Pain perception in healthy volunteers: effect of repeated exposure to experimental systemic inflammation

Janum, Susanne; Nielsen, Signe Tellerup; Werner, Mads U.; Mehlsen, Jesper; Kehlet, Henrik; Møller, Kirsten

doi:10.1177/1753425916663638

Cited by 17 publications

(72 citation statements)

References 37 publications

(83 reference statements)

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“…We compute nominal parameter values using a combination of literature and subject‐specific values extracted from the individual data reported by Janum et al . (2016) and the mean data reported by Copeland et al . (2005).…”

Section: Methodsmentioning

confidence: 60%

“…The model is calibrated to data from 20 healthy young individuals using data reported by Janum et al . (2016) and validated against data reported by Copeland et al . (2005).…”

Section: Introductionmentioning

confidence: 69%

“…The present study analyzes previously published data reported by Janum et al . (2016) and Copeland et al . (2005).…”

Section: Methodsmentioning

confidence: 97%

“…2014; Janum et al . 2016) have shown a dose‐dependent relationship between pain perception and inflammation. Thus, we model the PT as

\frac{d PT}{d t} = - k_{PT E} E normalPT + k_{normalPT} (P {normalT}_{normalb} - PT),

where

k_{P T E}

and

k_{P T}

are rate constants,

P {normalT}_{normalb}

is the baseline PT, and

E

is the endotoxin.…”

Section: Methodsmentioning

confidence: 99%

“…2015) and lowers the pain perception threshold (Janum et al . 2016). Temperature and BP modulate HR (Karjalainen & Viitasalo, 1986; Yamazaki et al .…”

Section: Methodsmentioning

confidence: 99%

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A physiological model of the inflammatory‐thermal‐pain‐cardiovascular interactions during an endotoxin challenge

Dobreva

Brady‐Nicholls

Larripa

et al. 2021

The Journal of Physiology

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Key points Inflammation in response to bacterial endotoxin challenge impacts physiological functions, including cardiovascular, thermal and pain dynamics, although the mechanisms are poorly understood. We develop an innovative mathematical model incorporating interaction pathways between inflammation and physiological processes observed in response to an endotoxin challenge. We calibrate the model to individual data from 20 subjects in an experimental study of the human inflammatory and physiological responses to endotoxin, and we validate the model against human data from an independent study. Using the model to simulate patient responses to different treatment modalities reveals that a multimodal treatment combining several therapeutic strategies gives the best recovery outcome. Abstract Uncontrolled, excessive production of pro‐inflammatory mediators from immune cells and traumatized tissues can cause systemic inflammatory conditions such as sepsis, one of the ten leading causes of death in the USA, and one of the three leading causes of death in the intensive care unit. Understanding how inflammation affects physiological processes, including cardiovascular, thermal and pain dynamics, can improve a patient's chance of recovery after an inflammatory event caused by surgery or a severe infection. Although the effects of the autonomic response on the inflammatory system are well‐known, knowledge about the reverse interaction is lacking. The present study develops a mathematical model analyzing the inflammatory system's interactions with thermal, pain and cardiovascular dynamics in response to a bacterial endotoxin challenge. We calibrate the model with individual data from an experimental study of the inflammatory and physiological responses to a one‐time administration of endotoxin in 20 healthy young men and validate it against data from an independent endotoxin study. We use simulation to explore how various treatments help patients exposed to a sustained pathological input. The treatments explored include bacterial endotoxin adsorption, antipyretics and vasopressors, as well as combinations of these. Our findings suggest that the most favourable recovery outcome is achieved by a multimodal strategy, combining all three interventions to simultaneously remove endotoxin from the body and alleviate symptoms caused by the immune system as it fights the infection.

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Section: Methodsmentioning

confidence: 60%

“…The model is calibrated to data from 20 healthy young individuals using data reported by Janum et al . (2016) and validated against data reported by Copeland et al . (2005).…”

Section: Introductionmentioning

confidence: 69%

“…The present study analyzes previously published data reported by Janum et al . (2016) and Copeland et al . (2005).…”

Section: Methodsmentioning

confidence: 97%

“…2014; Janum et al . 2016) have shown a dose‐dependent relationship between pain perception and inflammation. Thus, we model the PT as

\frac{d PT}{d t} = - k_{PT E} E normalPT + k_{normalPT} (P {normalT}_{normalb} - PT),

where

k_{P T E}

and

k_{P T}

are rate constants,

P {normalT}_{normalb}

is the baseline PT, and

E

is the endotoxin.…”

Section: Methodsmentioning

confidence: 99%

“…2015) and lowers the pain perception threshold (Janum et al . 2016). Temperature and BP modulate HR (Karjalainen & Viitasalo, 1986; Yamazaki et al .…”

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations