Causal interactions, fuzzy sets and cerebrovascular 'accident': The limitsof evidence-based medicine and the advent of complexity-based medicine

In evidence-based medicine, stroke subtype is diagnosed after a sequential search for etiology; the first positive test result of significant severity rounds off to one overwhelming cause. Degree of severity, interaction amon g variables, and concomitant variable conditions are not considered in defi ning the cause of stroke. Yet, thrombus formation, and possibly vascular ru pture, is an interactive process involving the vascular wall, flow properti es of the blood and blood constituents; this process occurs in homeostasis and pathology. Evidence-based medicine ignores this process and instead stu dies stroke using crisp 'all or none' classification where subtypes are dis tinct and interactively relate only to outcome. As a result, scientific inq uiry is focused on prediction for the collective of patients. The statistic al approach of evidence-based medicine is founded on probability theory, it self rooted in classical set theory where elementhood is all (1) or none (0 ), and opposites interact only to form the null set. Fuzzy set theory, wher e set membership is to degree [0, 1], encompasses classical set theory, all ows for an interactive process between variables, and therefore becomes the measure of complexity. Fuzzy set theory can change the scientific method o f evidence-based medicine.