Risk Of Malignant Ventricular Arrhythmias Research Articles

Concealed cardiomyopathy as an emerging cause of sudden cardiac arrest and sudden cardiac death.

The inherited cardiomyopathies exhibit a broad spectrum of disease, with some patients remaining asymptomatic throughout life, while, for others, the first symptom of disease is sudden cardiac death at a young age. The risk of malignant ventricular arrhythmia in these conditions has traditionally been linked to the degree of structural myocardial abnormalities and functional impairment. However, recent advances in genetic testing and knowledge of the genetic basis of the diseases have led to the identification of concealed cardiomyopathy, in which sudden cardiac arrest or sudden cardiac death occurs in the absence of observable clinical features of cardiomyopathy, with a diagnosis being made only after the identification of a causative genetic variant. Increased awareness of concealed cardiomyopathy, a better understanding of mechanisms of arrhythmia and identification of risk modulators will be vital to improve care for families with concealed cardiomyopathy.

The Role of Nuclear Medicine in the Diagnostic Work-Up of Athletes: An Essential Guide for the Sports Cardiologist.

Athletes with heart disease are at increased risk of malignant ventricular arrhythmias and sudden cardiac death compared to their sedentary counterparts. When athletes have symptoms or abnormal findings at preparticipation screenings, a precise diagnosis by differentiating physiological features of the athlete's heart from pathological signs of cardiac disease is as important as it is challenging. While traditional imaging methods such as echocardiography, cardiac magnetic resonance, and computed tomography are commonly employed, nuclear medicine offers unique advantages, especially in scenarios requiring stress-based functional evaluation. This article reviews the use of nuclear medicine techniques in the diagnostic work-up of athletes with suspected cardiac diseases by highlighting their ability to investigate myocardial perfusion, metabolism, and innervation. The article discusses the application of single photon emission computed tomography (SPECT) and positron emission tomography (PET) using radiotracers such as [99mTc]MIBI, [99mTc]HDP, [18F]FDG, and [123I]MIBG. Several clinical scenarios are explored, including athletes with coronary atherosclerosis, congenital coronary anomalies, ventricular arrhythmias, and non-ischemic myocardial scars. Radiation concerns are addressed, highlighting that modern SPECT and PET equipment significantly reduces radiation doses, making these techniques safer for young athletes. We conclude that, despite being underutilized, nuclear medicine provides unique opportunities for accurate diagnosis and effective management of cardiac diseases in athletes.

Deep behavioural representation learning reveals risk profiles for malignant ventricular arrhythmias

We aimed to identify and characterise behavioural profiles in patients at high risk of SCD, by using deep representation learning of day-to-day behavioural recordings. We present a pipeline that employed unsupervised clustering on low-dimensional representations of behavioural time-series data learned by a convolutional residual variational neural network (ResNet-VAE). Data from the prospective, observational SafeHeart study conducted at two large tertiary university centers in the Netherlands and Denmark were used. Patients received an implantable cardioverter-defibrillator (ICD) between May 2021 and September 2022 and wore wearable devices using accelerometer technology during 180 consecutive days. A total of 272 patients (mean age of 63.1 ± 10.2 years, 81% male) were eligible with a total sampling of 37,478 days of behavioural data (138 ± 47 days per patient). Deep representation learning identified five distinct behavioural profiles: Cluster A (n = 46) had very low physical activity levels and a disturbed sleep pattern. Cluster B (n = 70) had high activity levels, mainly at light-to-moderate intensity. Cluster C (n = 63) exhibited a high-intensity activity profile. Cluster D (n = 51) showed above-average sleep efficiency. Cluster E (n = 42) had frequent waking episodes and poor sleep. Annual risks of malignant ventricular arrhythmias ranged from 30.4% in Cluster A to 9.8% and 9.5% for Clusters D-E, respectively. Compared to low-risk profiles (D-E), Cluster A demonstrated a three-to-four fold increased risk of malignant ventricular arrhythmias adjusted for clinical covariates (adjusted HR 3.63, 95% CI 1.54–8.53, p < 0.001). These behavioural profiles may guide more personalised approaches to ventricular arrhythmia and SCD prevention.

Missense and Non-Missense Lamin A/C Gene Mutations Are Similarly Associated with Major Arrhythmic Cardiac Events: A 20-Year Single-Centre Experience.

