Aims: Arrhythmogenic right ventricular cardiomyopathy (ARVC) causes ventricular arrhythmias (VAs) and sudden cardiac death (SCD). In 2019, a risk prediction model that estimates the 5-year risk of incident VAs in ARVC was developed (ARVCrisk.com). This study aimed to externally validate this prediction model in a large international multicentre cohort and to compare its performance with the risk factor approach recommended for implantable cardioverter-defibrillator (ICD) use by published guidelines and expert consensus. Methods and results: In a retrospective cohort of 429 individuals from 29 centres in North America and Europe, 103 (24%) experienced sustained VA during a median follow-up of 5.02 (2.05–7.90) years following diagnosis of ARVC. External validation yielded good discrimination [C-index of 0.70 (95% confidence interval-CI 0.65–0.75)] and calibration slope of 1.01 (95% CI 0.99–1.03). Compared with the three published consensus-based decision algorithms for ICD use in ARVC (Heart Rhythm Society consensus on arrhythmogenic cardiomyopathy, International Task Force consensus statement on the treatment of ARVC, and American Heart Association guidelines for VA and SCD), the risk calculator performed better with a superior net clinical benefit below risk threshold of 35%. Conclusion: Using a large independent cohort of patients, this study shows that the ARVC risk model provides good prognostic information and outperforms other published decision algorithms for ICD use. These findings support the use of the model to facilitate shared decision making regarding ICD implantation in the primary prevention of SCD in ARVC.

Risk stratification of patients with long QT syndrome (LQTS) represents a difficult task. In 2018, we proposed a granular estimate of the baseline 5-year risk of life-threatening arrhythmias (LAE) for patients with LQTS, based on the genotype (long QT syndrome Type 1, long QT syndrome Type 2, and long QT syndrome Type 3) and the duration of the QTc interval. We sought to externally validate a novel risk score model (1-2-3-LQTS-Risk model) in a geographically diverse cohort from the USA and to evaluate its performance and assess potential clinical implication of this novel model. The prognostic model (1-2-3-LQTS-Risk model) was derived using data from a prospective, single-centre longitudinal cohort study published in 2018 (discovery cohort) and was validated using an independent cohort of 1689 patients enrolled in the International LQTS Registry (Rochester NY, USA). The validation study revealed a C-index of 0.69 [95% confidence interval (CI): 0.61–0.77] in the validation cohort, when compared with C-index of 0.79 (95% CI: 0.70–0.88) in the discovery cohort. Adopting a 5-year risk ≥5%, as suggested by the ROC curve analysis as the most balanced threshold for implantable cardioverter-defibrillator (ICD) implantation, would result in a number needed to treat (NNT) of nine (NNT = 9; 95% CI: 6.3–13.6). The 1-2-3-LQTS-Risk model, the first validated 5-year risk score model for patients with LQTS, can be used to aid clinicians to identify patients at the highest risk of LAE who could benefit most from an ICD implant and avoid unnecessary implants.

Background: Insight into type 5 long QT syndrome (LQT5) has been limited to case reports and small family series. Improved understanding of the clinical phenotype and genetic features associated with rare KCNE1 variants implicated in LQT5 was sought through an international multicenter collaboration. Methods: Patients with either presumed autosomal dominant LQT5 (N = 229) or the recessive Type 2 Jervell and Lange-Nielsen syndrome (N = 19) were enrolled from 22 genetic arrhythmia clinics and 4 registries from 9 countries. KCNE1 variants were evaluated for ECG penetrance (defined as QTc >460 ms on presenting ECG) and genotype-phenotype segregation. Multivariable Cox regression was used to compare the associations between clinical and genetic variables with a composite primary outcome of definite arrhythmic events, including appropriate implantable cardioverter-defibrillator shocks, aborted cardiac arrest, and sudden cardiac death. Results: A total of 32 distinct KCNE1 rare variants were identified in 89 probands and 140 genotype positive family members with presumed LQT5 and an additional 19 Type 2 Jervell and Lange-Nielsen syndrome patients. Among presumed LQT5 patients, the mean QTc on presenting ECG was significantly longer in probands (476.9±38.6 ms) compared with genotype positive family members (441.8±30.9 ms, P <0.001). ECG penetrance for heterozygous genotype positive family members was 20.7% (29/140). A definite arrhythmic event was experienced in 16.9% (15/89) of heterozygous probands in comparison with 1.4% (2/140) of family members (adjusted hazard ratio [HR] 11.6 [95% CI, 2.6–52.2]; P =0.001). Event incidence did not differ significantly for Type 2 Jervell and Lange-Nielsen syndrome patients relative to the overall heterozygous cohort (10.5% [2/19]; HR 1.7 [95% CI, 0.3–10.8], P =0.590). The cumulative prevalence of the 32 KCNE1 variants in the Genome Aggregation Database, which is a human database of exome and genome sequencing data from now over 140 000 individuals, was 238-fold greater than the anticipated prevalence of all LQT5 combined (0.238% vs 0.001%). Conclusions: The present study suggests that putative/confirmed loss-of-function KCNE1 variants predispose to QT prolongation, however, the low ECG penetrance observed suggests they do not manifest clinically in the majority of individuals, aligning with the mild phenotype observed for Type 2 Jervell and Lange-Nielsen syndrome patients.

Mitral valve prolapse is a common cardiac condition, with an estimated prevalence between 1% and 3%. Most patients have a benign course, but ever since its initial description mitral valve prolapse has been associated to sudden cardiac death. Although the causal relationship between mitral valve prolapse and sudden cardiac death has never been clearly demonstrated, different factors have been implicated in arrhythmogenesis in patients with mitral valve prolapse. In this work, we offer a comprehensive overview of the etiology and the genetic background, epidemiology, pathophysiology, and we focus on the state-of-the-art imaging-based diagnosis of mitral valve prolapse. Going beyond the classical, well-described clinical factors, such as young age, female gender and auscultatory findings, we investigate multimodality imaging features, such as alterations of anatomy and function of the mitral valve and its leaflets, the structural and contractile anomalies of the myocardium, all of which have been associated to sudden cardiac death.