Wilde, Arthur A

Abstract Background and Aims Patients with catecholaminergic polymorphic ventricular tachycardia (CPVT) are at risk for potentially life-threatening arrhythmic events (AEs) even while treated with β-blockers. The aim was to develop a model for individualized prediction of AEs in patients with RYR2-mediated CPVT on β-blocker monotherapy. Methods The derivation and independent validation cohorts included 743 and 129 patients, respectively. AEs were defined as arrhythmic syncope, appropriate implantable cardioverter–defibrillator shock, sudden cardiac arrest (SCA), and sudden cardiac death. Near-fatal or fatal AEs (nf/fAEs) included all AEs except for arrhythmic syncope. Prediction models using Cox regression were developed and internally and externally validated. Results A total of 102 (13.7%) patients in the derivation cohort and 24 (18.6%) patients in the validation cohort experienced ≥1 AE over a median follow-up of 5.1 [interquartile range (IQR), 7.7] and 2.4 (IQR, 4.4) years, respectively. Predictors of AE were arrhythmic syncope or SCA prior to diagnosis and age at β-blocker initiation. In the derivation and validation cohorts, the optimism-corrected C-indices of the models for AE were 0.67 [95% confidence interval (CI) 0.62–0.72] and 0.59 (95% CI 0.48–0.71), respectively. For nf/fAEs, ventricular arrhythmia severity before β-blocker initiation was a fourth independent predictor, and C-indices of the models in the derivation and validation cohorts were 0.74 (95% CI 0.68–0.80) and 0.60 (95% CI 0.47–0.72), respectively. In the derivation cohort, calibration slopes were 1.00 (95% CI 0.59–1.41) for AE and 1.00 (95% CI 0.69–1.32) for nf/fAE. Conclusions These externally validated risk prediction models using clinical parameters accurately distinguished CPVT patients on β-blocker monotherapy at low and high risk for future AEs while treated with β-blockers. These models provide guidance for implementation of clinical management therapies to prevent AEs in patients with CPVT.

Background: Long-QT syndrome (LQTS), an inherited cardiac repolarization disorder, is an important cause of fetal and neonatal mortality. Detecting LQTS prenatally is challenging. A fetal heart rate (FHR) less than third percentile for gestational age is specific for LQTS, but the sensitivity is only ≈50%. Left ventricular isovolumetric relaxation time (LVIRT) was evaluated as a potential diagnostic marker for fetal LQTS. Methods and Results: LV isovolumetric contraction time, LV ejection time, LVIRT, cycle length, and FHR were measured using pulsed Doppler waveforms in fetuses. Time intervals were expressed as percentages of cycle length, and the LV myocardial performance index was calculated. Single measurements were stratified by gestational age and compared between LQTS fetuses and controls. Receiver-operator curves were performed for FHR and normalized LVIRT (N-LVIRT). A linear mixed-effect model including multiple measurements was used to analyze trends in FHR, N-LVIRT, and LV myocardial performance index. There were 33 LQTS fetuses and 469 controls included. In LQTS fetuses, the LVIRT was prolonged in all gestational age groups ( P <0.001), as was the N-LVIRT. The best cutoff to diagnose LQTS was N-LVIRT ≥11.3 at ≤20 weeks (92% sensitivity, 70% specificity). Simultaneous analysis of N-LVIRT and FHR improved the sensitivity and specificity for LQTS (area under the curve=0.96; 95% confidence interval, 0.82–1.00 at 21–30 weeks). N-LVIRT, LV myocardial performance index, and FHR trends differed significantly between LQTS fetuses and controls through gestation. Conclusions: The LVIRT is prolonged in LQTS fetuses. Findings of a prolonged N-LVIRT and sinus bradycardia can improve the prenatal detection of fetal LQTS.

Background— A 2% to 5% background rate of rare SCN5A nonsynonymous single nucleotide variants (nsSNVs) among healthy individuals confounds clinical genetic testing. Therefore, the purpose of this study was to enhance interpretation of SCN5A nsSNVs for clinical genetic testing using estimated predictive values derived from protein-topology and 7 in silico tools. Methods and Results— Seven in silico tools were used to assign pathogenic/benign status to nsSNVs from 2888 long-QT syndrome cases, 2111 Brugada syndrome cases, and 8975 controls. Estimated predictive values were determined for each tool across the entire SCN5A -encoded Na v 1.5 channel as well as for specific topographical regions. In addition, the in silico tools were assessed for their ability to correlate with cellular electrophysiology studies. In long-QT syndrome, transmembrane segments S3–S5+S6 and the DIII/DIV linker region were associated with high probability of pathogenicity. For Brugada syndrome, only the transmembrane spanning domains had a high probability of pathogenicity. Although individual tools distinguished case- and control-derived SCN5A nsSNVs, the composite use of multiple tools resulted in the greatest enhancement of interpretation. The use of the composite score allowed for enhanced interpretation for nsSNVs outside of the topological regions that intrinsically had a high probability of pathogenicity, as well as within the transmembrane spanning domains for Brugada syndrome nsSNVs. Conclusions— We have used a large case/control study to identify regions of Na v 1.5 associated with a high probability of pathogenicity. Although topology alone would leave the variants outside these identified regions in genetic purgatory, the synergistic use of multiple in silico tools may help promote or demote a variant’s pathogenic status.