Arrhythmic risk stratification in patients with Lamin A/C gene (LMNA)-related cardiomyopathy influences clinical decisions. An implantable cardioverter defibrillator (ICD) should be considered in patients with an estimated 5-year risk of malignant ventricular arrhythmia (MVA) of ≥10%. The risk prediction score for MVA includes non-missense LMNA mutations, despite their role as an established risk factor for sudden cardiac death (SCD) has been questioned in several studies. The purpose of this study is to investigate cardiac features and find gene-phenotype correlations that would contribute to the evidence on the prognostic implications of non-missense vs. missense mutations in a cohort of LMNA mutant patients. An observational, prospective study was conducted in which 54 patients positive for a Lamin A/C mutation were enrolled, and 20 probands (37%) were included. The median age at first clinical manifestation was 41 (IQR 19) years. The median follow-up was 8 years (IQR 8). The type of LMNA gene mutation was distributed as follows: missense in 26 patients (48%), non-frameshift insertions in 16 (30%), frameshift deletions in 5 (9%), and nonsense in 7 (13%). Among the missense mutation carriers, two (8%) died and four (15%) were admitted onto the heart transplant list or underwent transplantation, with a major adverse cardiovascular event (MACE) rate of 35%. No statistically significant differences in MACE prevalence were identified according to the missense and non-missense mutation groups (p value = 0.847). Our data shift the spotlight on this considerable topic and could suggest that some missense mutations may deserve attention regarding SCD risk stratification in real-world clinical settings.

Construction and validation of nomogram model for predicting the risk of ventricular arrhythmia after emergency PCI in patients with acute myocardial infarction.

To make predictions about the risk of MVA (Malignant Ventricular Arrhythmia) after primary PCI (Percutaneous Coronary Intervention) in patients with AMI (Acute Myocardial Infarction) through constructing and validating the Nomogram model. 311 AMI patients who suffered from emergency PCI in Hefei Second People's Hospital from January 2020 to May 2023 were selected as the training set; 253 patients suffering from the same symptom in Hefei First People's Hospital during the same period were selected as the validation set. Risk factors were further screened by means of multivariate logistic and stepwise regression. The nomogram model was constructed, and then validated by using C-index, ROC curve, decision curve and calibration curve. Multivariate logistic analysis revealed that urea, systolic pressure, hypertension, Killip class II-IV, as well as LVEF (Left Ventricular Ejection Fraction) were all unrelated hazards for MVA after emergency PCI for AMI (P<0.05); a risk prediction nomogram model was constructed. The C-index was calculated to evaluate the predictive ability of the model. Result showed that the index of the training and the validation set was 0.783 (95% CI: 0.726-0.84) and 0.717 (95% CI: 0.65-0.784) respectively, which suggested that the model discriminated well. Meanwhile, other tools including ROC curve, calibration curve and decision curve also proved that this nomogram plays an effective role in forecasting the risk for MVA after PCI in AMI patients. The study successfully built the nomogram model and made predictions for the development of MVA after PCI in AMI patients.

Risk of malignant ventricular arrhythmias in patients with mildly to moderately reduced ejection fraction after permanent pacemaker implantation

BackgroundMany patients with mildly to moderately reduced left ventricular ejection fraction (LVEF) who require permanent pacemaker (PPM) implantation do not have a concurrent indication for implantable cardioverter-defibrillator (ICD) therapy. However, the risk of ventricular tachycardia/ventricular fibrillation (VT/VF) in this population is unknown. ObjectiveThe aim of this study was to describe the risk of VT/VF after PPM implantation in patients with mildly to moderately reduced LVEF. MethodsRetrospective analysis was performed of 243 patients with LVEF between 35% and 49% who underwent PPM placement and did not meet indications for an ICD. The primary end point was occurrence of sustained VT/VF. Competing risks regression was performed to calculate subhazard ratios for the primary end point. ResultsMedian follow-up was 27 months; 73% of patients were male, average age was 79 ± 10 years, average LVEF was 42% ± 4%, and 70% were New York Heart Association class II or above. Most PPMs were implanted for sick sinus syndrome (34%) or atrioventricular block (50%). Of 243 total patients, 11 (4.5%) met the primary end point of VT/VF. Multivessel coronary artery disease (CAD) was associated with significantly higher rates of VT/VF, with a subhazard ratio of 5.4 (95% CI, 1.5–20.1; P = .01). Of patients with multivessel CAD, 8 of 82 (9.8%) patients met the primary end point for an annualized risk of 4.3% per year. ConclusionPatients with mildly to moderately reduced LVEF and multivessel CAD undergoing PPM implantation are at increased risk for the development of malignant ventricular arrhythmias. Patients in this population may benefit from additional risk stratification for VT/VF and consideration for upfront ICD implantation.

