Optimization of Oxygen Delivery in Fluid Resuscitation for Hemorrhagic Shock: A Computer Simulation Study

Siam, Jamal; Mandel, Yossi; Barnea, Ofer

doi:10.1007/s13239-013-0169-z

Cited by 9 publications

(36 citation statements)

References 23 publications

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“…Given the undeniable complexity that underlies fluid shift between the intravascular and interstitial compartments, it can be challenging to mathematically model the fluid shift in an individual subject or patient. Existing models of fluid shift can reproduce the volume changes in the blood and interstitial fluid (Cervera and Moss, 1974 ; Pirkle and Gann, 1975 ; Hedlund et al, 1988 ; Mazzoni et al, 1988 ; Arturson et al, 1989 ; Carlson et al, 1996 ; Gyenge et al, 2003 ; Tatara et al, 2007 ) and even intracellular fluid (Hedlund et al, 1988 ; Mazzoni et al, 1988 ; Arturson et al, 1989 ; Carlson et al, 1996 ; Ursino and Innocenti, 1997 ; Gyenge et al, 2003 ; Fernandez de Canete and Del Saz Huang, 2010 ; Siam et al, 2013 ). However, there are so many disparate factors that, without exhaustive and impractical measurements, it is not possible to comprehensively characterize the fluid shift associated with an individual.…”

Section: Introductionmentioning

confidence: 99%

A Lumped-Parameter Subject-Specific Model of Blood Volume Response to Fluid Infusion

2016

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This paper presents a lumped-parameter model that can reproduce blood volume response to fluid infusion. The model represents the fluid shift between the intravascular and interstitial compartments as the output of a hypothetical feedback controller that regulates the ratio between the volume changes in the intravascular and interstitial fluid at a target value (called “target volume ratio”). The model is characterized by only three parameters: the target volume ratio, feedback gain (specifying the speed of fluid shift), and initial blood volume. This model can obviate the need to incorporate complex mechanisms involved in the fluid shift in reproducing blood volume response to fluid infusion. The ability of the model to reproduce real-world blood volume response to fluid infusion was evaluated by fitting it to a series of data reported in the literature. The model reproduced the data accurately with average error and root-mean-squared error (RMSE) of 0.6 and 9.5% across crystalloid and colloid fluids when normalized by the underlying responses. Further, the parameters derived for the model showed physiologically plausible behaviors. It was concluded that this simple model may accurately reproduce a variety of blood volume responses to fluid infusion throughout different physiological states by fitting three parameters to a given dataset. This offers a tool that can quantify the fluid shift in a dataset given the measured fractional blood volumes.

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Section: Introductionmentioning

confidence: 99%

A Lumped-Parameter Subject-Specific Model of Blood Volume Response to Fluid Infusion

2016

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“…It is perceived as "restoration of the circulation" and that it improves oxygen delivery to tissue. Our previous study [3] showed that this is true to a limited extent. In fact we showed that continuing fluid infusion beyond the point of maximum oxygen delivery will be harmful due to the continuing drop in the oxygen delivery rate ( ).…”

Section: Discussionmentioning

confidence: 88%

“…Mathematical modeling has been used to study and better understand the effects of hemorrhage and fluid resuscitation on blood oxygen transport and its diffusion into tissue. Some of these studies focused on the cardiovascular, hemodynamic and oxygen related phenomena at the system level [3][4][5][6][7][8][9][10][11][12][13], while others developed tissue and oxygen diffusion models using specific parameters at the tissue side [14][15][16][17][18][19][20][21][22][23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Oxygen Transfer to Tissue in Fluid Resuscitation

Siam

Barnea

2015

IFMBE Proceedings

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Abstract-Fluid resuscitation affects blood flow and oxygen concentration which is a direct function of hematocrit and hemoglobin saturation. Administered fluid increases blood flow and oxygen delivery rate but also decreases blood oxygen concentration. This study aims at analyzing the effects of changing blood flow, hematocrit and hemoglobin saturation on oxygen supply to tissue. For this purpose a novel tissue model composed of a set of cascaded and coaxial tissue cylinders was developed. Simulation results showed that oxygen diffusion has higher sensitivity to changes in hematocrit and hemoglobin saturation than to changes in blood flow. Therefore, increasing oxygen carriers and hemoglobin saturation is essential for improving fluid therapy outcomes.

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“…The following equations express the concentration and the amount of oxygen delivered by a deciliter of blood (Eq. ( 18)) [14]:…”

Section: Siammentioning

confidence: 99%

“…Authors such as Frank [2], Guyton et al [3][4][5][6][7][8][9], and Grodins et al [1,10] conducted experiments in their own laboratories, while others, like Beard et al [11], Batzel et al [12], and Zenker et al [13], used reported results obtained from animal models. Still others, such as Siam et al [14], relied mainly on theoretical models.…”

Section: Introductionmentioning

confidence: 99%

Seven Mathematical Models of Hemorrhagic Shock

Curcio

D’Orsi

Gaetano

2021

Computational and Mathematical Methods in Medicine

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Although mathematical modelling of pressure-flow dynamics in the cardiocirculatory system has a lengthy history, readily finding the appropriate model for the experimental situation at hand is often a challenge in and of itself. An ideal model would be relatively easy to use and reliable, besides being ethically acceptable. Furthermore, it would address the pathogenic features of the cardiovascular disease that one seeks to investigate. No universally valid model has been identified, even though a host of models have been developed. The object of this review is to describe several of the most relevant mathematical models of the cardiovascular system: the physiological features of circulatory dynamics are explained, and their mathematical formulations are compared. The focus is on the whole-body scale mathematical models that portray the subject’s responses to hypovolemic shock. The models contained in this review differ from one another, both in the mathematical methodology adopted and in the physiological or pathological aspects described. Each model, in fact, mimics different aspects of cardiocirculatory physiology and pathophysiology to varying degrees: some of these models are geared to better understand the mechanisms of vascular hemodynamics, whereas others focus more on disease states so as to develop therapeutic standards of care or to test novel approaches. We will elucidate key issues involved in the modeling of cardiovascular system and its control by reviewing seven of these models developed to address these specific purposes.

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Optimization of Oxygen Delivery in Fluid Resuscitation for Hemorrhagic Shock: A Computer Simulation Study

Cited by 9 publications

References 23 publications

A Lumped-Parameter Subject-Specific Model of Blood Volume Response to Fluid Infusion

A Lumped-Parameter Subject-Specific Model of Blood Volume Response to Fluid Infusion

Oxygen Transfer to Tissue in Fluid Resuscitation

Seven Mathematical Models of Hemorrhagic Shock

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