FORECASTING OF CCD IN FAMILIES BY MEANS OF A METHOD OF LOGISTIC REGRESSION IN KRASNOYARSK

Abstract

Aim. Forecasting of emergence of cardiac conduction defects (CCD) by means of a method of multiple logistic regression for implementation of early diagnostics, primary prevention and the personified approach to treatment. Material and methods. To all probands with CCD and to their relatives clinicinstrumental research on the following program was conducted: clinical examination, electrocardiography, echocardiography, Holter monitoring, stresstest, genealogical and molecular and genetic researches. For the differential diagnosis between primary and secondary CCD to probands and their relatives according to indications coronarography and an isotope scanning was carried out. According to design of research, it was selected 81 probands with CCD (26 families with RBBB (right bundle branch block) and 55 families with LBBB (left bundle branch block). Patients were subdivided into 2 subgroups: 1 subgroup – 61 patients from idiopathic RBBB (26 пробандов and 35 sick relatives with RBBB); The 2nd subgroup – 121 patients with idiopathic LBBB (55 пробандов and 66 sick relatives with LBBB); Results. We presented an innovative technique of an assessment of risk of development of CCD, such as RBBB and LBBB. This mathematical model of forecasting of CCD in families of Krasnoyarsk. For forecasting of level of determination of RBBB the logistic regression model expressed by the following equation was received. Measure of definiteness of RBBB – 28,0%. For forecasting of a measure of determination of LBBB the logistic regression model expressed by the following equation was received. Determination level for LBBB – 29,0%. Conclusion. The logistic regression model of forecasting of CCD is an additional mathematical method of the forecast of level of CCD in families. It is on the practical level important that relatives of patients with CCD are truly threatened concerning development of these pathologies of carrying-out system of heart since this pathology has genetic determinacy and is accurately traced in families with monogenic type of inheritance. It is necessary to emphasize that as emergence of a disease is caused by a complex of hereditary and environmental factors, existence of genetic predisposition at an individual isn’t fatal inevitability of his incidence. Therefore forecasting of these diseases in families by means of computer technologies will allow to carry out an early stage of primary prevention for incidence prevention.