Arrhythmic risk stratification in non-ischaemic dilated cardiomyopathy beyond ejection fraction

Inherited Arrhythmias in the Pediatric Population: An Updated Overview

Pediatric cardiomyopathies (CMs) and electrical diseases constitute a heterogeneous spectrum of disorders distinguished by structural and electrical abnormalities in the heart muscle, attributed to a genetic variant. They rank among the main causes of morbidity and mortality in the pediatric population, with an annual incidence of 1.1-1.5 per 100,000 in children under the age of 18. The most common conditions are dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). Despite great enthusiasm for research in this field, studies in this population are still limited, and the management and treatment often follow adult recommendations, which have significantly more data on treatment benefits. Although adult and pediatric cardiac diseases share similar morphological and clinical manifestations, their outcomes significantly differ. This review summarizes the latest evidence on genetics, clinical characteristics, management, and updated outcomes of primary pediatric CMs and electrical diseases, including DCM, HCM, arrhythmogenic right ventricular cardiomyopathy (ARVC), Brugada syndrome (BrS), catecholaminergic polymorphic ventricular tachycardia (CPVT), long QT syndrome (LQTS), and short QT syndrome (SQTS).

Prediction of adverse outcomes in nonischemic dilated cardiomyopathy: A CMR-based nomogram

OBJECTIVES

To develop and validate a novel nomogram score to predict outcomes in patients with nonischemic dilated cardiomyopathy (NIDCM) over a long follow-up period.

METHODS

A total of 335 consecutive NIDCM patients who underwent cardiac magnetic resonance (CMR) imaging were retrospectively enrolled. Comprehensive clinical evaluation and imaging investigation were obtained, including measurements of late gadolinium enhancement (LGE) and feature tracking (FT) images. All patients were followed up for a composite endpoint of major adverse cardiac events (MACE) including all-cause mortality and heart transplantation. These patients were randomly divided into development and validation cohorts (7:3).

RESULTS

MACE occurred in 87 (37.2%) out of 234 patients in the development cohort, and in 31 (30.7%) out of 101 patients in the validation cohort. Five variables including NYHA class III-IV, NT-proBNP, beta-blocker medication, LGE presence, and LV global longitudinal strain (GLS) were found to be significantly associated with MACE and were used for constructing the nomogram. The nomogram achieved good discrimination with C-indexes in development and validation cohorts respectively. The calibration curve for 1-, 3-, and 5-year survival probability also showed high coherence between the predicted and actual probability of MACE. Decision curve analysis identified the model was significantly better net benefit in predicting MACE.

CONCLUSION

A novel nomogram score of a predictive model that incorporates clinical factors and imaging features was constructed, which could be conveniently used to facilitate risk evaluation in patients with NIDCM.

Primary prevention implantable cardioverter-defibrillator use in non-ischemic dilated cardiomyopathy based on arrhythmic risk stratification and left ventricular reverse remodeling prediction

Sudden cardiac death (SCD) and significant ventricular arrhythmias in patients with dilated cardiomyopathy (DCM) have been markedly reduced over the last couple of decades as a result of the advances in pharmacological and non-pharmacological treatment. Primary prevention implantable cardioverter-defibrillator (ICD) plays an important role in the treatment of patients at risk of SCD caused by ventricular arrhythmias. However, the arrhythmic risk stratification in patients with DCM remains extremely challenging, and the decision for primary prevention ICD implantation based on left ventricular ejection fraction (LVEF) solely appears to be insufficient. This review provides an update on current evidence for primary prevention ICD implantation, arrhythmic risk stratification, and left ventricular reverse remodeling (LVRR) prediction in patients with DCM in addition to most recent guideline recommendations for primary prevention ICD implantation in DCM patients and a proposed multiparametric algorithm based on arrhythmic risk stratification and left ventricular reverse remodeling (LVRR) prediction to better identify patients who are likely to benefit from primary prevention ICD.

