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Updated: Aug 9, 2026

A Thrombotic Stroke Model Based On Transient Cerebral Hypoxia-ischemia
Published on: August 18, 2015
Thrombophilia in ischemic stroke subtypes: implications for treatment
1Department of Neurology, University of Illinois College of Medicine at Chicago, 912 South Wood Street, Room 855N, Chicago, IL 60612, USA. helgason@uic.edu
The current understanding of thrombogenesis is modeled on Virchow's triad: stasis, hypercoagulability, and vessel wall injury. There is a dynamic (always changing) nonlinear interaction between the vascular wall, blood components, and flow, which at times defined "pathologic" leads to thrombosis or hemorrhage, at other times called "healthy" to normal hemostasis. The triad named after Virchow was not designated as such in Virchow's work. Instead, Virchow showed that thrombosis itself leads to endothelial damage, hypercoagulability, and stasis. Thus, cause and effect regarding the elements of Virchow's triad and thrombosis become indistinguishable if linearity is considered mandatory. Considering a nonlinear relation solves this problem. In the real patient, each element is present to a degree. At every moment in time, the direction of coagulation (toward hemostasis, thrombosis, or hemorrhage) and the dynamic of interaction of the elements of the triad change. The complexity and nonlinearity of the thrombotic context is evident. These facts suggest a new venue for diagnostic classification of stroke (ischemic and hemorrhagic) by causation and have implications for its prevention and treatment. Clinical and laboratory evidence can be gathered for the elements of Virchow's triad as well as for fibrinolysis and thrombosis. Mathematical methods other than probability-based statistics can represent the measured presence of these elements to a degree and their nonlinear relationship. These include, but may not be limited to, Riemannian geometry, fuzzy logic, cellular automata, and infinitesimals, all proscribed by evidence-based medicine. However, by using these methods, diagnosis and treatment measures for stroke can be built on a causal rather than risk methodology, individualizing medical decisions to the patient. All current clinical guidelines are based on linear methods of probability-based statistics and group-based data. The therapeutic choice of antithrombotic therapy in the individual patient for whom measured elements of thrombogenesis are available rests on the knowledge and expertise of the treating physician.
The current understanding of thrombogenesis is modeled on Virchow's triad: stasis, hypercoagulability, and vessel wall injury. There is a dynamic (always changing) nonlinear interaction between the vascular wall, blood components, and flow, which at times defined "pathologic" leads to thrombosis or hemorrhage, at other times called "healthy" to normal hemostasis. The triad named after Virchow was not designated as such in Virchow's work. Instead, Virchow showed that thrombosis itself leads to endothelial damage, hypercoagulability, and stasis. Thus, cause and effect regarding the elements of Virchow's triad and thrombosis become indistinguishable if linearity is considered mandatory. Considering a nonlinear relation solves this problem. In the real patient, each element is present to a degree. At every moment in time, the direction of coagulation (toward hemostasis, thrombosis, or hemorrhage) and the dynamic of interaction of the elements of the triad change. The complexity and nonlinearity of the thrombotic context is evident. These facts suggest a new venue for diagnostic classification of stroke (ischemic and hemorrhagic) by causation and have implications for its prevention and treatment. Clinical and laboratory evidence can be gathered for the elements of Virchow's triad as well as for fibrinolysis and thrombosis. Mathematical methods other than probability-based statistics can represent the measured presence of these elements to a degree and their nonlinear relationship. These include, but may not be limited to, Riemannian geometry, fuzzy logic, cellular automata, and infinitesimals, all proscribed by evidence-based medicine. However, by using these methods, diagnosis and treatment measures for stroke can be built on a causal rather than risk methodology, individualizing medical decisions to the patient. All current clinical guidelines are based on linear methods of probability-based statistics and group-based data. The therapeutic choice of antithrombotic therapy in the individual patient for whom measured elements of thrombogenesis are available rests on the knowledge and expertise of the treating physician.
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