Laboratory predictors in patients with acute myocardial infarction combined with nonalcoholic fatty liver disease
The aim of the study was to test a mathematical model for predicting the course of acute myocardial infarction period (MI) with Q wave, combined with hepatic steatosis (HS) or non-alcoholic steatohepatitis (NASH). Materials and methods. The study involved 74 patients with acute Q-positive left ventricular MI of different location, combined with HS (67 patients) and NASH (7 patients), aged 36 to 88 years (average age 64 ± 1 years). Among them there were 35 women and 39 men. To predict the outcome of acute MI period, combined with HS or NASH, we used an approach based on data mining (Data Mining) with mathematical tools of the decision tree method. Results. The decision tree algorithms allowed determine the laboratory parameters (attributes) and then use them as input data. Construction of contingency tables determined the adequacy of classification of these attributes. The accuracy of the calculation results is 98.65 %. Decision tree highlighted three most important laboratory parameters: aspartate aminotransferase (ASAT), age and red blood cells concentration. The significance of ASAT was 60.9 %, age — 25.8 %, and red blood cells — 13.3 %. With regard to Rules of visual analyzer, only the first rule earns confidence, in which the accuracy reaches 100 %, and the influence on the death (support) — 52.9 %. Conclusions. The decision tree algorithm identified important prognostic markers of acute MI and non-alcoholic fatty liver disease: ASAT and age. It determined that if patient’s ASAT level is less than 0.546 mmol/l, and age is less than 81, then a favorable outcome can be predicted with 98.65% accuracy.
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