Abstract
Clinical data analysis of 83 patients with implantable cardioverter-defibrillators (ICDs) for sudden cardiac death (SCD) primary prevention has been done. We revealed 5 parameters associated with the detection of life-threatening ventricular arrhythmias. These parameters formed the basis for constructing a logistic regression model. The model makes it possible to obtain the probability of occurrence of a specific event depending on the severity of the predictive parameters and the degree of its influence (risk of true ventricular arrhythmias detection). Estimating the potential risk of the life-threatening arrhythmias, individual programming options are required in implantable cardioverter-defibrillators (ICDs) to reduce the amount of unnecessary electrotherapy, as well as more accurate monitoring of the patient's drug therapy.
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