BACKGROUND The correct interpretation of the ECG is pivotal for the accurate diagnosis of many cardiac abnormalities, and conventional computerized interpretation has not been able to reach physician‐level accuracy in detecting (acute) cardiac abnormalities. This study aims to develop and validate a deep neural network for comprehensive automated ECG triage in daily practice. METHODS AND RESULTS We developed a 37‐layer convolutional residual deep neural network on a data set of free‐text physician‐annotated 12‐lead ECG s. The deep neural network was trained on a data set with 336.835 recordings from 142.040 patients and validated on an independent validation data set (n=984), annotated by a panel of 5 cardiologists electrophysiologists. The 12‐lead ECG s were acquired in all noncardiology departments of the University Medical Center Utrecht. The algorithm learned to classify these ECG s into the following 4 triage categories: normal, abnormal not acute, subacute, and acute. Discriminative performance is presented with overall and category‐specific concordance statistics, polytomous discrimination indexes, sensitivities, specificities, and positive and negative predictive values. The patients in the validation data set had a mean age of 60.4 years and 54.3% were men. The deep neural network showed excellent overall discrimination with an overall concordance statistic of 0.93 (95% CI , 0.92–0.95) and a polytomous discriminatory index of 0.83 (95% CI , 0.79–0.87). CONCLUSIONS This study demonstrates that an end‐to‐end deep neural network can be accurately trained on unstructured free‐text physician annotations and used to consistently triage 12‐lead ECG s. When further fine‐tuned with other clinical outcomes and externally validated in clinical practice, the demonstrated deep learning–based ECG interpretation can potentially improve time to treatment and decrease healthcare burden.

Aims Idiopathic ventricular fibrillation (IVF) is a rare cause of sudden cardiac arrest. Implantable cardioverter-defibrillator (ICD) implantation is currently the only treatment option. Limited data are available on the prevalence and complications of ICD therapy in these patients. We sought to investigate ICD therapy and its complications in patients with IVF. Methods and results Patients were selected from a national registry of IVF patients. Patients in whom no underlying diagnosis was found during follow-up were eligible for inclusion. Recurrence of ventricular arrhythmia (VA) was derived from medical and ICD records, electrogram records of ICD therapies were used to differentiate between appropriate or inappropriate interventions. Independent predictors for appropriate ICD shock were calculated using cox regression. In 217 IVF patients, recurrence of sustained VAs occurred in 66 patients (30%) during a median follow-up period of 6.1 years. Ten patients died (4.6%). Thirty-eight patients (17.5%) experienced inappropriate ICD therapy, and 32 patients (14.7%) had device-related complications. Symptoms before cardiac arrest [hazard ratio (HR): 2.51, 95% confidence interval (CI): 1.48–4.24], signs of conduction disease (HR: 2.27, 95% CI: 1.15–4.47), and carrier of the DPP6 risk haplotype (HR: 3.24, 1.70–6.17) were identified as independent predictors of appropriate shock occurrence. Conclusion Implantable cardioverter-defibrillator therapy is an effective treatment in IVF, treating recurrences of potentially lethal VAs in approximately one-third of patients during long-term follow-up. However, device-related complications and inappropriate shocks were also frequent. We found significant predictors for appropriate ICD therapy. This may imply that these patients require additional management to prevent recurrent events.

Inverse electrocardiography (iECG) estimates epi- and endocardial electrical activity from body surface potentials maps (BSPM). In individuals at risk for cardiomyopathy, non-invasive estimation of normal ventricular activation may provide valuable information to aid risk stratification to prevent sudden cardiac death. However, multiple simultaneous activation wavefronts initiated by the His-Purkinje system, severely complicate iECG. To improve the estimation of normal ventricular activation, the iECG method should accurately mimic the effect of the His-Purkinje system, which is not taken into account in the previously published multi-focal iECG. Therefore, we introduce the novel multi-wave iECG method and report on its performance. Multi-wave iECG and multi-focal iECG were tested in four patients undergoing invasive electro-anatomical mapping during normal ventricular activation. In each subject, 67-electrode BSPM were recorded and used as input for both iECG methods. The iECG and invasive local activation timing (LAT) maps were compared. Median epicardial inter-map correlation coefficient (CC) between invasive LAT maps and estimated multi-wave iECG versus multi-focal iECG was 0.61 versus 0.31. Endocardial inter-map CC was 0.54 respectively 0.22. Modeling the His-Purkinje system resulted in a physiologically realistic and robust non-invasive estimation of normal ventricular activation, which might enable the early detection of cardiac disease during normal sinus rhythm.

