Why the study?
Current cardiovascular mathematical models cannot mimic variable heart rates, presenting an obstacle to using them for clinical decision-making.
Novel extensions to multi-compartmental models of the cardiovascular and respiratory systems allow for realistic simulation of variable heart rates, improving agreement with measured bio-signals.
Variable-HR model may enable realistic vital-sign simulations for critical care; leaves open prospective validation before clinical adoption.
Current mathematical models of the cardiovascular system that are based on systems of ordinary differential equations are limited in their ability to mimic important features of measured patient data, such as variable heart rates (HR). Such limitations present a significant obstacle in the use of such models for clinical decision-making, as it is the variations in vital signs such as HR and systolic and diastolic blood pressure that are monitored and recorded in typical critical care bedside monitoring systems. In this paper, novel extensions to well-established multi-compartmental models of the cardiovascular and respiratory systems are proposed that permit the simulation of variable HR. Furthermore, a correction to current models is also proposed to stabilize the respiratory behaviour and enable realistic simulation of vital signs over the longer time scales required for clinical management. The results of the extended model developed here show better agreement with measured bio-signals, and these extensions provide an important first step towards estimating model parameters from patient data, using methods such as neural ordinary differential equations. The approach presented is generalizable to many other similar multi-compartmental models of the cardiovascular and respiratory systems.
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Lishak et al. (2023) studied this question.
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