A Multicenter External Validation of a Score Model to Predict Risk of Events in Patients With Brugada Syndrome.

A multivariate risk score model was proposed by Sieira et al in 2017 for sudden death in Brugada syndrome; their validation in 150 patients was highly encouraging, with a C-index of 0.81; however, this score is yet to be validated by an independent group. A total of 192 records of patients with Brugada syndrome were collected from 2 centers in the United Kingdom and retrospectively scored according to a score model by Sieira et al. Data were compiled summatively over follow-up to mimic regular risk re-evaluation as per current guidelines. Sudden cardiac death survivor data were considered perievent to ascertain the utility of the score before cardiac arrest. Scores were compared with actual outcomes. Sensitivity in our cohort was 22.7%, specificity was 57.6%, and C-index was 0.58. In conclusion, up to 75% of cardiac arrest survivors in this cohort would not have been offered a defibrillator if evaluated before their event. This casts doubt on the utility of the score model for primary prevention of sudden death. Inherent issues with modern risk scoring strategies decrease the likelihood of success even in robustly designed tools such as the Sieira score model.

Postinfarct ventricular tachycardia substrate: Characterization and ablation of conduction channels using ripple mapping.

BACKGROUND: Conduction channels have been demonstrated within the postinfarct scar and seem to be co-located with the isthmus of ventricular tachycardia (VT). Mapping the local scar potentials (SPs) that define the conduction channels is often hindered by large far-field electrograms generated by healthy myocardium. OBJECTIVE: The purpose of this study was to map conduction channel using ripple mapping to categorize SPs temporally and anatomically. We tested the hypothesis that ablation of early SPs would eliminate the latest SPs without direct ablation. METHODS: Ripple maps of postinfarct scar were collected using the PentaRay (Biosense Webster) during normal rhythm. Maps were reviewed in reverse, and clusters of SPs were color-coded on the geometry, by timing, into early, intermediate, late, and terminal. Ablation was delivered sequentially from clusters of early SPs, checking for loss of terminal SPs as the endpoint. RESULTS: The protocol was performed in 11 patients. Mean mapping time was 65 ± 23 minutes, and a mean 3050 ± 1839 points was collected. SP timing ranged from 98.1 ± 60.5 ms to 214.8 ± 89.8 ms post QRS peak. Earliest SPs were present at the border, occupying 16.4% of scar, whereas latest SPs occupied 4.8% at the opposing border or core. Analysis took 15 ± 10 minutes to locate channels and identify ablation targets. It was possible to eliminate latest SPs in all patients without direct ablation (mean ablation time 16.3 ± 11.1 minutes). No VT recurrence was recorded (mean follow-up 10.1 ± 7.4 months). CONCLUSION: Conduction channels can be located using ripple mapping to analyze SPs. Ablation at channel entrances can eliminate the latest SPs and is associated with good medium-term results.

Repolarization abnormalities unmasked with exercise in sudden cardiac death survivors with structurally normal hearts.

BACKGROUND: Models of cardiac arrhythmogenesis predict that nonuniformity in repolarization and/or depolarization promotes ventricular fibrillation and is modulated by autonomic tone, but this is difficult to evaluate in patients. We hypothesize that such spatial heterogeneities would be detected by noninvasive ECG imaging (ECGi) in sudden cardiac death (SCD) survivors with structurally normal hearts under physiological stress. METHODS: ECGi was applied to 11 SCD survivors, 10 low-risk Brugada syndrome patients (BrS), and 10 controls undergoing exercise treadmill testing. ECGi provides whole heart activation maps and >1,200 unipolar electrograms over the ventricular surface from which global dispersion of activation recovery interval (ARI) and regional delay in conduction were determined. These were used as surrogates for spatial heterogeneities in repolarization and depolarization. Surface ECG markers of dispersion (QT and Tpeak-end intervals) were also calculated for all patients for comparison. RESULTS: Following exertion, the SCD group demonstrated the largest increase in ARI dispersion compared to BrS and control groups (13 ± 8 ms vs. 4 ± 7 ms vs. 4 ± 5 ms; P = 0.009), with baseline dispersion being similar in all groups. In comparison, surface ECG markers of dispersion of repolarization were unable to discriminate between the groups at baseline or following exertion. Spatial heterogeneities in conduction were also present following exercise but were not significantly different between SCD survivors and the other groups. CONCLUSION: Increased dispersion of repolarization is apparent during physiological stress in SCD survivors and is detectable with ECGi but not with standard ECG parameters. The electrophysiological substrate revealed by ECGi could be the basis of alternative risk-stratification techniques.