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. Author summary: In the era of personalised healthcare, there is a growing need to develop computational models that accurately represent human physiology. Here, we examine two models of the human circulatory system, incorporating the effects of baroreflex regulation— a key neural homeostatic mechanism responsible for controlling blood pressure during rest and exercise on short timescales. We investigate the impact of including baroreflex regulation on clinically significant metrics such as cardiac output. Due to the model's complexity and a large number of parameters, quantifying the effects of regulation in a closed-loop operation was previously deemed infeasible, but by utilising an efficient in silico encapsulation and high-performance computing we are able, here, to quantify the baroreflex's impact on mechanical outputs. [ABSTRACT FROM AUTHOR]