Mathematical model for predicting treatment outcome in patients with destructive pulmonary multiresistant tuberculosis

Abstract

The cessation of bacterial excretion is the main condition for the effective treatment of multiresistant tuberculosis (MRTB). Surgical procedures for treating tuberculosis patients significantly increase the effectiveness of treatment for such patients. The selection of new selection criteria for surgical treatment of MRI is relevant, as it will increase the effectiveness of MRI treatment, which remains insufficient.Objective — to predicting the effectiveness of treatment for MRI of the lungs by developing a mathematical model to predict treatment outcomes.Materials and methods. 84 patients with MRI of the lungs: group 1 (n = 56) — with signs of effective TB treatment at the end of the intensive phase; group 2 (n = 28) — patients with signs of ineffective treatment. We used the multivariate discriminant analysis method using the statistical environment Statistica 13.Results and discussion. During the discriminant analysis, the parameters of the clinical blood analysis (monocytes, stab leukocytes, erythrocytes) were selected, which were associated with high (r > 0.5) statistically significant correlations with the levels of MMP-9, TIMP-1, oxyproline and its fractions and aldosterone in the formation of the prognosis. The mathematical model allows, in the form of comparing the results of solving two linear equations and comparing their results, to predict the outcome of treatment: 1 — effective treatment, 2 — ineffective treatment. Conсlusions. Early prediction of treatment effectiveness is promising, as it allows the use of the developed mathematical model as an additional criterion for the selection of patients for whom surgical treatment is recommended, in order to increase the effectiveness of treatment.