1
Pubmed: 38149491


Background: The coronary artery disease (CAD) remains the leading cause of morbidity that is characterized by broad spectrum of symptoms. Up to 30% of performed angiographies reveal normal coronary arteries. The aim of the study was to find simple predictor for significant epicardial artery stenosis among patients with chronic coronary syndrome. Methods: There were 187 patients (131 (709%) men and 56 (30%) women) in the median (Q1–Q3) age of 67 [58–72] presenting with stable CAD symptoms enrolled into the present retrospective analysis. The demographical, clinical and laboratory characteristics between patients with normal and significant coronary artery stenosis were compared. Results: The multivariable analysis revealed coexistence of hypercholesterolemia as significant differentiation factor (odds ratio [OR]: 4.38, 95% confidence interval [CI]: 1.78–10.80, p = 0.001) for significant CAD and inverse relation to serum high density lipoprotein (OR: 0.19, 95% CI: 0.05–0.72, p = 0.015) and relation to creatinine concentration (OR: 1.03, 95% CI: 1.00–1.05, p = 0.012). Among whole peripheral blood count analysis, the significant relation was noticed to be hemoglobin concentration (OR: 1.09, 95% CI: 1.10–1.18, p = 0.022) and monocyte count (OR: 32.3, 95% CI: 1.09–653.6, p = 0.017). Receiver operator curve revealed (AUC: 0.641, p = 0.001) with the optimal cut-off value above 0.45 K/uL for monocyte, yelding sensitivity of 81.82% and specificity of 58.06%. Conclusions: The peripheral monocyte count above 0.45 k/uL may be considered as a predictor of significant coronary artery disease in symptomatic patients with chronic coronary syndrome.

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  1. Kubica A, Pietrzykowski Ł, Michalski P, et al. The occurrence of cardiovascular risk factors and functioning in chronic illness in the Polish population of EUROASPIRE V. Cardiol J. 2022 [Epub ahead of print].
  2. Malakar AKr, Choudhury D, Halder B, et al. A review on coronary artery disease, its risk factors, and therapeutics. J Cell Physiol. 2019; 234(10): 16812–16823.
  3. Bertolone DT, Gallinoro E, Esposito G, et al. Contemporary management of stable coronary artery disease. High Blood Press Cardiovasc Prev. 2022; 29(3): 207–219.
  4. Knuuti J, Wijns W, Saraste A, et al. ESC Scientific Document Group. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. 2020; 41(3): 407–477.
  5. Tolunay H, Kurmus O. Comparison of coronary risk scoring systems to predict the severity of coronary artery disease using the SYNTAX score. Cardiol J. 2016; 23(1): 51–56.
  6. Winther S, Schmidt SE, Rasmussen LD, et al. Validation of the European Society of Cardiology pre-test probability model for obstructive coronary artery disease. Eur Heart J. 2021; 42(14): 1401–1411.
  7. Pellikka PA, Arruda-Olson A, Chaudhry FA, et al. Guidelines for performance, interpretation, and application of stress echocardiography in ischemic heart disease: from the American Society of Echocardiography. J Am Soc Echocardiogr. 2020; 33(1): 1–41.e8.
  8. Zaleska M, Kołtowski Ł, Maksym J, et al. Alternative methods for functional assessment of intermediate coronary lesions. Cardiol J. 2020; 27(6): 825–835.
  9. Nørgaard BL, Leipsic J, Gaur S, et al. NXT Trial Study Group. Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). J Am Coll Cardiol. 2014; 63(12): 1145–1155.
  10. Dorbala S, Ananthasubramaniam K, Armstrong IS, et al. Single photon emission computed tomography (SPECT) myocardial perfusion imaging guidelines: instrumentation, acquisition, processing, and interpretation. J Nucl Cardiol. 2018; 25(5): 1784–1846.
  11. Saraste A, Knuuti J. ESC 2019 guidelines for the diagnosis and management of chronic coronary syndromes: Recommendations for cardiovascular imaging. Herz. 2020; 45(5): 409–420.
  12. Kramer CM. Stress cardiac magnetic resonance, revascularization, and all-cause mortality: do we have a final answer? Circ Cardiovasc Imaging. 2021; 14(10): e013512.
  13. Zakynthinos E, Pappa N. Inflammatory biomarkers in coronary artery disease. J Cardiol. 2009; 53(3): 317–333.
  14. Ridker PM, Rifai N, Clearfield M, et al. Measurement of C-reactive protein for the targeting of statin therapy in the primary prevention of acute coronary events. N Engl J Med. 2001; 344(26): 1959–1965.
  15. Nidorf SM, Fiolet ATL, Mosterd A, et al. Colchicine in patients with chronic coronary disease. N Engl J Med. 2020; 383(19): 1838–1847.
  16. Liu GQ, Zhang WJ, Shangguan JH, et al. Association of derived neutrophil-to-lymphocyte ratio with prognosis of coronary heart disease after PCI. Front Cardiovasc Med. 2021; 8: 705862.
  17. Urbanowicz T, Olasińska-Wiśniewska A, Michalak M, et al. The prognostic significance of neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR) and platelet to lymphocyte ratio (PLR) on long-term survival in off-pump coronary artery bypass grafting (OPCAB) procedures. Biology (Basel). 2021; 11(1).
