A physiologically based model of vascular refilling during ultrafiltration in hemodialysis

Optical monitoring of hemodialysis using noninvasive measurement of uric acid in the dialysate

The aim of this study was to present a methodology for predicting changes in uric acid concentrations in the blood of chronically hemodialyzed patients based on an optical measurement of the intensity of selected wavelengths in the dialysate. Blood samples were taken from the arterial line every 30 min throughout the hemodialysis period, to measure uric acid levels. Simultaneously, optical measurements were made on dialysate flowing from the dialyzer. Uric acid concentration can be measured either directly from the blood or from dialyzer outflow with acceptable error. In addition, both methods reveal any increased dynamics in uric acid concentration in the initial phase of hemodialysis. The wavelength of the light was adjusted for optimal uric acid particle detection. Comparing the uric acid concentration measured in the blood of patients with the intensity of wave absorption in the dialysate, the functional relationship between the uric acid concentration levels was determined. Using the optical method for measuring uric acid concentration in the dialysate, the concentration of uric acid in the blood during hemodialysis can be non-invasively and accurately estimated. This method can be used to assess the adequacy of hemodialysis by computer acquisition of uric acid concentrations determined in on-line dialysate.

Prevention of Intradialytic Hypotension in Hemodialysis Patients: Current Challenges and Future Prospects

Intradialytic hypotension, defined as rapid decrease in systolic blood pressure of greater than or equal to 20 mmHg or in mean arterial pressure of greater than or equal to 10 mmHg that results in end-organ ischemia and requires countermeasures such as ultrafiltration reduction or saline infusion to increase blood pressure to improve patient's symptoms, is a known complication of hemodialysis and is associated with several potential adverse outcomes. Its pathogenesis is complex and involves both patient-related factors such as age and comorbidities, as well as factors related to the dialysis prescription itself. Key factors include the need for volume removal during hemodialysis and a suboptimal vascular response which compromises the ability to compensate for acute intravascular volume loss. Inadequate vascular refill, incorrect assessment or unaccounted changes of target weight, acute illnesses and medication interference are further potential contributors. Intradialytic hypotension can lead to compromised tissue perfusion and end-organ damage, both acutely and over time, resulting in repetitive injuries. To address these problems, a careful assessment of subjective symptoms, minimizing interdialytic weight gains, individualizing dialysis prescription and adjusting the dialysis procedure based on patients' risk factors can mitigate negative outcomes.

Advances in the Physiology of Transvascular Exchange and A New Look At Rational Fluid Prescription

The Starling principle is a model that explains the transvascular distribution of fluids essentially governed by hydrostatic and oncotic forces, which dynamically allow vascular refilling according to the characteristics of the blood vessel. However, careful analysis of fluid physiology has shown that the principle, while correct, is not complete. The revised Starling principle (Michel-Weinbaum model) provides relevant information on fluid kinetics. Special emphasis has been placed on the endothelial glycocalyx, whose subendothelial area allows a restricted oncotic pressure that limits the reabsorption of fluid from the interstitial space, so that transvascular refilling occurs mainly from the lymphatic vessels. The close correlation between pathological states of the endothelium (eg: sepsis, acute inflammation, or chronic kidney disease) and the prescription of fluids forces the physician to understand the dynamics of fluids in the organism; this will allow rational fluid prescriptions. A theory that integrates the physiology of exchange and transvascular refilling is the "microconstant model", whose variables include dynamic mechanisms that can explain edematous states, management of acute resuscitation, and type of fluids for common clinical conditions. The clinical-physiological integration of the concepts will be the hinges that allow a rational and dynamic prescription of fluids.

Vascular refilling coefficient is not a good marker of whole-body capillary hydraulic conductivity in hemodialysis patients: insights from a simulation study

Refilling of the vascular space through absorption of interstitial fluid by micro vessels is a crucial mechanism for maintaining hemodynamic stability during hemodialysis (HD) and allowing excess fluid to be removed from body tissues. The rate of vascular refilling depends on the imbalance between the Starling forces acting across the capillary walls as well as on their hydraulic conductivity and total surface area. Various approaches have been proposed to assess the vascular refilling process during HD, including the so-called refilling coefficient (Kr) that describes the rate of vascular refilling per changes in plasma oncotic pressure, assuming that other Starling forces and the flow of lymph remain constant during HD. Several studies have shown that Kr decreases exponentially during HD, which was attributed to a dialysis-induced decrease in the whole-body capillary hydraulic conductivity (L_pS). Here, we employ a lumped-parameter mathematical model of the cardiovascular system and water and solute transport between the main body fluid compartments to assess the impact of all Starling forces and the flow of lymph on vascular refilling during HD in order to explain the reasons behind the observed intradialytic decrease in Kr. We simulated several HD sessions in a virtual patient with different blood priming procedures, ultrafiltration rates, session durations, and constant or variable levels of L_pS. We show that the intradialytic decrease in Kr is not associated with a possible reduction of L_pS but results from the inherent assumption that plasma oncotic pressure is the only variable Starling force during HD, whereas in fact other Starling forces, in particular the oncotic pressure of the interstitial fluid, have an important impact on the transcapillary fluid exchange during HD. We conclude that Kr is not a good marker of L_pS and should not be used to guide fluid removal during HD or to assess the fluid status of dialysis patients.

