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7089265 
Journal Article 
Architectural T-Wave Analysis and Identification of On-Therapy Breakthrough Arrhythmic Risk in Type 1 and Type 2 Long-QT Syndrome 
Fang, J; Sugrue, A; Brady, P; Asirvatham, SJ; Friedman, PA; Ackerman, MLi; Rohatgi, RamK; Noseworthy, PShengqian; Liu, Vaclavlin; Bos, Ghua; Qiang, Bo; Sapir, Y; Attia, ZI; Scott, CG; , 
2017 
Yes 
Circulation: Arrhythmia and Electrophysiology
ISSN: 1941-3149 
LIPPINCOTT WILLIAMS & WILKINS 
PHILADELPHIA 
29141844 
WOS:000415949800010 
BACKGROUND: Although the hallmark of long-QT syndrome (LQTS) is abnormal cardiac repolarization, there are varying degrees of phenotypic expression and arrhythmic risk. Our aim was to evaluate the performance of a morphological T-wave analysis program in defining breakthrough LQTS arrhythmic risk beyond the QTc value.METHODS AND RESULTS: We analyzed 407 genetically confirmed patients with LQT1 (n=246; 43% men) and LQT2 (n=161; 41% men) over the mean follow-up period of 6.4 +/- 3.9 years. ECG analysis was conducted using a novel, proprietary T-wave analysis program. Time to a LQTS-associated cardiac event was analyzed using Cox proportional hazards regression methods. Twenty-three patients experienced >= 1 defined breakthrough cardiac arrhythmic events with 5-and 10-year event rates of 4% and 7%. Two independent predictors of future LQTS-associated cardiac events from the surface ECG were identified: left slope of T wave in lead V6 (hazard ratio=0.40 [0.24-0.69]; P<0.001) and T-wave center of gravity x axis (last 25% of wave) in lead I (hazard ratio=1.90 [1.21-2.99]; P=0.005), C statistic of 0.77 (0.65-0.89). When added to the QTc (C statistic 0.68 for QTc alone), discrimination improved to 0.78. Genotype analysis showed weaker association between these T-wave variables and LQT1-triggered events while these features were stronger in patients with LQT2 and significantly outperformed the QTc (C statistic, 0.82 [0.71-0.93]).CONCLUSION: Detailed morphological analysis of the T wave provides novel insights into risk of breakthrough arrhythmic events in LQTS, particularly LQT2. This observation has the potential to guide clinical decision making and further refine risk stratification.