Longitudinal Prediction of Ventricular Arrhythmic Risk in Patients With Arrhythmogenic Right Ventricular Cardiomyopathy

A novel tool for arrhythmic risk stratification in desmoplakin gene variant carriers

BACKGROUND AND AIMS

Pathogenic desmoplakin (DSP) gene variants are associated with the development of a distinct form of arrhythmogenic cardiomyopathy known as DSP cardiomyopathy. Patients harbouring these variants are at high risk for sustained ventricular arrhythmia (VA), but existing tools for individualized arrhythmic risk assessment have proven unreliable in this population.

METHODS

Patients from the multi-national DSP-ERADOS (Desmoplakin SPecific Effort for a RAre Disease Outcome Study) Network patient registry who had pathogenic or likely pathogenic DSP variants and no sustained VA prior to enrolment were followed longitudinally for the development of first sustained VA event. Clinically guided, step-wise Cox regression analysis was used to develop a novel clinical tool predicting the development of incident VA. Model performance was assessed by c-statistic in both the model development cohort (n = 385) and in an external validation cohort (n = 86).

RESULTS

In total, 471 DSP patients [mean age 37.8 years, 65.6% women, 38.6% probands, 26% with left ventricular ejection fraction (LVEF) < 50%] were followed for a median of 4.0 (interquartile range: 1.6-7.3) years; 71 experienced first sustained VA events {2.6% [95% confidence interval (CI): 2.0, 3.5] events/year}. Within the development cohort, five readily available clinical parameters were identified as independent predictors of VA and included in a novel DSP risk score: female sex [hazard ratio (HR) 1.9 (95% CI: 1.1-3.4)], history of non-sustained ventricular tachycardia [HR 1.7 (95% CI: 1.1-2.8)], natural logarithm of 24-h premature ventricular contraction burden [HR 1.3 (95% CI: 1.1-1.4)], LVEF < 50% [HR 1.5 (95% CI: .95-2.5)], and presence of moderate to severe right ventricular systolic dysfunction [HR 6.0 (95% CI: 2.9-12.5)]. The model demonstrated good risk discrimination within both the development [c-statistic .782 (95% CI: .77-.80)] and external validation [c-statistic .791 (95% CI: .75-.83)] cohorts. The negative predictive value for DSP patients in the external validation cohort deemed to be at low risk for VA (<5% at 5 years; n = 26) was 100%.

CONCLUSIONS

The DSP risk score is a novel model that leverages readily available clinical parameters to provide individualized VA risk assessment for DSP patients. This tool may help guide decision-making for primary prevention implantable cardioverter-defibrillator placement in this high-risk population and supports a gene-first risk stratification approach.

Improved diagnosis of arrhythmogenic right ventricular cardiomyopathy using electrocardiographic deep-learning

BACKGROUND

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a rare genetic heart disease associated with life-threatening ventricular arrhythmias. Diagnosis of ARVC is based on the 2010 Task Force Criteria (TFC), application of which often requires clinical expertise at specialized centers.

OBJECTIVE

To develop and validate an electrocardiogram (ECG) deep-learning (DL) tool for ARVC diagnosis.

METHODS

ECGs of patients referred for ARVC evaluation were used to develop (n=551, 80.1%) and test (n=137, 19.9%) an ECG-DL model for prediction of TFC-defined ARVC diagnosis. The ARVC ECG-DL model was externally validated in a cohort of patients with pathogenic or likely pathogenic (P/LP) ARVC gene variants identified through the Geisinger MyCode Community Health Initiative (N=167).

RESULTS

Of 688 patients evaluated at JHH (57.3% male, mean age 40.2 years), 329 (47.8%) were diagnosed with ARVC. While ARVC diagnosis made by referring cardiologist ECG interpretation was unreliable (c-statistic 0.53 [CI: 0.52, 0.53]), ECG-DL discrimination in the hold-out testing cohort was excellent (0.87 [0.86, 0.89]) and compared favorably to that of ECG interpretation by an ARVC expert (0.85 [0.84, 0.86]). In the Geisinger cohort, prevalence of ARVC was lower (n=17, 10.2%), but ECG-DL based identification of ARVC phenotype remained reliable (0.80 [0.77, 0.83]). Discrimination was further increased when ECG-DL predictions were combined with non-ECG-derived TFC in the JHH testing (c-statistic 0.940 [95%CI: 0.933; 0.948]) and Geisinger validation (0.897 [95%CI: 0.883; 0.912]) cohorts.

