Key result
A novel T wave morphological analysis program using lead V6 distinguished 86.8% of LQTS patients and 83.33% of concealed LQTS patients from healthy controls.
Why the study?
Does a novel quantitative T wave morphological analysis program differentiate patients with LQT1 or LQT2 from healthy controls?
Observational (n=420)
Does a novel quantitative T wave morphological analysis program differentiate patients with LQT1 or LQT2 from healthy controls?
Answers are grounded in this paper and cite their sources.
A novel quantitative T wave morphological analysis program on the 12-lead ECG can effectively distinguish patients with LQT1 or LQT2, including those with concealed LQTS, from healthy controls.
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.
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Sugrue et al. (2016) conducted an observational in Congenital long QT syndrome (LQT1 or LQT2) (n=420). Novel T wave morphological analysis program vs. Healthy controls was evaluated on Distinguishing LQTS patients from healthy controls. A novel T wave morphological analysis program using lead V6 distinguished 86.8% of LQTS patients and 83.33% of concealed LQTS patients from healthy controls.
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