Sensitivity analysis of closed-loop one-chamber and four-chamber models with baroreflex

The baroreflex is one of the most important control mechanisms in the human cardiovascular system. This work utilises a closed-loop in silico model of baroreflex regulation, coupled to pulsatile mechanical models with (i) one heart chamber and 36-parameters and (ii) four chambers and 51 parameters. We perform the first global sensitivity analysis of these closed-loop systems which considers both cardiovascular and baroreflex parameters, and compare the models with their respective unregulated equivalents. Results show the reduced influence of regulated parameters compared to unregulated equivalents and that, in the physiological resting state, model outputs (pressures, heart rate, cardiac output etc.) are most sensitive to parasympathetic arc parameters. This work provides insight into the effects of regulation and model input parameter influence on clinical metrics, and constitutes a first step to understanding the role of regulation in models for personalised healthcare.

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Publication Details

Journal
PLoS Computational Biology
Published
2024-12-23
DOI
https://doi.org/10.1371/journal.pcbi.1012377
Citations
1
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
0.40

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article

Sensitivity analysis of closed-loop one-chamber and four-chamber models with baroreflex

Ian Halliday, Harry Saxton, Andrew Narracott, Karolina Tlałka et al.
1 citations
PLoS Computational Biology
Heart Rate Variability and Autonomic Control
0.40
article

Sensitivity analysis of closed-loop one-chamber and four-chamber models with baroreflex

Ian Halliday, Harry Saxton, Andrew Narracott, Karolina Tlałka, Xu Xu, Daniel James Taylor, M. Malawski
article en
1 citations

Abstract

The baroreflex is one of the most important control mechanisms in the human cardiovascular system. This work utilises a closed-loop in silico model of baroreflex regulation, coupled to pulsatile mechanical models with (i) one heart chamber and 36-parameters and (ii) four chambers and 51 parameters. We perform the first global sensitivity analysis of these closed-loop systems which considers both cardiovascular and baroreflex parameters, and compare the models with their respective unregulated equivalents. Results show the reduced influence of regulated parameters compared to unregulated equivalents and that, in the physiological resting state, model outputs (pressures, heart rate, cardiac output etc.) are most sensitive to parasympathetic arc parameters. This work provides insight into the effects of regulation and model input parameter influence on clinical metrics, and constitutes a first step to understanding the role of regulation in models for personalised healthcare.

PLoS Computational BiologyVol. 20(12)
Insigneo (GB), AGH University of Krakow (PL), University of Sheffield (GB)
European Commission, Fundacja na rzecz Nauki Polskiej, Infrastruktura PL-Grid, Ministry of Science and Higher Education of the Russian Federation, European Regional Development Fund, Academic Computer Centre Cyfronet, AGH University of Science and Technology
Good health and well-being
Openalex Percentile: Top 29%
Heart Rate Variability and Autonomic Control
0.40
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Sensitivity analysis of closed-loop one-chamber and four-chamber models with baroreflex — Ian Halliday, Harry Saxton, et al. · PLoS Computational Biology (2024) | TGRS Research Map | TGRS