METHOD FOR PREDICTING RESUMPTION OF CORONARY HEART DISEASE CLINICAL PICTURE BY MEANS OF NEURAL NETWORKS IN PATIENTS AFTER ENDOVASCULAR INTERVENTION

摘要

FIELD: medicine.;SUBSTANCE: invention relates to medicine, namely to cardiology and cardiac surgery, and can be used to predict the resumption of coronary heart disease clinical picture after endovascular intervention. State of the hemostatic system is determined by the Thrombin generation assay (TGA) in two parallel settings. One formulation without the addition of thrombomodulin (- rh-TM), and the other formulation with the addition of thrombomodulin (+ rh-TM). In each formulation, the time of initiation of LT coagulation (Lag Time), Peak thrombin concentration (Peak thrombin), time to reach peak trombin ttPeak (time to peak) concentrations and Endogenous Thrombin Potential endogenous potential are determined. Calculate the rate of formation of thrombin according to the claimed formula. Then, using neural networks, ETP, Peak, VI_TM and % LT programmed in the Mathematica Wolfram package are analyzed. Determine the personal rate of each patient. If the personal coefficient is in the range from 0.10 to 3.35, the risk of recurrence of coronary disease is considered minimal. If the personal coefficient is in the range from – 0.02 to – 4.58, the risk of recurrence of coronary disease is considered maximum.;EFFECT: method allows to increase the prognostic accuracy of the test results of the generation of thrombin in predicting the resumption of the clinic of coronary heart disease in patients after endovascular intervention, identify patients with high risk and provide an individual approach to the management of patients with high risk, increase the effectiveness of treatment through the use of neural networks and assess the complex of the most significant indicators.;1 cl, 1 dwg, 3 tbl