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Math Biosci. 2014 Jun;252:36-44. doi: 10.1016/j.mbs.2014.03.010. Epub 2014 Mar 26.

On heart rate variability and autonomic activity in homeostasis and in systemic inflammation.

Author information

1
Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA.
2
Department of Surgery, Robert Wood Johnson Medical School, Clinical Academic Building, 125 Patterson Street, New Brunswick, NJ 08901, USA.
3
Department of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, NJ 08854, USA; Department of Surgery, Robert Wood Johnson Medical School, Clinical Academic Building, 125 Patterson Street, New Brunswick, NJ 08901, USA; Department of Chemical and Biochemical Engineering, Rutgers University, 98 Brett Road, Piscataway, NJ 08854, USA. Electronic address: yannis@rci.rutgers.edu.

Abstract

Analysis of heart rate variability (HRV) is a promising diagnostic technique due to the noninvasive nature of the measurements involved and established correlations with disease severity, particularly in inflammation-linked disorders. However, the complexities underlying the interpretation of HRV complicate understanding the mechanisms that cause variability. Despite this, such interpretations are often found in literature. In this paper we explored mathematical modeling of the relationship between the autonomic nervous system and the heart, incorporating basic mechanisms such as perturbing mean values of oscillating autonomic activities and saturating signal transduction pathways to explore their impacts on HRV. We focused our analysis on human endotoxemia, a well-established, controlled experimental model of systemic inflammation that provokes changes in HRV representative of acute stress. By contrasting modeling results with published experimental data and analyses, we found that even a simple model linking the autonomic nervous system and the heart confound the interpretation of HRV changes in human endotoxemia. Multiple plausible alternative hypotheses, encoded in a model-based framework, equally reconciled experimental results. In total, our work illustrates how conventional assumptions about the relationships between autonomic activity and frequency-domain HRV metrics break down, even in a simple model. This underscores the need for further experimental work towards unraveling the underlying mechanisms of autonomic dysfunction and HRV changes in systemic inflammation. Understanding the extent of information encoded in HRV signals is critical in appropriately analyzing prior and future studies.

KEYWORDS:

Autonomic dysfunction; Human endotoxemia; Mathematical modeling

PMID:
24680646
PMCID:
PMC4159048
DOI:
10.1016/j.mbs.2014.03.010
[Indexed for MEDLINE]
Free PMC Article

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