Moussa I, Rodriguez M, Froning J, Froelicher V F
Cardiology Division, Palo Alto Medical Center, CA 94304.
J Electrocardiol. 1992;25 Suppl:49-58. doi: 10.1016/0022-0736(92)90061-4.
This study tested the hypothesis that discriminant function analysis of clinical and exercise-test variables including computerized ST measurements could improve the prediction of severe coronary artery disease. Secondary objectives were to demonstrate the effect of digoxin and/or resting electrocardiographic (ECG) abnormalities, and to evaluate the relative importance of ST measurements made during the recovery phase and in the three lead group areas. The design was a retrospective analysis of data collected during exercise testing and coronary angiography. The ECG data were gathered and stored in digital format on optical discs and all ST measurements were made off-line using the authors' own software. Univariate and multivariate analytic methods were used to analyze all pretest characteristics as well as hemodynamic and computerized ECG responses to exercise. A 1,000-bed Veterans Affairs Medical Center served as the setting. The study included 446 male veterans who underwent a sign or symptom limited treadmill exercise test and coronary angiography. Analysis was also performed on a subset of this population formed by excluding patients receiving digoxin or with resting ECGs exhibiting left ventricular hypertrophy or ST depression (n = 328). In the total study population, the authors derived a treadmill score using discriminant function analysis. This score included: (1) the time-slope area in lead V5 during recovery; (2) delta heart rate; (3) angina pectoris during the exercise test; and (4) presence of diagnostic Q waves on the resting ECG. This score was effective in predicting triple vessel/left main disease and outperformed exercise-induced ST depression for predicting severe coronary artery disease. After exclusion of patients with ECGs exhibiting left ventricular hypertrophy or resting ST depression and patients receiving digoxin, discriminant function analysis chose: (1) the time-slope area in lead V5 during recovery and (2) delta heart rate. Exclusion of these patients resulted in a nonsignificant decrease in specificity of all ST criteria. ST-segment amplitude or slope in lead V5 at 3.5 minutes in recovery clearly outperformed the maximal exercise measurements in both groups. Summing the depressions or selecting the most depression in the three areas (ie, lateral-V5, inferior-II, anterior-V2) did not improve test performance. Leads other than V5 did not contain significant diagnostic information. A quantitative approach to exercise testing using discriminant function analysis enhanced the tests' performance for predicting severe coronary disease. The inclusion of patients taking digoxin or with resting ECG abnormalities nonsignificantly decreases the specificity of all ST criteria.(ABSTRACT TRUNCATED AT 400 WORDS)
对包括计算机化ST段测量在内的临床和运动测试变量进行判别函数分析，可改善对严重冠状动脉疾病的预测。次要目标是证明地高辛和/或静息心电图（ECG）异常的影响，并评估恢复阶段和三个导联组区域进行的ST段测量的相对重要性。研究设计为对运动测试和冠状动脉造影期间收集的数据进行回顾性分析。ECG数据以数字格式收集并存储在光盘上，所有ST段测量均使用作者自己的软件离线进行。采用单变量和多变量分析方法分析所有测试前特征以及运动时的血流动力学和计算机化ECG反应。以一家拥有1000张床位的退伍军人事务医疗中心为研究场所。该研究纳入了446名男性退伍军人，他们接受了症状或体征受限的跑步机运动测试和冠状动脉造影。还对通过排除接受地高辛治疗或静息ECG显示左心室肥厚或ST段压低的患者形成的该人群子集进行了分析（n = 328）。在整个研究人群中，作者使用判别函数分析得出了一个跑步机评分。该评分包括：（1）恢复期间V5导联的时间-斜率面积；（2）心率变化；（3）运动测试期间的心绞痛；（4）静息ECG上诊断性Q波的存在。该评分在预测三支血管/左主干疾病方面有效，并且在预测严重冠状动脉疾病方面优于运动诱发的ST段压低。排除静息ECG显示左心室肥厚或ST段压低的患者以及接受地高辛治疗的患者后，判别函数分析选择了：（1）恢复期间V5导联的时间-斜率面积和（2）心率变化。排除这些患者导致所有ST标准的特异性无显著降低。恢复3.5分钟时V5导联的ST段振幅或斜率在两组中均明显优于最大运动测量值。将三个区域（即外侧-V5、下壁-II、前壁-V2）的压低值相加或选择最明显的压低值并不能提高测试性能。V5导联以外的导联不包含显著的诊断信息。使用判别函数分析的运动测试定量方法提高了测试对预测严重冠状动脉疾病的性能。纳入服用地高辛或有静息ECG异常的患者会使所有ST标准的特异性无显著降低。（摘要截短至400字）
