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BACKGROUND. The aim of this study was to evaluate the potential
advantages of sequential Bayesian testing for the identification of patients at high risk for arrhythmic events after
myo-cardial infarction.
METHODS. In 265 patients with remote myocardial infarction the QT dispersion, defined as the difference
between the maximum and the minimum QT interval across the 12-lead ECG was calculated.
RESULTS. During follow-up of 32±19 months the arrhythmic events (sustained ventricular tachycardia, ventricular
fibrillation or sudden death) were noted in 58 patients. At univariate analysis the QT dispersion ³80 ms (p = 0.0059),
RR interval <750 ms (p = 0.0003), left ventricular ejection fraction <40% (p = 0.0011), ST-segment depression
(p = 0.0224) and ³10/h ventricular premature beats on Holter monitoring (p = 0.0151) were significant predictors
of arrhythmic events. Positive predictive accuracy of 34% for QT dispersion ³80 ms in the total group increased
to 64% in subgroup with RR interval <750 ms, and to 50% in subgroup with left ventricular ejection fraction
<40%, but negative predictive accuracy decreased from 81 to 75% and 74%, respectively.
CONCLUSIONS. Prolonged QT dispersion was associated with a higher risk for arrhythmic events. Sequential
Bayesian testeng strongly increased the positive predictive value and less markedly decreased the negative
predictive value of QT dispersion in patients after myocardial infarction.
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