This study presents a novel non-invasive equivalent dipole layer (EDL) based inverse electrocardiography (iECG) technique which estimates both endocardial and epicardial ventricular activation sequences. We aimed to quantitatively compare our iECG approach with invasive electro-anatomical mapping (EAM) during sinus rhythm with the objective of enabling functional substrate imaging and sudden cardiac death risk stratification in patients with cardiomyopathy. Thirteen patients (77% males, 48 ± 20 years old) referred for endocardial and epicardial EAM underwent 67-electrode body surface potential mapping and CT imaging. The EDL-based iECG approach was improved by mimicking the effects of the His-Purkinje system on ventricular activation. EAM local activation timing (LAT) maps were compared with iECG-LAT maps using absolute differences and Pearson’s correlation coefficient, reported as mean ± standard deviation [95% confidence interval]. The correlation coefficient between iECG-LAT maps and EAM was 0.54 ± 0.19 [0.49–0.59] for epicardial activation, 0.50 ± 0.27 [0.41–0.58] for right ventricular endocardial activation and 0.44 ± 0.29 [0.32–0.56] for left ventricular endocardial activation. The absolute difference in timing between iECG maps and EAM was 17.4 ± 7.2 ms for epicardial maps, 19.5 ± 7.7 ms for right ventricular endocardial maps, 27.9 ± 8.7 ms for left ventricular endocardial maps. The absolute distance between right ventricular endocardial breakthrough sites was 30 ± 16 mm and 31 ± 17 mm for the left ventricle. The absolute distance for latest epicardial activation was median 12.8 [IQR: 2.9–29.3] mm. This first in-human quantitative comparison of iECG and invasive LAT-maps on both the endocardial and epicardial surface during sinus rhythm showed improved agreement, although with considerable absolute difference and moderate correlation coefficient. Non-invasive iECG requires further refinements to facilitate clinical implementation and risk stratification.

Background - Familial cascade screening is well established in patients with heritable cardiac disease and in cases of Sudden Arrhythmic Death Syndrome (SADS). The clinical benefit of family screening in idiopathic ventricular fibrillation (IVF) is unknown. Methods - Patients with IVF were identified from national and institutional registries. All underwent systematic and comprehensive clinical evaluation to exclude identifiable causes of cardiac arrest with a minimum requirement of ECG, cardiac (echocardiogram and/or MRI) and coronary imaging, exercise ECG and sodium channel blocker (SCB) provocation. Additional investigations including genetic testing were performed at the physician's discretion. First-degree relatives who were assessed with at least a 12-lead ECG were included in the final cohort. Results of additional investigations, performed at the physician's discretion, were also recorded. Results were coded as normal, abnormal or minor findings. Results - We identified 201 first-degree relatives of 96 IVF patients. In addition to a 12 lead ECG, echocardiography was performed in 159 (79%) and ≥ 1 additional investigation in 162 (80%) relatives. An inherited arrhythmia syndrome was diagnosed in 5 (3%) individuals from 4 (4%) families. Two relatives hosted the DPP6 risk haplotype identified in a single proband, one of whom received a primary prevention ICD. In three separate families an asymptomatic parent of the IVF proband developed a type 1 Brugada ECG pattern during SCB provocation. All were managed with lifestyle measures only. The Early Repolarisation ECG pattern (ER) was present in 16% probands and was more common in relatives in those families than those where the proband did not have ER (25% vs. 8%, p=0.04). Conclusions - The yield of family screening in relatives of IVF probands is low when the proband is comprehensively investigated. The significance of J wave syndromes in relatives and the role for systematic SCB provocation are, however, uncertain and require further research.

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The diagnosis and management of idiopathic ventricular fibrillation is challenging, as it requires extensive diagnostic testing and offers few curative options due to unknown underlying disease. The resulting population is a heterogeneous group of patients with a largely unknown natural history. Structural patient characterisation, follow-up and innovations in diagnostic testing can improve our understanding of the disease mechanisms of idiopathic ventricular fibrillation, detect underlying disease during follow-up and aid in therapeutic management. Recently, initiatives have been launched in the Netherlands to investigate the role of high-resolution non-invasive electrocardiographic imaging and genetic and familial screening in idiopathic ventricular fibrillation.

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