Mario Talajic

The prevalence of congenital heart disease (CHD) has surged in recent decades, owing to a substantial reduction in mortality. As individuals with CHD age, they become increasingly susceptible to late complications including arrhythmias. These arrhythmias often arise decades after surgical intervention and significantly impact quality of life, hospitalizations, and mortality. Catheter ablation has gained widespread acceptance as a critical intervention for managing arrhythmias in patients with CHD. However, anatomical and physiological features unique to this population pose challenges to standard manual ablation procedures, potentially impacting safety and efficacy. Robotic magnetic-guided navigation (RMN) has emerged as a technological solution to address these challenges. By utilizing soft and flexible catheters equipped with magnets at their tips, RMN enables robotic steering and orientation of catheters in three-dimensional space. This technology overcomes obstacles such as distorted vascular pathways and complex post-surgical reconstructions to facilitate access to target chambers and improve maneuverability within the heart. In this review, we present an overview of the safety and efficacy evidence for RMN-guided catheter ablation in CHD patients and highlight potential advantages. Additionally, we provide a detailed case presentation illustrating the practical application of RMN technology in this population. Although the literature on RMN-guided ablation in patients with CHD remains limited, it has shown promise in achieving successful outcomes, particularly in cases where manual ablation failed or was deemed non-feasible. Further validation through large-scale prospective studies is necessary to fully ascertain the benefits of RMN technology in this patient population.

Background: Patients with hypertrophic cardiomyopathy (HCM) are at risk of ventricular arrhythmia (VA) attributed to abnormal electrical activation arising from myocardial fibrosis and myocyte disarray. We sought to quantify intra‐QRS peaks (QRSp) in high‐resolution ECGs as a measure of abnormal activation to predict late VA in patients with HCM. Methods and Results: Prospectively enrolled patients with HCM (n=143, age 53±14 years) with prophylactic implantable cardioverter‐defibrillators had 3‐minute, high‐resolution (1024 Hz), digital 12‐lead ECGs recorded during intrinsic rhythm. For each precordial lead, QRSp was defined as the total number of peaks detected in the QRS complex that deviated from a smoothing filtered version of the QRS. The VA end point was appropriate implantable cardioverter‐defibrillator therapy during 5‐year prospective follow‐up. After 5 years, 21 (16%) patients had VA. Patients who were VA positive had greater QRSp (6.0 [4.0–7.0] versus 4.0 [2.0–5.0]; P P =0.038) compared with patients who were VA negative, but had similar established HCM risk metrics. Receiver operating characteristic analysis revealed that QRSp discriminated VA (area under the curve=0.76; P P =0.012). In multivariable Cox regression, age P =0.009) and QRSp (HR per QRS peak, 1.41; P =0.009) predicted VA after adjusting for established HCM risk metrics. In patients aged P =0.012). Conclusions: QRSp predicted VA in patients with HCM who were eligible for an implantable cardioverter‐defibrillator after adjusting for established HCM risk metrics, such that each additional QRS peak increases VA risk by 40%. QRSp <4 was associated with a <1% annual VA risk in all patients, and no VA risk among those aged <50 years. This novel ECG metric may improve patient selection for prophylactic implantable cardioverter‐defibrillator therapy by identifying those with low VA risk. These findings require further validation in a lower risk HCM cohort. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02560844.

Genetic testing is recommended in specific inherited heart diseases but its role remains unclear and it is not currently recommended in unexplained cardiac arrest (UCA). We sought to assess the yield and clinical utility of genetic testing in UCA using whole-exome sequencing (WES). Survivors of UCA requiring external defibrillation were included from the Cardiac Arrest Survivor with Preserved Ejection fraction Registry. Whole-exome sequencing was performed, followed by assessment of rare variants in previously reported cardiovascular disease genes. A total of 228 UCA survivors (mean age at arrest 39 ± 13 years) were included. The majority were males (66%) and of European ancestry (81%). Following advanced clinical testing at baseline, the likely aetiology of cardiac arrest was determined in 21/228 (9%) cases. Whole-exome sequencing identified a pathogenic or likely pathogenic (P/LP) variant in 23/228 (10%) of UCA survivors overall, increasing the proportion of ‘explained’ cases from 9% only following phenotyping to 18% when combining phenotyping with WES. Notably, 13 (57%) of the 23 P/LP variants identified were located in genes associated with cardiomyopathy, in the absence of a diagnosis of cardiomyopathy at the time of arrest. Genetic testing identifies a disease-causing variant in 10% of apparent UCA survivors. The majority of disease-causing variants was located in cardiomyopathy-associated genes, highlighting the arrhythmogenic potential of such variants in the absence of an overt cardiomyopathy diagnosis. The present study supports the use of genetic testing including assessment of arrhythmia and cardiomyopathy genes in survivors of UCA. Study flowchart and summary results. ARVC, arrhythmogenic right ventricular cardiomyopathy; BrS, Brugada syndrome; CPVT, catecholaminergic polymorphic ventricular tachycardia; CRDS, RYR2 Ca²⁺ release deficiency syndrome; DCM, dilated cardiomyopathy; ECG, electrocardiogram; HCM, hypertrophic cardiomyopathy; LQTS, long QT syndrome; LV, left ventricular; MRI, magnetic resonance imaging; MVP, mitral valve prolapse; SQTS, short QT syndrome; UCM, unclassified cardiomyopathy; WES, whole-exome sequencing.

