Daniel Cortez1, J Martijn Bos2, Michael J Ackerman3. 1. Department of Electrophysiology, Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania; Clinical Sciences, Lund University, Lund, Sweden. 2. Departments of Cardiovascular Diseases, Pediatrics, and Molecular Pharmacology and Experimental Therapeutics, Divisions of Heart Rhythm Services and Pediatric Cardiology, Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Rochester, Minnesota. 3. Departments of Cardiovascular Diseases, Pediatrics, and Molecular Pharmacology and Experimental Therapeutics, Divisions of Heart Rhythm Services and Pediatric Cardiology, Windland Smith Rice Sudden Death Genomics Laboratory, Mayo Clinic, Rochester, Minnesota. Electronic address: ackerman.michael@mayo.edu.
Abstract
BACKGROUND: Long QT syndrome (LQTS) and genotypic subtypes are associated with distinctive T-wave patterns, arrhythmogenic triggers, and corrected QT (QTc) interval risk associations. Twenty percent of patients with LQTS have normal QTc values, defined as electrographically concealed LQTS (ecLQTS). Vectorcardiography (VCG) has value for sudden cardiac death risk assessment. OBJECTIVE: The purpose of this study was to determine the use of VCG to identify patients with ecLQTS. METHODS: We performed a retrospective analysis in patients with ecLQTS with resting QTc values <440 ms. Computerized derivation of the spatial mean and peak QRS-T angles, QTpeak, Tpeak-Tend (angle between QRS and T-wave peak amplitudes in 3-dimensional space), and T-wave eigenvalues (TwEVs; amplitudes [in microvolts] for each of the first 4 TwEVs were derived from the 12-lead electrocardiogram) was performed. The results were compared with those for healthy controls. Intergenotype differences were analyzed. RESULTS: Of 610 patients with LQTS, 169 patients (28%) had ecLQTS (86 (51%) men; mean age 22 ± 16 years; mean QTc interval 422 ± 14 ms). There were 519 healthy controls (44% men; mean age 19.8 ± 13.8 years) with a mean QTc interval of 426 ± 28 ms. Among VCG parameters, QTpeak and TwEVs significantly differentiated patients with ecLQTS from controls (P ≤ .01 for each) as well as differentiated KCNQ1-encoded type 1 LQTS (ecLQT1), KCNH2-encoded type 2 LQTS (ecLQT2), and SCN5A-encoded type 3 LQTS (ecLQT3) from controls (P < .01). ecLQT3 was differentiated from controls and ecLQT1 and ecLQT2 by the fourth TwEV (P < .01 for each). The fourth TwEV differentiated symptomatic patients with ecLQTS from asymptomatic patients with ecLQTS (P < .01). CONCLUSION: ecLQTS can be distinguished from controls using QTpeak. ecLQT3 was best differentiated by the fourth TwEV. VCG may facilitate familial diagnostic anticipation of LQTS status before the completion of mutation-specific genetic testing even with normal resting QTc values.
BACKGROUND:Long QT syndrome (LQTS) and genotypic subtypes are associated with distinctive T-wave patterns, arrhythmogenic triggers, and corrected QT (QTc) interval risk associations. Twenty percent of patients with LQTS have normal QTc values, defined as electrographically concealed LQTS (ecLQTS). Vectorcardiography (VCG) has value for sudden cardiac death risk assessment. OBJECTIVE: The purpose of this study was to determine the use of VCG to identify patients with ecLQTS. METHODS: We performed a retrospective analysis in patients with ecLQTS with resting QTc values <440 ms. Computerized derivation of the spatial mean and peak QRS-T angles, QTpeak, Tpeak-Tend (angle between QRS and T-wave peak amplitudes in 3-dimensional space), and T-wave eigenvalues (TwEVs; amplitudes [in microvolts] for each of the first 4 TwEVs were derived from the 12-lead electrocardiogram) was performed. The results were compared with those for healthy controls. Intergenotype differences were analyzed. RESULTS: Of 610 patients with LQTS, 169 patients (28%) had ecLQTS (86 (51%) men; mean age 22 ± 16 years; mean QTc interval 422 ± 14 ms). There were 519 healthy controls (44% men; mean age 19.8 ± 13.8 years) with a mean QTc interval of 426 ± 28 ms. Among VCG parameters, QTpeak and TwEVs significantly differentiated patients with ecLQTS from controls (P ≤ .01 for each) as well as differentiated KCNQ1-encoded type 1 LQTS (ecLQT1), KCNH2-encoded type 2 LQTS (ecLQT2), and SCN5A-encoded type 3 LQTS (ecLQT3) from controls (P < .01). ecLQT3 was differentiated from controls and ecLQT1 and ecLQT2 by the fourth TwEV (P < .01 for each). The fourth TwEV differentiated symptomatic patients with ecLQTS from asymptomatic patients with ecLQTS (P < .01). CONCLUSION: ecLQTS can be distinguished from controls using QTpeak. ecLQT3 was best differentiated by the fourth TwEV. VCG may facilitate familial diagnostic anticipation of LQTS status before the completion of mutation-specific genetic testing even with normal resting QTc values.