The Role of AI in Characterizing the DCM Phenotype

Dilated Cardiomyopathy is conventionally defined by left ventricular dilatation and dysfunction in the absence of coronary disease. Emerging evidence suggests many patients remain vulnerable to major adverse outcomes despite clear therapeutic success of modern evidence-based heart failure therapy. In this era of personalized medical care, the conventional assessment of left ventricular ejection fraction falls short in fully predicting evolution and risk of outcomes in this heterogenous group of heart muscle disease, as such, a more refined means of phenotyping this disease appears essential. Cardiac MRI (CMR) is well-placed in this respect, not only for its diagnostic utility, but the wealth of information captured in global and regional function assessment with the addition of unique tissue characterization across different disease states and patient cohorts. Advanced tools are needed to leverage these sensitive metrics and integrate with clinical, genetic and biochemical information for personalized, and more clinically useful characterization of the dilated cardiomyopathy phenotype. Recent advances in artificial intelligence offers the unique opportunity to impact clinical decision making through enhanced precision image-analysis tasks, multi-source extraction of relevant features and seamless integration to enhance understanding, improve diagnosis, and subsequently clinical outcomes. Focusing particularly on deep learning, a subfield of artificial intelligence, that has garnered significant interest in the imaging community, this paper reviews the main developments that could offer more robust disease characterization and risk stratification in the Dilated Cardiomyopathy phenotype. Given its promising utility in the non-invasive assessment of cardiac diseases, we firstly highlight the key applications in CMR, set to enable comprehensive quantitative measures of function beyond the standard of care assessment. Concurrently, we revisit the added value of tissue characterization techniques for risk stratification, showcasing the deep learning platforms that overcome limitations in current clinical workflows and discuss how they could be utilized to better differentiate at-risk subgroups of this phenotype. The final section of this paper is dedicated to the allied clinical applications to imaging, that incorporate artificial intelligence and have harnessed the comprehensive abundance of data from genetics and relevant clinical variables to facilitate better classification and enable enhanced risk prediction for relevant outcomes.

Periodic Repolarization Dynamics Identifies ICD-responders in Non-ischemic Cardiomyopathy: A DANISH Substudy

Background: Identification of patients with non-ischemic cardiomyopathy who benefit from prophylactic implantation of a cardioverter-defibrillator (ICD) remains an unmet clinical need. We hypothesized that periodic repolarization dynamics (PRD), a marker of repolarization instability associated with sympathetic activity, could be used to identify patients that benefit from prophylactic ICD-implantation. Methods: Heart-failure (DANISH) study, in which patients with non-ischemic cardiomyopathy, left-ventricular ejection fraction (LVEF) ≤35% and elevated N-terminal pro-brain natriuretic peptides (NT-proBNP) were randomized to ICD-implantation or control group. Patients were included in the PRD-substudy if they had a 24-hour Holter monitor recording at baseline with technically acceptable ECG signals during the night hours (00:00-06.00 AM). PRD was assessed using wavelet analysis according to previously validated methods. Primary endpoint was all-cause mortality. Cox-regression models were adjusted for age, sex, NT-proBNP, estimated glomerular filtration rate, LVEF, atrial fibrillation, ventricular pacing, diabetes mellitus, cardiac resynchronization therapy and mean heart rate. We proposed PRD ≥10deg² as exploratory cut-off value for ICD-implantation. Results: Seven-hundred and forty-eight of the 1,116 DANISH patients qualified for the PRD-substudy. During a mean follow-up period of 5.1±2.0 years, 82 of 385 patients died in the ICD group and 85 of 363 patients died in the control group (p-value=0.40). In Cox-regression analysis, PRD was independently associated with mortality (HR 1.28 [1.09-1.50] per SD increase; p-value = 0.003). Moreover, PRD was significantly associated with mortality in the control group (HR 1.51 [1.25-1.81]; p<0.001) but not in the ICD-group 1.04 [0.83-1.54]; p-value=0.71). There was a significant interaction between PRD and the effect of ICD-implantation on mortality (p-value 0.008), with patients with higher PRD having the greater benefit in terms of mortality reduction. ICD-implantation was associated with an absolute mortality reduction of 17.5% in the 280 patients with PRD ≥10deg² (HR 0.54 [0.34-0.84]; p-value=0.006; number needed to treat 6), but not in the 468 patients with PRD<10deg² (HR 1.17 [0.77-1.78]; p-value=0.46; p-value for interaction 0.01). Conclusions: Increased PRD identified patients with non-ischemic cardiomyopathy, where prophylactic ICD-implantation led to significant mortality reduction.

