Centr Intellektualnyh Sistem Prognozirovaniya

Background & Objectives :  Prognostic and Health Management, PHMs a new IT trend whose purpose is the development of methods, algorithms and computing clusters to identify hidden early predictors of cardiovascular risks on basis of parallel computing resource. Cloud computing cluster supports low-cost ECG ultra-portable recorders and not limits the possibilities of using a more complex patient telemetry containing implantable sensors as pulmonary artery sensor, left atrial pressure sensor, CRT devices.

Methods: Using the above-mentioned technology and PHM predictive methods of detecting of early predictors of ventricular tachycardia were studied methods for optimizing drug treatment of arrhythmias in the persistent phase. ECG monitoring was carried out episodically or permanently depending on the ECG dynamics. The minimum time of ECG recording was in different cases from 5 minutes to 10 hours daily. ECG recording length was determined automatically by cloud cluster algorithms in interactive regime.

Results: Monitoring was held to 20 patients with persistent atrial fibrillation. Change of antiarrhythmic drugs was controlled cloud cluster. Early criteria of drug ineffectiveness were established. It also specified criteria of efficiency on the basis of modeling the evolution of latent early predictors. In some cases, the PHM systems prevent development of life threatening arrhythmias.

Conclusions:  Thus ECG analysis on base PHM cloud cluster is new possibilities for heart failure management, drug control efficient and drug therapy optimization. Low cost of recorders and cloud computing service  makes available remote preventive monitoring to all patients, and the potential risk groups.


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