Recent Advances and Future Perspectives in the Use of Machine Learning and Mathematical Models in Nephrology

We reviewed some of the latest advancements in the use of mathematical models in nephrology. We looked over 2 distinct categories of mathematical models that are widely used in biological research and pointed out some of their strengths and weaknesses when applied to health care, especially in the context of nephrology. A mechanistic dynamical system allows the representation of causal relations among the system variables but with a more complex and longer development/implementation phase. Artificial intelligence/machine learning provides predictive tools that allow identifying correlative patterns in large data sets, but they are usually harder-to-interpret black boxes. Chronic kidney disease (CKD), a major worldwide health problem, generates copious quantities of data that can be leveraged by choice of the appropriate model; also, there is a large number of dialysis parameters that need to be determined at every treatment session that can benefit from predictive mechanistic models. Following important steps in the use of mathematical methods in medical science might be in the intersection of seemingly antagonistic frameworks, by leveraging the strength of each to provide better care.

Dynamics of vascular refilling in extended nocturnal hemodialysis

INTRODUCTION

Long dialysis treatments are generally assumed to mitigate the ultrafiltration (UF) induced volume perturbation and to improve vascular refilling because of reduced UF rates and sufficient time for volume re-equilibration. The time course of vascular refilling was therefore examined during extended nocturnal dialysis.

METHODS

For each hour of dialysis, vascular refilling volume was calculated from the absolute blood volume changes and UF volume removed. Absolute blood volume was estimated by indicator dilution at the beginning of dialysis and then tracked with a relative blood volume monitor. The refilling fraction was defined as the ratio of refilling volume to UF volume.

FINDINGS

Ten stable chronic hemodialysis (HD) patients were studied during extended (7 h) nocturnal treatment sessions. Specific UF rate was 4.8 ± 1.8 ml/kg/h. In the 1 h, refilling volume amounted to only 23% of UF volume. Thereafter, refilling fraction steeply increased and reached maximum values in the 2, 3 and 4 h at about mean 90% (91.5%, 88.7%, and 91.1% respectively). From the 5 h on, refilling volume decreased (5 h 81.3%, 6 h 72.5%, 7 h 70.0% of UF volume). Cumulative refilling reached 73.6% of UF volume after 4 h of treatment time. This did not change during the further course of HD. Cumulative refilling volume showed a strong correlation (r = 0.94; p < 0.001) with UF volume. The ratio of blood volume to extracellular volume (R_bex ) was 0.306 ± 0.029 before and slightly but significantly increased to 0.326 ± 0.030 after UF.

DISCUSSION

In spite of low-UF rates and extended treatment times, overall refilling fraction reached only 74% and was not different from the refilling fraction observed in regular HD. This value seems to represent a point where UF-induced volume perturbation is adequately compensated by physiologic control mechanisms.

Impact of the nature of the capillary wall on plasma refilling during hemodialysis

OBJECTIVES

Our aim was to clarify the impact of the nature of the capillary wall, defined by the contribution of large (LP), small (SP), and ultrasmall (UP) pores, on plasma refilling in a hemodialysis session.

METHODS

This study included data from 78 patients. The relative blood volume change (ΔBV%) was monitored using a Crit-Line monitor. A bioimpedance device was used to measure extracellular and intracellular fluid volumes, and the excess fluid mass (M_ExF) was calculated. We simulated blood volume change (sΔBV%) based on a three-pore model. Hydraulic permeability of the capillary wall (LpS) and fractional contribution of LP to LpS (α_LP) were determined by fitting sΔBV to ΔBV. The total refilling volume (TV_ref) was calculated from the total ultrafiltration volume and total blood volume change. Values were standardized to a body surface area of 1.73 m² and are denoted by the subscript BSA.

RESULTS

LpS and α_LP were 3.09 (2.32, 4.68) mL/mmHg/min and 0.069 (0.023, 0.109), respectively. The standardized regression coefficient (β) of the ultrafiltration rate (UFR_BSA) and initial excess fluid mass (M_ExF,_BSA,0) by multiple linear regression analysis of TV_ref,BSA without (Model 1) and with (Model 2) α_LP were as follows: UFR_BSA, 0.714/<0.001 (β/p); M_ExF,_BSA,0, 0.247/<0.001 (Model 1); UFR_BSA, 0.799/<0.001; M_ExF,_BSA,0, 0.066/0.237; and α_LP, -0.327/<0.001 (Model 2).

