Значимость лабораторных показателей в прогнозировании исходов острого инфаркта миокарда

The study objective is to validate a mathematical model for prognosis of progression of the acute period of myocardial infarction. Materials and methods . We examined 135 patients with acute Q-wave myocardial infarction of the left ventricle aged between 34 and 88 years (mean age 66, standard deviation 12 years), among them 64 women and 71 men. For prognosis of the outcome of the acute period of myocardial infarction we used an approach based on intellectual data analysis (data mining) in combination with mathematical methods based on decision trees. Results. Using decision tree algorithms, we singled out laboratory parameters (attributes) which were subsequently used as input. Adequacy of classification of these attributes was determined by a contingency table. Accuracy of the obtained calculation results was 95.56 % demonstrating good agreement between the model and observed data. In a decision tree visualization, the most significant 8 laboratory parameters were determined. Significance of NO 2 metabolite was 24.9 %, triglycerides – 16.7 %, urea – 14.8 %, erythrocytes – 11.2 %, alanine aminotransferase – 9.4 %, very low density lipoproteins – 9.4 %, creatinine – 8.5 %, prothrombin index – 5.1 %. In the Rules tab, only rules 4 and 9 can be used with confidence, because their confidence level approaches 100 %, and effect cost for the fact of death was 33.59 % and 32.03 %, respectively. Conclusion. Using a decision tree algorithm, we determined prognostically significant factors for progression of acute myocardial infarction. The following set of parameters predicts unfavorable outcome (death) with 95.56 % accuracy: NO 2 < level 22.755 mmol/l, triglycerides ≥ 1.565 mmol/l, erythrocytes < 4.91 M/uL, alanine aminotransferase < 1.23 mmol/l, urea < 7.05 mmol/l, very low-density lipoproteins < 0.965 mmol/l, creatinine ≥ 91.55 µmol/l, NO 2 level ≥ 22.755 mmol/l predicts a favorable outcome with 95.56 % accuracy.