Yield of family screening for dilated cardiomyopathy: 10-year experience at a multidisciplinary cardiogenetic outpatient clinic.

Introduction: Current family screening approaches in dilated cardiomyopathy (DCM) depend on the presence or absence of a familial genetic variant, in which variant pathogenicity (i.e. benign or pathogenic) classification drives screening recommendations.

Altered circadian rhythmicity of the QT interval predicts mortality in a large real-world academic hospital population.

Objective And Rationale: Small studies have shown that the QT interval follows a circadian rhythm. This finding has never been confirmed in a large real-world hospital population and the clinical meaning of disrupted rhythmicity remains unknown.

Methods: In this cohort study, all consecutive adult patients with at least one 12-lead ECG acquired between 1991 and 2021 were considered.

On the design and development of a handheld electrocardiogram device in a clinical setting.

Cardiovascular diseases (CVDs) are a global burden that requires attention. For the detection and diagnosis of CVDs, the 12-lead ECG is a key tool. With technological advancements, ECG devices are becoming smaller and available for home use.

The Dutch Idiopathic Ventricular Fibrillation Registry: progress report on the quest to identify the unidentifiable.

Background: Idiopathic ventricular fibrillation (iVF) is a rare cause of sudden cardiac arrest and, by definition, a diagnosis of exclusion. Due to the rarity of the disease, previous and current studies are limited by their retrospective design and small patient numbers. Even though the incidence of iVF has declined owing to the identification of new disease entities, an important subgroup of patients remains.

Detection of acute coronary occlusion with a novel mobile electrocardiogram device: a pilot study.

Aims: Many portable electrocardiogram (ECG) devices have been developed to monitor patients at home, but the majority of these devices are single lead and only intended for rhythm disorders. We developed the miniECG, a smartphone-sized portable device with four dry electrodes capable of recording a high-quality multi-lead ECG by placing the device on the chest. The aim of our study was to investigate the ability of the miniECG to detect occlusive myocardial infarction (OMI) in patients with chest pain.

Comparing adolescent- and adult-onset unexplained cardiac arrest: Results from the Dutch Idiopathic VF Registry.

Background: Current cohorts of patients with idiopathic ventricular fibrillation (IVF) primarily include adult-onset patients. Underlying causes of sudden cardiac arrest vary with age; therefore, underlying causes and disease course may differ for adolescent-onset vs adult-onset patients.

Objective: The purpose of this study was to compare adolescent-onset with adult-onset patients having an initially unexplained cause of VF.

Automatic triage of twelve-lead electrocardiograms using deep convolutional neural networks: a first implementation study.

Aims: Expert knowledge to correctly interpret electrocardiograms (ECGs) is not always readily available. An artificial intelligence (AI)-based triage algorithm (DELTAnet), able to support physicians in ECG prioritization, could help reduce current logistic burden of overreading ECGs and improve time to treatment for acute and life-threatening disorders. However, the effect of clinical implementation of such AI algorithms is rarely investigated.

Outcomes in Dutch DPP6 risk haplotype for familial idiopathic ventricular fibrillation: a focused update.

Background: The genetic risk haplotype DPP6 has been linked to familial idiopathic ventricular fibrillation (IVF), but the associated long-term outcomes are unknown.

Methods: DPP6 risk haplotype-positive family members (DPP6 cases) and their risk haplotype-negative relatives (DPP6 controls) were included. Clinical follow-up data were collected through March 2023.

Electrocardiogram Devices for Home Use: Technological and Clinical Scoping Review.

Background: Electrocardiograms (ECGs) are used by physicians to record, monitor, and diagnose the electrical activity of the heart. Recent technological advances have allowed ECG devices to move out of the clinic and into the home environment. There is a great variety of mobile ECG devices with the capabilities to be used in home environments.

The relationship between physicians' self-kindness and professional fulfillment and the mediating role of personal resilience and work-home interference: A cross-sectional study.

Background: Professional fulfillment is crucial for physicians' well-being and optimal patient care. Highly demanding work environments, perfectionism and self-critical attitudes jeopardize physicians' professional fulfillment.

Objective: To explore to what extent a kinder attitude towards the self, i.

STereotactic Arrhythmia Radioablation (STAR): the Standardized Treatment and Outcome Platform for Stereotactic Therapy Of Re-entrant tachycardia by a Multidisciplinary consortium (STOPSTORM.eu) and review of current patterns of STAR practice in Europe.

