Why the study?
The study was conducted to analyze the prevalence of clinical events and the trends of physiologically significant parameters in CIED patients using remote monitoring.
Does remote monitoring using daily data transmission enable early diagnostics of patient state changes and prediction of arrhythmia episodes in patients with cardiac implantable electronic devices?
Does remote monitoring using daily data transmission enable early diagnostics of patient state changes and prediction of arrhythmia episodes in patients with cardiac implantable electronic devices?
Daily remote monitoring of CIED patients enables the detection of adverse events and demonstrates potential for predicting arrhythmia episodes using machine learning analysis of physiological trends.
Supports remote monitoring associations with adverse event detection in CIED patients; hypothesis-generating for ML arrhythmia prediction, needing prospective validation.
Aims. Analysis of the prevalence of clinical events and of the trends of the physiologically significant parameters in patients with cardiac implantable electronic devices (CIEDs) with the remote monitoring options. Methods. In 9 clinical centers of the Russian Federation and 2 clinical centers of the Republic of Kazakhstan, 126 patients with an ICD or a pacemaker provided with the Home Monitoring technology (BIOTRONIK, Berlin, Germany) have been enrolled into the ReHoming (Registry Home Monitoring) clinical study. Based on the daily data transmission, all alarm alerts and all the Home Monitoring options changes have been registered with dated alert content and undertaken measures. Results. The study patients, followed up at least for one year, demonstrated 42 adverse events (AE), 26 of which were serious AE (SAE) and 3 SAE were defined as device related (SADE). ICD patients (n=90) had statistically significantly higher SAE prevalence with attendant coronary artery disease (CAD) (p=0.0249). Patients with CRT/D compared to patients with dual-chamber or single-chamber ICD had less SAE rate (р=0.046). Downloads of Home Monitoring parameters for retrospective mathematical analysis were available for 60 ICD patients, 47 of which 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 correlation of the changes with arrhythmia episodes, the random forest method and the gradient boosting method giving the results strongly exceeding a random guess. Conclusion. Home Monitoring of CIED patients enables evaluation of clinical advantages of different device types application, also in regard to prevention of adverse events and possible iatrogenic effects of electrotherapy of the heart. The study results demonstrate a possibility to develop a predictor of arrhythmia episodes, based on daily transmission of trends of physiologically meaningful Home Monitoring parameters.
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Ревишвили et al. (2019) studied this question.
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