Autoimmune diseases (ADs) affect approximately 10% of the world’s population. Because ADs are frequently systemic disorders, cardiac involvement is common. In this review we focus on typical arrhythmias and their pathogenesis, arrhythmia-associated mortality, and possible treatment options among selected ADs (sarcoidosis, systemic lupus erythematosus, scleroderma, type 1 diabetes, Graves’ disease, rheumatoid arthritis, ankylosing spondylitis [AS], psoriasis, celiac disease [CD], and inflammatory bowel disease [IBD]). Rhythm disorders have different underlying pathophysiologies; myocardial inflammation and fibrosis seem to be the most important factors. Inflammatory processes and oxidative stress lead to cardiomyocyte necrosis, with subsequent electrical and structural remodeling. Furthermore, chronic inflammation is the pathophysiological basis linking AD to autonomic dysfunction, including sympathetic overactivation and a decline in parasympathetic function. Autoantibody-mediated inhibitory effects of cellular events (i.e., potassium or L-type calcium currents, M2muscarinic cholinergic or β1-adrenergic receptor signaling) can also lead to cardiac arrhythmia. Drug-induced arrhythmias, caused, for example, by corticosteroids, methotrexate, chloroquine, are also observed among AD patients. The most common arrhythmia in most AD presentations is atrial arrhythmia (primarily atrial fibrillation), expect for sarcoidosis and scleroderma, which are characterized by a higher burden of ventricular arrhythmia. Arrhythmia-associated mortality is highest among patients with sarcoidosis and lowest among those with AS; there are scant data related to mortality in patients with psoriasis, CD, and IBD.

The aim of this TeleCheck-AF sub-analysis was to evaluate motivation and adherence to on-demand heart rate/rhythm monitoring app in patients with atrial fibrillation (AF). Patients were instructed to perform 60 s app-based heart rate/rhythm recordings 3 times daily and in case of symptoms for 7 consecutive days prior to teleconsultation. Motivation was defined as number of days in which the expected number of measurements (≥3/day) were performed per number of days over the entire prescription period. Adherence was defined as number of performed measurements per number of expected measurements over the entire prescription period. Data from 990 consecutive patients with diagnosed AF [median age 64 (57–71) years, 39% female] from 10 centres were analyzed. Patients with both optimal motivation (100%) and adherence (≥100%) constituted 28% of the study population and had a lower percentage of recordings in sinus rhythm [90 (53–100%) vs. 100 (64–100%), P < 0.001] compared with others. Older age and absence of diabetes were predictors of both optimal motivation and adherence [odds ratio (OR) 1.02, 95% coincidence interval (95% CI): 1.01–1.04, P < 0.001 and OR: 0.49, 95% CI: 0.28–0.86, P = 0.013, respectively]. Patients with 100% motivation also had ≥100% adherence. Independent predictors for optimal adherence alone were older age (OR: 1.02, 95% CI: 1.00–1.04, P = 0.014), female sex (OR: 1.70, 95% CI: 1.29–2.23, P < 0.001), previous AF ablation (OR: 1.35, 95% CI: 1.03–1.07, P = 0.028). In the TeleCheck-AF project, more than one-fourth of patients had optimal motivation and adherence to app-based heart rate/rhythm monitoring. Older age and absence of diabetes were predictors of optimal motivation/adherence.

Risk stratification in patients with atrial fibrillation (AF) is critically important because this group is at high risk of mortality and morbidity. One of the comorbidities potentially affecting thromboembolic and total cardiovascular risk is obstructive sleep apnea (OSA). The aim of this study was to determine whether or not patients with atrial fibrillation and concomitant obstructive sleep apnea have a higher predicted cardiovascular risk than those without sleep-disordered breathing.

Cardiac rehabilitation after acute myocardial infarction is crucial and improves patients’ prognosis. It aims to optimize cardiovascular risk factors’ control. Providing additional support via mobile applications has been previously suggested. However, data from prospective, randomized trials evaluating digital solutions are scarce. In this study, we aimed to evaluate a mobile application—afterAMI—in the clinical setting and to investigate the impact of a digitally-supported model of care in comparison with standard rehabilitation. A total of 100 patients after myocardial infarction were enrolled. Patients were randomized into groups with either a rehabilitation program and access to afterAMI or standard rehabilitation alone. The primary endpoint was rehospitalizations and/or urgent outpatient visits after 6 months. Cardiovascular risk factors’ control was also analyzed. Median age was 61 years; 65% of the participants were male. This study failed to limit the number of primary endpoint events (8% with app vs. 27% without app; p = 0.064). However, patients in the interventional group had lower NT-proBNP levels (p = 0.0231) and better knowledge regarding cardiovascular disease risk factors (p = 0.0009), despite no differences at baseline. This study showcases how a telemedical tool can be used in the clinical setting.

Mobile, portable ECG-recorders allow the assessment of heart rhythm in out-of-hospital conditions and may prove useful for monitoring patients with cardiovascular diseases. However, the effectiveness of these portable devices has not been tested in everyday practice. A group of 98 consecutive cardiology patients [62 males (63%), mean age 69 ± 12.9 years] were included in an academic care centre. For each patient, a standard 12-lead electrocardiogram (SE), as well as a Kardia Mobile 6L (KM) and Istel (IS) HR-2000 ECG were performed. Two groups of experienced physicians analysed obtained recordings. After analysing ECG tracings from SE, KM, and IS, quality was marked as good in 82%, 80%, and 72% of patients, respectively (P < 0.001). There were no significant differences between devices in terms of detecting sinus rhythm [SE (60%, n = 59), KM (58%, n = 56), and IS (61%, n = 60); SE vs. KM P = 0.53; SE vs. IS P = 0.76) and atrial fibrillation [SE (22%, n = 22), KM (22%, n = 21), and IS (18%, n = 18); (SE vs. KM P = 0.65; SE vs. IS = 0.1)]. KM had a sensitivity of 88.1% and a specificity of 89.7% for diagnosing sinus rhythm. IS showed 91.5% and 84.6% sensitivity and specificity, respectively. The sensitivity of KM in detecting atrial fibrillation was higher than IS (86.4% vs. 77.3%), but their specificity was comparable (97.4% vs. 98.7%). Novel, portable devices are useful in showing sinus rhythm and detecting atrial fibrillation in clinical practice. However, ECG measurements concerning conduction and repolarization should be clarified with a standard 12-lead electrocardiogram.

MHealth solutions optimize cardiovascular risk factor control in coronary artery disease. The aim of this study was to investigate the influence of mobile app AfterAMI on quality of life in patients after myocardial infarction. 100 participants were randomized (1:1 ratio) into groups: (1) with a rehabilitation program and access to afterAMI or (2) standard rehabilitation alone (control group, CG). 3 questionnaires (MacNew, DASS21 and EQ-5D-5L) were used at baseline, 1 month and 6 months after discharge. Median age was 61 years; 35% of patients were female. At 1 month follow up patients using AfterAMI had higher general quality of life scores both in MacNew [5.78 vs. 5.5 in CG, p = 0.037] and EQ-5D-5L [80 vs. 70 in CG, p = 0.007]. At 6 months, according to MacNew, the app group had significantly higher scores in emotional [6.09 vs. 5.45 in CG, p= 0.017] and physical [6.2 vs. 6 in CG, p = 0.027] aspects. The general MacNew quality of life score was also higher in the AfterAMI group [6.11 vs. 5.7 in CG, p = 0.015], but differences in EQ-5D-5L were not significant. There were no differences between groups in the DASS21 questionnaire. mHealth interventions may improve quality of care in secondary prevention, however further studies are warranted.