Numerical Simulation of the Effect of Sodium Profile on Cardiovascular Response to Hemodialysis

Lim, Ki Moo; Choi, Sung Wook; Min, Byoung-Goo; Shim, Eun Bo

doi:10.3349/ymj.2008.49.4.581

Cited by 3 publications

(8 citation statements)

References 12 publications

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“…A model that combined whole body circulation with detailed kidneys representation, along with baroreflex control and dialysis unit was developed. While the present model derives from previous developments by others (Coli et al , 1998; Heldt, 2006; Lim et al , 2008), this work used it in assessing a therapy (therapeutic hypothermia) pertinent to our clinical research. As seen in Figure 1 , our implementation is capable of qualitatively reproducing flow-pressure waveforms (Olufsen et al , 2000), in addition to providing difficult to measure information such as shear as well as population wide expectation.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…The composite model consists of a whole body circulation model where baroreflex control is present, which is coupled to a representation of a dialysis machine. A whole body blood circulation model (Heldt et al , 2002; Heldt et al , 2010) with known baroreflex control mechanisms (deBoer et al , 1987; Schuessler et al , 1988; Lin et al , 2013a) was coupled to a virtual dialysis unit (Ursino et al , 2000; Lim et al , 2008). The circulation model was extended to include detailed kidneys.…”

Section: Methodsmentioning

confidence: 99%

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Using a Human Circulation Mathematical Model to Simulate the Effects of Hemodialysis and Therapeutic Hypothermia

Sun

et al. 2021

Preprint

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The human blood circulation is an intricate process regulated by multiple biophysical factors. Our patients often suffer from renal disease and atrial fibrillation, and are given treatments such as therapeutic hypothermia, exercise, and hemodialysis. In this work, a hemodynamic mathematical model of human circulation coupled to a representative dialysis machine is developed and used to explore causal mechanisms of our recent clinical observations. An ordinary differential equation model consisting of human whole body circulation, baroreflex control, and a hemodialysis machine was implemented. Experimentally informed parameter alterations were used to implement hemodialysis and therapeutic hypothermia. By means of parameter perturbation, four model populations encompassing baseline, dialyzed, hypothermia treated, and simultaneous dialyzed with hypothermia were generated. In model populations, multiple conditions including atrial fibrillation, exercise, and renal failure were simulated. The effects of all conditions on clinically relevant non-invasive measurables such as heart rate and blood pressure were quantified. A parameter sensitivity analysis was implemented to rank model output influencing parameters in the presented model. Results were interpreted as alterations of the respective populations mean values and standard deviations of the clinical measurables, both in relation to the baseline population. A clinical measurables smaller standard deviation (in comparison to baseline population) was interpreted as a stronger association between a given clinical measure and the corresponding underlying process, which may permit the use of deducing one by observation of the other. The modelled dialysis was observed to increase systolic blood pressure, vessel shear, and heart rate. Therapeutic hypothermia was observed to reduce blood pressure as well as the intra-population standard deviation (heterogeneity) of blood flow in the large (aorta) and small (kidney) vasculature. Therapeutic hypothermia reduced shear in vessels, suggesting a potential benefit with respect to endothelial dysfunction and maintenance of microcirculatory blood flow. The action of therapeutic hypothermia under conditions such as atrial fibrillation, exercise, and renal failure was to reduce total blood flow, which was applicable in all simulated populations. Therapeutic hypothermia did not affect the dialysis function, but exercise improved the efficacy of dialysis by facilitating water removal. This study illuminates some mechanisms of action for therapeutic hypothermia. It also suggests clinical measurables that may be used as surrogates to diagnose underlying diseases such as atrial fibrillation.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Using a Human Circulation Mathematical Model to Simulate the Effects of Hemodialysis and Therapeutic Hypothermia

Sun

et al. 2021

Preprint

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“…The composite model consists of a whole body human circulation model where baroreflex control is present, which is coupled to a representation of a dialysis machine. A whole body human circulation model [15,16] with known baroreflex control mechanisms [27][28][29] was coupled to a virtual dialysis unit [26,30] (see Figure 2 and Figures S1-S3). Model parameters were inherited from the respective calibrated parent sub-models [15,26,27].…”

