Abstract

This study aims to assess the capability of T-wave analysis to: 1) identify genotype-positive long QT syndrome (LQTS) patients; 2) identify LQTS patients with borderline or normal QTc interval (≤460 ms); and 3) classify LQTS subtype. LQTS often presents with a nondiagnostic electrocardiogram (ECG). T-wave abnormalities may be the only marker of this potentially lethal arrhythmia syndrome. ECGs taken at rest in 108 patients (43 with LQTS1, 20 with LQTS2, and 45 control subjects) were evaluated for T-wave flatness, asymmetry, and notching, which produces a morphology combination score (MCS) of the 3 features (MCS= 1.6× flatness+ asymmetry+ notch) using QT Guard Plus Software (GE Healthcare, Milwaukee, Wisconsin). Toassess for heterogeneity of repolarization, the principal component analysis ratio 2 (PCA-2) was calculated. Mean QTc intervals were 486 ± 50 ms (LQTS1), 479 ± 36 ms (LQTS2), and 418 ± 24 ms (control subjects) (p< 0.05). MCS and PCA-2 differed between LQTS patients and control subjects (MCS: 117.8 ± 57.4 vs. 71.9 ± 16.2; p<0.001; PCA-2: 20.2 ± 10.4% vs. 14.6 ± 5.5%; p< 0.001), LQTS1 and LQTS2 patients (MCS: 96.3 ± 28.7 vs. 164 ± 75.2; p< 0.001; PCA-2: 17.8 ± 8.3% vs. 25 ± 12.6%; p< 0.001), and between LQTS patients with borderline or normalQTc intervals (n= 17) and control subjects (MCS: 105.7 ± 49.9 vs. 71.9 ± 16.2; p< 0.001; PCA-2: 18.1 ± 7.2% vs. 14.6 ± 5.5%; p< 0.001). T-wave metrics were consistent across multiple ECGs from individual patients based on theaverage intraclass correlation coefficient (MCS: 0.96; PCA-2: 0.86). Automated T-wave morphology analysis accurately discriminates patients with pathogenic LQTS mutations from control subjects and between the 2 most common LQTS subtypes. Mutation carriers without baseline QTc prolongation were also identified. This may be a useful tool for screening families of LQTS patients, particularly when the QTc interval is subthreshold and genetic testing is unavailable.

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