Masoudkabir Farzad, Vasheghani-Farahani Ali, Hakki Elham, Poorhosseini Hamidreza, Sadeghian Saeed, Abbasi Seyed Hesameddin, Bahmanyar Shahram, Kassaian Seyed Ebrahim
Tex Heart Inst J. 2018 Feb 1;45(1):5-10. doi: 10.14503/THIJ-16-5906. eCollection 2018 Feb.
A major diagnostic challenge for cardiologists is to distinguish cardiac syndrome X (CSX) from obstructive coronary artery disease in women with typical angina and a positive exercise tolerance test (ETT). We performed this study to develop a scoring system that more accurately predicts CSX in this patient population. Data on 976 women with typical angina and a positive ETT who underwent coronary angiography at our center were randomly divided into derivation and validation datasets. We developed a backward stepwise logistic regression model that predicted the presence of CSX, and a scoring system was derived from it. The derivation dataset (809 patients) was calibrated by uing a Hosmer-Lemeshow goodness-of-fit test (8 degrees of freedom; χ=12.9; =0.115), and the area under the curve was 0.758. The validation dataset (167 patients) was calibrated in the same way (8 degrees of freedom; χ=9.0; =0.339), and the area under the curve was 0.782. Independent predictors of CSX were age <55 years; negative histories of smoking, diabetes mellitus, hyperlipidemia, hypertension, or familial premature coronary artery disease; and highly positive ETTs. A total score >9.5 was the optimal cutoff point for differentiating CSX from obstructive coronary artery disease. Our proposed scoring system is a simple, objective, and accurate system for distinguishing CSX from obstructive coronary artery disease in women with typical angina and positive ETTs. It may help determine which of these patients need invasive coronary angiograms or noninvasive tests like computed tomographic coronary angiography.
对于心脏病专家来说,一项主要的诊断挑战是在患有典型心绞痛且运动耐量试验(ETT)呈阳性的女性中,区分心脏X综合征(CSX)和阻塞性冠状动脉疾病。我们开展这项研究以开发一种评分系统,该系统能更准确地预测这一患者群体中的CSX。在我们中心接受冠状动脉造影的976名患有典型心绞痛且ETT呈阳性的女性的数据被随机分为推导数据集和验证数据集。我们开发了一个预测CSX存在的向后逐步逻辑回归模型,并从中得出了一个评分系统。推导数据集(809名患者)通过Hosmer-Lemeshow拟合优度检验(8个自由度;χ=12.9;P=0.115)进行校准,曲线下面积为0.758。验证数据集(167名患者)以相同方式进行校准(8个自由度;χ=9.0;P=0.339),曲线下面积为0.782。CSX的独立预测因素为年龄<55岁;吸烟、糖尿病、高脂血症、高血压或家族性早发冠状动脉疾病的病史为阴性;以及ETT高度阳性。总分>9.5是区分CSX和阻塞性冠状动脉疾病的最佳临界点。我们提出的评分系统是一种简单、客观且准确的系统,用于在患有典型心绞痛且ETT呈阳性的女性中区分CSX和阻塞性冠状动脉疾病。它可能有助于确定这些患者中哪些需要进行有创冠状动脉造影或计算机断层扫描冠状动脉造影等无创检查。