Diagnosis of ischemic cardiopathy in ambulatory care patients. Multivariate analysis of clinical and electrocardiographic data.

Abstract

This study was done on 113 subjects, 93 men and 20 women, whose ages ranged between 32 and 70 years (average 52.9 years). Males varied between 35 and 70 years (average 53.7) and females between 32 and 67 years (average 49.5). Our objective is: to give an account of the different discriminatory methods with mixed data usually used in medical applications, to apply these methods to all the subjects studied with the purpose of comparing their performance and, to develop a protocol for diagnosing coronary artery disease by noninvasive tests. All the subjects were referred for evaluation of chest pain, and were submitted to an exercise test on an ergometric bicycle, selective coronary angiography and left ventriculography. Patients with prior myocardial infarction, cardiomyopathy, valvular or congenital disease, mitral valve prolapse or intraventricular conduction defect were excluded. Subjects were classified as having coronary artery disease and not having coronary artery disease according to the coronarographic results. We used four clinical variables (age, sex, risk factor and chest pain) and five variables obtained from the stress test (ST depression, appearance of chest pain, appearance of arrhythmias, variations in blood pressure and R wave changes). For the analysis of this set of data we use well known univariate statistical methods, such as chi-squared test, F-test and t-test, and the following multivariate statistical methods: Fisher, Quadratic and Logistic, discriminant methods. To study the relative importance of the different variables in the discrimination of the individuals, we performed a stepwise linear discriminant analysis over the 113 subjects. Of the 9 variables tested R-wave was of little value and excluded.(ABSTRACT TRUNCATED AT 250 WORDS)