Open AccessRemote monitoring for the early detection of changes in patient status using the Home Monitoring technology
Author(s) -
А. Ш. Ревишвили,
N Lomidze,
Ayan Abdrakhmanov,
А. А. Нечепуренко,
E. A. Ivanitsky,
O. V. Belyaev,
С. В. Попов,
Д. С. Лебедев,
В. К. Лебедева,
С. П. Михаилов,
Е. А. Покушалов,
С. Е. Мамчур,
П. Л. Шугаев,
R. R. Rekvava,
S. N. Vasilyev,
V. V. Kuptsov,
В. И. Бердышев,
R. Sh. Sungatov,
I. Khassanov
Publication year - 2020
Publication title -
vestnik aritmologii
Language(s) - English
Resource type - Journals
eISSN - 2658-7327
pISSN - 1561-8641
DOI - 10.35336/va-2020-e-3-9
Subject(s) - medicine , ventricular tachycardia , atrial fibrillation , implantable cardioverter defibrillator , adverse effect , coronary artery disease , cardiology , emergency medicine
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.