The challenge of predicting sudden cardiac death: complementary role of risk scores, genetic testing, and clinical judgement

With thanks to Amelia Meier-Batschelet, Johanna Huggler, and Martin Meyer for help with compilation of this article. For the podcast associated with this article, please visit https://academic.oup.com/eurheartj/pages/Podcasts. This Focus Issue on arrhythmias contains the State of the Art Review article entitled ‘Electromechanical reciprocity and arrhythmogenesis in long-QT syndrome and beyond’ by Katja E. Odening from the University of Bern in Switzerland, and colleagues. The authors note that an abundance of literature describes physiological and pathological determinants of cardiac performance, building on the principles of excitation–contraction coupling.1 However, the mutual influence of excitation–contraction and mechano-electrical feedback in the beating heart, here designated ‘electromechanical reciprocity’, remains poorly recognized clinically, despite the awareness that external and cardiac-internal mechanical stimuli can trigger electrical responses and arrhythmia. This review focuses on electromechanical reciprocity in the long-QT syndrome (LQTS), historically considered a purely electrical disease,2–6 but now appreciated as paradigm for the understanding of mechano-electrical contributions to arrhythmogenesis in this and other cardiac conditions. Electromechanical dispersion in LQTS is characterized by heterogeneously prolonged ventricular repolarization, in addition to altered contraction duration and relaxation. Mechanical alterations may deviate from what would be expected from global and regional repolarization abnormalities. Pathological repolarization prolongation outlasts mechanical systole in patients with LQTS, yielding a negative electromechanical window (EMW), which is most pronounced in symptomatic patients. The electromechanical window is a superior and independent arrhythmia risk predictor compared with the heart rate-corrected QT. A negative EMW implies that the ventricle is deformed—by volume loading during the rapid filling phase—when repolarization is still ongoing. This creates a ‘sensitized’ electromechanical substrate, in which inadvertent electrical or mechanical stimuli such as local after-depolarizations, after-contractions, or dyssynchrony can trigger abnormal impulses. Increased sympathetic nerve activity and pause-dependent potentiation further exaggerate electromechanical heterogeneities, promoting arrhythmogenesis. Unravelling electromechanical reciprocity advances the understanding of arrhythmia formation in various conditions. Real-time image integration of cardiac electrophysiology and mechanics offers new opportunities to address challenges in arrhythmia management. In a second State of the Art Review article entitled ‘Implantable defibrillators in primary prevention of genetic arrhythmias. A shocking choice?’ Domenico Corrado from the University of Padova Medical School in Italy, and colleagues point out that many previously unexplained life-threatening ventricular arrhythmias and sudden cardiac deaths (SCDs) in young individuals are now recognized to be genetic in nature and are ascribed to a growing number of distinct inherited arrhythmogenic diseases.7 These include hypertrophic cardiomyopathy, arrhythmogenic cardiomyopathy, LQTS, Brugada syndrome, catecholaminergic polymorphic ventricular tachycardia (VT), and short QT syndrome.8–12 Because of their lower frequency compared with coronary disease, risk factors for SCD are not very precise in patients with inherited arrhythmogenic diseases. As randomized studies are generally not feasible and may even be ethically unjustifiable, especially in the presence of effective therapies, the risk assessment of malignant arrhythmic events to guide implantable cardioverter defibrillator (ICD) implantation is based on observational data and expert consensus. In this document, the authors review risk factors for SCD and indications for ICD implantation and additional therapies. What emerges is that, allowing for some important differences between cardiomyopathies and channelopathies, there is a growing and disquieting trend to create, and then use, semi-automated systems (risk scores, risk calculators) which then dictate therapeutic choices. Their common denominator is a tendency to favour ICD implantation, sometimes with reason, sometimes without it. This contrasts with the time-honoured approach of selecting, among the available therapies, the best option (ICDs included) based on the clinical judgement for the specific patient and after having assessed the protection provided by optimal medical treatment. Arrhythmogenic right ventricular cardiomyopathy (ARVC) causes ventricular arrhythmias (VAs) and SCD. In 2019, a risk prediction model that estimates the 5-year risk of incident VAs in ARVC was developed (ARVCrisk.com). In a Clinical Research article ‘Arrhythmic risk prediction in arrhythmogenic right ventricular cardiomyopathy: external validation of the arrhythmogenic right ventricular cardiomyopathy risk calculator’, Paloma Jordà from the Université de Montréal in Canada and colleagues 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 ICD use by published guidelines and expert consensus.13 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 years following diagnosis of ARVC. External validation yielded good discrimination (C-index of 0.70) and a calibration slope of 1.01. 