CONCLUSIONS

The impact of volume overload (M_ExF,_BSA,0) on plasma refilling became insignificant with the addition of α_LP in the model, suggesting that the nature of the capillary wall described by inter-endothelial gaps (LP) may have a greater impact on plasma refilling than volume overload.

Proportional integral feedback control of ultrafiltration rate in hemodialysis

BACKGROUND

Most hemodialysis patients without residual kidney function accumulate fluid between dialysis session that needs to be removed by ultrafiltration. Ultrafiltration usually results in a decline in relative blood volume (RBV). Recent epidemiological research has identified RBV ranges that were associated with significantly better survival. The objective of this work was to develop an ultrafiltration controller to steer a patient's RBV trajectory into these favorable RBV ranges.

METHODS

We designed a proportional-integral feedback ultrafiltration controller that utilizes signals from a device that reports RBV. The control goal is to attain the RBV trajectory associated with improved patient survival. Additional constraints such as upper and lower bounds of ultrafiltration volume and rate were realized. The controller was evaluated in in silico and ex vivo bench experiments, and in a clinical proof-of-concept study in two maintenance dialysis patients.

RESULTS

In all tests, the ultrafiltration controller performed as expected. In the in silico and ex vivo bench experiments, the controller showed robust reaction toward deliberate disruptive interventions (e.g. signal noise; extreme plasma refill rates). No adverse events were observed in the clinical study.

CONCLUSIONS

The ultrafiltration controller can steer RBV trajectories toward desired RBV ranges while obeying to a set of constraints. Prospective studies in hemodialysis patients with diverse clinical characteristics are warranted to further explore the controllers impact on intradialytic hemodynamic stability, quality of life, and long-term outcomes.

Changes in total and segmental extracellular and intracellular volumes with hypotension during hemodialysis measured with bioimpedance spectroscopy

BACKGROUND

Bioelectrical impedance analysis (BIA) devices have been advocated to guide volume management in hemodialysis (HD) patients. We hypothesized that understanding the dynamics of fluid shifts in different body segments may provide additional insight on preventive measures to reduce the risk of intradialytic hypotension.

METHODS

A prospective observational study was conducted among 42 HD patients at risk of hypotension who were admitted as emergencies inpatient.

RESULTS

A total of 191 BIA measurements were made during the 42 HD sessions, and hypotension occurred during 52 measurements (27%). The extracellular water (ECW) to intracellular water ratio (EIR) was measured in different body segments and declined significantly only in the non-access arm with increasing HD session duration (β = -0.04; 95% confidence interval (CI): -0.05 to -0.03, p < 0.01). There was no significant association between EIR and hypotension with respect to the different body segments. Only pre-HD N-terminal-pro b-type natriuretic peptide was significantly associated with hypotension (β = 0.20, 95% CI: 0.04 to 0.89, p = 0.04). There was no association between relative blood volume monitoring change and EIR.

CONCLUSION

In summary, we found that segmental BIA during HD was unable to detect or predict hypotension during dialysis. Although BIA is able to provide information about ECW and guide clinical assessment of volume in HD patients prior to dialysis, our findings did not suggest the use of serial measurements of changes in EIR in different body segments during HD provided sufficient information to predict intradialytic hypotension. Similarly, changes in EIR did not provide information on changes in plasma volume that could potentially trigger interventions to prevent or reduce intra-dialytic hypotension.

Dialysis-Induced Cardiovascular and Multiorgan Morbidity

Hemodialysis has saved many lives, albeit with significant residual mortality. Although poor outcomes may reflect advanced age and comorbid conditions, hemodialysis per se may harm patients, contributing to morbidity and perhaps mortality. Systemic circulatory "stress" resulting from hemodialysis treatment schedule may act as a disease modifier, resulting in a multiorgan injury superimposed on preexistent comorbidities. New functional intradialytic imaging (i.e., echocardiography, cardiac magnetic resonance imaging [MRI]) and kinetic of specific cardiac biomarkers (i.e., Troponin I) have clearly documented this additional source of end-organ damage. In this context, several factors resulting from patient-hemodialysis interaction and/or patient management have been identified. Intradialytic hypovolemia, hypotensive episodes, hypoxemia, solutes, and electrolyte fluxes as well as cardiac arrhythmias are among the contributing factors to systemic circulatory stress that are induced by hemodialysis. Additionally, these factors contribute to patients' symptom burden, impair cognitive function, and finally have a negative impact on patients' perception and quality of life. In this review, we summarize the adverse systemic effects of current intermittent hemodialysis therapy, their pathophysiologic consequences, review the evidence for interventions that are cardioprotective, and explore new approaches that may further reduce the systemic burden of hemodialysis. These include improved biocompatible materials, smart dialysis machines that automatically may control the fluxes of solutes and electrolytes, volume and hemodynamic control, health trackers, and potentially disruptive technologies facilitating a more personalized medicine approach.

