Diagnostic value of computerized exercise testing in men without previous myocardial infarction. A multivariate, compartmental and probabilistic approach

Abstract

The value of exercise testing for the diagnosis of coronary artery disease is disputed but very few studies have taken advantage of all recent improvements, namely computer averaging of the ECG signals, multivariate analysis of the data, a compartmental diagnostic approach and probabilistic interpretation of the results. These methods were tested in a group of 387 men who had a computer-assisted multistage maximal exercise test; none had a history of myocardial infarction. In 284 symptomatic patients, the diagnosis was made by arteriography; 103 ostensibly healthy men were also included. The computer-averaged ECG signals (X, Y, Z) recorded at maximal exercise, maximal heart rate, blood pressure and workload, and the onset of angina pectoris during exercise were submitted to a multivariate stepwise discriminant analysis. The pretest likelihood for CAD was calculated from age and history; the post-test likelihood was calculated from Bayes' theorem and the average information content of several diagnostic methods was assessed in categorical and compartmental models. By multivariate analysis, 5 variables collected at maximal exercise were selected, namely the heart-rate, the ST60 segment level, the onset of angina during the test, the workload and the slope of the ST segment in lead X. The average information content of the analysis using 5 variables was 44% in a categorical model versus 55% in a compartmental model (P less than 0.001). For comparison, the information content of the analysis using the ST60 segment level alone was only 16% in the categorical model and 27% in the compartmental model. The clinical value of these diagnostic methods (categorical versus compartmental, univariate versus multivariate) was assessed by a probabilistic classification of the patients. The classification provided by the analysis of the ST60 segment changes was barely better than that one provided by the simple history. The probabilistic use of a multivariate and compartmental analysis of the data led to a significantly better and more accurate classification of the patients (83% of correct classification).

Contribution of Exercise-Induced Mitral Regurgitation to Exercise Stroke Volume and Exercise Capacity in Patients With Left Ventricular Systolic Dysfunction

“…Throughout the exercise tests, the 3 Frank orthogonal ECG leads were monitored continuously, recorded on paper, and analyzed by computer as described previously. 17 In patients with ischemic heart disease, the presence of inducible myocardial ischemia was excluded by use of thallium imaging as described previously. 18 …”

The Value of Chest Pain during the Exercise Tolerance Test in Predicting Coronary Artery Disease

“…When considered simultaneously with the ST-segment response and other com monly measured exercise tolerance test (ETT) variables, the presence of exertional chest pain has been shown to either increase the risk of CAD [7. 23,29] or add no unique predic tive information [10,25,27,28,30] concern ing the presence or absence of CAD.…”

A new semiautomated algorithm to quantify holter-detected myocardial ischemia: Preliminary experience in the trimetazidine european multicenter trial (TEMS)

“…In order to test the accuracy of the whole Holter system, calibration signals and two leads (X and Y of the Frank system) were simultaneously recorded during a maximal bicycle exercise test through the same electrode system on a Holter tape and on our computerized system for the analysis and interpretation of the exertional ECG [6,15,16]; this was done in 20 coronary patients, yielding 47 simultaneous measurements for comparison.…”

“…This should be based on history (complaints), risk factor evaluation, and modern (i.e., computer-assisted) symptom-limited maximal exercise testing combined, whenever clinically useful, with stress perfusion scintigraphy and late imaging [1][2][3][4][5][6].…”

“…The Holter system was tested with an identical signal recorded on a previously designed and described system for the analysis of the exercise-induced STsegment shifts [6,15,16].…”