Heart Rate Recovery After Exercise Is Associated With Arrhythmic Events in Patients With Catecholaminergic Polymorphic Ventricular Tachycardia

BACKGROUND: Risk stratification in catecholaminergic polymorphic ventricular tachycardia remains ill defined. Heart rate recovery (HRR) immediately after exercise is regulated by autonomic reflexes, particularly vagal tone, and may be associated with symptoms and ventricular arrhythmias in patients with catecholaminergic polymorphic ventricular tachycardia. Our objective was to evaluate whether HRR after maximal exercise on the exercise stress test (EST) is associated with symptoms and ventricular arrhythmias. METHODS: In this retrospective observational study, we included patients ≤65 years of age with an EST without antiarrhythmic drugs who attained at least 80% of their age- and sex-predicted maximal HR. HRR in the recovery phase was calculated as the difference in heart rate (HR) at maximal exercise and at 1 minute in the recovery phase (ΔHRR1'). RESULTS: We included 187 patients (median age, 36 years; 68 [36%] symptomatic before diagnosis). Pre-EST HR and maximal HR were equal among symptomatic and asymptomatic patients. Patients who were symptomatic before diagnosis had a greater ΔHRR1' after maximal exercise (43 [interquartile range, 25-58] versus 25 [interquartile range, 19-34] beats/min; P<0.001). Corrected for age, sex, and relatedness, patients in the upper tertile for ΔHRR1' had an odds ratio of 3.4 (95% CI, 1.6-7.4) of being symptomatic before diagnosis (P<0.001). In addition, ΔHRR1' was higher in patients with complex ventricular arrhythmias at EST off antiarrhythmic drugs (33 [interquartile range, 22-48] versus 27 [interquartile range, 20-36] beats/min; P=0.01). After diagnosis, patients with a ΔHRR1' in the upper tertile of its distribution had significantly more arrhythmic events as compared with patients in the other tertiles (P=0.045). CONCLUSIONS: Catecholaminergic polymorphic ventricular tachycardia patients with a larger HRR following exercise are more likely to be symptomatic and have complex ventricular arrhythmias during the first EST off antiarrhythmic drug

Sudden cardiac death prediction in arrhythmogenic right ventricular cardiomyopathy: a multinational collaboration

Background:Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with ventricular arrhythmias (VA) and sudden cardiac death (SCD). A model was recently developed to predict incident sustained VA in patients with ARVC. However, since this outcome may overestimate the risk for SCD, we aimed to specifically predict life-threatening VA (LTVA) as a closer surrogate for SCD.Methods:We assembled a retrospective cohort of definite ARVC cases from 15 centers in North America and Europe. Association of 8 prespecified clinical predictors with LTVA (SCD, aborted SCD, sustained, or implantable cardioverter-defibrillator treated ventricular tachycardia >250 beats per minute) in follow-up was assessed by Cox regression with backward selection. Candidate variables included age, sex, prior sustained VA (>= 30s, hemodynamically unstable, or implantable cardioverter-defibrillator treated ventricular tachycardia; or aborted SCD), syncope, 24-hour premature ventricular complexes count, the number of anterior and inferior leads with T-wave inversion, left and right ventricular ejection fraction. The resulting model was internally validated using bootstrapping.Results:A total of 864 patients with definite ARVC (40 +/- 16 years; 53% male) were included. Over 5.75 years (interquartile range, 2.77-10.58) of follow-up, 93 (10.8%) patients experienced LTVA including 15 with SCD/aborted SCD (1.7%). Of the 8 prespecified clinical predictors, only 4 (younger age, male sex, premature ventricular complex count, and number of leads with T-wave inversion) were associated with LTVA. Notably, prior sustained VA did not predict subsequent LTVA (P=0.850). A model including only these 4 predictors had an optimism-corrected C-index of 0.74 (95% CI, 0.69-0.80) and calibration slope of 0.95 (95% CI, 0.94-0.98) indicating minimal over-optimism.Conclusions:LTVA events in patients with ARVC can be predicted by a novel simple prediction model using only 4 clinical predictors. Prior sustained VA and the extent of functional heart disease are not associated with subsequent LTVA events.Cardiolog

Sudden Cardiac Death Prediction in Arrhythmogenic Right Ventricular Cardiomyopathy: A Multinational Collaboration

