Arrhythmic risk prediction in arrhythmogenic right ventricular cardiomyopathy: external validation of the arrhythmogenic right ventricular cardiomyopathy risk calculator

Abstract

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.

Multimodality Imaging in Arrhythmogenic Left Ventricular Cardiomyopathy

“…In particular, this score includes the following variables: sex, age, recent cardiac syncope (defined as the transient loss of consciousness and postural tone with spontaneous recovery with a likely arrhythmic origin), NSVT, the number of premature ventricular complexes on 24-h Holter monitoring, the extent of T-wave inversion on anterior and inferior leads, and the right ventricular ejection fraction [ 40 ]. In addition, the model was externally validated to confirm its reproducibility and generalizability [ 41 ]. Despite some limitations [ 42 ], the proposed model has been demonstrated to provide accurate prognostic information for patients with ARVC without a prior history of sustained ventricular arrhythmias at diagnosis.…”

Electrocardiogram in arrhytmogenic cardiomyopathy

“…Our findings support the use of the model to facilitate the decision-making process about ICD implantation in the primary prevention of SCD in ARVC. 15 …”

State‐of‐the‐art document on optimal contemporary management of cardiomyopathies

“…com) and validated. 224,226 However, it seems to perform best in gene-positive ARVC (in particular, plakophilin mutations), suggesting that further refinement in the risk prediction tools is needed. 227 According to the 2022 ESC guidelines for the management of patients with ventricular arrhythmias and the prevention of SCD, indications for ICD implantation in secondary prevention in patients with ARVC, include ventricular fibrillation/haemodynamically not tolerated VT, and in primary prevention, arrhythmic syncope, significant RV dysfunction or moderate RV or LV dysfunction and either non-sustained VT or inducible sustained monomorphic VT. 148 According to the same guidelines, beta-blockers may be considered in all patients with ARVC.…”

“…Risk assessment models have been proposed for predicting the risk of life‐threatening ventricular arrhythmias (including SCD), 223,224 however their practical use requires further validation 225 . Recently, a risk prediction model to estimates the 5‐year risk of incident ventricular arrhythmias in ARVC has been developed (http://arvcrisk.com) and validated 224,226 . However, it seems to perform best in gene‐positive ARVC (in particular, plakophilin mutations), suggesting that further refinement in the risk prediction tools is needed 227 .…”