The clinical utility of pediatric cardiomyopathy genetic testing: From diagnosis to a precision medicine-based approach to care

Background

Pediatric-onset cardiomyopathies are rare yet cause significant morbidity and mortality in affected children. Genetic testing has a major role in the clinical evaluation of pediatric-onset cardiomyopathies, and identification of a variant in an associated gene can be used to confirm the clinical diagnosis and exclude syndromic causes that may warrant different treatment strategies. Further, risk-predictive testing of first-degree relatives can assess who is at-risk of disease and requires continued clinical follow-up.

Aim of Review

In this review, we seek to describe the current role of genetic testing in the clinical diagnosis and management of patients and families with the five major cardiomyopathies. Further, we highlight the ongoing development of precision-based approaches to diagnosis, prognosis, and treatment.

Key Scientific Concepts of Review

Emerging application of genotype-phenotype correlations opens the door for genetics to guide a precision medicine-based approach to prognosis and potentially for therapies. Despite advances in our understanding of the genetic etiology of cardiomyopathy and increased accessibility of clinical genetic testing, not all pediatric cardiomyopathy patients have a clear genetic explanation for their disease. Expanded genomic studies are needed to understand the cause of disease in these patients, improve variant classification and genotype-driven prognostic predictions, and ultimately develop truly disease preventing treatment.

Contemporary etiology and prognosis of dilated non-ischemic cardiomyopathy

INTRODUCTION

Non-ischemic dilated cardiomyopathy (NI-DCM) represents a specific etiology of systolic heart failure that usually affect young individuals with a genetic background in up to 40% of cases. Behind the term NI-DCM there is a spectrum of different diseases, and an accurate etiological classification appears pivotal for the clinical management and prognostic stratification of these patients.

EVIDENCE ACQUISITION

In the last years the prognosis of NI-DCM patients dramatically improved thanks to the progresses in medical treatment/ device therapy and earlier diagnosis especially in familial context. In this review we summarize the actual state of art in the management of these patients.

EVIDENCE SYNTHESIS

In the era of precision medicine, a lot of progresses have been made to expand our knowledge on the management of NI-DCM patients. A complex interaction between genotype and external triggers is the main determinant of the clinical phenotype in NI-DCM, and a lot of efforts must be done by clinicians to systematically rule out all the possible causes involved in the pathogenesis. Progresses in cardiac imaging and familial screening led us to detect subtle abnormalities in the initial phase of the disease and also helped us to furtherly stratify the prognosis and arrhythmic risk of these patients. It is plausible that a more precise etiological classification will be needed in the near future.

CONCLUSIONS

NI-DCM contains a spectrum of different diseases. Proper etiological classification, early diagnosis and strict follow-up are essential to tailor care of these patients.

A Novel Gene Signature to Predict Survival Time and Incident Ventricular Arrhythmias in Patients with Dilated Cardiomyopathy

The mortality in nonischaemic dilated cardiomyopathy (NIDCM) patients is still at a high level; sudden death in NIDCM can be caused by ventricular tachycardia. It is necessary to explore the pathogenesis of ventricular arrhythmias (VA) in NIDCM. Differentially expressed genes (DEGs) were identified by comparing the gene expression of NIDCM patients with or without VA in the gene expression profile of GSE135055. A total of 228 DEGs were obtained, and 3 genes were screened out to be significantly related to the survival time of NIDCM patients. We established a prediction model on two-gene (TOMM22, PPP2R5A) signature for the survival time of NIDCM patients. The area under the curve (AUC) was 0.75 calculated by the ROC curve analysis. These risk genes are probably new targets for exploring the pathogenesis of NIDCM with VA; the prediction model for survival time and incident ventricular arrhythmias is useful in clinical decision making for individual treatment.

