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

Karolina Tlałka,

Harry Saxton, Ian Halliday

и другие.

PLoS Computational Biology, Год журнала: 2024, Номер 20(12), С. e1012377 - e1012377

Опубликована: Дек. 23, 2024

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

Язык: Английский

Quantifying the influence of combined lung and kidney support using a cardiovascular model and sensitivity analysis-informed parameter identification DOI Creative Commons
Jan‐Niklas Thiel, Ana Martins Costa, Bettina Wiegmann

и другие.

Computers in Biology and Medicine, Год журнала: 2025, Номер 186, С. 109668 - 109668

Опубликована: Янв. 17, 2025

Язык: Английский

Процитировано

0

The Impact of Experimental Designs & System Sloppiness on the Personalisation Process: A Cardiovascular Perspective DOI Creative Commons
Harry Saxton, Daniel Taylor, Gabriele Faulkner

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 10, 2024

Abstract To employ a reduced-order cardiovascular model as digital twin for personalised medicine, it is essential to understand how uncertainties in the model’s input parameters affect its outputs. The aim identify set of that can serve clinical biomarkers, providing insight into patient’s physiological state. Given challenge finding useful data, careful consideration must be given experimental design used acquire patient-specific parameters. In this paper, we conduct first quantification system’s sloppiness elucidate structure parameter space. By utilising Sobol indices and examining various synthetic measures with increasing invasiveness, uncover personalisation process are contingent upon chosen design. Our findings reveal continuous induce system increase number personalisable whereas discrete measurements produce non-sloppy reduced biomarkers. This study underscores necessity available data differing measurement sets significantly impact personalisation. Author Summary computational models replicate physical systems — becoming vital tools understanding predicting individual health. explores models, which simulate heart circulatory functions from metrics may derived. These provide insights health treatment planning. A key building these addressing “sloppiness,” property provides response surface one calibrates searching global minimum point, position space best represents patients order personalise different types compared to. We examined ranging simple blood pressure readings detailed invasive waveform results show biomarkers but make more complex through increased sloppiness. contrast, simpler reduce simplifying yield fewer analysing designs on process, our work offers practical improving reliability twins, supporting their adoption medicine.

Язык: Английский

Процитировано

0

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

Karolina Tlałka,

Harry Saxton, Ian Halliday

и другие.

PLoS Computational Biology, Год журнала: 2024, Номер 20(12), С. e1012377 - e1012377

Опубликована: Дек. 23, 2024

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

Язык: Английский

Процитировано

0