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Comparison between two different cardiovascular models during a hemorrhagic shock scenario

1 CNR-IRIB BioMatLab (Biomathematics Laboratory), Via Ugo La Malfa 153, 90146 Palermo, Italy
2 CNR-IASI BioMatLab (Biomathematics Laboratory), UCSC Largo A. Gemelli 8, 00168 Rome, Italy
3 Department of Mathematics, King Mongkut’s Institute of Technology Ladkrabang Bangkok, 10520, Thailand

Hemorrhagic shock is a form of hypovolemic shock determined by rapid and large loss of intravascular blood volume and represents the first cause of death in the world, whether on the battlefield or in civilian traumatology. For this, the ability to prevent hemorrhagic shock remains one of the greatest challenges in the medical and engineering fields. The use of mathematical models of the cardiocirculatory system has improved the capacity, on one hand, to predict the risk of hemorrhagic shock and, on the other, to determine efficient treatment strategies. In this paper, a comparison between two mathematical models that simulate several hemorrhagic scenarios is presented. The models considered are the Guyton and the Zenker model. In the vast panorama of existing cardiovascular mathematical models, we decided to compare these two models because they seem to be at the extremes as regards the complexity and the detail of information that they analyze. The Guyton model is a complex and highly structured model that represents a milestone in the study of the cardiovascular system; the Zenker model is a more recent one, developed in 2007, that is relatively simple and easy to implement. The comparison between the two models offers new prospects for the improvement of mathematical models of the cardiovascular system that may prove more effective in the study of hemorrhagic shock.
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Keywords cardiovascular model; hemodynamics; blood flow simulation; hemorrhage; hemorrhagic shock

Citation: Luciano Curcio, Valerio Cusimano, Laura D’Orsi, Jiraphat Yokrattanasak, Andrea De Gaetano. Comparison between two different cardiovascular models during a hemorrhagic shock scenario. Mathematical Biosciences and Engineering, 2020, 17(5): 5027-5058. doi: 10.3934/mbe.2020272

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