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Embracing complexity in sepsis.

Alex R Schuurman1, Peter M A Sloot2, W Joost Wiersinga1,3

  • 1Centre for Experimental and Molecular Medicine (CEMM), Amsterdam University Medical Centres - Location AMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.

Critical Care (London, England)
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Summary
This summary is machine-generated.

Sepsis is a complex, dysregulated state. Embracing complexity theory and computational methods, alongside continuous biological data, is crucial for advancing sepsis research and treatment.

Keywords:
ComplexityComputational modelsHost responseNon-linearitySepsis

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Area of Science:

  • Sepsis research
  • Complexity theory
  • Computational biology

Background:

  • Sepsis is a complex, dynamic, and dysregulated state resulting from pathogen-host interactions and organ system failure.
  • Current understanding and methods for sepsis complexity are underappreciated.
  • Traditional approaches struggle to govern the multifaceted nature of sepsis.

Purpose of the Study:

  • To reframe sepsis understanding through the lens of complexity theory.
  • To advocate for the use of complex systems science methods in sepsis research.
  • To identify barriers and solutions for integrating computational approaches into sepsis management.

Main Methods:

  • Viewing sepsis as a highly complex, non-linear, and spatio-dynamic system.
  • Highlighting progress in complex systems methods like computational modeling and network analysis.
  • Advocating for longitudinal, continuous biological data collection.

Main Results:

  • Complex systems methods are pivotal for a fuller understanding of sepsis.
  • Computational modeling and network analyses remain underutilized in sepsis research.
  • Integration of computational approaches with biological data can refine models and identify therapeutic targets.

Conclusions:

  • A multidisciplinary effort integrating computational approaches and biological data is essential for advancing sepsis understanding.
  • Embracing nonlinear, system-based thinking is necessary to move the field of sepsis research forward.
  • Focusing on continuous data collection and agile clinical trials can improve sepsis management.