Imagenetics for Precision Medicine in Dilated Cardiomyopathy.

Dilated cardiomyopathy (DCM) is a common heart muscle disorder of nonischemic etiology associated with heart failure development and the risk of malignant ventricular arrhythmias and sudden cardiac death. A tailored approach to risk stratification and prevention of sudden cardiac death is required in genetic DCM given its variable presentation and phenotypic severity. Currently, advances in cardiogenetics have shed light on disease mechanisms, the complex genetic architecture of DCM, polygenic contributors to disease susceptibility and the role of environmental triggers. Parallel advances in imaging have also enhanced disease recognition and the identification of the wide spectrum of phenotypes falling under the DCM umbrella. Genotype-phenotype associations have been also established for specific subtypes of DCM, such as DSP (desmoplakin) or FLNC (filamin-C) cardiomyopathy but overall, they remain elusive and not readily identifiable. Also, despite the accumulated knowledge on disease mechanisms, certain aspects remain still unclear, such as which patients with DCM are at risk for disease progression or remission after treatment. Imagenetics, that is, the combination of imaging and genetics, is expected to further advance research in the field and contribute to precision medicine in DCM management and treatment. In the present article, we review the existing literature in the field, summarize the established knowledge and emerging data on the value of genetics and imaging in establishing genotype-phenotype associations in DCM and in clinical decision making for DCM patients.

Arrhythmic Mitral Valve Prolapse and Sports Activity: Pathophysiology, Risk Stratification, and Sports Eligibility Assessment.

Although mitral valve prolapse (MVP) is the most prevalent valvular abnormality in Western countries and generally carries a good prognosis, a small subset of patients is exposed to a significant risk of malignant ventricular arrhythmias (VAs) and sudden cardiac death (SCD), the so-called arrhythmic MVP (AMVP) syndrome. Recent work has emphasized phenotypical risk features of severe AMVP and clarified its pathophysiology. However, the appropriate assessment and risk stratification of patients with suspected AMVP remains a clinical conundrum, with the possibility of both overestimating and underestimating the risk of malignant VAs, with the inappropriate use of advanced imaging and invasive electrophysiology study on one hand, and the catastrophic occurrence of SCD on the other. Furthermore, the sports eligibility assessment of athletes with AMVP remains ill defined, especially in the grey zone of intermediate arrhythmic risk. The definition, epidemiology, pathophysiology, risk stratification, and treatment of AMVP are covered in the present review. Considering recent guidelines and expert consensus statements, we propose a comprehensive pathway to facilitate appropriate counseling concerning the practice of competitive/leisure-time sports, envisioning shared decision making and the multidisciplinary "sports heart team" evaluation of borderline cases. Our final aim is to encourage an active lifestyle without compromising patients' safety.

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

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. 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. 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. 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. 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).

X-linked Emery-Dreifuss muscular dystrophy is associated with a high risk of malignant ventricular arrhythmia

Abstract Background Emery-Dreifuss muscular dystrophy (EDMD) is caused by variants in EMD (X-linked) and LMNA (autosomal dominant). LMNA variants are known to cause end-stage heart failure (ESHF) and malignant ventricular arrhythmia (MVA) [1], but the risk of cardiac complications in EMD variant-carriers is unknown. Purpose To determine the incidence of MVA and ESHF in EMD variant-carriers. Methods Consecutively referred individuals carrying EMD variants were recruited from 12 cardiomyopathy units in Europe and the USA. The incidence of MVA and ESHF in male and female EMD variant-carriers was determined. Male EMD variant-carriers with a cardiac phenotype at baseline (EMDcardiac) were compared to consecutively recruited male LMNA variant-carriers with a cardiac phenotype (LMNAcardiac). Results Longitudinal follow-up data were available for 38 male and 21 female EMD variant-carriers (mean (SD) ages 33.4 (13.3) and 43.3 (16.8) years, respectively; Table 1). Nine (23.6%) males developed MVA and five (13.2%) developed ESHF during a median follow-up time of 65.0 [24.3, 109.5] months. No female EMD variant-carrier had MVA or ESHF, but nine (42.8%) developed a mild cardiac phenotype at a median [IQR] age of 58.6 [53.2, 60.4] years. Incidence rates for MVA were similar for EMDcardiac and LMNAcardiac (4.8 versus 6.6 per hundred person-years, respectively; log-rank test p = 0.49; Figure 1). Incidence rates for ESHF were 2.4 per hundred person-years for EMDcardiac and 5.9 per hundred person-years for LMNAcardiac (log-rank test p = 0.09; Figure 1). Conclusions Male EMD variant-carriers have a high risk of progressive heart failure and ventricular arrhythmias similar to that of male LMNA variant-carriers. These data suggest that early ICD implantation and heart failure drug therapy should be considered in male EMD variant-carriers with cardiac disease.Table 1Figure 1

