Examining the controllability of sepsis using genetic algorithms on an agent-based model of systemic inflammation.

ABSTRACT: Sepsis, a manifestation of the body's inflammatory response to injury and infection, has a mortality rate of between 28%-50% and affects approximately 1 million patients annually in the United States. Currently, there are no therapies targeting the cellular/molecular processes driving sepsis that have demonstrated the ability to control this disease process in the clinical setting. We propose that this is in great part due to the considerable heterogeneity of the clinical trajectories that constitute clinical "sepsis," and that determining how this system can be controlled back into a state of health requires the application of concepts drawn from the field of dynamical systems. In this work, we consider the human immune system to be a random dynamical system, and investigate its potential

SUBMITTER: Cockrell RC 

PROVIDER: S-EPMC5813897 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature