PloS one · 2014
Relation of leukocytes and its subsets counts with the severity of stable coronary artery disease in patients with diabetic mellitus.
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Hong Li-Feng, Li Xiao-Lin, Luo Song-Hui, Guo Yuan-Lin, Liu Jun, Zhu Cheng-Gang, Qing Ping, Xu Rui-Xia, Wu Na-Qiong, Jiang Li-Xin, Li Jian-Jun
Аннотация
BACKGROUND: Both coronary artery disease (CAD) and diabetes mellitus (DM) are associated with inflammation. However, whether and which leukocytes can predict the presence and extent of CAD in patients with DM has not been investigated. The aim of the present study was to examine the association of leukocyte and its subsets counts with the severity of CAD in patients with DM.
METHODS AND FINDINGS: Three hundred and seventy-three diabetic patients who were scheduled for coronary angiography due to typical stable angina pectoris were enrolled in this study. They were classified into the three groups according to tertiles of Gensini score (GS, low group <8, n=143; intermediate group 8~28, n=109; high group >28, n=121). The relationship between the leukocyte and its subsets counts with the severity of CAD were evaluated. The data indicated that there were significant correlations between leukocyte and neutrophil counts with GS (r=0.154 and 0.156, respectively, all P<0.003 for Pearson's correlation). Similarly, area under the receivers operating characteristic curve of leukocyte and neutrophil counts were 0.61 and 0.60 respectively (95%CI: 0.55-0.67, all P=0.001) for predicting high GS. Multivariate logistic regression analysis demonstrated that leukocyte count was an independent predictor for high GS patients with DM (OR=1.20, 95%CI 1.03-1.39, P=0.023) after adjusting for conventional risk factors of CAD.
CONCLUSIONS: Compared with its subsets, leukocyte count appeared to be an independent predictor for the severity of CAD and the optimal cut-off value for predicting high GS (>28 points) was 5.0 × 10(9) cells/L in diabetic patients.
METHODS AND FINDINGS: Three hundred and seventy-three diabetic patients who were scheduled for coronary angiography due to typical stable angina pectoris were enrolled in this study. They were classified into the three groups according to tertiles of Gensini score (GS, low group <8, n=143; intermediate group 8~28, n=109; high group >28, n=121). The relationship between the leukocyte and its subsets counts with the severity of CAD were evaluated. The data indicated that there were significant correlations between leukocyte and neutrophil counts with GS (r=0.154 and 0.156, respectively, all P<0.003 for Pearson's correlation). Similarly, area under the receivers operating characteristic curve of leukocyte and neutrophil counts were 0.61 and 0.60 respectively (95%CI: 0.55-0.67, all P=0.001) for predicting high GS. Multivariate logistic regression analysis demonstrated that leukocyte count was an independent predictor for high GS patients with DM (OR=1.20, 95%CI 1.03-1.39, P=0.023) after adjusting for conventional risk factors of CAD.
CONCLUSIONS: Compared with its subsets, leukocyte count appeared to be an independent predictor for the severity of CAD and the optimal cut-off value for predicting high GS (>28 points) was 5.0 × 10(9) cells/L in diabetic patients.