SCN5A mutation is associated with a higher Shanghai Score in patients with type 1 Brugada ECG pattern.

Brugada syndrome (BrS) is an inherited arrhythmic disease characterized by a coved ST-segment elevation in the right precordial electrocardiogram leads (type 1 ECG pattern) and is associated with a risk of malignant ventricular arrhythmias and sudden cardiac death. In order to assess the predictive value of the Shanghai Score System for the presence of a SCN5A mutation in clinical practice, we studied a cohort of 125 patients with spontaneous or fever/drug-induced BrS type 1 ECG pattern, variably associated with symptoms and a positive family history. The Shanghai Score System items were collected for each patient and PR and QRS complex intervals were measured. Patients were genotyped through a next-generation sequencing (NGS) custom panel for the presence of SCN5A mutations and the common SCN5A polymorphism (H558R). The total Shanghai Score was higher in SCN5A+ patients than in SCN5A- patients. The 81% of SCN5A+ patients and the 100% of patients with a SCN5A truncating variant exhibit a spontaneous type 1 ECG pattern. A significant increase in PR (P = 0.006) and QRS (P = 0.02) was detected in the SCN5A+ group. The presence of the common H558R polymorphism did not significantly correlate with any of the items of the Shanghai Score, nor with the total score of the system. Data from our study suggest the usefulness of Shanghai Score collection in clinical practice in order to maximize genetic test appropriateness. Our data further highlight SCN5A mutations as a cause of conduction impairment in BrS patients.

Emery-Dreifuss muscular dystrophy Type 1 is associated with a high risk of malignant ventricular arrhythmias and end-stage heart failure.

Emery-Dreifuss muscular dystrophy (EDMD) is caused by variants in EMD (EDMD1) and LMNA (EDMD2). Cardiac conduction defects and atrial arrhythmia are common to both, but LMNA variants also cause end-stage heart failure (ESHF) and malignant ventricular arrhythmia (MVA). This study aimed to better characterize the cardiac complications of EMD variants. Consecutively referred EMD variant-carriers were retrospectively recruited from 12 international cardiomyopathy units. MVA and ESHF incidences in male and female variant-carriers were determined. Male EMD variant-carriers with a cardiac phenotype at baseline (EMDCARDIAC) were compared with consecutively recruited male LMNA variant-carriers with a cardiac phenotype at baseline (LMNACARDIAC). Longitudinal follow-up data were available for 38 male and 21 female EMD variant-carriers [mean (SD) ages 33.4 (13.3) and 43.3 (16.8) years, respectively]. Nine (23.7%) males developed MVA and five (13.2%) developed ESHF during a median (inter-quartile range) follow-up of 65.0 (24.3-109.5) months. No female EMD variant-carrier had MVA or ESHF, but nine (42.8%) developed a cardiac phenotype at a median (inter-quartile range) age of 58.6 (53.2-60.4) years. Incidence rates for MVA were similar for EMDCARDIAC and LMNACARDIAC (4.8 and 6.6 per 100 person-years, respectively; log-rank P = .49). Incidence rates for ESHF were 2.4 and 5.9 per 100 person-years for EMDCARDIAC and LMNACARDIAC, respectively (log-rank P = .09). Male EMD variant-carriers have a risk of progressive heart failure and ventricular arrhythmias similar to that of male LMNA variant-carriers. Early implantable cardioverter defibrillator implantation and heart failure drug therapy should be considered in male EMD variant-carriers with cardiac disease.

