ANKMJ

Ankyra Medical Journal (AnkMJ), formerly known as the Journal of Translational and Practical Medicine, regularly publishes international quality issues in the field of Medicine in the light of current information.

EndNote Style
Index
Original Article
Association between red cell distribution width coefficient of variation and coronary slow flow
Aims: Coronary slow flow (CSF) is an angiographic phenomenon characterized by delayed distal coronary opacification in the absence of significant epicardial stenosis. Red cell distribution width (RDW), a routinely measured hematologic parameter, has been proposed as a potential marker of inflammation and microvascular dysfunction. However, although several studies have demonstrated an association, its role as an independent predictor of CSF remains to be fully established. This study aimed to evaluate the association between RDW coefficient of variation (RDW-CV) and CSF using multivariate logistic regression and receiver operating characteristic (ROC) analyses.
Methods: We retrospectively analyzed 153 patients with normal or near-normal coronary arteries on angiography, classified into CSF (n = 73, 47.7%) and non-CSF (n = 80, 52.3%) groups based on corrected TIMI frame counts. Clinical, demographic, and laboratory data were compared between groups. Variables with p < 0.10 in univariate analysis were included in multivariate logistic regression. Diagnostic performance was assessed using ROC curve analysis.
Results: RDW-CV values were slightly higher in the CSF group (13.83 ± 1.24%) compared with the non-CSF group (13.69 ± 1.41%, p = 0.419). In multivariate analysis, RDW-CV showed a non-significant trend toward predicting CSF (OR = 1.338, 95% CI: 0.967–1.852, p = 0.079). Hyperlipidemia (n = 31, 40.4% vs. n = 16, 21.7%), CRP, HDL, and LDL were independent predictors of CSF. RDW-CV alone demonstrated poor discriminative ability (AUC = 0.571), whereas the multivariate model achieved good performance (AUC = 0.833).
Conclusion: RDW-CV is not a strong stand alone predictor of CSF but may contribute to diagnostic accuracy when integrated with other clinical and laboratory variables. Further prospective studies with larger populations are warranted to clarify its prognostic role.