Sudden cardiac death: A comparative review of humans, dogs and cats

Sudden death is one of the most common causes of death in humans in Western countries. Approximately 85% of these cases are of cardiac origin. In dogs and cats, sudden cardiac death (SCD) also commonly occurs, but fewer pathophysiological and prevalence data are available. Both structural, primarily 'electrical' and ischemic heart diseases are known to cause SCD, many of which share similar underlying arrhythmogenic mechanisms between humans and companion animals. As for underlying genetics, numerous mutations on multiple loci have been related to SCD in humans, but only a few mutations associated with dilated cardiomyopathy and SCD have been identified in dogs, e.g. in the phospholamban and titin genes. Information published from human medicine can therefore inform future veterinary studies, but also dogs and cats could act as spontaneous models of SCD in humans. Further research in both fields is therefore warranted to better understand the pathophysiology, genetics, and prevention of SCD.

A clinical score for predicting left ventricular reverse remodelling in patients with dilated cardiomyopathy

Aims

Left ventricular reverse remodelling (LVRR) is a well‐established predictor of a good prognosis in patients with dilated cardiomyopathy (DCM). The prediction of LVRR is important when developing a long‐term treatment strategy. This study aimed to assess the clinical predictors of LVRR and establish a scoring system for predicting LVRR in patients with DCM that can be used at any institution.

Methods and results

We consecutively enrolled 131 patients with DCM and assessed the clinical predictors of LVRR. LVRR was defined as an absolute increase in left ventricular ejection fraction (LVEF) from ≥10% to a final value of >35%, accompanied by a decrease in left ventricular end‐diastolic dimension (LVEDD) ≥ 10% on echocardiography at 1 ± 0.5 years after a diagnosis of DCM. The mean patient age was 50.1 ± 11.9 years. The mean LVEF was 32.2 ± 9.5%, and the mean LVEDD was 64.1 ± 12.5 mm at diagnosis. LVRR was observed in 45 patients (34%) at 1 ± 0.5 years. In a multivariate analysis, hypertension [odds ratio (OR): 6.86; P = 0.002], no family history of DCM (OR: 10.45; P = 0.037), symptom duration <90 days (OR: 6.72; P < 0.001), LVEF <35% (OR: 13.66; P < 0.0001), and QRS duration <116 ms (OR: 5.94; P = 0.005) were found to be independent predictors of LVRR. We scored the five independent predictors according to the ORs (1 point, 2 points, 1 point, 2 points, and 1 point, respectively), and the total LVRR predicting score was calculated by adding these scores. The LVRR rate was stratified by the LVRR predicting score (0–2 points: 0%; 3 points: 6.7%; 4 points: 17.4%; 5 points: 48.2%; 6 points: 79.2%; and 7 points: 100%). The cut‐off value of the LVRR predicting score was >5 in receiver‐operating characteristic curve analysis (area under the curve: 0.89; P < 0.0001; sensitivity: 87%; specificity: 78%). An LVRR predicting score of >5 was an independent predictor compared with the presence of late gadolinium enhancement on cardiovascular magnetic resonance or the severity of fibrosis on endomyocardial biopsy (OR: 11.79; 95% confidence interval: 2.40–58.00; P = 0.002).

Conclusions

The LVRR predicting score using five predictors including hypertension, no family history of DCM, symptom duration <90 days, LVEF <35%, and QRS duration <116 ms can stratify the LVRR rate in patients with DCM. The LVRR predicting score may be a useful clinical tool that can be used easily at any institution.

Detection and functional characterization of a novel MEF2A variation responsible for familial dilated cardiomyopathy

OBJECTIVES

Dilated cardiomyopathy (DCM) represents the most frequent form of cardiomyopathy, leading to heart failure, cardiac arrhythmias and death. Accumulating evidence convincingly demonstrates the crucial role of genetic defects in the pathogenesis of DCM, and over 100 culprit genes have been implicated with DCM. However, DCM is of substantial genetic heterogeneity, and the genetic determinants underpinning DCM remain largely elusive.

METHODS

Whole-exome sequencing and bioinformatical analyses were implemented in a consanguineous Chinese family with DCM. A total of 380 clinically annotated control individuals and 166 more DCM index cases then underwent Sanger sequencing analysis for the identified genetic variation. The functional characteristics of the variant were delineated by utilizing a dual-luciferase assay system.