Risks of Ventricular Arrhythmia and Heart Failure in Carriers of RBM20 Variants.

Variants in RBM20 are reported in 2% to 6% of familial cases of dilated cardiomyopathy and may be associated with fatal ventricular arrhythmia and rapid heart failure progression. We sought to determine the risk of adverse events in RBM20 variant carriers and the impact of sex on outcomes. Consecutive probands and relatives carrying RBM20 variants were retrospectively recruited from 12 cardiomyopathy units. The primary end point was a composite of malignant ventricular arrhythmia (MVA) and end-stage heart failure (ESHF). MVA and ESHF end points were also analyzed separately and men and women compared. Left ventricular ejection fraction (LVEF) contemporary to MVA was examined. RBM20 variant carriers with left ventricular systolic dysfunction (RBM20LVSD) were compared with variant-elusive patients with idiopathic left ventricular systolic dysfunction. Longitudinal follow-up data were available for 143 RBM20 variant carriers (71 men; median age, 35.5 years); 7 of 143 had an MVA event at baseline. Thirty of 136 without baseline MVA (22.0%) reached the primary end point, and 16 of 136 (11.8%) had new MVA with no significant difference between men and women (log-rank P=0.07 and P=0.98, respectively). Twenty of 143 (14.0%) developed ESHF (17 men and 3 women; log-rank P<0.001). Four of 10 variant carriers with available LVEF contemporary to MVA had an LVEF >35%. At 5 years, 15 of 67 (22.4%) RBM20LVSD versus 7 of 197 (3.6%) patients with idiopathic left ventricular systolic dysfunction had reached the primary end point (log-rank P<0.001). RBM20 variant carriage conferred a 6.0-fold increase in risk of the primary end point. RBM20 variants are associated with a high risk of MVA and ESHF compared with idiopathic left ventricular systolic dysfunction. The risk of MVA in male and female RBM20 variant carriers is similar, but male sex is strongly associated with ESHF.

Development and Validation of Nomogram for the Prediction of Malignant Ventricular Arrhythmia Including Circulating Inflammatory Cells in Patients with Acute ST-Segment Elevation Myocardial Infarction.

Malignant ventricular arrhythmia (MVA) can seriously affect the hemodynamic changes of the body. In this study, we developed and validated a nomogram to predict the in-hospital MVA risk in patients with STEMI after emergency PCI. The multivariable logistic regression analysis included variables with a P<0.05 in the univariate logistic regression analysis and investigated the independent predictors affecting in-hospital MVA after PCI in patients with STEMI in the training cohort. The construction of a nomogram model used independent predictors to predict the risk of in-hospital MVA, and C-index, Hosmer-Lemeshow (HL) test, calibration curves, decision curve analysis (DCA), and receiver operating characteristic (ROC) were used to validate the nomogram. Killip class [OR=5.034 (95% CI: 1.596-15.809), P=0.005], CK-MB [OR=1.002 (95% CI: 1.001-1.004), P=0.022], serum potassium [OR=0.618 (95% CI: 0.406-0.918), P=0.020], NLR [OR=1.073 (95% CI: 1.034-1.115), P<0.001], and monocyte [OR=1.974 (95% CI: 1.376-2.925), P<0.001] were the independent predictors of in-hospital MVA after PCI in patients with STEMI. A nomogram including the 5 independent predictors was developed to predict the risk of in-hospital MVA. The C-index, equivalent to the area under the ROC curve (AUC), was 0.803 (95% confidence interval [CI]: 0.738-0.868) in the training cohort, and 0.801 (95% CI:0.692-0.911) in the validation cohort, showing that the nomogram had a good discrimination. The HL test (χ2=8.439, P=0.392 in the training cohort; χ2=9.730, P=0.285 in the validation cohort) revealed a good calibration. The DCA suggested an obvious clinical net benefit. Killip class, CK-MB, serum potassium, NLR, and monocyte were independent factors for in-hospital MVA after PCI in patients with STEMI. The nomogram model constructed based on the above factors to predict the risk of in-hospital MVA had satisfactory discrimination, calibration, and clinical effectiveness, and was an excellent tool for early prediction of the risk of in-hospital MVA after PCI in patients with STEMI.

