Literature DB >> 15385755

Nonlinear dynamics, complex systems, and the pathobiology of critical illness.

Timothy G Buchman1.   

Abstract

PURPOSE OF REVIEW: The review considers problems in critical illness and critical care in the context of complex systems science. Normal physiology is characterized by nonlinear dynamics, and it appears that the pathophysiology of critical illness alters those dynamics. RECENT
FINDINGS: Recent evidence confirms and extends the observation that the rich variability that characterizes normal physiology "decomplexifies" with critical illness. Experimental data in animals and now in humans suggests that physiologic support that mimics normal variability may reduce the severity and/or duration of the illness.
SUMMARY: Physiologic dynamics in health and in critical illness appear to reflect complex, interconnected systems biology. Alterations in illness and during recovery may provide important clues to the underlying structure of the system. With knowledge of the structure, therapy could be better focused toward supporting both function and dynamics, offering hope for improved outcomes. Copyright 2004 Lippincott Williams & Wilkins

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Mesh:

Year:  2004        PMID: 15385755     DOI: 10.1097/01.ccx.0000139369.65817.b6

Source DB:  PubMed          Journal:  Curr Opin Crit Care        ISSN: 1070-5295            Impact factor:   3.687


  31 in total

1.  Toward an integrated research agenda for critical illness in aging.

Authors:  Eric B Milbrandt; Basil Eldadah; Susan Nayfield; Evan Hadley; Derek C Angus
Journal:  Am J Respir Crit Care Med       Date:  2010-06-17       Impact factor: 21.405

2.  Evidence-based modeling of critical illness: an initial consensus from the Society for Complexity in Acute Illness.

Authors:  Yoram Vodovotz; Gilles Clermont; C Anthony Hunt; Rolf Lefering; John Bartels; Ruediger Seydel; John Hotchkiss; Shlomo Ta'asan; Edmund Neugebauer; Gary An
Journal:  J Crit Care       Date:  2007-03       Impact factor: 3.425

Review 3.  Translational systems biology: introduction of an engineering approach to the pathophysiology of the burn patient.

Authors:  Gary An; James Faeder; Yoram Vodovotz
Journal:  J Burn Care Res       Date:  2008 Mar-Apr       Impact factor: 1.845

Review 4.  The evolution of an inflammatory response.

Authors:  Stephen F Lowry
Journal:  Surg Infect (Larchmt)       Date:  2009-10       Impact factor: 2.150

Review 5.  Multimodal monitoring and neurocritical care bioinformatics.

Authors:  J Claude Hemphill; Peter Andrews; Michael De Georgia
Journal:  Nat Rev Neurol       Date:  2011-07-12       Impact factor: 42.937

Review 6.  Data collection and interpretation.

Authors:  Giuseppe Citerio; Soojin Park; J Michael Schmidt; Richard Moberg; Jose I Suarez; Peter D Le Roux
Journal:  Neurocrit Care       Date:  2015-06       Impact factor: 3.210

7.  From static to dynamic: a sepsis-specific dynamic model from clinical criteria in polytrauma patients.

Authors:  Rami A Namas; Yoram Vodovotz
Journal:  Ann Transl Med       Date:  2016-12

8.  Early sepsis detection in critical care patients using multiscale blood pressure and heart rate dynamics.

Authors:  Supreeth P Shashikumar; Matthew D Stanley; Ismail Sadiq; Qiao Li; Andre Holder; Gari D Clifford; Shamim Nemati
Journal:  J Electrocardiol       Date:  2017-08-16       Impact factor: 1.438

Review 9.  The stressed host response to infection: the disruptive signals and rhythms of systemic inflammation.

Authors:  Stephen F Lowry
Journal:  Surg Clin North Am       Date:  2009-04       Impact factor: 2.741

10.  Coefficient of Variation of Coarsely Sampled Heart Rate is Associated With Early Vasopressor Independence in Severe Sepsis and Septic Shock.

Authors:  Samuel M Brown; M Quinn Tate; Jason P Jones; Kathryn G Kuttler; Michael J Lanspa; Matthew T Rondina; Colin K Grissom; V J Mathews
Journal:  J Intensive Care Med       Date:  2014-02-26       Impact factor: 3.510

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