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• W3099349528 abstract "Coronary artery disease (CAD) is the leading cause of morbidity and mortality worldwide. Coronary angiography allows an accurate assessment of the extent and severity of atherosclerotic coronary narrowing, but it provides little characterization of early detection of potentially asymptomatic vulnerable plaque. The identification of the coronary “vulnerable patient” or high-risk plaques remains a major challenge in the treatment of CAD. Recently, growing evidence shows that DNA damage plays a role in the initiation and progression of atherosclerotic plaque. Cytokinesis-block micronucleus (CBMN) assay is one of the most frequently used and validated method for assessing chromosomal damage and genetic instability. Accordingly, the purpose of this systematic review was to retrieve and discuss existing literature on the studies assessing the association between MN and angiographically-proven CAD. A total of 8 studies published between 2001 and 2017 were included in the meta-analysis. Despite a large heterogeneity between studies (I2= 99.7 %, p < 0.0001), an overall increase of MN frequencies was found in patients with CAD compared with control group (meta-MR = 1.96; 95 % CI, 1.5–3.2, p = 0.009). A subgroup analysis showed an increase in the frequency of MN formation for both two- vessel (MR = 2.13, 95 % CI: 0.9–6.9, p = 0.08) and three-vessel disease (MR = 2.89, 95 % CI: 1.84–4.55, P = 0.06). Overall, the results of this meta-analysis provide evidence of an association between CBMN and presence, extent and severity of angiographically-assessed CAD. However, the small number of papers analyzed requires further large and more rigorously designed studies, carefully considering a series of clinical confounding factors, such as the quality of the metabolic control, the influence of drugs and radiation imaging treatments." @default.
• W3099349528 created "2020-11-23" @default.
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• W3099349528 date "2021-01-01" @default.
• W3099349528 modified "2023-10-16" @default.
• W3099349528 title "Micronucleus assay for predicting coronary artery disease: A systematic review and meta-analysis" @default.
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• W3099349528 doi "https://doi.org/10.1016/j.mrrev.2020.108348" @default.
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