Volume 33, Issue 7 (October 2022)                   Studies in Medical Sciences 2022, 33(7): 520-527 | Back to browse issues page

Ethics code: IR.UMSU.REC.1401.330


XML Persian Abstract Print


Assistant Professor of Echocardiography, Department of Cardiology, Urmia Medical School, Urmia University of Medical Sciences, Urmia, Iran (Corresponding Author) , vahidalinejad64@gmail.com
Abstract:   (950 Views)
Background & Aims: In this study, we aimed to investigate the differences between laboratory indices and angiographic characteristics of the patients with coronary artery disease in two groups of metabolic syndrome and non-metabolic syndrome.
Materials & Methods: In this retrospective cohort study, 180 patients who were hospitalized due to coronary artery occlusion were included in the study. The patients were divided into two groups of with and without metabolic syndrome. The patients were then divided based on the number of coronary artery occlusions into four subgroups, in terms of cardiac output into 4 subgroups, and in terms of BMI into three subgroups. Finally, the studied variables were compared between these two groups and the analysis of this information was done using SPSS 20 software.
Results: In this study, 84 patients (46.7%) had metabolic syndrome. All of these patients had coronary artery disease, 81(45%) with stenosis in one vessel, 53(29.4%) in 2 vessels, 33(18.3%) in 3 vessels, and 13(7.2%) with stenosis in 4 vessels. 147 patients (81.7%) were male, and the mean age of the participants was 57.24±12.52 years. The mean age and HDL in the group with metabolic syndrome were lower than those without it. However, the mean count of Hb, WBC, and Neutrophils in the group with metabolic syndrome was higher than the group without it.
Conclusion: Patients with metabolic syndrome who had been hospitalized for heart disease had lower age and HDL but higher BMI than the patients without metabolic syndrome. There was no difference between patients with and without metabolic syndrome in terms of left ventricular output and the number of coronary arteries involved. In general, simultaneously having metabolic syndrome affects the laboratory and angiographic indices of the patients with coronary artery disease.
 
Full-Text [PDF 471 kb]   (557 Downloads)    
Type of Study: Research | Subject: قلب و عروق

