Weintraub W S, Barr-Alderfer V A, Seelaus P A, Bodenheimer M M, Madeira S W, Katz R I, Feldman M S, Agarwal J B, Banka V S, Helfant R H
Am Heart J. 1985 May;109(5 Pt 1):999-1005. doi: 10.1016/0002-8703(85)90241-8.
There has been considerable interest in recent years in enhancing the accuracy of noninvasive tests in diagnosing coronary artery disease. The recognition that no currently available test is a perfect predictor has led to the use of probability analysis as a means of assessing the presence or absence of coronary disease. In this article we present a multivariate approach to the diagnosis of coronary disease. One hundred forty-seven patients undergoing coronary angiography, thallium-201 imaging, and exercise ECG were studied. Patients were classified according to age, sex, and typical vs atypical chest pain. Sequential stepwise logistic regression analysis was performed to develop probability statements prior to testing, after exercise ECG, and after exercise ECG and thallium-201. The results indicate that this sequential approach can be used to develop strategies for the diagnosis of coronary disease in the same way as Bayes' theorem, while permitting integration of multiple characteristics into one model.
近年来，提高非侵入性检测诊断冠状动脉疾病的准确性备受关注。由于认识到目前没有一种检测方法是完美的预测指标，概率分析已被用作评估冠状动脉疾病是否存在的一种手段。在本文中，我们提出了一种用于诊断冠状动脉疾病的多变量方法。对147例接受冠状动脉造影、铊-201心肌显像和运动心电图检查的患者进行了研究。患者根据年龄、性别以及典型或非典型胸痛进行分类。在检测前、运动心电图后以及运动心电图和铊-201心肌显像后，进行了逐步逻辑回归分析以得出概率陈述。结果表明，这种逐步方法可用于制定诊断冠状动脉疾病的策略，其方式与贝叶斯定理相同，同时允许将多个特征整合到一个模型中。