The EU Horizon 2020 Framework-funded Standardized Treatment and Outcome Platform for Stereotactic Therapy Of Re-entrant tachycardia by a Multidisciplinary (STOPSTORM) consortium has been established as a large research network for investigating STereotactic Arrhythmia Radioablation (STAR) for ventricular tachycardia (VT). The aim is to provide a pooled treatment database to evaluate patterns of practice and outcomes of STAR and finally to harmonize STAR within Europe. The consortium comprises 31 clinical and research institutions.

Importance of Systematic Diagnostic Testing in Idiopathic Ventricular Fibrillation: Results From the Dutch iVF Registry.

Background: Idiopathic ventricular fibrillation (iVF) is a diagnosis of exclusion. Systematic diagnostic testing is important to exclude alternative causes for VF. The early use of "high yield" testing, including cardiac magnetic resonance (CMR), exercise testing, and sodium channel blocker provocation, has been increasingly recognized.

Deep neural networks reveal novel sex-specific electrocardiographic features relevant for mortality risk.

Aims: Incorporation of sex in study design can lead to discoveries in medical research. Deep neural networks (DNNs) accurately predict sex based on the electrocardiogram (ECG) and we hypothesized that misclassification of sex is an important predictor for mortality. Therefore, we first developed and validated a DNN that classified sex based on the ECG and investigated the outcome.

Improving explainability of deep neural network-based electrocardiogram interpretation using variational auto-encoders.

Aims: Deep neural networks (DNNs) perform excellently in interpreting electrocardiograms (ECGs), both for conventional ECG interpretation and for novel applications such as detection of reduced ejection fraction (EF). Despite these promising developments, implementation is hampered by the lack of trustworthy techniques to explain the algorithms to clinicians. Especially, currently employed heatmap-based methods have shown to be inaccurate.

Work-Related Well-Being Among Dutch Cardiologists - A National Survey.

This is the first study to provide a holistic examination of cardiologists' well-being, investigating positive and negative dimensions, and its determinants. We conducted a national, multicenter, self-administered web-based questionnaire. We used frequencies to depict scores on three well-being indicators (professional fulfillment, work exhaustion and interpersonal disengagement) and performed three multiple regression analyses to elucidate their determinants.

Atrial fibrillation begets ventricular fibrillation when the AV node fails.

Deterioration of atrial fibrillation into ventricular fibrillation has frequently been described in patients with pre-excitation of the ventricles. We report two cases of atrial fibrillation without pre-excitation leading to rapid ventricular tachycardias and recurrent implantable cardioverter defibrillator therapy in young idiopathic ventricular fibrillation patients.

Electrocardiogram-based deep learning improves outcome prediction following cardiac resynchronization therapy.

Aims: This study aims to identify and visualize electrocardiogram (ECG) features using an explainable deep learning-based algorithm to predict cardiac resynchronization therapy (CRT) outcome. Its performance is compared with current guideline ECG criteria and QRSAREA.

Methods And Results: A deep learning algorithm, trained on 1.

State-of-the-Art Multimodality Imaging in Sudden Cardiac Arrest with Focus on Idiopathic Ventricular Fibrillation: A Review.

Idiopathic ventricular fibrillation is a rare cause of sudden cardiac arrest and a diagnosis by exclusion. Unraveling the mechanism of ventricular fibrillation is important for targeted management, and potentially for initiating family screening. Sudden cardiac arrest survivors undergo extensive clinical testing, with a growing role for multimodality imaging, before diagnosing "idiopathic" ventricular fibrillation.

Prevalence of Mitral Annulus Disjunction and Mitral Valve Prolapse in Patients With Idiopathic Ventricular Fibrillation.

Background Idiopathic ventricular fibrillation (IVF) is diagnosed in patients with ventricular fibrillation of which the origin is not identified after extensive evaluations. Recent studies suggest an association between mitral annulus disjunction (MAD), mitral valve prolapse (MVP), and ventricular arrhythmias. The prevalence of MAD and MVP in patients with IVF in this regard is not well established.

Life-threatening ventricular arrhythmia prediction in patients with dilated cardiomyopathy using explainable electrocardiogram-based deep neural networks.

Aims: While electrocardiogram (ECG) characteristics have been associated with life-threatening ventricular arrhythmias (LTVA) in dilated cardiomyopathy (DCM), they typically rely on human-derived parameters. Deep neural networks (DNNs) can discover complex ECG patterns, but the interpretation is hampered by their 'black-box' characteristics. We aimed to detect DCM patients at risk of LTVA using an inherently explainable DNN.