Document Detail


Prediction of severe coronary artery disease using computerized ECG measurements and discriminant function analysis.
MedLine Citation:
PMID:  1297708     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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)
Authors:
I Moussa; M Rodriguez; J Froning; V F Froelicher
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Journal of electrocardiology     Volume:  25 Suppl     ISSN:  0022-0736     ISO Abbreviation:  J Electrocardiol     Publication Date:  1992  
Date Detail:
Created Date:  1993-05-06     Completed Date:  1993-05-06     Revised Date:  2009-11-11    
Medline Journal Info:
Nlm Unique ID:  0153605     Medline TA:  J Electrocardiol     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  49-58     Citation Subset:  IM    
Affiliation:
Cardiology Division, Palo Alto Medical Center, CA 94304.
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MeSH Terms
Descriptor/Qualifier:
Adult
Aged
Confounding Factors (Epidemiology)
Coronary Angiography
Coronary Disease / diagnosis*,  drug therapy,  radiography
Digoxin / therapeutic use
Discriminant Analysis
Electrocardiography*
Exercise Test
Humans
Male
Middle Aged
Predictive Value of Tests
ROC Curve
Retrospective Studies
Signal Processing, Computer-Assisted*
Chemical
Reg. No./Substance:
20830-75-5/Digoxin

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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