Arrhythmic Risk Prediction in ARVC | 175 fact that patients were selected by the RV focused 2010 TFC and mostly PKP2 variant carriers were included, who typically present with the classical right dominant ARVC phenotype. Previous papers showed that the ARVC risk calculator performs well in PKP2 dominated cohorts, while for patients with a different genetic background incorporation of measures of LV function might be important.8,32 When integrated with the ARVC risk calculator, both indices of regional RV deformation still showed independent prognostic value. Models that combined the ARVC risk calculatorpredicted risk with regional RV deformation patterns or RVFWLS were superior at predicting VA compared to either of these predictors alone. This confirms our hypothesis that inclusion of measures of regional RV function can improve arrhythmic risk prediction in ARVC. Clinical implications This was the first study showing added value of deformation imaging in a clinical practicebased, multimodality approach. Both RV deformation patterns and RVFWLS were able to refine risk stratification when added to the existing ARVC risk calculator. Especially negative predictive value of deformation imaging was high; none of the patients with normal regional RV deformation patterns at baseline experienced VA within 5 years from the echocardiogram. The existing risk calculator already performs very well when it comes to guiding ICD implantation in the high- and low-risk group. In the intermediate arrhythmic risk group (5-25% at 5 years), the timing of ICD implantation is most challenging. With a two-step approach, this additional stratification tool can probably be of greatest use in this intermediate arrhythmic risk group as predicted by the ARVC risk calculator. Normal RV deformation could in this case reassure both clinician and patient in a watchful waiting strategy regarding ICD implantation. While echocardiographic deformation imaging has shown the ability to reveal early signs of disease associated to arrhythmic outcome in multiple genetic cardiomyopathies27,33,34, predictive value when added to clinical risk prediction tools in these diseases is yet to be investigated. Limitations Due to the high prevalence of patients with P/LP variants in the PKP2 gene (66%), generalizability to patient populations with other dominating variants is uncertain. A genotype specific approach might improve predictive value especially for non-PKP2 patients, as pointed out in a recent validation of the ARVC risk calculator8, but is hindered by lack of power. The feasibility of echocardiographic deformation imaging depends on image quality. With >95% for both LV and RV deformation imaging, feasibility was high in the ARVC cohorts included in this study. If centres do not routinely perform dedicated RV focused images, feasibility may drop. Missing data also represent a limitation of this retrospective cohort. Although a complete case analysis demonstrates a similar trend towards added value of deformation imaging, missing data could influence the relative benefit. Despite our efforts to assemble the largest cohort of definite ARVC patients with deformation imaging to date, this study is underpowered for development of a new ARVC-risk calculator with incorporation of RV deformation imaging. Larger multi-centre collaborations are much needed. Last, this was an observational study with inherent limitations by study design. Validation in an external cohort will be important for the clinical implementation of integrating deformation imaging with the ARVC risk calculator. 8
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