Identification of Concealed and Manifest Long QT Syndrome Using a Novel T Wave Analysis Program

Circ Arrhythm Electrophysiol. 2016 Jul;9(7):e003830. doi: 10.1161/CIRCEP.115.003830.

Abstract

Background: Congenital long QT syndrome (LQTS) is characterized by QT prolongation. However, the QT interval itself is insufficient for diagnosis, unless the corrected QT interval is repeatedly ≥500 ms without an acquired explanation. Further, the majority of LQTS patients have a corrected QT interval below this threshold, and a significant minority has normal resting corrected QT interval values. Here, we aimed to develop and validate a novel, quantitative T wave morphological analysis program to differentiate LQTS patients from healthy controls.

Methods and results: We analyzed a genotyped cohort of 420 patients (22±16 years, 43% male) with either LQT1 (61%) or LQT2 (39%). ECG analysis was conducted using a novel, proprietary T wave analysis program that quantitates subtle changes in T wave morphology. The top 3 discriminating features in each ECG lead were determined and the lead with the best discrimination selected. Classification was performed using a linear discriminant classifier and validated on an untouched cohort. The top 3 features were Tpeak-Tend interval, T wave left slope, and T wave center of gravity x axis (last 25% of the T wave). Lead V6 had the best discrimination. It could distinguish 86.8% of LQTS patients from healthy controls. Moreover, it distinguished 83.33% of patients with concealed LQTS from controls, despite having essentially identical resting corrected QT interval values.

Conclusions: T wave quantitative analysis on the 12-lead surface ECG provides an effective, novel tool to distinguish patients with either LQT1/LQT2 from healthy matched controls. It can provide guidance while mutation-specific genetic testing is in motion for family members.

Keywords: T wave analysis; diagnosis; electrocardiography; long QT syndrome; sudden cardiac death; ventricular repolarization.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Electrocardiography / methods*
  • Female
  • Genotype
  • Humans
  • Long QT Syndrome / classification
  • Long QT Syndrome / diagnosis*
  • Long QT Syndrome / genetics
  • Male
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted
  • Young Adult