4.8 Article

Analysis of 12-lead T-wave morphology for risk stratification after myocardial infarction

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CIRCULATION
卷 102, 期 11, 页码 1252-1257

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LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/01.CIR.102.11.1252

关键词

myocardial infarction; death, sudden; risk factors; waves; electrocardiography

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Background-The stratification of post-myocardial infarction (MI) patients at risk of sudden cardiac death remains important. The aim of the present study was to assess the prognostic value of novel T-wave morphology descriptors derived from resting 12-lead ECGs. Methods and Results-In 280 consecutive post-MI patients, a 12-lead ECG was recorded before discharge, optically scanned, and digitized. For the present study, 5 T-wave morphology descriptors were automatically calculated after singular value decomposition of the ECG signal. The total cosine R-to-T (TCRT [describes the global angle between repolarization and depolarization wavefront]) and the T-wave loop dispersion were univariately associated (P = 0.0002 and P < 0.002, respectively, U test) with 27 prospectively defined clinical events in 261 patients (mean follow-up 32 +/- 10 months). Kaplan-Meier event probability curves for strata above and below the median confirmed the strong risk discrimination by TCRT and T-wave loop dispersion (P < 0.003 and P < 0.001, respectively, log-rank test). On Cox regression analysis, with the entering of age, left ventricular ejection fraction, heart rate, QRS width, reperfusion therapy, beta-adrenergic-blocker treatment, and standard deviation of R-R intervals on 24-hour Holter monitoring, TCRT (P < 0.03) yielded independent predictive value, whereas T-wave loop dispersion was of borderline independence (P = 0.064). Heart rate (P < 0.02), left ventricular ejection fraction (P < 0.02), and reperfusion therapy (P < 0.02) also remained in the final model. Conclusions-Computerized T-wave morphology analysis of the 12-lead resting ECG permits independent assessment of post-MI risk and an improved risk stratification when combined with other risk markers.

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