CONCLUSION

ECG-DL augments diagnosis of ARVC to the level of an ARVC expert and can differentiate true ARVC diagnosis from phenotype-mimics and at-risk family members/genotype-positive individuals.

Long-term reliability of the phospholamban (PLN) p.(Arg14del) risk model in predicting major ventricular arrhythmia: a landmark study

AIMS

Recently, a genetic variant-specific prediction model for phospholamban (PLN) p.(Arg14del)-positive individuals was developed to predict individual major ventricular arrhythmia (VA) risk to support decision-making for primary prevention implantable cardioverter defibrillator (ICD) implantation. This model predicts major VA risk from baseline data, but iterative evaluation of major VA risk may be warranted considering that the risk factors for major VA are progressive. Our aim is to evaluate the diagnostic performance of the PLN p.(Arg14del) risk model at 3-year follow-up.

METHODS AND RESULTS

We performed a landmark analysis 3 years after presentation and selected only patients with no prior major VA. Data were collected of 268 PLN p.(Arg14del)-positive subjects, aged 43.5 ± 16.3 years, 38.9% male. After the 3 years landmark, subjects had a mean follow-up of 4.0 years (± 3.5 years) and 28 (10%) subjects experienced major VA with an annual event rate of 2.6% [95% confidence interval (CI) 1.6-3.6], defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. The PLN p.(Arg14del) risk score yielded good discrimination in the 3 years landmark cohort with a C-statistic of 0.83 (95% CI 0.79-0.87) and calibration slope of 0.97.

CONCLUSION

The PLN p.(Arg14del) risk model has sustained good model performance up to 3 years follow-up in PLN p.(Arg14del)-positive subjects with no history of major VA. It may therefore be used to support decision-making for primary prevention ICD implantation not merely at presentation but also up to at least 3 years of follow-up.

Implantable cardioverter defibrillator use in arrhythmogenic right ventricular cardiomyopathy in North America and Europe

BACKGROUND AND AIMS

Implantable cardioverter-defibrillators (ICDs) are critical for preventing sudden cardiac death (SCD) in arrhythmogenic right ventricular cardiomyopathy (ARVC). This study aims to identify cross-continental differences in utilization of primary prevention ICDs and survival free from sustained ventricular arrhythmia (VA) in ARVC.

METHODS

This was a retrospective analysis of ARVC patients without prior VA enrolled in clinical registries from 11 countries throughout Europe and North America. Patients were classified according to whether they received treatment in North America or Europe and were further stratified by baseline predicted VA risk into low- (<10%/5 years), intermediate- (10%-25%/5 years), and high-risk (>25%/5 years) groups. Differences in ICD implantation and survival free from sustained VA events (including appropriate ICD therapy) were assessed.

RESULTS

One thousand ninety-eight patients were followed for a median of 5.1 years; 554 (50.5%) received a primary prevention ICD, and 286 (26.0%) experienced a first VA event. After adjusting for baseline risk factors, North Americans were more than three times as likely to receive ICDs {hazard ratio (HR) 3.1 [95% confidence interval (CI) 2.5, 3.8]} but had only mildly increased risk for incident sustained VA [HR 1.4 (95% CI 1.1, 1.8)]. North Americans without ICDs were at higher risk for incident sustained VA [HR 2.1 (95% CI 1.3, 3.4)] than Europeans.

CONCLUSIONS

North American ARVC patients were substantially more likely than Europeans to receive primary prevention ICDs across all arrhythmic risk strata. A lower rate of ICD implantation in Europe was not associated with a higher rate of VA events in those without ICDs.

AAV-Mediated Delivery of Plakophilin-2a Arrests Progression of Arrhythmogenic Right Ventricular Cardiomyopathy in Murine Hearts: Preclinical Evidence Supporting Gene Therapy in Humans

BACKGROUND

Pathogenic variants in PKP2 (plakophilin-2) cause arrhythmogenic right ventricular cardiomyopathy, a disease characterized by life-threatening arrhythmias and progressive cardiomyopathy leading to heart failure. No effective medical therapy is available to prevent or arrest the disease. We tested the hypothesis that adeno-associated virus vector-mediated delivery of the human PKP2 gene to an adult mammalian heart deficient in PKP2 can arrest disease progression and significantly prolong survival.

