Sugrue Alan, Rohatgi Ram K, Noseworthy Peter A, Kremen Vaclav, Bos J Martijn, Qiang Bo, Sapir Yehu, Attia Zachi I, Scott Christopher G, Brady Peter, Asirvatham Samuel J, Friedman Paul A, Ackerman Michael J
From 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.).
Circ Arrhythm Electrophysiol. 2017 Nov;10(11). doi: 10.1161/CIRCEP.117.005648.
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.
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]; <0.001) and T-wave center of gravity axis (last 25% of wave) in lead I (hazard ratio=1.90 [1.21-2.99]; =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]).
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.
尽管长QT综合征（LQTS）的标志是心脏复极异常，但存在不同程度的表型表达和心律失常风险。我们的目的是评估一种形态学T波分析程序在定义突破QTc值之外的LQTS心律失常风险方面的性能。
我们分析了407例经基因确诊的LQT1患者（n = 246；43%为男性）和LQT2患者（n = 161；41%为男性），平均随访时间为6.4±3.9年。使用一种新颖的专有T波分析程序进行心电图分析。采用Cox比例风险回归方法分析发生LQTS相关心脏事件的时间。23例患者经历了≥1次明确的突破性心律失常事件，5年和10年事件发生率分别为4%和7%。从体表心电图中确定了两个未来LQTS相关心脏事件的独立预测因素：V6导联T波左斜率（风险比 = 0.40 [0.24 - 0.69]；P < 0.001）和I导联T波重心轴（波的最后25%）（风险比 = 1.90 [1.21 - 2.99]；P = 0.005），C统计量为0.77（0.65 - 0.89）。当将其添加到QTc（单独QTc的C统计量为0.68）中时，辨别能力提高到0.78。基因型分析显示这些T波变量与LQT1引发的事件之间的关联较弱，而在LQT2患者中这些特征更强，并且显著优于QTc（C统计量，0.82 [0.71 - 0.93]）。
对T波进行详细的形态学分析为LQTS，尤其是LQT2的突破性心律失常事件风险提供了新的见解。这一观察结果有可能指导临床决策并进一步完善风险分层。
