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• W2121802010 abstract "The term high-resolution (signal-averaged) electrocardiogram (ECG) encompasses any techniques that results in improvement of the ECG signal-to-noise ratio, and thus allows analysis of signals which are too small to be detected by routine measurement techniques. Among such signals are those which arise from areas of slow inhomogeneous conduction in depressed ventricular myocardium (usually called late potentials). These signals are small because the activation front is slow and fractionated and/or the mass of tissue being depolarised is small. They are important for diagnostic purposes, because they may identify an arrhythmogenic substrate. Different averaging techniques utilised in high-resolution ECG include: (1) temporal averaging — this technique is applicable only to repetitive ECG signals; the averaged signal may be analysed either in the time domain or the frequency domain, or a combination of both time and frequency display in the form of spectrotemporal maps; (2) spatial averaging — this technique may record the late potentials on a beat-to-beat basis. Time domain analysis of the signal-averaged ECG is the most commonly used technique in clinical practice. It derives data from the QRS vector magnitude (the root mean square of averaged X, Y and Z leads) that has been subjected to bandpass filters (typically between 25 and 250 Hz, or 40 and 250 Hz). This analysis mainly consists of the determination of three parameters: the filtered QRS duration, the root mean square voltage of the terminal 40 ms of the filtered QRS (RMS40), and the duration of low-amplitude signals, i.e. the time that the filtered QRS voltage remains below 40 µV1. The most common clinical applications of the time domain signal-averaged ECG include risk stratification for future arrhythmic events in survivors of myocardial infarction; prediction of induced sustained ventricular tachycardia in patients with organic heart disease and spontaneous nonsustained ventricular tachycardia, or unexplained syncope; assessment of the results of thrombolytic treatment in acute myocardial infarction2. Current techniques for time domain analysis have several limitations. First, there is lack of agreement on recording techniques, such as the optimal filter characteristics and algorithms to identify QRS onset and offset, as well as on the best numerical criteria of abnormality. A second problem is represented by the fact that, in the presence of intraventricular conduction defect, assessment of late potentials may be difficult. Finally, the technique has low predictive value (around 10–20%) in the postinfarction period. The attempt to develop frequency domain techniques for signal-averaged ECG analysis was based on these considerations." @default.
• W2121802010 created "2016-06-24" @default.
• W2121802010 creator A5081321042 @default.
• W2121802010 date "1998-01-01" @default.
• W2121802010 modified "2023-09-27" @default.
• W2121802010 title "Signal Averaging for Risk Stratification after Myocardial Infarction: Do New Technologies Improve its Predictive Value?" @default.
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• W2121802010 doi "https://doi.org/10.1007/978-94-011-5254-9_28" @default.
• W2121802010 hasPublicationYear "1998" @default.
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