BACKGROUND: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with ventricular arrhythmias (VA) and sudden cardiac death (SCD). A model was recently developed to predict incident sustained VA in patients with ARVC. However, since this outcome may overestimate the risk for SCD, we aimed to specifically predict life-threatening VA (LTVA) as a closer surrogate for SCD. METHODS: We assembled a retrospective cohort of definite ARVC cases from 15 centers in North America and Europe. Association of 8 prespecified clinical predictors with LTVA (SCD, aborted SCD, sustained, or implantable cardioverter-defibrillator treated ventricular tachycardia >250 beats per minute) in follow-up was assessed by Cox regression with backward selection. Candidate variables included age, sex, prior sustained VA (≥30s, hemodynamically unstable, or implantable cardioverter-defibrillator treated ventricular tachycardia; or aborted SCD), syncope, 24-hour premature ventricular complexes count, the number of anterior and inferior leads with T-wave inversion, left and right ventricular ejection fraction. The resulting model was internally validated using bootstrapping. RESULTS: A total of 864 patients with definite ARVC (40±16 years; 53% male) were included. Over 5.75 years (interquartile range, 2.77-10.58) of follow-up, 93 (10.8%) patients experienced LTVA including 15 with SCD/aborted SCD (1.7%). Of the 8 prespecified clinical predictors, only 4 (younger age, male sex, premature ventricular complex count, and number of leads with T-wave inversion) were associated with LTVA. Notably, prior sustained VA did not predict subsequent LTVA (P=0.850). A model including only these 4 predictors had an optimism-corrected C-index of 0.74 (95% CI, 0.69-0.80) and calibration slope of 0.95 (95% CI, 0.94-0.98) indicating minimal over-optimism. CONCLUSIO

A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy

AIMS: Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients. METHODS AND RESULTS: Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 ± 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44-9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73-0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92-0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.6% reduction of ICD placements with the same proportion of protected patients (P < 0.001). CONCLUSION: Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs (www.arvcrisk.com)

2022 ESC guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: developed by the task force for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death of the European Society of Cardiology (ESC) endorsed by the Association for European Paediatric and Congenital Cardiology (A

Cardiolog

The EACVI survey on cardiac imaging in cardio-oncology

Early and late cardiovascular (CV) toxicities related to many cancer treatments may complicate the clinical course of patients, offsetting therapeutic benefits, and altering prognosis. The early detection, monitoring, and treatment of cardiotoxicity have therefore become essential parts of cancer patient care. CV imaging is a cornerstone of every cardio-oncology unit, but its use may vary across Europe because of the non-uniform availability of advanced imaging techniques and differences in the organization and logistics of cardio-oncology services. The purpose of this EACVI survey in cardio-oncology is to obtain real-world data on the current usage of cardiac imaging in cancer patients. Data from 104 centres and 35 different countries confirmed that cardiac imaging plays a pivotal role in the detection and monitoring of cardiac toxicity in oncology patients in Europe and beyond. However, it also revealed gaps between guidelines recommendations and everyday clinical practice, highlighting some of the challenges that need to be overcome in this rapidly advancing field

Uncertainty Quantification of Regional Cardiac Tissue Properties in Arrhythmogenic Cardiomyopathy Using Adaptive Multiple Importance Sampling

Introduction: Computational models of the cardiovascular system are widely used to simulate cardiac (dys)function. Personalization of such models for patient-specific simulation of cardiac function remains challenging. Measurement uncertainty affects accuracy of parameter estimations. In this study, we present a methodology for patient-specific estimation and uncertainty quantification of parameters in the closed-loop CircAdapt model of the human heart and circulation using echocardiographic deformation imaging. Based on patient-specific estimated parameters we aim to reveal the mechanical substrate underlying deformation abnormalities in patients with arrhythmogenic cardiomyopathy (AC). Methods: We used adaptive multiple importance sampling to estimate the posterior distribution of regional myocardial tissue properties. This methodology is implemented in the CircAdapt cardiovascular modeling platform and applied to estimate active and passive tissue properties underlying regional deformation patterns, left ventricular volumes, and right ventricular diameter. First, we tested the accuracy of this method and its inter- and intraobserver variability using nine datasets obtained in AC patients. Second, we tested the trueness of the estimation using nine in silico generated virtual patient datasets representative for various stages of AC. Finally, we applied this method to two longitudinal series of echocardiograms of two pathogenic mutation carriers without established myocardial disease at baseline. Results: Tissue characteristics of virtual patients were accurately estimated with a highest density interval containing the true parameter value of 9% (95% CI [0–79]). Variances of estimated posterior distributions in patient data and virtual data were comparable, supporting the reliability of the patient estimations. Estimations were highly reproducible with an overlap in posterior distributions of 89.9% (95% CI [60.1–95.9]). Clinically measured deformation, ejection fraction, and end-diastolic volume were accurately simulated. In presence of worsening of deformation over time, estimated tissue properties also revealed functional deterioration. Conclusion: This method facilitates patient-specific simulation-based estimation of regional ventricular tissue properties from non-invasive imaging data, taking into account both measurement and model uncertainties. Two proof-of-principle case studies suggested that this cardiac digital twin technology enables quantitative monitoring of AC disease progression in early stages of disease