Current techniques evaluating beat-to-beat variability of repolarization rely on accurate determination of T-wave endpoints. This study proposes a method to detect a very short-term repolarization variability in a standard 12-lead ECG using the wavelet transformation (WT) technique.

Methods: Using wavelets from the second gaussian derivative, we filtered the repolarization segment to evaluate variability in 10 LQTS pts with SCN5A mutation (SCN5A+), 13 nonlinked family members (SCN5A-), and 28 unrelated healthy subjects (N). From 10-second ECGs, segments beginning 100 ms after the R peak and ending 220 ms before the following R peak were analyzed. Two parameters quantified beat-to-beat changes of the repolarization segment: the temporal variability in time (TVT) and in amplitude (TVA). Mean value of TVT and TVA from the 12 leads were computed and compared to the mean value of the standard deviation of RT apex duration (SDRTm), a time-domain measure of variability.

Results: Comparison of TVA, TVT, their combination, and SDRTm is shown in the Table (* p<.01, ** p<.00001 in reference to group N).

Conclusions: 1) SCN5A+ pts have increased beat-to-beat repolarization variability. 2) WT provides insight into time and amplitude of T-wave variability without the need to identify T wave endpoints. 3) The combination of wavelet time and amplitude variability parameters provided very effective phenotypic identification of SCN5A+ pts.