Understanding post-spaceflight orthostatic intolerance - a simulation study

Heldt, Thomas; Mark, Roger G.

doi:10.1109/cic.2005.1588180

Cited by 7 publications

(3 citation statements)

References 6 publications

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“…It is a safe, cost-effective and feasible way to predict changes and responses to treatment in space travelers. The approach has been used to simulate post flight orthostatic intolerance 16 , 17 , short-term adaptations to low gravity and the effectiveness of the LBNP countermeasure 18 , and cardiovascular deconditioning during long-term space flight 19 . However, the effect of a prolonged (>6 months) exposure to microgravity on orthostatic intolerance has never been modelled.…”

Section: Introductionmentioning

confidence: 99%

Computational modeling of orthostatic intolerance for travel to Mars

et al. 2022

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Astronauts in a microgravity environment will experience significant changes in their cardiopulmonary system. Up until now, there has always been the reassurance that they have real-time contact with experts on Earth. Mars crew however will have gaps in their communication of 20 min or more. In silico experiments are therefore needed to assess fitness to fly for those on future space flights to Mars. In this study, we present an open-source controlled lumped mathematical model of the cardiopulmonary system that is able simulate the short-term adaptations of key hemodynamic parameters to an active stand test after being exposed to microgravity. The presented model is capable of adequately simulating key cardiovascular hemodynamic changes—over a short time frame—during a stand test after prolonged spaceflight under different gravitational conditions and fluid loading conditions. This model can form the basis for further exploration of the ability of the human cardiovascular system to withstand long-duration space flight and life on Mars.

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Section: Introductionmentioning

confidence: 99%

Computational modeling of orthostatic intolerance for travel to Mars

et al. 2022

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“…In this study, a cardiovascular model of five differential equations is presented, which is a reduced proposal based on the closed-loop model of Pironet et al Due to the complex circulatory interactions, the model-based method and the mathematical descriptions of the system has been used for monitoring and analyzing haemodynamic signals. Some applications of this kind of models are teaching quantitative physiology [8], simulating cardiovascular adaptation to orthostatic stress [7] and computing stressed blood volume [12].…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modelling of the Cardiovascular System Haemodynamics

Hernández-Ramírez

Fraguela-Collar

López

2016

RCS

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In this paper we propose a model of the cardiovascular system, where stressed blood volume is a model parameter instead of an initial condition. Stressed blood volume (SBV) is an important indicator of fluid responsiveness, i.e., this term can help to classify patients between responders and non-responders to fluid therapy. We study a six compartment model, then using the conservation of total blood volume, one differential equation of the original model is omitted and a new model is obtained. Comparing the haemodynamic signals of the previous model and the new version, we show that the simulations are qualitatively similar. One important difference with the original model is that the initial conditions for solving the proposed model are arbitrary. This allows us to perform a sensitivity analysis using automatic differentiation of the reduced model for all model parameters without excluding any parameter a priori, unlike the authors of the original formulation have done. This analysis showed that two parameters, the heart period and the stressed blood volume, have a major effect on the performance of the model.

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“…We tested our simulations against a series of experimental observations by implementing a variety of stress tests, such as head-up tilt, supine to standing, lower-body negative pressure, and short-radius centrifugation, all of which are commonly used in clinical or research settings to assess orthostatic tolerance [17,52]. Figure 3 shows simulations (solid lines) of the steady-state changes in mean arterial blood pressure and heart rate in response to head-up tilts to varying angles of elevation [17,19], along with experimental data taken from Smith and co-workers [40]. (The dashed lines in this and later figures from simulations indicate the 95% confidence limits of the nominal simulation on the basis of representative population Fig.…”

Section: Simulationmentioning

confidence: 99%

Mathematical Modeling of Physiological Systems

Heldt

Verghese

Mark

2012

Lecture Notes in Mathematics

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Although mathematical modeling has a long and very rich tradition in physiology, the recent explosion of biological, biomedical, and clinical data from the cellular level all the way to the organismic level promises to require a renewed emphasis on computational physiology, to enable integration and analysis of vast amounts of life-science data. In this introductory chapter, we touch upon four modeling-related themes that are central to a computational approach to physiology, namely simulation, exploration of hypotheses, parameter estimation, and modelorder reduction. In illustrating these themes, we will make reference to the work of others contained in this volume, but will also give examples from our own work on cardiovascular modeling at the systems-physiology level.

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Understanding post-spaceflight orthostatic intolerance - a simulation study

Abstract: Abstract

Cited by 7 publications

References 6 publications

Computational modeling of orthostatic intolerance for travel to Mars

Computational modeling of orthostatic intolerance for travel to Mars

Mathematical Modelling of the Cardiovascular System Haemodynamics

Mathematical Modeling of Physiological Systems

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