Improving the appropriateness of sudden arrhythmic death primary prevention by implantable cardioverter-defibrillator therapy in patients with low left ventricular ejection fraction. Point of view

The role of cardiac magnetic resonance imaging in defining the prognosis of patients with acute <i>ST</i>-segment elevation myocardial infarction. Part 2. Assessment of the disease prognosis

Currently the incidence of congestive heart failure after ST-segment elevation myocardial infarction (STEMI) tends to increase. Reperfusion therapy is still the only effective method to reduce an infarct size. Therefore, there is a high unmet need of novel cardioprotective treatments that would improve outcomes in such patients. Recent advances in cardiovascular magnetic resonance (CMR) methods enabled the identification of certain new infarct characteristics associated with the development of heart failure and sudden cardiac death. These characteristics can help identify new groups of high risk patients and used as a targets for novel cardioprotective treatments. This part of the review summarizes novel CMR-based characteristics of myocardial infarction and their role in the prognostic stratification of STEMI patients.

Selvester score predicts implantable cardioverter defibrillator shocks in patients with non-ischemic cardiomyopathy

BACKGROUND

The implantable cardiac defibrillator is the cornerstone of prevention of sudden cardiac death in non-ischemic cardiomyopathy. The Selvester score, which is frequently investigated in ischemic cardiomyopathy, has not been investigated in the field of non-ischemic cardiomyopathy.

AIM

The aim of this study was to evaluate the Selvester score for determining appropriate implantable cardiac defibrillator shocks in non-ischemic cardiomyopathy patients.

MATERIALS AND METHODS

In all, 131 non-ischemic cardiomyopathy patients were included in the study. A simplified Selvester score was calculated from ECG data. Patients were divided into two groups according to whether they received ICD shock.

RESULTS

Of the patients, 28.2% received appropriate implantable cardiac defibrillator shock. The Selvester score was significantly higher in patients receiving appropriate shock when compared to patients with no implantable cardiac defibrillator shocks (8.8 ± 4.6 vs 7.2 ± 3.3, P = .040). The median QRS duration was significantly longer in patients receiving appropriate shock than in patients with no shocks (130.14 ± 35.08 ms vs 120.12 ± 20.57 ms, P = .045). We determined that the cutoff value for the Selvester score to predict ICD shocks was 6.5 with a sensitivity of 72.0% and a specificity of 83% (AUC = 0.717; %95 GA: 0.627-0.807, P < .001).

CONCLUSION

Selvester score was higher in patients receiving appropriate shock than in patients who did not receive any implantable cardiac defibrillator shock. From this study, the Selvester score is associated with the risk of ventricular tachycardia/ventricular fibrillation in non-ischemic cardiomyopathy so that careful attention is necessary to manage the patients with high Selvester score.

Diagnosis and Risk Prediction of Dilated Cardiomyopathy in the Era of Big Data and Genomics

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and life-threatening ventricular arrhythmias (LTVA). Work-up and risk stratification of DCM is clinically challenging, as there is great heterogeneity in phenotype and genotype. Throughout the last decade, improved genetic testing of patients has identified genotype-phenotype associations and enhanced evaluation of at-risk relatives leading to better patient prognosis. The field is now ripe to explore opportunities to improve personalised risk assessments. Multivariable risk models presented as "risk calculators" can incorporate a multitude of clinical variables and predict outcome (such as heart failure hospitalisations or LTVA). In addition, genetic risk scores derived from genome/exome-wide association studies can estimate an individual's lifetime genetic risk of developing DCM. The use of clinically granular investigations, such as late gadolinium enhancement on cardiac magnetic resonance imaging, is warranted in order to increase predictive performance. To this end, constructing big data infrastructures improves accessibility of data by using electronic health records, existing research databases, and disease registries. By applying methods such as machine and deep learning, we can model complex interactions, identify new phenotype clusters, and perform prognostic modelling. This review aims to provide an overview of the evolution of DCM definitions as well as its clinical work-up and considerations in the era of genomics. In addition, we present exciting examples in the field of big data infrastructures, personalised prognostic assessment, and artificial intelligence.

