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25th anniversary of the International Long-QT Syndrome Registry: an ongoing quest to uncover the secrets of long-QT syndrome.
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Correlation Method for Detection of Transient T-Wave Alternans in Digital ECG Recordings
No full textBackground: Spectral and complex demodulation methods for detection of microvolt T-wave alternans (TWA) have limited ability to identify transient (nonstationary) TWA episodes. We aimed to develop and test new time-domain technique allowing TWA detection and quantification in as few as 7 consecutive beats from sinus rhythm ECGs. Methods and Results: Quantification of TWA during sinus rhythm required preprocessing consisting of: low-pass filtering, RR stability testing, baseline and respiratory modulation removal, and T-wave windowing and synchronization. Our time-domain correlation method (CM) detects TWA by computing, for each consecutive T wave, an alternans correlation index based on a cross-correlation technique. CM allows quantitative analysis of the amplitude, duration, and overall magnitude of the TWA episode. The technical performance of CM was confirmed in testing with simulated TWA of varying amplitude, duration, and noisy conditions. The clinical performance of CM was demonstrated by analyzing digital Holter recordings of 39 long QT syndrome patients compared to 36 healthy subjects. CM identified TWA in 17 (44%) patients with nonstationary TWA detected in 8. Conclusion: Our computer algorithms consisting of ECG preprocessing and TWA quantification by the correlation method provides the opportunity to detect nonstationary and stationary TWA in sinus rhythm of digital Holter ECG recordings
Optimizing ECG Signal Sampling Frequency for T-Wave Alternans Detection
No full textComputer detection of microvolt T-wave alternans (TWA) is an non-invasive method to identify patients at high risk for ventricular arrhythmias. Since TWA is a transient phenomenon, there is the need for continuous long-term TWA analysis in Holter ECG recordings. TWA detection, usually detected in ECGs sampled at 1000 samples per second (sps), in computationally demanding. We determined the ability of our correlation method (CM) to identify TWA in ECGs sampled at lower frequencies. TWA was identified in 39 long QT syndrome patients, whose ECGs were originally acquired at 1000 sps, and then resampled at 100, 250, 500, and 750 sps. Results obtained at different sampling conditions were compared. We found that TWA can be effectively detected with the CM using sampling frequencies as low as 250 sps. Such sampling frequency seems to be optimal since it provides high accuracy of TWA measurements and substantial saving of computational time
IMPROVED SURVIVAL WITH AN IMPLANTED DEFIBRILLATOR IN PATIENTS WITH CORONARY DISEASE AT HIGH RISK FOR VENTRICULAR ARRHYTHMIA.
No full textFOR THE MULTICENTER AUTOMATIC DEFIBRILLATOR IMPLANTATION TRIAL INVESTIGATOR
Detection of Abnormal Time-Frequency Components of the QT interval using a Wavelet Transformation Technique
No full textECG Repolarization abnormalities are likely to be manifested by different time-frequency (TF) components but no specific technique to detect them has yet been proposed. This study aims to describe the usefulness of a time-scale technique for the analysis of the repolarization segment components. Affected patients with Long QT Syndrome (LQTS) were used as group of patients with abnormalities in repolarization. Time-scale (TS) analysis of the repolarization interval revealed modification of the TF components with different shapes according to the leads. Comparison of ROC curves for QTc measurements and wavelet parameters demonstrates that wavelets are able to quantify T wave prolongation without the need for T endpoint determination
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