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Modelling the dynamic interaction of systemic inflammation and the hypothalamic–pituitary–adrenal (HPA) axis during and after cardiac surgery

Major surgery and critical illness produce a potentially life-threatening systemic inflammatory response. The hypothalamic–pituitary–adrenal (HPA) axis is one of the key physiological systems that counterbalances this systemic inflammation through changes in adrenocorticotrophic hormone (ACTH) and c...

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Autores principales: Galvis, Daniel, Zavala, Eder, Walker, Jamie J., Upton, Thomas, Lightman, Stafford L., Angelini, Gianni D., Evans, Jon, Rogers, Chris A., Phillips, Kirsty, Gibbison, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9042572/
https://www.ncbi.nlm.nih.gov/pubmed/35472267
http://dx.doi.org/10.1098/rsif.2021.0925
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author Galvis, Daniel
Zavala, Eder
Walker, Jamie J.
Upton, Thomas
Lightman, Stafford L.
Angelini, Gianni D.
Evans, Jon
Rogers, Chris A.
Phillips, Kirsty
Gibbison, Ben
author_facet Galvis, Daniel
Zavala, Eder
Walker, Jamie J.
Upton, Thomas
Lightman, Stafford L.
Angelini, Gianni D.
Evans, Jon
Rogers, Chris A.
Phillips, Kirsty
Gibbison, Ben
author_sort Galvis, Daniel
collection PubMed
description Major surgery and critical illness produce a potentially life-threatening systemic inflammatory response. The hypothalamic–pituitary–adrenal (HPA) axis is one of the key physiological systems that counterbalances this systemic inflammation through changes in adrenocorticotrophic hormone (ACTH) and cortisol. These hormones normally exhibit highly correlated ultradian pulsatility with an amplitude modulated by circadian processes. However, these dynamics are disrupted by major surgery and critical illness. In this work, we characterize the inflammatory, ACTH and cortisol responses of patients undergoing cardiac surgery and show that the HPA axis response can be classified into one of three phenotypes: single-pulse, two-pulse and multiple-pulse dynamics. We develop a mathematical model of cortisol secretion and metabolism that predicts the physiological mechanisms responsible for these different phenotypes. We show that the effects of inflammatory mediators are important only in the single-pulse pattern in which normal pulsatility is lost—suggesting that this phenotype could be indicative of the greatest inflammatory response. Investigating whether and how these phenotypes are correlated with clinical outcomes will be critical to patient prognosis and designing interventions to improve recovery.
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spelling pubmed-90425722022-04-29 Modelling the dynamic interaction of systemic inflammation and the hypothalamic–pituitary–adrenal (HPA) axis during and after cardiac surgery Galvis, Daniel Zavala, Eder Walker, Jamie J. Upton, Thomas Lightman, Stafford L. Angelini, Gianni D. Evans, Jon Rogers, Chris A. Phillips, Kirsty Gibbison, Ben J R Soc Interface Life Sciences–Mathematics interface Major surgery and critical illness produce a potentially life-threatening systemic inflammatory response. The hypothalamic–pituitary–adrenal (HPA) axis is one of the key physiological systems that counterbalances this systemic inflammation through changes in adrenocorticotrophic hormone (ACTH) and cortisol. These hormones normally exhibit highly correlated ultradian pulsatility with an amplitude modulated by circadian processes. However, these dynamics are disrupted by major surgery and critical illness. In this work, we characterize the inflammatory, ACTH and cortisol responses of patients undergoing cardiac surgery and show that the HPA axis response can be classified into one of three phenotypes: single-pulse, two-pulse and multiple-pulse dynamics. We develop a mathematical model of cortisol secretion and metabolism that predicts the physiological mechanisms responsible for these different phenotypes. We show that the effects of inflammatory mediators are important only in the single-pulse pattern in which normal pulsatility is lost—suggesting that this phenotype could be indicative of the greatest inflammatory response. Investigating whether and how these phenotypes are correlated with clinical outcomes will be critical to patient prognosis and designing interventions to improve recovery. The Royal Society 2022-04-27 /pmc/articles/PMC9042572/ /pubmed/35472267 http://dx.doi.org/10.1098/rsif.2021.0925 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Mathematics interface
Galvis, Daniel
Zavala, Eder
Walker, Jamie J.
Upton, Thomas
Lightman, Stafford L.
Angelini, Gianni D.
Evans, Jon
Rogers, Chris A.
Phillips, Kirsty
Gibbison, Ben
Modelling the dynamic interaction of systemic inflammation and the hypothalamic–pituitary–adrenal (HPA) axis during and after cardiac surgery
title Modelling the dynamic interaction of systemic inflammation and the hypothalamic–pituitary–adrenal (HPA) axis during and after cardiac surgery
title_full Modelling the dynamic interaction of systemic inflammation and the hypothalamic–pituitary–adrenal (HPA) axis during and after cardiac surgery
title_fullStr Modelling the dynamic interaction of systemic inflammation and the hypothalamic–pituitary–adrenal (HPA) axis during and after cardiac surgery
title_full_unstemmed Modelling the dynamic interaction of systemic inflammation and the hypothalamic–pituitary–adrenal (HPA) axis during and after cardiac surgery
title_short Modelling the dynamic interaction of systemic inflammation and the hypothalamic–pituitary–adrenal (HPA) axis during and after cardiac surgery
title_sort modelling the dynamic interaction of systemic inflammation and the hypothalamic–pituitary–adrenal (hpa) axis during and after cardiac surgery
topic Life Sciences–Mathematics interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9042572/
https://www.ncbi.nlm.nih.gov/pubmed/35472267
http://dx.doi.org/10.1098/rsif.2021.0925
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