METHODS

Experiments were performed using a PKP2-cKO (cardiac-specific, tamoxifen-activated PKP2 knockout murine model). The potential therapeutic, adeno-associated virus vector of serotype rh.74 (AAVrh.74)-PKP2a (PKP2 variant A; RP-A601) is a recombinant AAVrh.74 gene therapy viral vector encoding the human PKP2 variant A. AAVrh.74-PKP2a was delivered to adult mice by a single tail vein injection either before or after tamoxifen-activated PKP2-cKO. PKP2 expression was confirmed by molecular and histopathologic analyses. Cardiac function and disease progression were monitored by survival analyses, echocardiography, and electrocardiography.

RESULTS

Consistent with prior findings, loss of PKP2 expression caused 100% mortality within 50 days after tamoxifen injection. In contrast, AAVrh.74-PKP2a-mediated PKP2a expression resulted in 100% survival for >5 months (at study termination). Echocardiographic analysis revealed that AAVrh.74-PKP2a prevented right ventricle dilation, arrested left ventricle functional decline, and mitigated arrhythmia burden. Molecular and histological analyses showed AAVrh.74-PKP2a-mediated transgene mRNA and protein expression and appropriate PKP2 localization at the cardiomyocyte intercalated disc. Importantly, the therapeutic benefit was shown in mice receiving AAVrh.74-PKP2a after disease onset.

CONCLUSIONS

These preclinical data demonstrate the potential for AAVrh.74-PKP2a (RP-A601) as a therapeutic for PKP2-related arrhythmogenic right ventricular cardiomyopathy in both early and more advanced stages of the disease.

The pivotal role of compelling high-risk electrocardiographic markers in prediction of ventricular arrhythmic risk in arrhythmogenic right ventricular cardiomyopathy: A systematic review and meta-analysis

INTRODUCTION

Several investigations have shown that existing risk stratification processes remain insufficient for stratifying sudden cardiac death risk in arrhythmogenic right ventricular cardiomyopathy (ARVC). Multiple auxiliary parameters are investigated to offer a more precise prognostic model. Our aim was to assess the association between several ECG markers (epsilon waves, prolonged terminal activation duration (TAD) of QRS, fragmented QRS (fQRS), late potentials on signal-averaged electrocardiogram (SA-ECG), T-wave inversion (TWI) in right precordial leads, and extension of TWI in inferior leads) with the risk of developing poor outcomes in ARVC.

METHODS

A systematic literature search from several databases was conducted until September 9th, 2023. Studies were eligible if it investigated the relationship between the ECG markers with the risk of developing ventricular arrhythmic events.

RESULTS

This meta-analysis encompassed 25 studies with a total of 3767 participants. Our study disclosed that epsilon waves, prolonged TAD of QRS, fQRS, late potentials on SA-ECG, TWI in right precordial leads, and extension of TWI in inferior leads were associated with the incremental risk of ventricular arrhythmias, implantable cardioverter-defibrillator shock, and sudden cardiac death, with the risk ratios ranging from 1.46 to 2.11. In addition, diagnostic test accuracy meta-analysis stipulated that the extension of TWI in inferior leads had the uppermost overall area under curve (AUC) value amidst other ECG markers apropos of our outcomes of interest.

CONCLUSION

A multivariable risk assessment strategy based on the previously stated ECG markers potentially enhances the current risk stratification models in ARVC patients, especially extension of TWI in inferior leads.

Dynamic prediction of malignant ventricular arrhythmias using neural networks in patients with an implantable cardioverter-defibrillator

BACKGROUND

Risk stratification for ventricular arrhythmias currently relies on static measurements that fail to adequately capture dynamic interactions between arrhythmic substrate and triggers over time. We trained and internally validated a dynamic machine learning (ML) model and neural network that extracted features from longitudinally collected electrocardiograms (ECG), and used these to predict the risk of malignant ventricular arrhythmias.