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 a risk threshold of 35%. The authors conclude that using a large independent cohort of patients, this study shows that the ARVC risk calculator 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. In a Clinical Research article entitled ‘Importance of genotype for risk stratification in arrhythmogenic right ventricular cardiomyopathy using the 2019 ARVC risk calculator’, Alexandros Protonotarios from University College London in the UK, and colleagues studied the impact of genotype on the performance of the 2019 risk model for ARVC.14 The study cohort comprised 554 patients with a definite diagnosis of ARVC and no history of sustained VA. During a median follow-up of 6 years, 100 patients (18%) experienced the primary VA outcome (sustained VT, appropriate ICD intervention, aborted sudden cardiac arrest, or SCD), corresponding to an annual event rate of 2.6%. Risk estimates for VA using the 2019 ARVC risk model showed reasonable discriminative ability but with overestimation of risk. The ARVC risk model was compared in four gene groups: PKP2 (n = 118, 21%); desmoplakin (DSP) (n = 79, 14%); other desmosomal (n = 59, 11%); and gene elusive (n = 160, 29%). Discrimination and calibration were highest for PKP2 and lowest for the gene-elusive group. Univariable analyses revealed the variable performance of individual clinical risk markers in the different gene groups, e.g. right ventricular dimensions and systolic function were significant risk markers in PKP2 but not in DSP patients, and the opposite is true for left ventricular systolic function. Protonotarios et al. conclude that 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. The two contributions by Protonotarios and Jordà are linked to a common Editorial by Estelle Gandjbakhch from the Pitié-Salpêtrière University Hospital in Paris, France and Annina S. Vischer from the University Hospital Basel in Switzerland.15 Gandjbakhch and Vischer conclude that similarly to risk calculators proposed in other inherited cardiac diseases, the ARVC risk calculator is not a magic tool and should be used cautiously by clinicians. The calculator should only be used in patients with the classical right dominant form fulfilling the 2010 ARVC criteria, and clinicians should be aware of its limits, i.e. the possible risk overestimation, low specificity for thresholds <15%, and lower performance in non-PKP2 mutation carriers and gene-negative patients. As no threshold has been validated to date, this score can only provide an estimation of the 5-year VA risk, which, importantly, is different from the SCD risk. ICD indication should remain a shared decision, based not only on the result of the score but also on the overall evaluation of the patient. Study flowchart and summary results. ARVC, arrhythmogenic right ventricular cardiomyopathy; BrS, Brugada syndrome; CPVT, catecholaminergic polymorphic ventricular tachycardia; CRDS, RYR2 Ca2+ release deficiency syndrome; DCM, dilated cardiomyopathy; ECG, electrocardiogram; HCM, hypertrophic cardiomyopathy; LQTS, long QT syndrome; LV, left ventricular; MRI, magnetic resonance imaging; MVP, mitral valve prolapse; SQTS, short QT syndrome; UCM, unclassified cardiomyopathy; WES, whole-exome sequencing.18 While most cardiac arrests occur in an older population with coronary artery disease, some occur in young and otherwise healthy individuals. In the latter group, diagnostic testing with electrocardiography and cardiac imaging may identify the cause of arrest, including heritable electrical or structural disorders.6,17 When a specific heritable diagnosis is established, genetic testing using targeted panels is recommended, mainly to facilitate family screening. In contrast, the role of genetic testing in the absence of a definite diagnosis of inherited arrhythmia and/or cardiomyopathy is questionable, with concerns regarding cost and challenging interpretation of the genetic test results, especially for variants of uncertain significance. Current guidelines do not support the role of ‘exploratory’ genetic testing in this context. In a Clinical Research article entitled ‘Importance of genetic testing in unexplained cardiac arrest’, Steffany Grondin from the Université de Montréal in Canada, and colleagues assess the role of genetic testing in unexplained cardiac arrest (UCA) using whole-exome sequencing (WES).18 A total of 228 UCA survivors (mean age at arrest 39 ± 13 years) were included. The majority were males (66%) and of European ancestry (81%). Following advanced clinical testing at baseline, the likely aetiology of cardiac arrest was determined in 21/228 (9%) cases. Whole-exome sequencing identified a pathogenic or likely pathogenic (P/LP) variant in 23/228 (10%) of UCA survivors overall, increasing the proportion of ‘explained’ cases from 9% only following phenotyping to 18% when combining phenotyping with WES. Notably, 13 (57%) of the 23 P/LP variants identified were located in genes associated with cardiomyopathy, in the absence of a diagnosis of cardiomyopathy at the time of arrest (Figure 1). The authors conclude that genetic testing identifies a disease-causing variant in 10% of apparent UCA survivors. Most disease-causing variants were located in cardiomyopathy-associated genes, highlighting the arrhythmogenic potential of such variants in the absence of an overt cardiomyopathy diagnosis. The present study supports the use of genetic testing including assessment of arrhythmia and cardiomyopathy genes in survivors of UCA. The contribution is accompanied by an Editorial by Elijah R. Behr from the University of London in the UK.19 Behr note that the work of Grondin et al. coupled with others further promotes the role for genetic testing, implying that cardiomyopathy genes with robust disease associations should be included in gene panels, albeit with careful adjudication of variant pathogenicity. Furthermore, the systematic application of genetic testing in patients suffering UCA can be useful and could therefore be upgraded to Class 2a. Ultimately their further utility will be realized when a P/LP variant is detected in the index case which can then be applied for predictive testing for diagnosis in family members and then their subsequent management. If genetic testing does not return such a finding, then clinical evaluation should still proceed in first-degree relatives of sudden arrhythmic death syndrome decedents. The evidence supporting a role for clinal evaluation of relatives of a UCA survivor without signs of genetic heart disease is, however, weaker. The challenge that awaits is to determine the causation of cases of UCA that remain unexplained despite the aforementioned clinical and genetic investigations. If there is a genetic basis, could it be polygenic and how much risk is environmentally determined? This will require even larger cohorts with extensive genomic and clinical characterization to tease out further and will be addressed by a unique European and International collaboration: the GenUCA Investigators The editors hope that this issue of the European Heart Journal will be of interest to its readers. Dr. Crea reports speaker fees from Amgen, Astra Zeneca, Servier, BMS, other from GlyCardial Diagnostics, outside the submitted work.