1. Tambe AA, Demany MA, Zimmerman HA, et al. Angina pectoris and slow flow velocity of dye in coronary arteries: a new angiographic finding. Am Heart J. 1972;84(1):66-71. doi:10.1016/0002-8703(72)90307-9
2. Gibson CM, Cannon CP, Daley WL, et al. TIMI frame count: a quantitative method of assessing coronary artery flow. Circulation. 1996;93(5):879-888. doi:10.1161/01.CIR.93.5.879
3. Sezgin AT, Sigirci A, Barutcu I, et al. Vascular endothelial function in patients with slow coronary flow. Coron Artery Dis. 2003;14(2):155-161. doi:10.1097/00019501-200304000-00008
4. Mangieri E, Macchiarelli G, Ciavolella M, et al. Slow coronary flow: clinical and histopathological features in patients with otherwise normal epicardial coronary arteries. Cathet Cardiovasc Diagn. 1996;37(4):375-381. doi:10.1002/(SICI)1097-0304(199604)37:4<375::AID-CCD5>3.0.CO;2-D
5. Zhu Q, Wang S, Huang X, et al. Understanding the pathogenesis of coronary slow flow: recent advances. Trends Cardiovasc Med. 2024;34: 137-144. doi:10.1016/j.tcm.2022.12.001
6. Camsarı A, Pekdemir H, Cicek D, et al. Endothelin-1 and nitric oxide concentrations and their response to exercise in patients with slow coronary flow. Circ J. 2003;67:1022-1028. doi:10.1253/circj.67.1022
7. Beltrame JF, Limaye SB, Horowitz JD. The coronary slow flow phenomenon: a new coronary microvascular disorder. Cardiology. 2002;97(4):197-202. doi:10.1159/000063121
8. Lippi G, Targher G, Montagnana M, et al. Relation between red blood cell distribution width and inflammatory biomarkers in a large cohort of unselected outpatients. Arch Pathol Lab Med. 2009;133(4):628-632. doi:10.5858/133.4.628
9. Felker GM, Allen LA, Pocock SJ, et al. Red cell distribution width as a novel prognostic marker in heart failure. J Am Coll Cardiol. 2007;50(1): 40-47. doi:10.1016/j.jacc.2007.02.067
10. Ani C, Ovbiagele B. Elevated RDW predicts mortality in persons with known stroke. J Neurol Sci. 2009;277(1-2):103-108. doi:10.1016/j.jns. 2008.10.024
11. Tonelli M, Sacks F, Arnold M, et al. Relation between RDW and cardiovascular event rate in people with coronary disease. Circulation. 2008;117(2):163-168. doi:10.1161/CIRCULATIONAHA.107.727545
12. Azab B, Shah N, Akerman M, et al. Value of RDW in predicting long-term mortality after non-ST-elevation myocardial infarction. Am J Cardiol. 2011;107(12):1796-1801. doi:10.1016/j.amjcard.2011.02.015
13. Luo SH, Jia YJ, Nie SP, et al. Increased red cell distribution width in patients with slow coronary flow syndrome. Clinics (Sao Paulo). 2013; 68(6):732-737. doi:10.6061/clinics/2013(06)02
14. Kalay N, Aytekin M, Kaya MG, et al. The relationship between inflammation and slow coronary flow: increased RDW and serum uric acid levels. Turk Kardiyol Dern Ars. 2011;39(6):463-468. doi:10.5543/tkda.2011.01578
15. Akpinar I, Sayin MR, Gursoy YC, et al. Plateletcrit and RDW are independent predictors of slow coronary flow. Cardiol J. 2015;22(5):517-525. doi:10.1016/j.jjcc.2013.07.010
16. Nishizaki Y, Daida H. The relationship between high red blood cell distribution width and low coronary flow reserve in patients with idiopathic dilated cardiomyopathy. Anadolu Kardiyol Derg. 2014;14(4): 349-350. doi:10.5152/akd.2014.12446120141
17. Ozyurtlu F, Yavuz V, Cetin N, et al. The association between coronary slow flow and platelet distribution width among patients with stable angina pectoris. Postepy Kardiol Interw. 2014;10(3):161-165. doi:10.5114/pwki.2014.45142
18. Seyyed Mohammadzad MH, Hosseinsabet A, Zamani B, et al. Echocardiographic and laboratory findings in coronary slow flow: a case-control study. BMC Cardiovasc Disord. 2021;21:230. doi:10.1186/s12872-021-02044-z
19. Nagula P, Karumuri S, Otikunta AN, et al. Correlation of red blood cell distribution width with the severity of coronary artery disease: a single-center study. Indian Heart J. 2017;69(1):97-99. doi:10.1016/j.ihj.2017.04.007
20. Osadnik T, Strzelczyk J, Hawranek M, et al. Red cell distribution width is associated with long-term prognosis in patients with stable coronary artery disease. BMC Cardiovasc Disord. 2013;13:113. doi:10.1186/1471-2261-13-113
21. Zalawadiya SK, Veeranna V, Panaich SS, et al. Red cell distribution width and risk of coronary heart disease events. Am J Cardiol. 2010; 106(7):988-993. doi:10.1016/j.amjcard.2010.06.006
22. Isik T, Uyarel H, Tanboga IH, et al. Relation of red cell distribution width with the presence, severity, and complexity of coronary artery disease. Coron Artery Dis. 2012;23(1):51-56. doi:10.1097/MCA.0b013e 32834e4f5c
23. Dabbah S, Hammerman H, Markiewicz W, et al. Relation between red cell distribution width and clinical outcomes after acute myocardial infarction. Am J Cardiol. 2010;105(3):312-317. doi:10.1016/j.amjcard. 2009.09.027
24. Patel KV, Mohanty JG, Kanapuru B, Hesdorffer C, Ershler WB, Rifkind JM. Association of the red cell distribution width with red blood cell deformability. Adv Exp Med Biol. 2013;765:211-216. doi:10.1007/978-1-4614-4989-8_29
25. Bujak K, Wasilewski J, Osadnik T, et al. The prognostic role of red blood cell distribution width in coronary artery disease: a review of the pathophysiology. Dis Markers. 2015;2015:824624. doi:10.1155/2015/ 824624
26. Patel KV, Ferrucci L, Ershler WB, et al. Red blood cell distribution width and the risk of death in middle-aged and older adults. Arch Intern Med. 2009;169(5):515-523. doi:10.1001/archinternmed.2009.11
27. Ananthaseshan S, Sampath S, Subramanian R, et al. Effect of red blood cell distribution width on blood flow and wall shear stress: a computational study. Sci Rep. 2022;12:13764. doi:10.1038/s41598-022-17847-z
28. Solak Y, Yilmaz MI, Saglam M, et al. Red cell distribution width is independently related to endothelial dysfunction in patients with chronic kidney disease. Am J Med Sci. 2014;347(2):118-124. doi:10.1097/MAJ.0b013e3182996a96
Volume 4, Issue 4, 2025
Page : 80-84
_Footer