Review article
GRAPHIC MAPPING OF CLINICAL DISEASE PATHWAYS REVEALS A COMPLEX NETWORKING AND CLUSTERING DUE TO NATURAL ETIOPATHOGENETIC INTERCONNECTIVITY
Zdenko Kovač
Abstract
Human physiology is a complex, nonlinear, self-regulated system, in which multiple functional subsystems act within the whole body reactivity. Understanding of physiology and pathophysiology requires integration of both clinical and basic factual knowledge and regulatory homeodynamic concepts. Two integrative methods have been developed to improve understanding of disease processes and natural development. Their features are here shortly presented. Matrix led algorhythmic analysis and re-synthesis puts together patients’ clinical data along with a broad academic knowledge which may be relevant to it. Graphic representation enables outlining a multiple interconnections among etiopathogenetic components within the human body. The etiopathogenetic clusters (EPCs) are crossing points, the integrative hubs of disease pathways. Multiple diseases of triggered by independent etiologies often converge to a common EPC, and thus contributing to natural networking of physiological processes in health and diseases. Contemporary biomedical sciences have been daily producing copious amounts of data whose participation in integrative
physiology is yet to be explored within the whole body reactivity. Graphic representation and active composition of patho-physiological processes stimulates a synthetic reasoning as a subroutine intellectual habit, critically relevant to both physicians and biomedical researchers. Integrative pathophysiology facilitates anchoring of a whole body and local etiopathogenetic mechanisms.This may be of special importance in contemporary trends of the intensive compartmentalization in medicine.
Keywords
integrative pathophysiology; etiopathogenesis; graph theory; etiopathogenetic clusters; EPC; algorhythms; ISP; Declaration; complexity; etiology; big data
Hrčak ID:
262689
URI
Publication date:
4.4.2019.
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