Prospects for the application of mathematical modeling in clinical medicine
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The aims of the study are to follow the correlation of СAD development with various clinical and laboratory parameters and risk factors in a cohort of patients with multiple medical conditions and evaluate the effect of various parameters in the development of the disease using a new mathematical model approach.
Materials and methods
This study covers a limited patient cohort (n = 12) formed according to the rules of a local register. We have applied the methods of probabilistic mathematical modeling of cardiovascular disease with the formation of an aggregated matrix. Matrix fields were presented the instrumental methods of diagnosis and clinical and biochemical blood tests of patients.
When using various methods of mathematical and statistical analysis (including cluster and factor analysis), created has been a graphic model of interaction of clinical, biochemical and instrumental parameters with the development of CAD. The mathematical and statistical completeness of the description of the patient’s condition by the parameters of pathology on the basis of the measure of reliability of the completeness of the description was R=0,98-1,0, the coefficient of determination was equal to R2=92,0-98,0%. The main clinical and laboratory parameters that affect the progression of the disease, as well as the main triggers for the initiation of the process have been identified in the application of this method.
The results of the study, obtained by applying a new mathematical analysis of the data, confirmed the theory of atherosclerosis. Total cholesterol and LDL cholesterol were the main factors in the formation of CAD in this model. Blood pressure, GGT and triglycerides become essential trigger-factors in the development of disease. The presence of atherosclerotic plaque in the carotid artery appeared as the marker of the disease. This method requires further study, creating models of other pathological conditions, and interactions of the essential trigger-factors should be investigated.
Oleg V. Gaisenok, Victor N. Lituev. Prospects for the application of mathematical modeling in clinical medicine. Cardiometry; Issue 14; May 2019; p.64-70; DOI: 10.12710/cardiometry.2019.14.6470; Available from: http://www.cardiometry.net/issues/no14-may-2019/mathematical-modeling-in-clinical-medicine