References
1. Carter AR, Gill D, Davies NM, Taylor AE, Tillmann T, Vaucher J, et al. Understanding the consequences of education inequality on cardiovascular disease: mendelian randomisation study. Br Med J 2019;365:l1855. [DOI:10.1136/bmj.l1855] [PMID] [PMCID]
2. Pinaire J, Azé J, Bringay S, Cayla G, Landais P. Hospital burden of coronary artery disease: Trends of myocardial infarction and/or percutaneous coronary interventions in France 2009-2014. PLoS One 2019;14(5):e0215649. [DOI:10.1371/journal.pone.0215649] [PMID] [PMCID]
3. Alhabib KF, Kinsara AJ, Alghamdi S, Al-Murayeh M, Hussein GA, AlSaif S, et al. The first survey of the Saudi Acute Myocardial Infarction Registry Program: Main results and long-term outcomes (STARS-1 Program). PLoS One 2019;14(5):e0216551. [DOI:10.1371/journal.pone.0216551] [PMID] [PMCID]
4. Rencuzogullari I, Karabağ Y, Çağdaş M, Karakoyun S, Seyis S, Gürsoy MO, et al. Assessment of the relationship between preprocedural C-reactive protein/albumin ratio and stent restenosis in patients with ST-segment elevation myocardial infarction. Rev Port Cardiol 2019;38(4):269-77. [DOI:10.1016/j.repc.2018.08.008] [PMID]
5. Odoi EW, Nagle N, Roberson S, Kintziger KW. Geographic disparities and temporal changes in risk of death from myocardial infarction in Florida, 2000-2014. BMC Pub Health 2019;19(1):505. [DOI:10.1186/s12889-019-6850-x] [PMID] [PMCID]
6. Roth C, Berger R, Kuhn M. The role of the socio-economic environment on medical outcomes after ST-segment elevation myocardial infarction. BMC Pub Health 2019;19(1):630. [DOI:10.1186/s12889-019-6966-z] [PMID] [PMCID]
7. Huang HL, Chen CH, Kung CT, Li YC, Sung PH, You HL, et al. Clinical utility of mean platelet volume and immature platelet fraction in acute coronary syndrome. Biomed J 2019;42(2):107-15. [DOI:10.1016/j.bj.2018.12.005] [PMID] [PMCID]
8. Xu L, Wang L, Li K, Zhang Z, Sun H, Yang X. Nicorandil prior to primary percutaneous coronary intervention improves clinical outcomes in patients with acute myocardial infarction: a meta-analysis of randomized controlled trials. Drug Des Devel Ther 2019;13:1389-400. [DOI:10.2147/DDDT.S195918] [PMID] [PMCID]
9. Lee HJ, Jang J, Lee SA, Choi DW, Park EC. Association between Breakfast Frequency and Atherosclerotic Cardiovascular Disease Risk: A Cross-Sectional Study of KNHANES Data, 2014-2016. Int J Environ Res Public Health 2019;16(10). [DOI:10.3390/ijerph16101853] [PMID] [PMCID]
10. Dzubur A, Gacic E, Mekic M. Comparison of Patients with Acute Myocardial Infarction According to Age. Med Arch 2019;73(1):23-7. [DOI:10.5455/medarh.2019.73.23-27] [PMID] [PMCID]
11. Hardy DS, Garvin JT, Mersha TB, Racette SB. Ancestry specific associations of FTO gene variant and metabolic syndrome: A longitudinal ARIC study. Medicine (Baltimore). 2020;99(6):e18820. [DOI:10.1097/MD.0000000000018820] [PMID] [PMCID]
12. Lima MDCP, Melo ASO, Sena ASS, Barros VO, Amorim MMR. Metabolic syndrome in pregnancy and postpartum: prevalence and associated factors. Rev Assoc Med Bras 2019;65(12):1489-95. [DOI:10.1590/1806-9282.65.12.1489] [PMID]
13. Kim HJ, Ko Y, Kim H, Cha YY, Jang BH, Song YK, et al. A pilot study exploring the efficacy and safety of herbal medicine on Korean obese women with metabolic syndrome risk factors: Double blinded, randomized, multicenter, placebo controlled study protocol clinical trial. Medicine (Baltimore) 2020;99(5):e18955. [DOI:10.1097/MD.0000000000018955] [PMID] [PMCID]
14. Chen PY, Cripps AW, West NP, Cox AJ, Zhang P. A correlation-based network for biomarker discovery in obesity with metabolic syndrome. BMC Bioinf 2019;20(Suppl 6):477. [DOI:10.1186/s12859-019-3064-2] [PMID] [PMCID]
15. Lukács A, Horváth E, Máté Z, Szabó A, Virág K, Papp M, et al. Abdominal obesity increases metabolic risk factors in non-obese adults: a Hungarian cross-sectional study. BMC Pub Health 2019;19(1):1533. [DOI:10.1186/s12889-019-7839-1] [PMID] [PMCID]
16. Adachi N, Kobayashi Y. One-year follow-up study on associations between dental caries, periodontitis, and metabolic syndrome. J Oral Sci 2020;62(1):52-6. [DOI:10.2334/josnusd.18-0251] [PMID]
17. Fan L, Hao Z, Gao L, Qi M, Feng S, Zhou G. Non-linear relationship between sleep duration and metabolic syndrome: A population-based study. Medicine (Baltimore) 2020;99(2):e18753. [DOI:10.1097/MD.0000000000018753] [PMID] [PMCID]
18. Zhao Y, Yu Y, Li H, Li M, Zhang D, Guo D, Yu X, et al. The Association between Metabolic Syndrome and Biochemical Markers in Beijing Adolescents. Int J Environ Res Public Health 2019 18;16(22). [DOI:10.3390/ijerph16224557] [PMID] [PMCID]
19. Misselbeck K, Parolo S, Lorenzini F, Savoca V, Leonardelli L, Bora P, et al. A network-based approach to identify deregulated pathways and drug effects in metabolic syndrome. Nat Commun. 2019;10(1):5215. [DOI:10.1038/s41467-019-13208-z] [PMID] [PMCID]
20. Yang YJ, Park HJ, Won KB, Chang HJ, Park GM, Kim YG, et al. Relationship between the optimal cut-off values of anthropometric indices for predicting metabolic syndrome and carotid intima-medial thickness in a Korean population. Medicine (Baltimore) 2019;98(42):e17620. [DOI:10.1097/MD.0000000000017620] [PMID] [PMCID]
21. Mirmiran P, Ziadlou M, Karimi S, Hosseini-Esfahani F, Azizi F. The association of dietary patterns and adherence to WHO healthy diet with metabolic syndrome in children and adolescents: Tehran lipid and glucose study. BMC Public Health 2019;19(1):1457. [DOI:10.1186/s12889-019-7779-9] [PMID] [PMCID]
22. Liu CC, Ko HJ, Liu WS, Hung CL, Hu KC, Yu LY, et al. Neutrophil-to-lymphocyte ratio as a predictive marker of metabolic syndrome. Medicine (Baltimore) 2019;98(43):e17537. [DOI:10.1097/MD.0000000000017537] [PMID] [PMCID]
23. Jang I, Kim JS. Risk of Cardiovascular Disease Related to Metabolic Syndrome in College Students: A Cross-Sectional Secondary Data Analysis. Int J Environ Res Public Health 20191;16(19). [DOI:10.3390/ijerph16193708] [PMID] [PMCID]
24. Rimárová K, Dorko E, Diabelková J, Sulinová Z, Urdzík P, Pelechová N, et al. Prevalence of lifestyle and cardiovascular risk factors in a group of medical students. Cent Eur J Public Health 2018 Dec;26 Suppl:S12-S8. [DOI:10.21101/cejph.a5477] [PMID]
25. Tran BT, Jeong BY, Oh JK. The prevalence trend of metabolic syndrome and its components and risk factors in Korean adults: results from the Korean National Health and Nutrition Examination Survey 2008-2013. BMC Pub Health 2017;17(1):71. [DOI:10.1186/s12889-016-3936-6] [PMID] [PMCID]
26. Kim S, Kim DI. Association of regular walking and body mass index on metabolic syndrome among an elderly Korean population. Exp Gerontol 2018;106:178-82. [DOI:10.1016/j.exger.2018.03.004] [PMID]
27. Kranjcec D, Altabas V. Metabolic syndrome influencing infarct size and heart failure in patients with acute coronary syndrome: does gender matter? Endocr J 2012;59(12):1065-76. Epub 2012 Aug 17. [DOI:10.1507/endocrj.EJ12-0131] [PMID]
28. Voulgari C, Tentolouris N, Dilaveris P, Tousoulis D, Katsilambros N, Stefanadis C. Increased heart failure risk in normal-weight people with metabolic syndrome compared with metabolically healthy obese individuals. J Am Coll Cardiol 2011;58(13):1343-50. [DOI:10.1016/j.jacc.2011.04.047] [PMID]
29. von Bibra H, Ströhle A, St John Sutton M, Worm N. Dietary therapy in heart failure with preserved ejection fraction and/or left ventricular diastolic dysfunction in patients with metabolic syndrome. Int J Cardiol 2017;234:7-15. [DOI:10.1016/j.ijcard.2017.01.003] [PMID]

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.