Current challenges in sudden cardiac death prevention

Ischemic heart disease and non-ischemic dilated cardiomyopathy are the most common causes of arrhythmic sudden cardiac death (SCD). Implantable cardioverter defibrillator (ICD) therapy is the only strategy that proved to be effective in preventing SCD in high-risk individuals while the role of antiarrhythmic drugs is limited to symptoms relief. Current guidelines recommend selecting candidates to ICD implantation based on etiology, symptoms of heart failure (NYHA class), and severely depressed left ventricular ejection fraction, but these parameters are neither sensitive nor specific. The review addresses the mechanisms of SCD in patients with heart failure of either ischemic or non-ischemic etiology, risk stratification, and strategies for prevention of SCD in the clinical practice (including optimization of heart failure therapy, avoidance of triggering factors, antiarrhythmic drugs, ICD therapy, early resuscitation, and public access defibrillators).

The prevalence of left ventricular thrombus among patients with low ejection fraction by trans-thoracic echocardiography

Background and objectives:

Ejection fraction (EF) is a measurement of heart function that reflects the portion of pumped out blood from the filled left ventricle per each heartbeat. The current study aimed to investigate the prevalence of left ventricular thrombus in patients with EF lower than 35% by using Transthoracic Echocardiography (TTE).

Methods:

In this prospective study, 82 cardiac patients underwent TTE procedure in order to assess the presence of left ventricular thrombus (LVT) from January 1^st to December 31st 2017 at the Military Cardiac Centre in Sana’a, Yemen.

Results:

Out of 82 patients enrolled in this study, the mean age was 49.13 ± 14.8 years and 87.8% were male. The mean of EF was 31.16% and LVT was found in 6.1%. The spontaneous contrast was seen in 25.6% of patients indicating strong relationship with low EF (p < 0.001). Among patients with low EF, ischemic heart disease (IHD) was identified in 50%, hypertension in 30.5%, diabetes mellitus (DM) type 2 in 23.2%, and hyperlipidemia 12.2%. Exactly 80% of LVT were detected in IHD patients with dilated cardiomyopathy (DCMP) and 80% of detected LVT were apical in site.

Conclusion:

Cardiac patients with low ejection fraction developed left ventricular thrombosis, and most of the affected patients were ischemic heart disease with dilated cardiomyopathy. Interestingly, spontaneous contrast was found high significantly in these patients, which may reflect the continuous process of thrombus formation.

The Role of Contrast-Enhanced Cardiac Magnetic Resonance in the Assessment of Patients with Malignant Ventricular Arrhythmias

Cardiac magnetic resonance (CMR) imaging has gained significant traction as an imaging modality of choice in the evaluation of individuals with, or at risk for, heart failure. Ventricular arrhythmias, often malignant, may be sequelae of heart failure and arise from fibrosis. Late gadolinium enhancement evaluation by CMR has become a preferred modality to assess individuals at risk for malignant ventricular arrhythmias. A spectrum of various pathologies that predispose individuals to malignant ventricular arrhythmias, as well as the usefulness of CMR in their identification and prognostication, are reviewed.

Ventricular tachycardia-inducibility predicts arrhythmic events in post-myocardial infarction patients with low ejection fraction. A systematic review and meta-analysis

Background

Inducibility of ventricular arrhythmias at electrophysiological study (EPS) has long been suggested as predictive for subsequent arrhythmic events. Nevertheless, the usefulness of EPS in the clinical practice is still unclear. We performed a systematic review and meta-analysis to assess the predictive power of EPS in primary prevention of ventricular arrhythmias in post-myocardial infarction (MI) patients with left ventricular dysfunction.