Evaluation of frontal QRS-T angle values in electrocardiography in patients with chronic rhinosinusitis

BackgroundChronic Rhinosinusitis (CRS) refers to inflammation of the paranasal sinuses and nasal mucosa. Electrocardiographic indicators of ventricular repolarization have been shown to correlate with systemic inflammation parameters. Recently, the frontal QRS-T (fQRS-T) angle has been accepted as a new indicator of ventricular depolarization and repolarization heterogeneity. The (fQRS-T) angle is recommended in predicting the risk of malignant ventricular arrhythmia. In this study, we aimed to evaluate the ventricular arrhythmia potential in patients with chronic rhinosinusitis by examining the relationship between fQRS-T angle on ECG and inflammation markers.MethodsInflammatory markers as well as electrocardiographc (ECG) f(QRS-T) angle, QRS duration, QT interval and corrected QT interval were examined in 54 patients with CRS versus 56 healthy control subjects.ResultsThe f(QRS-T) angle was significantly higher in CRS patients than in healthy controls (p < .001). The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and monocyte-to-lymphocyte ratio (MLR) were significantly higher in CRS patients compared to healthy controls (p < .001, for all). Based on correlation analysis, NLR and f(QRS-T) angles were highly correlated (r = .845, p < .001), and according to the results of linear regression analysis, NLR was independently associated with the f(QRS-T) angle (t = 5.149, Beta = 0.595, p = < 0.001).ConclusionBoth f(QRS-T) angle and NLR are significantly increased in CRS patients compared to healthy controls, with increases in NLR also independently associating with increases in f(QRS-T) angle. While the increases in f(QRS-T) angle did not result in clinically alarming absolute values for f(QRS-T), CRS patients might nonetheless be at relatively higher risk for malignant cardiac arrhythmias.

Right Ventricular Free Wall Strain and Effect of Defibrillator Implantation in Patients With Nonischemic Systolic Heart Failure

BackgroundPatients with nonischemic systolic heart failure have an increased risk of malignant ventricular arrhythmias and sudden cardiovascular death. Because the risk is less pronounced than for patients with ischemic cause of heart failure more discriminating tools are needed to identify patients most likely to benefit from implantable cardioverter-defibrillator (ICD) implantation. Right ventricular (RV) dysfunction is associated with a worse prognosis, but whether RV free wall strain (RV-FWS) measured with echocardiography can identify the patients most likely to benefit from ICD implantation is not known. Methods and ResultsIn this extended follow-up analysis of the Danish Study to Assess the Efficacy of ICDs in Patients with Non-ischemic Systolic Heart Failure on Mortality (DANISH) trial, RV-FWS was measured with echocardiography in 445 patients before randomization. RV dysfunction was defined as an RV-FWS of greater than –20%. The primary end point was all-cause mortality. The median RV-FWS was –18% (quartiles –23% to –14%), and RV dysfunction was measured in 255 patients (57%). During a median follow-up of 5.7 years, 170 patients (38%) died. There was a statistically significant interaction between RV dysfunction and the effect of ICD implantation (P = .003), also after adjusting for known cardiovascular risk factors (P = .01). ICD implantation significantly decreased all-cause mortality in patients with RV dysfunction (hazard ratio 0.54, 95% confidence interval 0.36-0.80, P = .002), but not in patients with normal RV function (hazard ratio 1.34, 95% confidence interval 0.84-2.12, P = .22). ConclusionsIn patients with nonischemic systolic heart failure, RV dysfunction on echocardiography was associated with a greater effect of ICD implantation and could be used to select patients with benefit from ICD treatment.

The effect of coronary slow flow on ventricular repolarization parameters

IntroductionIschemia due to microvascular dysfunction may be responsible for the heterogeneity of ventricular repolarization in coronary slow flow. To our knowledge, there is no study in which QT interval, Tp-Te interval, index of cardiac-electrophysiological balance (iCEB), and frontal QRS-T angle were evaluated together in patients with CSF. In this study, we examined for the first time the relationship between all these myocardial repolarization parameters and CSF. Materials and methodsThe study group included 178 patients (99 female, mean age: 50.6 ± 8.6 years) with isolated CSF without stenotic lesions and with angiographically proven normal coronary arteries. The control group included 120 patients (71 female, mean age: 49.3 ± 9.4 years) with normal coronary angiography. QRS duration, QT interval, QTc interval, Tp-Te interval, Tp-Te/QT, Tp- Te/QTc, iCEB score, and frontal QRS-T angle were calculated from 12‑lead ECGs. ResultsThere was no significant difference in demographic parameters between the two groups. Compared with the control group, patients with CSF had significantly longer QTmax duration, QT dispersion, Tp-Te interval, and higher iCEB score, wider frontal QRS-T angle. ConclusionIn our study, we found that many of the ventricular repolarization parameters were adversely affected in patients with CSF. Impaired parameters may be associated with the risk of malignant ventricular arrhythmias.

