FIELD: medicine.
SUBSTANCE: invention refers to medicine, namely to cardiology, and can be used for prediction of recurrent myocardial infarction (MI) in elderly and senile patients within one year after MI. Factors are determined: presence in the medical history of CVA, type 2 diabetes, coronary stenting in acute period of index MI, development of acute left ventricular failure (ALVF) in MI acute period. Probability of recurrent MI is determined by formula: p = 1/1 + exp(-z), where p is the probability of developing repeated MI; z is the value of the discriminant function, and the value of the discriminant function is determined by the formula: z = a + bx1 + cx2 + dx3 + ex4, where a is a constant, x1-x4 are values of variables corresponding to the considered indicators, coefficients b, c, d, e are weight coefficients of the corresponding values: a = -2.539, b = 0.921, x1 is the presence of a CVA history in the anamnesis, x1 = 1 - in the presence of a history of CVA, x1 = 0 - in the absence of a history of CVA, c = 0.925, x2 - presence in the previous history of type 2 diabetes mellitus, x2 = 1 - in the presence of type 2 diabetes mellitus, x2 = 0 - in the absence of type 2 diabetes mellitus, d = - 1.186, x3 - coronary stenting in acute period of index MI, x3 = 1 - when performing coronary stenting in acute period of index IM, x3 = 0 - with no coronary stenting in acute period of index MI, e = 1.678, x4 - development of ALVF in acute period of index IM, x4 = 1 - with development of ALVF in acute period of index MI, x4 = 0 - in the absence of the development of ALVF in the acute period of the index MI, and if the value of p is more than 0.09 - the development of repeated MI within one year of the postinfarction period is predicted.
EFFECT: method enables predicting recurrent MI in elderly and senile patients within one year after suffering MI by determining a set of factors influencing the development of recurrent myocardial infarction using an inverse step-by-step regression technique.
1 cl, 1 tbl, 2 ex
Authors
Dates
2020-06-30—Published
2019-10-10—Filed