Section: Model Componentsmentioning

confidence: 99%

“…Each renal microvascular bed was assigned resistance and capacitance values derived from the parent model [15]. A virtual hemodialysis system [26,30] was incorporated to model the impact of dialysis as a clearance of solutes (toxins and water). The implementation of hemodialysis consists of three fluid compartments and two solute compartments, as well as the dialyzer unit.…”

Section: Model Componentsmentioning

confidence: 99%

Using a Human Circulation Mathematical Model to Simulate the Effects of Hemodialysis and Therapeutic Hypothermia

et al. 2021

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Background: We developed a hemodynamic mathematical model of human circulation coupled to a virtual hemodialyzer. The model was used to explore mechanisms underlying our clinical observations involving hemodialysis. Methods: The model consists of whole body human circulation, baroreflex feedback control, and a hemodialyzer. Four model populations encompassing baseline, dialysed, therapeutic hypothermia treated, and simultaneous dialysed with hypothermia were generated. In all populations atrial fibrillation and renal failure as co-morbidities, and exercise as a treatment were simulated. Clinically relevant measurables were used to quantify the effects of each in silico experiment. Sensitivity analysis was used to uncover the most relevant parameters. Results: Relative to baseline, the modelled dialysis increased the population mean diastolic blood pressure by 5%, large vessel wall shear stress by 6%, and heart rate by 20%. Therapeutic hypothermia increased systolic blood pressure by 3%, reduced large vessel shear stress by 15%, and did not affect heart rate. Therapeutic hypothermia reduced wall shear stress by 15% in the aorta and 6% in the kidneys, suggesting a potential anti-inflammatory benefit. Therapeutic hypothermia reduced cardiac output under atrial fibrillation by 12% and under renal failure by 20%. Therapeutic hypothermia and exercise did not affect dialyser function, but increased water removal by approximately 40%. Conclusions: This study illuminates some mechanisms of the action of therapeutic hypothermia. It also suggests clinical measurables that may be used as surrogates to diagnose underlying diseases such as atrial fibrillation.

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“…ODE models of organs [12], feedback mechanisms such as baroreflex [ref], and surgical instruments such as dialyzer machines [13,14] have also been used to improve our understanding of processes underlying clinical practices. Others have used composite models to assess the efficacy of surgeries such as dialysis [15].…”

Section: Introductionmentioning

confidence: 99%

The Role of Extra-Coronary Vascular Conditions that Affect Coronary Fractional Flow Reserve Estimation

Joseph

Lee

Goldman

et al. 2021

Functional Imaging and Modeling of the Heart

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The treatment of coronary stenosis is often based upon invasive high risk surgical assessment. The surgical assessment quantifies the fractional flow reserve (FFR), a ratio of distal to proximal pressures in respect of the stenosis. Non-invasive imaging-computational methodologies call for robust and calibrated mathematical descriptions of the coronary vasculature that can be personalized. In addition, it is important to understand non-vascular factors that FFR. In this preliminary work, a 0D coronary vasculature model capable of personalization was implemented. The model was used to demonstrate the roles of focal and extended stenosis (intra-vascular), as well as microvascular disease and atrial fibrillation (extra-vascular) on FFR. It was found that FFR the right coronary artery is maximally affected by disease conditions. Interestingly, the severity of both microvascular disease and atrial fibrillation were found to be secondary to their mere presence regarding the modelling based FFR estimation. The 0D model provides a computationally inexpensive instrument for in silico coronary blood flow investigation as well as clinical-imaging decision making. Furthermore, it establishes a basis for 3D computational fluid dynamics assessment of FFR in patient specific geometries.

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Numerical Simulation of the Effect of Sodium Profile on Cardiovascular Response to Hemodialysis

Cited by 3 publications

References 12 publications

Using a Human Circulation Mathematical Model to Simulate the Effects of Hemodialysis and Therapeutic Hypothermia

Using a Human Circulation Mathematical Model to Simulate the Effects of Hemodialysis and Therapeutic Hypothermia

Using a Human Circulation Mathematical Model to Simulate the Effects of Hemodialysis and Therapeutic Hypothermia

The Role of Extra-Coronary Vascular Conditions that Affect Coronary Fractional Flow Reserve Estimation

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