title: A quantitative assessment of T-wave morphology in LQT1, LQT2, and healthy individuals based on Holter recording technology.
abstract: BACKGROUND
  The clinical course and the precipitating risk factors in the congenital long QT syndrome (LQTS) are genotype specific.
  
  
  OBJECTIVE
  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).
  
  
  CONCLUSIONS
  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.
authors.affiliation: Heart Research Follow-Up Program, University of Rochester Medical Center, Rochester, New York, USA.
authors.forename: Martino
authors.initials: M
authors.lastname: Vaglio
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Couderc
authors.forename: Scott
authors.initials: S
authors.lastname: McNitt
authors.forename: Xiaojuan
authors.initials: X
authors.lastname: Xia
authors.forename: Arthur J
authors.initials: AJ
authors.lastname: Moss
authors.forename: Wojciech
authors.initials: W
authors.lastname: Zareba
mesh_terms: D000465:Algorithms; D016002:Discriminant Analysis; D000072237:ERG1 Potassium Channel; D004562:Electrocardiography; D015716:Electrocardiography, Ambulatory; D051638:Ether-A-Go-Go Potassium Channels; D005260:Female; D006801:Humans; D008133:Long QT Syndrome / Q000175:diagnosis / Q000235:genetics / Q000503:physiopathology; D008297:Male; D009154:Mutation; D029597:Romano-Ward Syndrome / Q000175:diagnosis* / Q000235:genetics / Q000503:physiopathology
chemical_list: D000072237:ERG1 Potassium Channel; D051638:Ether-A-Go-Go Potassium Channels