Mean platelet volume: An important predictor of coronary collateral development
Mean platelet volume: An important predictor of coronary collateral development
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DOI：
10.3109/09537104.2012.675107
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发表时间：
2013-01-01
期刊：
影响因子：
3.3
通讯作者：
Kisacik, Halil
中科院分区：
文献类型：
--
作者：
Ege, Meltem Refiker;Acikgoz, Savas;Kisacik, Halil
由于冠状动脉疾病（CAD）引起的缺血性刺激而发生的结肠炎有助于缩小梗死面积、左心室功能障碍和死亡率。然而，有相当大的差异，冠心病患者之间的冠状动脉侧支循环的发展（CCD）的程度。在这项研究中，我们的目的是通过平均血小板体积（MPV）研究血小板活化程度与冠状动脉侧支循环的关系。因此，210例接受冠状动脉造影术且至少一条冠状动脉狭窄>= 50%的患者被纳入研究。临床信息和血液样本的分析是从患者病历的审查中获得的。通过K3 EDTA分析MPV血样，并根据Rentrop分类对侧支血管进行分级。在研究组中，210名患者中有150名被发现CCD不足。尽管两组之间的血小板计数没有差异，但在CCD不足的患者中MPV水平显著较高（11.3 +/- 1.0 fl vs. 9.5 +/- 1.5 fl，p< 0.001）。此外，CCD不足的患者的Gensini评分显著较低（45 +/- 46 vs. 91 +/- 35，p< 0.001）。MPV、Gensini评分、年龄、女性、总胆固醇、红细胞分布宽度、甘油三酯和空腹血糖水平与不良CCD有单变量相关性。多因素Logistic回归分析显示，MPV（OR = 2.45，p< 0.001）和Gensini评分（OR = 0.98，p< 0.001）是CCD受损的独立预测因素。在受试者工作特征曲线分析中，发现MPV预测CCD不足的最佳截止值为>9.6 fl，敏感性为96%，阳性预测值为84.7%。总之，我们可以说，MPV是一个重要的，简单的，不费力的，成本效益的工具，可以用于预测严重CAD患者的CCD。
Collaterals, which develop in response to ischemic stimuli derived from coronary artery disease (CAD), contribute to reduction of infarct size, left ventricular dysfunction, and mortality. However, there is considerable variation among patients with coronary heart disease regarding the extent of coronary collateral development (CCD). In this study, we aimed to investigate the association of the degree of platelet activation via mean platelet volume (MPV) with coronary collateral circulation. Therefore, 210 patients who underwent coronary angiography and had coronary stenosis >= 50 % in at least one coronary artery were included in the study. Clinical information and analyses of blood samples were obtained from a review of the patients' chart. Blood samples for MPV were analyzed by K3 EDTA and collateral vessels were graded according to the Rentrop classification. In the study group, 150 of the 210 patients were found to have inadequate CCD. Although there was no difference between the two groups with regard to platelet count, MPV levels were significantly higher in the patients who had inadequate CCD (11.3 +/- 1.0 fl vs. 9.5 +/- 1.5 fl, p< 0.001). Furthermore, the Gensini score was significantly lower in patients who had inadequate CCD (45 +/- 46 vs. 91 +/- 35, p< 0.001). MPV, Gensini score, age, female gender, total cholesterol, red cell distribution width, triglyceride, and fasting glucose levels were found to have univariate association with poor CCD. In multivariate logistic regression model, MPV (OR = 2.45, p< 0.001) and Gensini score (OR = 0.98, p< 0.001) were found to be the independent predictors of impaired CCD. In receiver operator characteristic curve analysis, optimal cut-off value of MPV to predict inadequate CCD was found as >9.6 fl, with 96% sensitivity and 84.7% positive predictive value. In conclusion, we can say that MPV is an important, simple, effortless, and cost effective tool and can be useful in predicting the CCD in patients with significant CAD.