A quantitative assessment of T-wave morphology in LQT1, LQT2, and healthy individuals based on Holter recording technology.

A quantitative assessment of T-wave morphology in LQT1, LQT2, and healthy individuals based on Holter recording technology. Research Abstract Details 

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A quantitative assessment of T-wave morphology in LQT1, LQT2, and healthy individuals based on Holter recording technology. Abstract Text:

Martino Vaglio,Jean-Philippe Couderc,Scott McNitt,Xiaojuan Xia,Arthur J Moss,Wojciech Zareba,Martino Vaglio,Jean-Philippe Couderc,Scott McNitt,Xiaojuan Xia,Arthur J Moss,Wojciech Zareba,

BACKGROUND: The clinical course and the precipitating risk factors in the congenital long QT syndrome (LQTS) are genotype specific. OBJECTIVES: The goal of this study was to develop a computer algorithm allowing for electrocardiogram (ECG)-based identification and differentiation of LQT1 and LQT2 carriers. METHODS: Twelve-lead ECG Holter monitor recordings were acquired in 49 LQT1 carriers, 25 LQT2 carriers, and 38 healthy subjects as controls. The cardiac beats were clustered based on heart-rate bin method. Scalar and vectorial repolarization parameters were compared for similar heart rates among study groups. The Q to Tpeak (QTpeak), the Tpeak to Tend interval, T-wave magnitude and T-loop morphology were automatically quantified using custom-made algorithms. RESULTS: QTpeak from lead II and the right slope of the T-wave were the most discriminant parameters for differentiating the 3 groups using prespecified heart rate bin (75.0 to 77.5 beats/min). The predictive model utilizing these scalar parameters was validated using the entire spectrum of heart rates. Both scalar and vectorcardiographic models provided very effective identification of tested subjects in heart rates between 60 and 100 beats/min, whereas they had limited performance during tachycardia and slightly better discrimination in bradycardia. In the 60 to 100 beats/min heart rate range, the best 2-variable model identified correctly 89% of healthy subjects, 84% of LQT1 carriers, and 92% of LQT2 carriers. A model including 3 parameters based purely on scalar ECG parameters could correctly identify 90% of the population (89% of healthy subjects, 90% of LQT1 carriers, and 92% of LQT2 carriers). CONCLUSION: Automatic algorithm quantifying T-wave morphology discriminates LQT1 and LQT2 carriers and healthy subjects with high accuracy. Such computerized ECG methodology could assist physicians evaluating subjects suspected for LQTS.

A quantitative assessment of T-wave morphology in LQT1, LQT2, and healthy individuals based on Holter recording technology. Publishing Authors By Initials

M Vaglio,JP Couderc,S McNitt,X Xia,AJ Moss,W Zareba,M Vaglio,JP Couderc,S McNitt,X Xia,AJ Moss,W Zareba,

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A quantitative assessment of T-wave morphology in LQT1, LQT2, and healthy individuals based on Holter recording technology. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Heart rhythm : the official journal of the Heart R

VOLUME: 5

Page Numbers: 11-8

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ISSN: 1547-5271

DAY: 28

MONTH: 08

YEAR: 2007

A quantitative assessment of T-wave morphology in LQT1, LQT2, and healthy individuals based on Holter recording technology. Information

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LANGUAGE: eng

NlmUniqueID: 101200317

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AFFILIATION: Heart Research Follow-Up Program, University of Rochester Medical Center, Rochester, New York.

Country: United States

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MEDLINETA: Heart Rhythm

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