Algorithm for Management of Patients with Ventricular Arrhythmia Since the Moment of its Identification

Tatiana Tulintseva Research Laboratory of Electrocardiology, Almazov National Medical Research Centre, Saint-Petersburg, Russia

Identification of correct management of patients with ventricular arrhythmias (VA) takes a special place and is a complex task in modern arrhythmology.

Our experience allowed us to introduce several medical technologies into clinical practice. In addiition, new published data have been taken as a basis to create a novel algorithm for management of patients with VA from its first identification till selection of therapy approach. This algorithm is divided into stages. At the first stages, the priority is focused on the identification of structural myocardial disease and, especially, the exclusion of ischemic VA as well as the autonomic and central nervous systems participation in ventricular arrhythmogenesis. The role of psychological diagnostics with questionnaires and mental testing is emphasized.

A long-term continuous ECG monitoring with telemetry implemented in our practice allows to start the treatment sooner, to reduce the number of proarrhythmogenic effects, to eliminate the variability of arrhythmias and to assess the effectiveness of therapy more impartially.

An important advantage of telemonitoring is the ability to provide treatment on an outpatient basis (by transmitting information via the Internet). Moreover, monitoring can be contunued when patient is at work.

The selection between antiarrhythmic drug solution or radiofrequency catheter is done individually based on the disease form and the clinical and electrocardiographic characteristics of the VA (duration of existence, number of ventricular ectopic complexes per 24h, presence or absence of unstable ventricular tachycardia, its complexity, etc.). The algorithm is shown on the scheme in stages. The selection of treatment method (medical/surgical) substantially depends on the VA characteristics, patient`s compliance and psychological characteristics.

The algorithm described here provide a safe prevention of patient sudden cardiac death.









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