n Medical Technology SA - The collective risk hypothesis : fibrin network architecture and cardiovascular disease

Volume 22, Issue 2
  • ISSN : 1011-5528



Fibrinogen is an important risk factor for atherosclerosis, stroke and cardiovascular disease (CVD). This risk is increased when associated with high serum cholesterol, increased blood pressure, obesity and smoking. However, it is also believed that not only the fibrinogen itself, but also the quality of resultant fibrin networks may be a predisposing risk factor for the development of CVD. Changes in the fibrin network architecture are caused by changes in the fibrin polymerisation conditions in the blood. Kinetic and modulating factors determine polymerisation conditions. The kinetic factors are thrombin and fibrinogen concentrations. The modulating factors affect the fibrin structures independent of the kinetic factors. Such factors include all biochemical and physical properties of the direct surrounding within which the circulating fibrinogen molecule finds itself. Current literature describes only the concentration of the circulating plasma fibrinogen to have predictive value for CVD. The main aim of this article is to present a hypothesis that provides a novel way of looking at fibrinogen related CVD risk. We will refer to this hypothesis as the Collective Risk Hypothesis, in which it is postulated that the fibrin network architecture provides a better estimate of CVD risk than just plasma fibrinogen concentration. The fibrin network architecture depends not only on the fibrinogen concentration alone, but also on the collective effect of all other chemical and physical interactions within its direct environment (the modulating factors), which also includes that of the other more established independent CVD risk factors, such as LDL-C, glucose and smoking. This model provides the potential for additional laboratory analysis to establish CVD risk by means of fibrin network architecture analyses, in addition to providing a valuable tool for prevention, diagnosis and monitoring of patients with CVD.

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