  18. Maleki M, Tajlil A, Separham A, et al. Association of neutrophil to lymphocyte ratio (NLR) with angiographic SYNTAX score in patients with non-ST-Segment elevation acute coronary syndrome (NSTE-ACS). J Cardiovasc Thorac Res. 2021; 13(3): 216–221.
  19. Arnold KA, Blair JE, Paul JD, et al. Monocyte and macrophage subtypes as paired cell biomarkers for coronary artery disease. Exp Physiol. 2019; 104(9): 1343–1352.
  20. Moore KJ, Sheedy FJ, Fisher EA. Macrophages in atherosclerosis: a dynamic balance. Nat Rev Immunol. 2013; 13(10): 709–721.
  21. Hochman JS, Anthopolos R, Reynolds HR, et al. ISCHEMIA Research Group. Initial invasive or conservative strategy for stable coronary disease. N Engl J Med. 2020; 382(15): 1395–1407.
  22. Hojo Y, Ikeda U, Takahashi M, et al. Increased levels of monocyte-related cytokines in patients with unstable angina. Atherosclerosis. 2002; 161(2): 403–408.
  23. Sato T, Takebayashi S, Kohchi K. Increased subendothelial infiltration of the coronary arteries with monocytes/macrophages in patients with unstable angina. Histological data on 14 autopsied patients. Atherosclerosis. 1987; 68(3): 191–197.
  24. Li G, Saguner AM, An J, et al. Cardiovascular disease during the COVID-19 pandemic: Think ahead, protect hearts, reduce mortality. Cardiol J. 2020; 27(5): 616–624.
  25. Akıl MA, Oylumlu M, Oylumlu M, et al. Predictive value of lymphocyte to monocyte ratio for cardiac syndrome X. Eur Rev Med Pharmacol Sci. 2022; 26(12): 4303–4308.
  26. Soleymani M, Masoudkabir F, Shabani M, et al. Updates on pharmacologic management of microvascular angina. Cardiovasc Ther. 2022; 2022: 6080258.
  27. Dogan A, Oylumlu M. Increased monocyte-to-HDL cholesterol ratio is related to cardiac syndrome X. Acta Cardiol. 2017; 72(5): 516–521.
  28. Okyay K, Yilmaz M, Yildirir A, et al. Relationship between neutrophil-to-lymphocyte ratio and impaired myocardial perfusion in cardiac syndrome X. Eur Rev Med Pharmacol Sci. 2015; 19(10): 1881–1887.
  29. Schirmer SH, Fledderus JO, van der Laan AM, et al. Suppression of inflammatory signaling in monocytes from patients with coronary artery disease. J Mol Cell Cardiol. 2009; 46(2): 177–185.
  30. Gdowski MA, Murthy VL, Doering M, et al. Association of isolated coronary microvascular dysfunction with mortality and major adverse cardiac events: a systematic review and meta-analysis of aggregate data. J Am Heart Assoc. 2020; 9(9): e014954.
  31. Murthy VL, Naya M, Taqueti VR, et al. Effects of sex on coronary microvascular dysfunction and cardiac outcomes. Circulation. 2014; 129(24): 2518–2527.
  32. Pasqualetto MC, Tuttolomondo D, Cutruzzolà A, et al. Human coronary inflammation by computed tomography: Relationship with coronary microvascular dysfunction. Int J Cardiol. 2021; 336: 8–13.
  33. Cimmino G, Di Serafino L, Cirillo P. Pathophysiology and mechanisms of Acute Coronary Syndromes: atherothrombosis, immune-inflammation, and beyond. Expert Rev Cardiovasc Ther. 2022; 20(5): 351–362.
  34. Johannesen CD, Mortensen MB, Langsted A, et al. Apolipoprotein B and non-hdl cholesterol better reflect residual risk than LDL cholesterol in statin-treated patients. J Am Coll Cardiol. 2021; 77(11): 1439–1450.
  35. Ridker PM, Bhatt DL, Pradhan AD, et al. Inflammation and cholesterol as predictors of cardiovascular events among patients receiving statin therapy: a collaborative analysis of three randomised trials. Lancet. 2023; 401(10384): 1293–1301.
  36. Andreotti F, Maggioni AP, Scambia G. Sex- and gender‑specific precision medicine for chronic coronary syndromes: challenges and opportunities. Kardiol Pol. 2021; 79(4): 373–375.
  37. Kozieł P, Jankowski P, Kosior DA, et al. Smoking cessation in patients with established coronary artery disease: data from the POLASPIRE survey. Kardiol Pol. 2021; 79(4): 418–425.
  38. Paquette M, Bernard S, Baass A. Hemoglobin concentration, hematocrit and red blood cell count predict major adverse cardiovascular events in patients with familial hypercholesterolemia. Atherosclerosis. 2021; 335: 41–46.
  39. Ramljak S, Lock JP, Schipper C, et al. Hematocrit interference of blood glucose meters for patient self-measurement. J Diabetes Sci Technol. 2013; 7(1): 179–189.
  40. Liu F, Ma G, Tong C, et al. Elevated blood urea nitrogen-to-creatinine ratio increased the risk of Coronary Artery Disease in patients living with type 2 diabetes mellitus. BMC Endocr Disord. 2022; 22(1): 50.