RESULTS

A heterozygous variation in the MEF2A gene (encoding myocyte enhancer factor 2A, a transcription factor pivotal for embryonic cardiogenesis and postnatal cardiac adaptation), NM_001365204.1: c.718G>T; p. (Gly240*), was identified, and verified by Sanger sequencing to segregate with autosome-dominant DCM in the family with complete penetrance. The nonsense variation was neither detected in 760 control chromosomes nor found in 166 more DCM probands. Functional analyses revealed that the variant lost transactivation on the validated target genes MYH6 and FHL2, both causally linked to DCM. Furthermore, the variation nullified the synergistic activation between MEF2A and GATA4, another key transcription factor involved in DCM.

CONCLUSIONS

The findings firstly indicate that MEF2A loss-of-function variation predisposes to DCM in humans, providing novel insight into the molecular mechanisms of DCM and suggesting potential implications for genetic testing and prognostic evaluation of DCM patients.

Mildly symptomatic heart failure with reduced ejection fraction: diagnostic and therapeutic considerations

AIMS

Whereas up to about half of patients with heart failure with reduced ejection fraction (HFrEF) report no or only mild symptoms and are considered as clinically stable, the progressive nature of HFrEF, often silent, renders clinical stability a misleading situation, especially if disease progression is unrecognized. We highlight the challenges in the definition of clinical stability and mild symptomatic status in HFrEF, outline clinical characteristics and available diagnostic tools, and discuss evidence and gaps in the current guidelines for the management of these patients.

METHODS AND RESULTS

This is a state-of-the-art review that focuses on clinical, diagnostic, and therapeutic aspects in mildly symptomatic HFrEF patients; summarizes the challenges; and proposes directions for future research in this group of patients. The New York Heart Association classification has been widely used as a measure of prognosis in HFrEF, but it lacks objectivity and reproducibility in terms of symptoms assessment. The definition of clinical stability as described in current guidelines is vague and may often lead to underdiagnosis of disease progression in patients who appear to be 'stable' but in fact are at an increased risk of clinical worsening, hospitalization, or death. Although an increasing number of clinical trials proved that the efficacy of HFrEF therapies was unrelated to the symptomatic status of patients and led to their implementation early in the course of the disease, clinical inertia in terms of under-prescription or underdosing of guideline-recommended medications in mildly symptomatic HFrEF patients is still a challenging issue to deal with.

CONCLUSIONS

Mildly symptomatic status in a patient with HFrEF is very frequent; it should not be ignored and should not be regarded as an index of disease stability. The application of risk scores designed to predict mortality and mode of death should be engaged among mildly symptomatic patients, not only to identify the most suitable HF candidates for cardioverter defibrillator implantation, but also to identify patients who might benefit from early intensification of medical treatment before the implementation of more interventional approaches.

Arrhythmic risk stratification by cardiac magnetic resonance tissue characterization: disclosing the arrhythmic substrate within the heart muscle

Sudden cardiac death (SCD) is a pivotal health problem worldwide. The identification of subjects at increased risk of SCD is crucial for the accurate selection of candidates for implantable cardioverter defibrillator (ICD) therapy. Current strategies for arrhythmic stratification largely rely on left ventricular (LV) ejection fraction (EF), mostly measured by echocardiography, and New York Heart Association functional status for heart failure with reduced EF. For specific diseases, such as hypertrophic and arrhythmogenic cardiomyopathy, some risk scores have been proposed; however, these scores take into account some parameters that are a partial reflection of the global arrhythmic risk and show a suboptimal accuracy. Thanks to a more comprehensive evaluation, cardiac magnetic resonance (CMR) provides insights into the heart muscle (the so-called tissue characterization) identifying cardiac fibrosis as an arrhythmic substrate. Combining sequences before and after administration of contrast media and mapping techniques, CMR is able to characterize the myocardial tissue composition, shedding light on both intracellular and extracellular alterations. Over time, late gadolinium enhancement (LGE) emerged as solid prognostic marker, strongly associated with major arrhythmic events regardless of LVEF, adding incremental value over current strategy in ischemic heart disease and non-ischemic cardiomyopathies. The evidence on a potential prognostic role of mapping imaging is promising. However, mapping techniques require further investigation and standardization. Disclosing the arrhythmic substrate within the myocardium, CMR should be considered as part of a multiparametric approach to personalized arrhythmic stratification.