Current techniques evaluating beat-to-beat variability of repolarization rely on accurate determination of T wave endpoints. This study proposes a T wave endpoint-independent method to quantify repolarization variability in a standard 12-lead ECG using a wavelet transformation. Our method was used to identify repolarization variability in long QT syndrome patients (LQTS) with the SCN5A sodium channel gene mutation. Using wavelet transformations based on the second Gaussian derivative, we evaluated repolarization variability in 11 LOTS patients with the mutation, 13 noncarrier family members, and 28 unrelated healthy subjects. Time-domain repolarization variability parameters (SDRTo, SDRTm) and wavelet parameters describing temporal (beat-to-beat) variability of repolarization in time (TVT) and in amplitude (TVA) were analyzed. Reproducibility of wavelet parameters and relationship of wavelet-based variability with heart rate and preceding RR interval were investigated. The wavelet-based method quantified beat-to-beat variability of the entire repolarization segment (regardless of QT interval identification) providing insight into variability in repolarization morphology. Our method showed that SCN5A carriers have significantly increased repolarization variability in amplitude (23% +/- 24% vs 8 +/- 4%, P < 0.001) and in time (14 +/- 17 ms vs 3 +/- 2 ms, P < 0.004) compared to noncarriers. Variability of repolarization amplitude was found to be heart rate dependent with variability decreasing with increasing heart rate. Relative error describing reproducibility of TVA and TVT was less than or equal to 5% and less than or equal to 10%, respectively. Our method quantifies repolarization variability in amplitude and in time without the need to identify T or U wave endpoints, wavelet-detected repolarization variability contributes to phenotypic identification of SCN5A carriers, with more pronounced beat-to-beat variability in repolarization amplitude than in time.
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