Computational analysis of clot formation risk in diabetes: A mathematical modeling approach

Abstract

Diabetes mellitus poses a significant risk for cardiovascular complications, including the formation of blood clots, which can lead to severe consequences such as heart attacks and strokes. In this study, we employ mathematical modeling and computational analysis to investigate the mechanisms underlying the increased risk of clot formation in diabetic patients. Our approach integrates physiological data, hemodynamic principles, and mathematical equations to simulate blood flow dynamics and clot formation processes within the vasculature of diabetic individuals. By incorporating key factors such as altered blood viscosity, resistance to flow, endothelial dysfunction, and platelet aggregation, we obtained insights into the complex interplay between diabetes related factors and clotting propensity. Changes in blood composition, such as increased levels of fibrinogen and other clotting factors, can make blood thicker and more prone to clotting and the reason for increased resistance to flow and viscosity. As blood clots enlarge in blood vessels, they obstruct blood flow, increasing resistance. This makes blood movement harder. Clot size also affects nearby blood viscosity. Accumulating cells and clotting factors thicken blood, worsening circulation. Larger clots heighten flow resistance and viscosity, potentially causing issues like tissue damage. Thus, larger clots worsen blood flow and cardiovascular health. Through computational simulations, we explored various scenarios to assess the impact of different parameters on clot formation risk, thereby offering valuable insights for the development of preventive strategies and targeted interventions for diabetic patients.

Keywords

• Computational analysis, Clot formation, diabetes mellitus, Mathematical modeling, cardiovascular complications, Hemodynamics, Blood viscosity, Endothelial dysfunction, Platelet aggregation.