The implantation of cardiac devices significantly reduces morbidity and mortality in patients with cardiac arrhythmias. Arrhythmias as well as therapy delivered by the device may impact quality of life of patients concerned considerably. Therefore we aimed at conducting a systematic search and meta-analysis of trials examining the impact of the implantation of cardiac devices, namely implantable cardioverter-defibrillators (ICD), pacemakers and left-ventricular assist devices (LVAD) on quality of life. After pre-registering the trial with the PROSPERO database, we searched Medline, PsycINFO, Web of Science and the Cochrane databases for relevant publications. Study quality was assessed by two independent reviewers using standardized protocols. A total of 37 trials met our inclusion criteria. Of these, 31 trials were cohort trials while 6 trials used a randomized controlled design. We found large pre-post effect sizes for positive associations between quality of life and all types of devices. The effect sizes for LVAD, pacemaker and ICD patients were g = 1.64, g = 1.32 and g = 0.64, respectively. There was a lack of trials examining the effect of implantation on quality of life relative to control conditions. Trials assessing quality of life in patients with cardiac devices are still scarce. Yet, the existing data suggest beneficial effects of cardiac devices on quality of life. We recommend that clinical trials on cardiac devices routinely assess quality of life or other parameters of psychological well-being as a decisive study endpoint. Furthermore, improvements in psychological well-being should influence decisions about implantations of cardiac devices and be part of patient education and may impact shared decision-making.

Background: Several case reports have suggested an increased risk of sudden cardiac death due to energy drinks. Therefore, the purpose of this study was to assess acute electrophysiologic effects of caffeine and taurine, two of the main ingredients of energy drinks, in an experimental whole‐heart model.Methods and Results: Twenty‐five rabbit hearts were excised, retrogradely perfused, and assigned to two groups. Hearts were perfused with caffeine (2, 10, and 50 µM) or taurine (2, 10, and 50 µM) after generating baseline data. Eight monophasic action potentials and electrocardiography recordings showed a significant abbreviation of action potential duration (APD₉₀), QT interval, and effective refractory periods (ERP) after caffeine treatment. With taurine, cardiac repolarization duration and ERP were significantly shortened. A ventricular vulnerability was assessed by a predefined pacing protocol. With caffeine, we observed a trend towards more ventricular arrhythmias in a dose‐dependent manner. After treatment with taurine, significantly more episodes of ventricular arrhythmias occurred.Conclusion: In this experimental whole‐heart study, treatment with caffeine and taurine provoked ventricular arrhythmias. The underlying mechanism was an abbreviation of cardiac repolarizations and effective refractory periods that may facilitate re‐entry and thereby provokes arrhythmias. These findings help to understand the potentially hazardous and fatal outcomes after intoxication with energy drinks.

Introduction: Automated echocardiography image interpretation has the potential to transform clinical practice. However, neural networks developed in general cohorts may underperform in the setting of altered cardiac anatomy. Methods: Consecutive echocardiographic studies of patients with congenital or structural heart disease (C/SHD) were used to validate an existing convolutional neural network trained on 14,035 echocardiograms for automated view classification. In addition, a new convolutional neural network for view classification was trained and tested specifically in patients with C/SHD. Results: Overall, 9793 imaging files from 262 patients with C/SHD (mean age 49 years, 60% male) and 62 normal controls (mean age 45 years, 50.0% male) were included. Congenital diagnoses included among others, tetralogy of Fallot (30), Ebstein anomaly (18) and transposition of the great arteries (TGA, 48). Assessing correct view classification based on 284,250 individual frames revealed that the non-congenital model had an overall accuracy of 48.3% for correct view classification in patients with C/SHD compared to 66.7% in patients without cardiac disease. Our newly trained convolutional network for echocardiographic view detection based on over 139,910 frames and tested on 35,614 frames from C/SHD patients achieved an accuracy of 76.1% in detecting the correct echocardiographic view. Conclusions: The current study is the first to validate view classification by neural networks in C/SHD patients. While generic models have acceptable accuracy in general cardiology patients, the quality of image classification is only modest in patients with C/SHD. In contrast, our model trained in C/SHD achieved a considerably increased accuracy in this particular cohort.

Introduction: The long-QT syndrome (LQTS) is the most common ion channelopathy, typically presenting with a prolonged QT interval and clinical symptoms such as syncope or sudden cardiac death. Patients may present with a concealed phenotype making the diagnosis challenging. Correctly diagnosing at-risk patients is pivotal to starting early preventive treatment. Objective: Identification of congenital and often concealed LQTS by utilizing novel deep learning network architectures, which are specifically designed for multichannel time series and therefore particularly suitable for ECG data. Design and Results: A retrospective artificial intelligence (AI)-based analysis was performed using a 12-lead ECG of genetically confirmed LQTS (n = 124), including 41 patients with a concealed LQTS (33%), and validated against a control cohort (n = 161 of patients) without known LQTS or without QT-prolonging drug treatment but any other cardiovascular disease. The performance of a fully convolutional network (FCN) used in prior studies was compared with a different, novel convolutional neural network model (XceptionTime). We found that the XceptionTime model was able to achieve a higher balanced accuracy score (91.8%) than the associated FCN metric (83.6%), indicating improved prediction possibilities of novel AI architectures. The predictive accuracy prevailed independently of age and QT_c parameters. Conclusions: In this study, the XceptionTime model outperformed the FCN model for LQTS patients with even better results than in prior studies. Even when a patient cohort with cardiovascular comorbidities is used. AI-based ECG analysis is a promising step for correct LQTS patient identification, especially if common diagnostic measures might be misleading.

Background: Ablation emerged as first line therapy in the treatment of various arrhythmias. Nevertheless, in older patients (pts), decision is often made pro drug treatment as more complications and less benefit are suspected.Hypothesis: We hypothesized that different kind of ablations can be performed safely regardless of the pts age.Methods: We enrolled all pts aged >80 years (yrs) who underwent ablation for three different arrhythmias (atrial flutter [AFL], atrioventricular nodal re‐entry tachycardia [AVNRT], ventricular tachycardia [VT]) between August 2002 and December 2018. Procedural data and outcome were compared with matched groups aged 60 to 80 years and 40 to 60 years, respectively. Periprocedural and in‐hospital complications were analyzed.Results: The analysis included 1191 patients (397 pts per group: 63% AFL, 23% AVNRT, 14% VT) who underwent ablation. Acute success was high in all types of arrhythmias irrespective of age (>80, 60‐80, 40‐60 years: AFL 97%/98%/98%, AVNRT 97%/95%/97%, VT 82%/86%/93%). Rate of periprocedural complications were similar in all groups treated for AFL and AVNRT. For VT ablations significant differences were noted between pts > 80 or 60 to 80 years and those aged 40‐60 years (16.1%/14.3%/3.6%). Most complications were infections and groin haematoma. No strokes, iatrogenic atrioventricular blocks and deaths related to the ablation occurred.Conclusion: Ablation appears safe in pts > 80 years. Success rates were comparable to matched younger cohorts. A significant difference was observed for VT patients.