This page provides an overview of the different external validation studies available, last updated Feb 7th 2023:
Model 1. Primary prevention sustained VA model
Arrhythmic risk prediction in ARVC: external validation of the ARVC risk calculator (Eur Heart J. 2022)
Cohort: 429 patients with definite ARVC, primary prevention
Authors’ 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.
Importance of genotype for risk stratification in ARVC using the 2019 ARVC risk calculator (Eur Heart J. 2022)
Cohort: 554 patients with definite ARVC, primary prevention
Authors’ conclusion: The 2019 ARVC risk model performs reasonably well in gene-positive ARVC (particularly for PKP2) but is more limited in gene-elusive patients. Genotype should be included in future risk models for ARVC.
Longitudinal prediction of ventricular arrhythmic risk in patients with ARVC (Circ Arrhythm Electrophysiol 2022)
Cohort: 408 patients with definite ARVC, primary prevention
Authors’ conclusion: Risk factors for VA in ARVC are dynamic, and overall risk for incident sustained VA decreases during follow-up. Up-to-date risk factor assessment improves VA risk stratification.
External validation of a risk prediction model for ventricular arrhythmias in ARVC (Can J Cardiol 2021)
Cohort: 115 patients with definitive ARVC, primary prevention
Authors’ conclusion: Overall, in a relatively large European ARVC cohort with restrictive indications for ICD placement, the ARVC model for VA prediction successfully identified ARVC patients with VA during follow-up. Yet, our study underscores the need for careful threshold selection, considering the model’s associated risk overestimation in low- to intermediate-risk patients.
Novel risk calculator performance in athletes with ARVC (Heart Rhythm 2020)
Cohort: 25 athletes with definitive ARVC, primary and secondary prevention
Authors’ conclusion: Clinical detraining is associated with PVC burden reduction in athletes with ARVC. The novel risk prediction algorithm does not seem to require any correction for its application to ARVC athletes.
Long-term follow-up analysis of a highly characterized arrhythmogenic cardiomyopathy cohort with classical and non-classical phenotypes – a real-world assessment of a novel prediction model: does the subtype really matter (Europace 2020)
Cohort: 101 patients with at least borderline ARVC, primary and secondary prevention
Authors’ conclusion: Non-classical ACM forms appear more prone to VAs than classical forms. The novel prediction model effectively predicted arrhythmic risk in the classical R-ACM cohort, but seemed to underestimate it in non-classical forms.
Prognostic Value of Magnetic Resonance Phenotype in Patients With ARVC (J Am Coll Cardiol 2020)
Cohort: 140 patients with definite ARVC, primary and secondary prevention
Authors’ conclusion: Different CMR presentations of ARVC are associated with different prognoses. The 5-year ARVC risk score is valid for the estimation of risk in patients with lone-RV presentation but underestimated the risk when LV is involved.
Comparison of different prediction models for the indication of implanted ICD in patients with ARVC (ESC Heart Fail 2020)
Cohort: 140 patients with definite ARVC, primary and secondary prevention
Authors’ conclusion: The 5 year score with a threshold of >10% was more effective for predicting events than the ITFC and HRS criteria.
Model 2. Primary prevention sustained VA model + PVS adjustment
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Model 3. Fast-sustained VA model
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