Methods

MEDLINE and the Cochrane Library databases were systematically searched to identify studies, which analyzed EPS predictive value in post-MI patients with mean EF < 40% for the composite arrhythmic endpoint defined by: sudden cardiac death (SCD), aborted SCD, ventricular tachycardia (VT), ventricular fibrillation (VF), appropriate implantable cardioverter-defibrillator (ICD) interventions.

Results

Nine studies, evaluating 3959 patients with 647 arrhythmic events, were included in the meta-analyses. EPS showed a strong predictive power for the arrhythmic endpoint with a pooled odds ratio (OR) of 4.00 (95% confidence interval [CI]: 2.30–6.96) in the whole set of studies, albeit a high level of heterogeneity among studies. EPS predictive power was higher in studies where VT-inducibility was tested (OR 6.52; 95% CI: 2.30–18.44; sensitivity 0.65, specificity 0.78, and negative predictive value 0.94), versus those assessing VT/VF-inducibility (OR 2.09; 95% CI: 1.34–3.26). VT-inducibility was predictive even when assessed within one month after MI (OR 7.85; 95% CI: 3.67–16.80).

Conclusions

Inducibility of ventricular arrhythmias at EPS is a strong predictor of the arrhythmic endpoint in post-MI patients with impaired EF, particularly when VT-inducibility is tested. EPS could help selecting the patients who can mostly benefit from ICD therapy.

Cardiac magnetic resonance imaging: Which information is useful for the arrhythmologist?

Cardiac magnetic resonance (CMR) is a non-invasive, non-ionizing, diagnostic technique that uses magnetic fields, radio waves and field gradients to generate images with high spatial and temporal resolution. After administration of contrast media (e.g., gadolinium chelate), it is also possible to acquire late images, which make possible the identification and quantification of myocardial areas with scar/fibrosis (late gadolinium enhancement, LGE). CMR is currently a useful instrument in clinical cardiovascular practice for the assessment of several pathological conditions, including ischemic and non-ischemic cardiomyopathies and congenital heart disease. In recent years, its field of application has also extended to arrhythmology, both in diagnostic and prognostic evaluation of arrhythmic risk and in therapeutic decision-making. In this review, we discuss the possible useful applications of CMR for the arrhythmologist. It is possible to identify three main fields of application of CMR in this context: (1) arrhythmic and sudden cardiac death risk stratification in different heart diseases; (2) decision-making in cardiac resynchronization therapy device implantation, presence and extent of myocardial fibrosis for left ventricular lead placement and cardiac venous anatomy; and (3) substrate identification for guiding ablation of complex arrhythmias (atrial fibrillation and ventricular tachycardias).

Myocardial fibrosis predicts ventricular tachyarrhythmias

Myocardial fibrosis is a common pattern in the setting of different heart diseases, and promotes ventricular tachyarrhythmias by creating a vulnerable substrate for reentrant activity and by favoring the emergence of triggers. Currently, late gadolinium enhancement (LGE) cardiac magnetic resonance is considered the reference method for the noninvasive assessment of ventricular fibrosis. Several studies and meta-analyses have shown that ventricular fibrosis detected by LGE is a powerful predictor of ventricular tachyarrhythmic events in ischemic, non-ischemic dilated cardiomyopathy and hypertrophic cardiomyopathy patients. Both the presence and extension of ventricular fibrosis were shown to correlate with the occurrence of ventricular arrhythmias and sudden cardiac death, irrespective of the grade of left ventricular dysfunction. Based on these results, the assessment of ventricular fibrosis has been suggested as a candidate marker to improve the decision making for implantable cardioverter-defibrillator therapy in patients with left ventricular dysfunction. These points will be discussed in the review.

Heart Rate Turbulence Is a Powerful Predictor of Cardiac Death and Ventricular Arrhythmias in Postmyocardial Infarction and Heart Failure Patients: A Systematic Review and Meta-Analysis

BACKGROUND

Heart rate turbulence (HRT) has been proposed as a candidate marker of altered autonomic tone, and some studies showed its prognostic value for both cardiac death (CD) and sudden death. Nevertheless, HRT is not currently used in the clinical practice.

