The beginning of 2020 was characterized by the development of a new coronavirus pandemic (COVID-19). Information about the epidemiology, etiology, pathogenesis, clinical and laboratory diagnostics, as well as prevention and therapy for this disease is constantly being expanded and reviewed. The COVID-19 pandemic creates the need for the emergence of new conditions of specialized care for patients with heart rhythm and conduction disorders [1]. These recommendations are intended for general practitioners, internists, cardiologists, electrophysiologists/arrhythmologists, cardiovascular surgeons, functional diagnostics doctors, anesthesiologists-resuscitators, laboratory diagnostics specialists, health care organizers in the system of organizations and healthcare institutions that provide specialized care to patients with heart rhythm and conduction disorders.
HighlightsThe article is a comprehensive literature review on anatomical variations and anomalies of cardiac veins. A classification of coronary venous anatomy and anomalies detailing clinical, anatomical and radiological features is proposed. Developing such classification is important for the field of left ventricular lead placement, as it would cover a variety of clinically significant anomalies of cardiac veins. AbstractWith the advancements in the cardiac resynchronization therapy, the role of cardiac vein anatomy has become vital due to the complications associated with poor left ventricle lead placement. The cardiac vein anatomy varies much more than the anatomy of the coronary arteries, thus making cardiac veins much harder to study. In this article we have analyzed different approaches to description and naming of cardiac veins, and have summarized venous anomalies and features described in literature or encountered in real clinical practice. All anatomical features described in the article have a clinical significance in the left ventricle lead placement. Moreover, we have analyzed the wide variety of suggestions to overcoming anatomical obstacles. As a result of the analysis, we have proposed a clinical classification of the coronary venous anomalies and features that can be used during the implantation of cardiac resynchronization therapy devices.
Aims: To perform the analysis of adverse events (AE) rate and trends of physiologically meaningful parameters in patients with cardiac implantable electronic devices (CIEDs) with the mobile remote monitoring option.Methods: In 9 clinical centers of the Russian Federation and 2 clinical centers of the Republic of Kazakhstan, 126 patients with an implantable cardioverter-defibrillator (ICD) or a pacemaker (PM) equipped with the Home Monitoring (HM) technology (BIOTRONIK, Berlin, Germany) were enrolled. Based on the daily data transmission, all alarm alerts, all HM options changes and all AE were recorded with dated alert content and undertaken measures.Results: The study patients, followed up at least for one year, experienced 42 adverse events (AE), of which 26 were serious AE (SAE) and 3 SAE were defined as device-related (SAED). ICD patients (N=90) with concomitant coronary artery disease (CAD) had a statistically significantly higher SAE prevalence (p=0.0249). Patients with CRT-D had a lower SAE rate than patients with dual- or single-chamber ICD (р=0.046). Downloads of Home Monitoring parameters for retrospective mathematical analysis were available for 60 ICD patients, of which 47 had episodes of ventricular tachycardia (VT), ventricular fibrillation (VF) and/or atrial tachyarrhythmia (AT). Machine learning analysis of the trends of the physiologically meaningful parameters revealed correlations between changes and arrhythmia episodes, with the random forest and gradient boosting methods demonstrating the random effect of the results.Conclusion: Home Monitoring of CIED patients enables the evaluation of different devices applications and their clinical advantages. This might implement the prevention of adverse events and iatrogenic effects of pacing. Based on daily transmission of physiologically meaningful Home Monitoring parameters, the study results demonstrate the feasibility of developing a prediction algorithm for adverse events.
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