Problems of Radiation Medicine and Radiobiology

V. V. Kundina, T. M. Babkina

Shupyk National Healthcare University of Ukraine, 9 Dorohozhytska Str., Kyiv, 04112 Ukraine

MULTIMODAL LOGIT MODEL FOR PREDICTING THE EFFICIENCY OF MYOCARDIAL REVASCULARIZATION BY THE METHOD OF CORONARY ARTERY BYPASS GRAFTING IN PATIENTS WITH CORONARY HEART DISEASE

Objective: building of a mathematical logit model for possible prediction of the outcome of surgical treatment by the method of coronary artery bypass grafting (CABG) in patients of different groups with coronary heart disease (CHD) based on myocardial viability (MV) assessment.
Material and methods. To implement the set clinical tasks, 62 patients with coronary heart disease with preserved systolic function and systolic dysfunction were examined. The mean age of the subjects was (59.6 ± 8.2) years. 35 (56 %) patients had a variant of heart failure (HF) with an ejection fraction (EF) of 45 % or less. 27 (44 %) patients had EF of 46 % or more. 5 (8.0 %) patients denied myocardial infarction (MI). Myocardial scintigraphy (MSG) was performed on Infinia Hawkeye combined gamma-camera (GE, USA) with integrated CT. The studies were performed in SPECT and SPECT / CT with ECG synchronization (Gated SPECT) modes. ^99mTc-MIBI with an activity of 555–740 MBq was used. MSG was performed in the dynamics of treatment (before CABG and after CABG) according to One Day Rest protocol. A total of 124 scintigraphic studies were performed.
Results. Samples of patients studied «before» and «after» the treatment were compared using nonparametric Wilcoxon test (Wilcoxon Matched Pairs Test). A multivariate regression model, that reflects a statistically significant effect on the treatment response (MV after treatment) of such cardiac activity indicators as LV EF (%), coronary bed lesion area and MV level (%) before treatment, was built. The above-described regression relationship between the three above-defined functional factors of cardiac activity before treatment and the therapeutic effect in the form of the change in MV can be construed as a diagnostic model that predicts the treatment outcome.
Conclusions. This scientific study allows to build logit models to predict the expected outcome of coronary heart disease surgical treatment in patients of different groups. The presented multivariate regression model is characterised by a sufficiently high for biostatistical studies adjusted coefficient of determination (Adjusted R² = 0,893 (F = 173,4; p < 0,001)).
Key words: coronary heart disease, revascularization, myocardial scintigraphy, myocardial viability.

Problems of Radiation Medicine and Radiobiology.
2021;26:513-525. doi: 10.33145/2304-8336-2021-26-513-525

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