Right ventricular cardiac resynchronization therapy in patients with right ventricular conduction delay and heart failure

Right ventricular cardiac resynchronization therapy in patients with right ventricular conduction delay and heart failure

Electrophysiological study in chagasics with syncope and conduction disorder.

Investigation of syncope involves the use of electrophysiological study, particularly in patients with cardiac conduction disorder. There is conflicting evidence about the role of electrophysiological study in patients with Chagas disease. The objective of this study was to evaluate the electrophysiological study findings in patients with Chagas disease and bundle branch block and/or divisional block presenting with syncope. This is a retrospective study of patients with Chagas disease and cardiac conduction disorder who underwent electrophysiological study from 2017 to 2021 for the investigation of syncope in a tertiary hospital in São Paulo, Brazil. Those with non-interpretable ECG, known coronary artery disease, and/or other cardiomyopathies were excluded. HV interval and electrophysiological study-induced malignant ventricular arrhythmias data were analyzed. A total of 45 patients (60.2±11.29 years, 57.8% males) were included. The mean HV interval was 58.37 ms±10.68; 22.2% of the studied population presented an HV interval of ≥70 ms; and malignant ventricular arrhythmias were induced in 57.8% patients. The use of beta-blockers and amiodarone (p=0.002 and 0.036, respectively), NYHA functional class≥II (p=0.013), wide QRS (p=0.047), increased HV interval (p=0.02), Rassi score >6.5 (p=0.003), and reduced left ventricular ejection fraction (p=0.031) were associated with increased risk of inducible malignant ventricular arrhythmias. More than half of the patients with Chagas disease, syncope, and cardiac conduction disorder have inducible malignant ventricular arrhythmias. Prolonged HV interval was observed in only 20% of population. Wide QRS, prolonged HV, reduced ejection fraction, and higher Rassi score were associated with increased risk of malignant ventricular arrhythmias.

Abstract 12434: ECG-Only Deep Learning Algorithm Predicts Risk of Arrhythmia in Phospholamban Cardiomyopathy

Introduction Phospholamban (PLN) p.Arg14del mutation carriers are at risk of developing arrhythmogenic cardiomyopathy, but phenotypic penetrance is incomplete and much interpatient variability exists in the risk of malignant ventricular arrhythmias (MVA). Accurate risk stratification allows for timely device implantation which may prevent sudden cardiac death (SCD). The current prediction model is multimodal and uses data from ECG, echocardiography, MRI and 24-hour Holter monitoring. Hypothesis We hypothesized that a deep learning-based approach may allow for accurate risk prediction using only 12-lead ECG data. Methods A total of 679 PLN p.Arg14del mutation carriers without MVA at baseline were identified. MVA was defined as sustained VA, appropriate ICD intervention or (aborted) SCD. Prediction models were developed using Cox regression and validated using a bootstrap-based optimism corrected area under the receiver operating curve (AUC). A deep learning-based variational auto-encoder, trained on 1.1 million ECGs, was used to convert the median beat baseline ECG into its FactorECG. The FactorECG is a compressed version of the ECG which summarizes it into 21 explainable factors. Seven ECG factors that were previously shown to be associated with reduced ejection fraction were included in the model. A comparison to conventional ECG parameters and the current prediction model was performed. Results The deep learning-based ECG-only approach was able to predict MVA in PLN mutation carriers with an AUC of 0.82 [95% CI 0.78 - 0.86], comparable to the current multimodal prediction model (AUC 0.84 [95% CI 0.80 - 0.88]) and outperforming a model based on conventional ECG parameters (low voltage ECG and negative T waves; AUC 0.66 [95% CI 0.59 - 0.73]). Conclusions In conclusion, our deep learning-based algorithm uses only ECG data to accurately predict the occurrence of MVA in PLN mutation carriers, which could allow for easier stratification of patients at risk.