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• W2016199581 abstract "Background Time domain analysis (TD) of the signal-averaged electrocardiogram (SAECG) presents a higher incidence of false positives in inferior myocardial infarction (MI), whereas spectral turbulence analysis (STA) suffers from a higher incidence of false positives in anterior MI. We investigated the hypothesis that a combined TD and STA (TD+STA) analysis of the SAECG could improve its predictive accuracy for major arrhythmic events (MAE) after MI. Methods Signal-averaged electrocardiograms were prospectively recorded 10.1 ± 2.6 days after acute MI in 602 patients. Time domain analysis and STA were performed using standard parameters and criteria for abnormality. For the combined TD+STA model, stepwise discriminant analysis was utilized to optimize prediction of MAE. Receiver operating characteristic curves were utilized to optimize cutoff values for each SAECG parameter separately, and also for the combined TD+STA model. Results During a one-year follow-up period, 38 patients had MAE: 14 sustained ventricular tachycardia, 2 resuscitated ventricular fibrillation and 22 sudden cardiac deaths. The total predictive accuracy of combined TD+STA (89.9%) was significantly higher than TD (75.1%) or STA (77.6%). The negative predictive accuracy of all three analyses was high (98%). The positive predictive accuracy of TD (19.6%) or STA (18.3%) was quite low, and significantly improved to 35.8% by combined TD+STA analysis. The positive predictive accuracy of TD+STA improved to 51.2% in patients with left ventricular ejection fraction <40%. Conclusions Combined TD+STA analysis of the SAECG significantly improves its prognostic ability for MAE in post-MI patients compared with TD or STA analyzed separately." @default.
• W2016199581 created "2016-06-24" @default.
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• W2016199581 date "1999-02-01" @default.
• W2016199581 modified "2023-09-27" @default.
• W2016199581 title "Improved diagnostic value of combined time and frequency domain analysis of the signal-averaged electrocardiogram after myocardial infarction" @default.
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• W2016199581 doi "https://doi.org/10.1016/s0735-1097(98)00581-6" @default.
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