METHODS AND RESULTS

We performed a systematic review and meta-analysis of the predictive value of HRT for the end points of total mortality, CD, and fatal and nonfatal ventricular arrhythmias in postacute myocardial infarction and heart failure patients. MEDLINE and The Cochrane Library databases were systematically searched to identify studies, which analyzed the predictive value of abnormal HRT for the defined end points. Twenty studies (25 cohorts: 12 832 patients) were identified by the systematic review, and 15 studies (20 cohorts: 11 499 patients) were included in the meta-analyses. Abnormal HRT was a predictive marker for all the end points in heart failure patients and more markedly in postacute myocardial infarction patients, where 9 out of the 10 cohorts had an ejection fraction >30%. In postacute myocardial infarction patients, HRT had pooled risk ratios of 3.53 (95% confidence interval [CI], 2.54-4.90), 4.82 (95% CI, 3.12-7.45), and 4.48 (95% CI, 3.04-6.60), and positive likelihood ratios of 3.5 (95% CI, 2.6-4.8), 4.1 (95% CI, 3.0-5.7), and 2.7 (95% CI, 2.2-3.3) for total mortality, CD, and arrhythmic events, respectively. The combination of abnormal HRT and T-wave alternans (5 cohorts: 1516 patients) increased the predictive power for CD and arrhythmic events.

CONCLUSIONS

HRT is a powerful predictor of both CD and arrhythmic events, particularly in postacute myocardial infarction patients with ejection fraction >30%. HRT power increases in combination with T-wave alternans analysis.

Soluble ST2 and Risk of Arrhythmias, Heart Failure, or Death in Patients with Mildly Symptomatic Heart Failure: Results from MADIT-CRT

Soluble ST2 is an established biomarker of heart failure (HF) progression. Data about its prognostic implications in patients with mildly symptomatic HF eligible to receive cardiac resynchronization therapy defibrillators (CRT-D) are limited. In a cohort of 684 patients enrolled in Multicenter Automated Defibrillator Implantation Trial (MADIT)-CRT, levels of soluble ST2 (sST2) were serially assessed at baseline and 1 year (n = 410). In multivariable-adjusted models, elevated baseline sST2 was associated with an increased risk of death, death or HF, and death or ventricular arrhythmia (VA) even when adjusting for baseline brain natriuretic protein (BNP) levels. In addition, patients with lower baseline sST2 levels had greater risk reduction with CRT-D (p = 0.006). Serial assessment revealed increased risk of VA and death or VA (HR per 10 % increase in sST2 1.11 (1.04-1.20), p = 0.004). Among patients with mildly symptomatic HF and eligibility for CRT-D, baseline and serial assessments sST2 may provide important information for risk stratification.

Surface Electrocardiogram Predictors of Sudden Cardiac Arrest

BACKGROUND

Heart disease is a major cause of death in industrialized nations, with approximately 50% of these deaths attributable to sudden cardiac arrest. If patients at high risk for sudden cardiac arrest can be identified, their odds of surviving fatal arrhythmias can be significantly improved through prophylactic implantable cardioverter defibrillator placement. This review summarizes the current knowledge pertaining to surface electrocardiogram (ECG) predictors of sudden cardiac arrest.

METHODS

We conducted a literature review focused on methods of predicting sudden cardiac arrest through noninvasive electrocardiographic testing.

RESULTS

Several electrocardiographic-based methods of risk stratification of sudden cardiac arrest have been studied, including QT prolongation, QRS duration, fragmented QRS complexes, early repolarization, Holter monitoring, heart rate variability, heart rate turbulence, signal-averaged ECG, T wave alternans, and T-peak to T-end. These ECG findings have shown variable effectiveness as screening tools.

CONCLUSION

At this time, no individual ECG finding has been found to be able to adequately stratify patients with regard to risk for sudden cardiac arrest. However, one or more of these candidate surface ECG parameters may become useful components of future multifactorial risk stratification calculators.