İleri Mehmet, Güray Ümit, Yetkin Ertan, Gürsoy Havva Tuğba, Bayır Pınar Türker, Şahin Deniz, Elalmış Özgül Uçar, Büyükaşık Yahya
Department of Cardiology, Ankara Numune Education and R esearch Hospital, Ankara, Turkey.
Cardiol J. 2016;23(1):107-13. doi: 10.5603/CJ.a2015.0064. Epub 2015 Sep 28.
We aimed to investigate the clinical features associated with development of coronary collateral circulation (CCC) in patients with acute non-ST-elevation myocardial infarction (NSTEMI) and to develop a scoring model for predicting poor collateralization at hospital admission.
The study enrolled 224 consecutive patients with NSTEMI admitted to our coronary care unit. Patients were divided into poor (grade 0 and 1) and good (grade 2 and 3) CCC groups.
In logistic regression analysis, presence of diabetes mellitus, total white blood cell (WBC) and neutrophil counts and neutrophil to lymphocyte ratio (NLR) were found as independent positive predictors of poor CCC, whereas older age (≥ 70 years) emerged as a negative indicator. The final scoring model was based on 5 variables which were significant at p < 0.05 level following multivariate analysis. Presence of diabetes mellitus, and elevated total WBC (≥ 7.85 × 103/μL) and neutrophil counts (≥ 6.25 × 103/μL) were assigned with 2 points; high NLR (≥ 4.5) with 1 point and older age (≥ 70 years old) with -1 point. Among 30 patients with risk score ≤ 1, 29 had good CCC (with a 97% negative predictive value). On the other hand, 139 patients had risk score ≥ 4; out of whom, 130 (with a 93.5% positive predictive value) had poor collateralization. Sensitivity and specificity of the model in predicting poor collateralization in patients with scores ≤ 1 and ≥ 4 were 99.2% (130/131) and +76.3 (29/38), respectively.
This study represents the first prediction model for degree of coronary collateralization in patients with acute NSTEMI.
我们旨在研究急性非ST段抬高型心肌梗死（NSTEMI）患者冠状动脉侧支循环（CCC）形成的相关临床特征，并建立一个用于预测入院时侧支循环不良的评分模型。
该研究纳入了连续224例入住我们冠心病监护病房的NSTEMI患者。患者被分为CCC不良（0级和1级）和良好（2级和3级）两组。
在逻辑回归分析中，发现糖尿病的存在、白细胞（WBC）总数和中性粒细胞计数以及中性粒细胞与淋巴细胞比值（NLR）是CCC不良的独立阳性预测因素，而年龄较大（≥70岁）则是一个阴性指标。最终的评分模型基于多变量分析后在p < 0.05水平具有显著性的5个变量。糖尿病的存在、WBC总数升高（≥7.85×10³/μL）和中性粒细胞计数升高（≥6.25×10³/μL）各赋值2分；高NLR（≥4.5）赋值1分，年龄较大（≥70岁）赋值 -1分。在30例风险评分≤1的患者中，29例CCC良好（阴性预测值为97%）。另一方面，13
