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Complexity modeling: Identify instability early

Pinsky, MR (2010) Complexity modeling: Identify instability early. Critical Care Medicine, 38 (10 SUP). ISSN 0090-3493

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Abstract

Biological systems are innately complex, display nonlinear behavior, and respond to both disease and its treatment in similar complex ways. Complex systems display self-organization and predictive behavior along a range of possible states, often referred to as chaotic behavior, and can be both characterized and quantified in terms of this chaotic behavior, which defined strange attractors (ρ) and variability. In this context, disease can be characterized as a difference in a disease state ρ and a healthy ρ. Furthermore, effectiveness of treatment can be defined as a minimization problem to decrease the phase-state difference between disease and health ρ values, such that effective treatment is defined as the ability to restore the healthy ρ. Importantly, this approach will be effective without anything being known about the physiologic processes that define health or disease. The implication is that this approach is a powerful tool to define the determinants of instability as compared with normal variability, to answer why disease is not healthy, and to identify all potentially effective treatment options independent of known pharmacology and physiology. Copyright © 2010 by the Society of Critical Care Medicine and Lippincott Williams & Wilkins.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Pinsky, MRpinsky@pitt.eduPINSKY0000-0001-6166-700X
Date: 1 January 2010
Date Type: Publication
Journal or Publication Title: Critical Care Medicine
Volume: 38
Number: 10 SUP
DOI or Unique Handle: 10.1097/ccm.0b013e3181f24484
Schools and Programs: School of Medicine > Critical Care Medicine
Refereed: Yes
ISSN: 0090-3493
PubMed ID: 21164410
Date Deposited: 07 Mar 2012 20:47
Last Modified: 13 Feb 2021 17:55
URI: http://d-scholarship.pitt.edu/id/eprint/11351

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