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Published on: May 23, 2021
Architectural T-Wave Analysis and Identification of On-Therapy Breakthrough Arrhythmic Risk in Type 1 and Type 2
Alan Sugrue1, Ram K Rohatgi1, Peter A Noseworthy1
1From the Division of Heart Rhythm Services, Department of Cardiovascular Diseases (A.S., P.A.N., V.K., B.Q., Z.I.A., P.B., S.J.A., P.A.F., M.J.A.), Division of Pediatric Cardiology, Department of Pediatric and Adolescent Medicine (R.K.R., J.M.B., S.J.A., M.J.A.), and Department of Molecular Pharmacology and Experimental Therapeutics (J.M.B., M.J.A.), Windland Smith Rice Sudden Death Genomics Laboratory, and Division of Biomedical Statistics and Informatics (C.G.S.), Mayo Clinic, Rochester, MN; Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague (V.K.); and Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer Sheva, Israel (Y.S.).
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.
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