Background: Following an unexplained cardiac arrest, clinical genetic testing is increasingly becoming standard of care. Periodic review of variant classification is required, as reinterpretation can change the diagnosis, prognosis, and management of patients and their relatives. Methods: This study aimed to develop and validate a standardized algorithm to facilitate clinical application of the 2015 American College of Medical Genetics and Association for Molecular Pathology guidelines for the interpretation of genetic variants. The algorithm was applied to genetic results in the Cardiac Arrest Survivors With Preserved Ejection Fraction Registry, to assess the rate of variant reclassification over time. Variant classifications were then compared with the classifications of 2 commercial laboratories to determine the rate and identify sources of variant interpretation discordance. Results: Thirty-one percent of participants (40 of 131) had at least 1 genetic variant with a clinically significant reclassification over time. Variants of uncertain significance were more likely to be downgraded (73%) to benign than upgraded to pathogenic (27%; P =0.03). For the second part of the study, 50% (70 of 139) of variants had discrepant interpretations (excluding benign variants), provided by at least 1 team. Conclusions: Periodic review of genetic variant classification is a key component of follow-up care given rapidly changing information in the field. There is potential for clinical care gaps with discrepant variant interpretations, based on the interpretation and application of current guidelines. The development of gene- and disease-specific guidelines and algorithms may provide an opportunity to further standardize variant interpretation reporting in the future. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT00292032.

Background: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with ventricular arrhythmias (VA) and sudden cardiac death (SCD). A model was recently developed to predict incident sustained VA in patients with ARVC. However, since this outcome may overestimate the risk for SCD, we aimed to specifically predict life-threatening VA (LTVA) as a closer surrogate for SCD. Methods: We assembled a retrospective cohort of definite ARVC cases from 15 centers in North America and Europe. Association of 8 prespecified clinical predictors with LTVA (SCD, aborted SCD, sustained, or implantable cardioverter-defibrillator treated ventricular tachycardia >250 beats per minute) in follow-up was assessed by Cox regression with backward selection. Candidate variables included age, sex, prior sustained VA (≥30s, hemodynamically unstable, or implantable cardioverter-defibrillator treated ventricular tachycardia; or aborted SCD), syncope, 24-hour premature ventricular complexes count, the number of anterior and inferior leads with T-wave inversion, left and right ventricular ejection fraction. The resulting model was internally validated using bootstrapping. Results: A total of 864 patients with definite ARVC (40±16 years; 53% male) were included. Over 5.75 years (interquartile range, 2.77–10.58) of follow-up, 93 (10.8%) patients experienced LTVA including 15 with SCD/aborted SCD (1.7%). Of the 8 prespecified clinical predictors, only 4 (younger age, male sex, premature ventricular complex count, and number of leads with T-wave inversion) were associated with LTVA. Notably, prior sustained VA did not predict subsequent LTVA ( P =0.850). A model including only these 4 predictors had an optimism-corrected C-index of 0.74 (95% CI, 0.69–0.80) and calibration slope of 0.95 (95% CI, 0.94–0.98) indicating minimal over-optimism. Conclusions: LTVA events in patients with ARVC can be predicted by a novel simple prediction model using only 4 clinical predictors. Prior sustained VA and the extent of functional heart disease are not associated with subsequent LTVA events.

Introduction: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetically determined disease associated with a significant risk of ventricular arrhythmias and sudden cardiac death (SCD). Implantable cardioverter-defibrillators (ICDs) are the only effective preventive measure. Over the past 30 years, much effort has been invested in determining predictors of adverse arrhythmic events in these patients. Areas covered: This review summarizes available evidence on risk stratification for ARVC, with an emphasis on recent research findings. While efforts are ongoing to define risk predictors, several recent publications have synthetized and built on this knowledge base. A recently published meta-analysis has clarified the strongest predictors of ventricular arrhythmias in ARVC, which vary depending on the population included. Three management guidelines/expert consensus documents have integrated the previously described risk predictors into proposed ICD recommendations. Furthermore, a risk prediction model has allowed the integration of multiple risk factors to provide individualized risk prediction and to inform shared-decision making regarding ICD implantation. Expert opinion: Over the past few years, knowledge of risk prediction in ARVC has been consolidated and refined. Further improvements may be made by the considering additional predictors such as exercise and by targeting more specific surrogate outcomes for SCD.