Finite-Element Modeling of Time-Dependent Sodium Exchange across the Hollow Fiber of a Hemodialyzer by Coupling with a Blood Pool Model

Ravagli, Enrico; Grandi, Elena; Riccio, P.; Severi, Stefano

doi:10.5301/ijao.5000528

Cited by 3 publications

(2 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The balance of osmotically active small solutes between intra- and extracellular fluid, being the main driving force for the transport of water across the cellular membrane, must be properly described as well for a correct assessment of the latter. The problem of modelling electrolytes balance during HD has been long discussed with different scope and approaches, from lumped-parameters models with varying degrees of complexity [13–19] to finite elements models of the exchange within the dialyzer [20]. Some of the more recent models proposed the simultaneous description of multiple solutes [15, 18], albeit with a simplified view on transcapillary transport; moreover, very few examples were found of models assessing the contribution of the Na/K ATPase to the kinetics of total osmolarity during HD [14, 21, 22].…”

Section: Introductionmentioning

confidence: 99%

Model of fluid and solute shifts during hemodialysis with active transport of sodium and potassium

et al. 2018

View full text Add to dashboard Cite

BackgroundMathematical models are useful tools to predict fluid shifts between body compartments in patients undergoing hemodialysis (HD). The ability of a model to accurately describe the transport of water between cells and interstitium (Jv,ISIC), and the consequent changes in intracellular volume (ICV), is important for a complete assessment of fluid distribution and plasma refilling. In this study, we propose a model describing transport of fluid in the three main body compartments (intracellular, interstitial and vascular), complemented by transport mechanisms for proteins and small solutes.MethodsThe model was applied to data from 23 patients who underwent standard HD. The substances described in the baseline model were: water, proteins, Na, K, and urea. Small solutes were described with two-compartment kinetics between intracellular and extracellular compartments. Solute transport across the cell membrane took place via passive diffusion and, for Na and K, through the ATPase pump, characterized by the maximum transport rate, JpMAX. From the data we estimated JpMAX and two other parameters linked to transcapillary transport of fluid and protein: the capillary filtration coefficient Lp and its large pores fraction αLP. In an Expanded model one more generic solute was included to evaluate the impact of the number of substances appearing in the equation describing Jv,ISIC.ResultsIn the baseline model, median values (interquartile range) of estimated parameters were: Lp: 11.63 (7.9, 14.2) mL/min/mmHg, αLP: 0.056 (0.050, 0.058), and JpMAX: 5.52 (3.75, 7.54) mmol/min. These values were significantly different from those obtained by the Expanded model: Lp: 8.14 (6.29, 10.01) mL/min/mmHg, αLP: 0.046 (0.038, 0.052), and JpMAX: 16.7 (11.9, 25.2) mmol/min. The relative RMSE (root mean squared error)averaged between all simulated quantities compared to data was 3.9 (3.1, 5.6) %.ConclusionsThe model was able to accurately reproduce most of the changes observed in HD by tuning only three parameters. While the drop in ICV was overestimated by the model, the difference between simulations and data was less than the measurement error. The biggest change in the estimated parameters in the Expanded model was a marked increase of JpMAX indicating that this parameter is highly sensitive to the number of species modeled, and that the value of JpMAX should be interpreted only in relation to this factor.

show abstract

Section: Introductionmentioning

confidence: 99%

Model of fluid and solute shifts during hemodialysis with active transport of sodium and potassium

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Therapies such as hemodialysis [1]- [3] and peritoneal dialysis [4] are the standard for CKD patients; while for AKI, slow, prolonged, one-time treatments are chosen to perform blood purification until kidney function is regained [5]- [7]. The effect of RRTs on the patient has been studied both clinically and with mathematical tools such as kinetic models, developed to describe the transfer of water and solutes across body compartments during RRTs [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

A Differential Optical Sensor for Non-Invasive Real-Time Monitoring of Ultrafiltration Rate in Hemofiltration Therapies

Visotti¹,

Ravagli

Perazzini³

et al. 2018

IEEE Sensors J.

Self Cite

View full text Add to dashboard Cite

Abstract-Hemofiltration (HF) is a group of blood purification therapies used to treat patients with kidney injury. HF works using a process called ultrafiltration (UF) that removes excess liquid accumulated in the patient's body caused by lack of excretion. UF progress is monitored by the HF machine, but the state-of-the-art method is cumbersome and could be more accurate. In this work, a system composed by two optical sensors is proposed for real-time non-invasive estimation of ultrafiltration rate. This new system is simple, rugged, low-cost and operates on sound theoretical foundations. The sensor system has been tested with two different experimental protocols and showed good correlation between its output and the reference value of the ultrafiltration rate (R 2 =0.97), as well as improved accuracy compared to the available commercial machine (≃12ml/h). This system also has the potential to simplify the architecture required by critical care blood purification machines to perform UF control.Index Terms -Biomedical Measurement, Blood, Blood Purification, Hemofiltration, Hemoglobin, Measurement, Optical Sensor, Ultrafiltration I. INTRODUCTIONRenal replacement therapies (RRTs) have been developed to treat individuals affected by kidney failure, known as nephropathic patients. RRTs have the following targets:• Removal of excess fluid accumulated by the patient due to lack of kidney excretion.• Re-balancing concentration of specific substances in blood, for example electrolytes such as sodium.• Removal of the toxic by-products of metabolism, such as urea.Several types of therapies and machines have been developed. The main distinction of therapies is between those developed † First two authors A. Visotti and E. Ravagli contributed equally to this work. A. Visotti, C. Perazzini, D. Drudi, and C. Ghidini are with the company IBD Srl (https://www.ibdsrl.com/), Forlì, Italy.E. Ravagli and S. Severi* are with the Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Cesena, Italy (e-mail: stefano.severi@unibo.it).to treat patients with acute kidney injury (AKI), who are expected to partially or fully regain kidney functionality, and those for patients with chronic kidney disease (CKD), who require periodic treatment for the rest of their lives or until kidney transplant. Therapies such as hemodialysis [1]-[3] and peritoneal dialysis [4] are the standard for CKD patients; while for AKI, slow, prolonged, one-time treatments are chosen to perform blood purification until kidney function is regained [5]- [7]. The effect of RRTs on the patient has been studied both clinically and with mathematical tools such as kinetic models, developed to describe the transfer of water and solutes across body compartments during .This work represents a technological improvement for AKI therapies where fluid removal is the main target -therapies also known as hemofiltration (HF). Fluid removal is performed by means of a physical principle called ultrafiltration (UF) [11]-[13]. Example...

show abstract

A New Method for Continuous Relative Blood Volume and Plasma Sodium Concentration Estimation During Hemodialysis

Ravagli

Holmer

Sörnmo³

et al. 2019

IEEE Trans. Biomed. Eng.

View full text Add to dashboard Cite

Finite-Element Modeling of Time-Dependent Sodium Exchange across the Hollow Fiber of a Hemodialyzer by Coupling with a Blood Pool Model

Abstract: Coupling our FEM hollow fiber model to a simple blood pool model proved to be an effective approach for dynamical analysis of the properties of the hemodialyzer.

Cited by 3 publications

References 36 publications

Model of fluid and solute shifts during hemodialysis with active transport of sodium and potassium

Model of fluid and solute shifts during hemodialysis with active transport of sodium and potassium

A Differential Optical Sensor for Non-Invasive Real-Time Monitoring of Ultrafiltration Rate in Hemofiltration Therapies

A New Method for Continuous Relative Blood Volume and Plasma Sodium Concentration Estimation During Hemodialysis

Contact Info

Product

Resources

About