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

摘要

In evidence based medicine a stroke subtype is diagnosed after a sequential search for single etiology. Degree of severity, interaction, and concomitant variables are not considered. Yet, thrombus formation, and possibly vascular rupture involves an interactive process of the vascular wall, flow properties and blood constituents in homeostasis and pathology. Evidence based medicine ignores this process and instead studies stroke using crisp "all or none" classification where subtypes are distinct and interactively relate only to outcome. The statistical approach of evidence based medicine is founded on probability theory, which, in turn, is 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, where set membership is to degree [0, 1], encompasses classical set theory, allows for an interactive process between variables, and becomes the measure of complexity. Fuzzy set theory changes the scientific method of evidence based-medicine. It is a challenge to introduce a new conception of stroke diagnosis and its potential effect on evidence based medicine. This paper shows how complexity based medicine is beginning to replace evidence based medicine by the introduction of fuzzy sets and measures to replace the conventional probability theory based a statistical approach.