A Whole-Body Mathematical Model of Sepsis Progression and Treatment Designed in the BioGears Physiology Engine.

Matthew Mcdaniel,Jonathan M Keller,Austin Baird,Steven White

doi:10.3389/fphys.2019.01321

Matthew Mcdaniel, Jonathan M Keller + Show 2 more

Open Access

https://doi.org/10.3389/fphys.2019.01321

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Abstract

Sepsis is a debilitating condition associated with a high mortality rate that greatly strains hospital resources. Though advances have been made in improving sepsis diagnosis and treatment, our understanding of the disease is far from complete. Mathematical modeling of sepsis has the potential to explore underlying biological mechanisms and patient phenotypes that contribute to variability in septic patient outcomes. We developed a comprehensive, whole-body mathematical model of sepsis pathophysiology using the BioGears Engine, a robust open-source virtual human modeling project. We describe the development of a sepsis model and the physiologic response within the BioGears framework. We then define and simulate scenarios that compare sepsis treatment regimens. As such, we demonstrate the utility of this model as a tool to augment sepsis research and as a training platform to educate medical staff.

Highlights

Sepsis represents an array of dysregulated physiologic responses from the body in response to suspected or confirmed infection
Some bacteria invaded the bloodstream from the infection site (Figure 4), but the effectiveness of the immune response in curbing bacterial growth in the blood varied
We demonstrated that applying fluid bolus actions produced transient increases in blood volume, mean arterial pressure (MAP), and urine output (UO), the magnitude of which depended on the length of time over which the patient had been septic

Summary

Introduction

Sepsis represents an array of dysregulated physiologic responses from the body in response to suspected or confirmed infection. The physiologic changes are often overwhelming, can result in severe tissue damage, and are potentially life-threatening. Large cohort studies indicate sepsis is a leading contributor to hospital mortality (Liu et al, 2014). Patients who acquire sepsis in the hospital have a mortality rate of 25% (Rhee et al, 2017). Sepsis accounts for 6.2% of the aggregate costs for all hospitalizations, or nearly $23.7 billion annually, making it the most expensive condition treated in the hospital (Torio and Moore, 2016). There is increasing recognition of sepsis survivors experiencing long-term disability (Iwashyna et al, 2010)

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