METHODS

A multicentre study in patients implanted with an implantable cardioverter-defibrillator (ICD) between 2007 and 2021 in two academic hospitals was performed. Variational autoencoders (VAEs), which combine neural networks with variational inference principles, and can learn patterns and structure in data without explicit labelling, were trained to encode the mean ECG waveforms from the limb leads into 16 variables. Supervised dynamic ML models using these latent ECG representations and clinical baseline information were trained to predict malignant ventricular arrhythmias treated by the ICD. Model performance was evaluated on a hold-out set, using time-dependent receiver operating characteristic (ROC) and calibration curves.

FINDINGS

2942 patients (61.7 ± 13.9 years, 25.5% female) were included, with a total of 32,129 ECG recordings during a mean follow-up of 43.9 ± 35.9 months. The mean time-varying area under the ROC curve for the dynamic model was 0.738 ± 0.07, compared to 0.639 ± 0.03 for a static (i.e. baseline-only model). Feature analyses indicated dynamic changes in latent ECG representations, particularly those affecting the T-wave morphology, were of highest importance for model predictions.

INTERPRETATION

Dynamic ML models and neural networks effectively leverage routinely collected longitudinal ECG recordings for personalised and updated predictions of malignant ventricular arrhythmias, outperforming static models.

FUNDING

This publication is part of the project DEEP RISK ICD (with project number 452019308) of the research programme Rubicon which is (partly) financed by the Dutch Research Council (NWO). This research is partly funded by the Amsterdam Cardiovascular Sciences (personal grant F.V.Y.T).

The added value of abnormal regional myocardial function for risk prediction in arrhythmogenic right ventricular cardiomyopathy

AIMS

A risk calculator for individualized prediction of first-time sustained ventricular arrhythmia (VA) in arrhythmogenic right ventricular cardiomyopathy (ARVC) patients has recently been developed and validated (www.ARVCrisk.com). This study aimed to investigate whether regional functional abnormalities, measured by echocardiographic deformation imaging, can provide additional prognostic value.

METHODS AND RESULTS

From two referral centres, 150 consecutive patients with a definite ARVC diagnosis, no prior sustained VA, and an echocardiogram suitable for deformation analysis were included (aged 41 ± 17 years, 50% female). During a median follow-up of 6.3 (interquartile range 3.1-9.8) years, 37 (25%) experienced a first-time sustained VA. All tested left and right ventricular (LV and RV) deformation parameters were univariate predictors for first-time VA. While LV function did not add predictive value in multivariate analysis, two RV deformation parameters did; RV free wall longitudinal strain and regional RV deformation patterns remained independent predictors after adjusting for the calculator-predicted risk [hazard ratio 1.07 (95% CI 1.02-1.11); P = 0.004 and 4.45 (95% CI 1.07-18.57); P = 0.040, respectively] and improved its discriminative value (from C-statistic 0.78 to 0.82 in both; Akaike information criterion change > 2). Importantly, all patients who experienced VA within 5 years from the echocardiographic assessment had abnormal regional RV deformation patterns at baseline.

CONCLUSIONS

This study showed that regional functional abnormalities measured by echocardiographic deformation imaging can further refine personalized arrhythmic risk prediction when added to the ARVC risk calculator. The excellent negative predictive value of normal RV deformation could support clinicians considering the timing of implantable cardioverter defibrillator implantation in patients with intermediate arrhythmic risk.

Arrhythmic risk stratification in arrhythmogenic right ventricular cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a heritable cardiomyopathy characterized by a predominantly arrhythmic presentation. It represents the leading cause of sudden cardiac death (SCD) among athletes and poses a significant morbidity threat in the general population. As a causative treatment for ARVC is still not available, the placement of an implantable cardioverter defibrillator represents the current cornerstone for SCD prevention in this setting. Thanks to international ARVC-dedicated efforts, significant steps have been achieved in recent years towards an individualized, patient-centred risk stratification approach. A novel risk calculator algorithm estimating the 5-year risk of arrhythmias of patients with ARVC has been introduced in clinical practice and subsequently validated. The purpose of this article is to summarize the body of evidence that has allowed the development of this tool and to discuss the best way to implement its use in the care of an individual patient.

Prevention of Sudden Death and Management of Ventricular Arrhythmias in Arrhythmogenic Cardiomyopathy

Arrhythmogenic cardiomyopathy is an umbrella term for a group of inherited diseases of the cardiac muscle characterized by progressive fibro-fatty replacement of the myocardium. As suggested by the name, the disease confers electrical instability to the heart and increases the risk of the development of life-threatening arrhythmias, representing one of the leading causes of sudden cardiac death (SCD), especially in young athletes. In this review, the authors review the current knowledge of the disease, highlighting the state-of-the-art approaches to the prevention of the occurrence of SCD.

Evolution and triggers of defibrillator shocks in patients with arrhythmogenic right ventricular cardiomyopathy

INTRODUCTION

Implantable cardioverter-defibrillators (ICDs) can prevent sudden cardiac death due to ventricular arrhythmias in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC). The aim of our study was to assess the cumulative burden, evolution and potential triggers of appropriate ICD shocks during long-term follow-up, which may help to reduce and further refine individual arrhythmic risk in this challenging disease.

METHODS

This retrospective cohort study included 53 patients with definite ARVC according to the 2010 Task Force Criteria from the multicentre Swiss ARVC Registry with an implanted ICD for primary or secondary prevention. Follow-up was conducted by assessing all available patient records from patient visits, hospitalisations, blood samples, genetic analysis, as well as device interrogation and tracings.

RESULTS

Fifty-three patients (male 71.7%, mean age 43±2.2 years, genotype positive 58.5%) were analysed during a median follow-up of 7.9 (IQR 10) years. In 29 (54.7%) patients, 177 appropriate ICD shocks associated with 71 shock episodes occurred. Median time to first appropriate ICD shock was 2.8 (IQR 3.6) years. Long-term risk of shocks remained high throughout long-term follow-up. Shock episodes occurred mainly during daytime (91.5%, n=65) and without seasonal preference. We identified potentially reversible triggers in 56 of 71 (78.9%) appropriate shock episodes, the main triggers representing physical activity, inflammation and hypokalaemia.

CONCLUSION

The long-term risk of appropriate ICD shocks in patients with ARVC remains high during long-term follow-up. Ventricular arrhythmias occur more often during daytime, without seasonal preference. Reversible triggers are frequent with the most common triggers for appropriate ICD shocks being physical activity, inflammation and hypokalaemia in this patient population.

Anthracycline-Induced Cardiotoxicity in Breast Cancer Patients: A Five-Year Retrospective Study in 10 Centers

Background

Cardiotoxicity as a result of anthracycline chemotherapy has been linked to increased morbidity and mortality in breast cancer patients. There is a need for early detection through risk factor identification. To date, no large multicenter study has been conducted to describe the incidence, risk factors and clinical and demographic profiles of breast cancer patients with anthracycline-induced cardiotoxicity (AIC) in the Philippines.

Methods

This was a nationwide multicenter retrospective cohort study among adult breast cancer patients who underwent anthracycline chemotherapy from 2015 to 2020 in 10 sites in the Philippines. Baseline characteristics and possible risk factors for AIC were retrieved from medical records and cancer registries. AIC was defined as a reduction of left ventricular ejection fraction (LVEF) by > 10% from baseline to a value of < 53% or the development of overt left ventricular systolic dysfunction or heart failure (HF). Odds ratios from logistic regression were computed to determine risk factors associated with AIC using STATA-15.0 software.

Results

Out of 341 patients included, 33 had AIC, accounting for an incidence of 9.68%. Nine patients (2.6%) had clinical HF. AIC patients had a mean age of 53.91 ± 10.84 years. Breast cancer AIC patients were significantly older and had lower body mass index (BMI) than those without AIC. AIC patients had significantly more comorbidities, especially hypertension and atrial fibrillation. Multivariate analysis showed that patients with any preexisting comorbidity are approximately 12.37 times as likely to have AIC, while those with concurrent chemotherapy are 0.07 times or 93% less likely to have AIC.

Conclusion

Among adult breast cancer patients undergoing anthracycline chemotherapy, we determined a high incidence of cardiotoxicity at 9.68%. Having preexisting comorbidities gave patients 12 times increased odds of developing anthracycline cardiotoxicity. The presence of concurrent non-anthracycline chemotherapy showed an inverse association with the development of AIC which we attribute largely to patient selection in a retrospective study. The significantly higher propensity for AIC development in patients with preexisting comorbidities may warrant closer monitoring and control of patient comorbidities such as hypertension among patients undergoing anthracycline chemotherapy.