Mean Platelet Volume is Associated with Coronary Artery Disease and Cardiovascular Risk Factors, but Platelet Distribution Width Not
Journal: Medical Journal of Clinical Trials & Case Studies (Vol.2, No. 9)Publication Date: 2018-08-31
Authors : Sinem N Ahmet Goktug E Engin S; Tolga Han E;
Page : 1-7
Keywords : Coronary artery disease; Platelet indices; High sensitive C-reactive protein;
Abstract
Objective: Coronary atherosclerosis, the primary cause of coronary artery disease, is a multifactorial disease, the etiology of which involves interaction of many humoral and cellular factors. It has been also known that platelets play a pivotal role in atherothrombosis. In this study, we aimed to find out whether there is a correlation between mean platelet volume levels (MPV), platelet distribution width (PDW) levels and coronary artery disease (CAD), other diseases that may cause cardiovascular risks and to determine the relationship between high-sensitivity C-reactive protein (hs-CRP), MPV and PDW. Materials and Methods: We included 132 patients with CAD, who were diagnosed by angiography, and 82 control subjects. We evaluated MPV, PDW, and hs-CRP levels, and determined the association between these levels with cardiovascular risk factors. Results: MPV levels of the patients group were found significantly lower than the control group levels. (p=0.041). There were no significant difference between the patients group and control group in terms of PDW values (p=0.332). The hsCRP levels of the patients group was found significantly higher than the control group levels (p=0.010). In patients group there were found no significant correlation between hs-CRP levels and platelet indices levels. Conclusion: In conclusion, MPV was lower in CAD patients compared with control subjects, but PDW had no significant. There were association between MPV, and number of chronic disease. After correlation analysis, we found negative and weak correlation between platelet levels and MPV levels in CAD group. These findings may be related to our small sample size. There is a need for large-scale and new studies, to gain powerful data
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