Schmermund A, Bailey K R, Rumberger J A, Reed J E, Sheedy P F, Schwartz R S
Division of Cardiovascular Diseases and Internal Medicine, Mayo Clinic and Foundation, Rochester, Minnesota, USA.
J Am Coll Cardiol. 1999 Feb;33(2):444-52. doi: 10.1016/s0735-1097(98)00565-8.
We sought to model an algorithm for noninvasive identification of angiographically obstructive three-vessel and/or left main disease based on conventional cardiac risk assessment and site and extent of coronary calcium determined by electron-beam computed tomography (EBCT).
Such an algorithm would greatly facilitate clinical triage in symptomatic patients with no previous diagnosis of coronary artery disease (CAD).
We examined 291 patients with suspected, but not previously diagnosed, CAD who underwent coronary angiography for clinical indications. Cardiac risk factors were determined as defined by the National Cholesterol Education Program. An EBCT scan was performed in all patients, and a coronary calcium score (Agatston method) was computed. Total per-patient calcium scores and separate scores for the major coronary arteries were generated. These scores were also analyzed for localization of coronary calcium in the more distal versus proximal tomographic sections. These parameters and the risk factors were considered for the model described in the following section.
Sixty-eight patients (23%) had angiographic three-vessel and/or left main CAD. Multiple logistic regression analysis determined male sex, presence of diabetes and left anterior descending (LAD) and circumflex (LCx) coronary calcium scores, independent from more distal calcium localization, as independent predictors for identification of three-vessel and/or left main CAD. Based on this four variable model, a simple noninvasive index (NI) was constructed as the following: loge(LAD score) + log(e)(LCx score) + 2[if diabetic] + 3[if male]. Receiver operating characteristic curve analysis for this NI yielded an area under the curve of 0.88+/-0.03 (p < 0.0001) for separating patients with, versus without, angiographic three-vessel and/or left main CAD. Various NI cutpoints demonstrated sensitivities from 87-97% and specificities from 46-74%. The NI values >14 increased the probability of angiographic three-vessel and/or left main CAD from 23% (pretest) to 65-100% (posttest), and NI values <10 increased the probability of no three-vessel and/or left main CAD from 77% (pretest) to 95-100% (posttest).
On the basis of a simple algorithm ("noninvasive index"), EBCT calcium scanning in conjunction with risk factor analysis can rule in or rule out angiographically severe disease, i.e., three-vessel and/or left main CAD, in symptomatic patients.
我们试图构建一种算法，用于基于传统心脏风险评估以及通过电子束计算机断层扫描（EBCT）测定的冠状动脉钙化部位和范围，对血管造影显示为阻塞性三支血管病变和/或左主干病变进行无创识别。
这样一种算法将极大地有助于对既往未诊断为冠状动脉疾病（CAD）的有症状患者进行临床分诊。
我们检查了291例因临床指征接受冠状动脉造影的疑似但既往未诊断为CAD的患者。按照国家胆固醇教育计划的定义确定心脏危险因素。所有患者均进行了EBCT扫描，并计算了冠状动脉钙化评分（阿加斯顿法）。得出每位患者的总钙化评分以及主要冠状动脉的单独评分。还分析了这些评分以确定冠状动脉钙化在断层扫描较远端与较近端节段的定位情况。在下文中描述的模型中考虑了这些参数和危险因素。
68例患者（23%）血管造影显示为三支血管病变和/或左主干CAD。多因素逻辑回归分析确定男性、糖尿病的存在以及左前降支（LAD）和回旋支（LCx）冠状动脉钙化评分（独立于更远端的钙定位）为识别三支血管病变和/或左主干CAD的独立预测因素。基于这个四变量模型，构建了一个简单的无创指数（NI）如下：loge（LAD评分）+ loge（LCx评分）+ 2[如果是糖尿病患者]+ 3[如果是男性]。该NI的受试者工作特征曲线分析得出，用于区分血管造影显示为三支血管病变和/或左主干CAD与无此类病变患者的曲线下面积为0.88±0.03（p < 0.0001）。不同的NI切点显示敏感性为87 - 97%，特异性为46 - 74%。NI值>14使血管造影显示为三支血管病变和/或左主干CAD的概率从23%（检查前）增加到65 - 100%（检查后），而NI值<10使无三支血管病变和/或左主干CAD的概率从77%（检查前）增加到95 - 100%（检查后）。
基于一种简单算法（“无创指数”），EBCT钙化扫描结合危险因素分析可以在有症状患者中判断血管造影显示的严重疾病，即三支血管病变和/或左主干CAD是否存在。