All-cause mortality in relation to changes in relative blood volume during hemodialysis

Background

Relative blood volume (RBV) monitoring is widely used in hemodialysis (HD) patients, yet the association between intradialytic RBV and mortality is unknown.

Methods

Intradialytic RBV was recorded once/min during a 6-month baseline period; all-cause mortality was noted during follow-up. RBV at 1, 2 and 3 h into HD served as a predictor of all-cause mortality during follow-up. We employed Kaplan–Meier analysis, univariate and adjusted Cox proportional hazards models for survival analysis.

Results

We studied 842 patients. During follow-up (median 30.8 months), 249 patients (29.6%) died. The following hourly RBV ranges were associated with improved survival: first hour, 93–96% [hazard ratio (HR) 0.58 (95% confidence interval (CI) 0.42–0.79)]; second hour, 89–94% [HR 0.54 (95% CI 0.39–0.75)]; third hour, 86–92% [HR 0.46 (95% CI 0.33–0.65)]. In about one-third of patients the RBV was within these ranges and in two-thirds it was above. Subgroup analysis by median age (≤/> 61 years), sex, race (white/nonwhite), predialysis systolic blood pressure (SBP; ≤/> 130 mmHg) and median interdialytic weight gain (≤/> 2.3 kg) showed comparable favorable RBV ranges. Patients with a 3-h RBV between 86 and 92% were younger, had higher ultrafiltration volumes and rates, similar intradialytic average and nadir SBPs and hypotension rates, lower postdialysis SBP and a lower prevalence of congestive heart failure when compared with patients with an RBV >92%. In the multivariate Cox analysis, RBV ranges remained independent and significant outcome predictors.

Conclusion

Specific hourly intradialytic RBV ranges are associated with lower all-cause mortality in chronic HD patients.

Association between intradialytic central venous oxygen saturation and ultrafiltration volume in chronic hemodialysis patients

Background

Cardiac disease is highly prevalent in hemodialysis (HD) patients. Decreased tissue perfusion, including cardiac, due to high ultrafiltration volumes (UFVs) is considered to be one of the drivers of cardiac dysfunction. While central venous oxygen saturation (ScvO₂) is frequently used as an indicator of cardiac output in non-uremic populations, the relationship of ScvO₂ and UFV in HD patients remains unclear. Our aim was to determine how intradialytic ScvO₂ changes associate with UFV.

Methods

We conducted a 6-month retrospective cohort study in maintenance HD patients with central venous catheters as vascular access. Intradialytic ScvO₂ was measured with the Critline monitor. We computed treatment-level slopes of intradialytic ScvO₂ over time (ScvO₂ trend) and applied linear mixed effects models to assess the association between patient-level ScvO₂ trends and UFV corrected for body weight (cUFV).

Results

We studied 6042 dialysis sessions in 232 patients. In about 62.4% of treatments, ScvO₂ decreased. We observed in nearly 80% of patients an inverse relationship between cUFV and ScvO₂ trend, indicating that higher cUFV is associated with steeper decline in ScvO₂ during dialysis.

Conclusions

In most patients, higher cUFV volumes are associated with steeper intradialytic ScvO₂ drops. We hypothesize that in a majority of patients the intradialytic cardiac function is fluid dependent, so that in the face of high ultrafiltration rates or volume, cardiac pre-load and consequently cardiac output decreases. Direct measurements of cardiac hemodynamics are warranted to further test this hypothesis.

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

Background

Mathematical 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 (J_v,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.

Methods

The 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, Jp_MAX. From the data we estimated Jp_MAX and two other parameters linked to transcapillary transport of fluid and protein: the capillary filtration coefficient Lp and its large pores fraction α_LP. In an Expanded model one more generic solute was included to evaluate the impact of the number of substances appearing in the equation describing J_v,ISIC.

Results

In the baseline model, median values (interquartile range) of estimated parameters were: Lp: 11.63 (7.9, 14.2) mL/min/mmHg, α_LP: 0.056 (0.050, 0.058), and Jp_MAX: 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, α_LP: 0.046 (0.038, 0.052), and Jp_MAX: 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) %.

Conclusions

The 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 Jp_MAX indicating that this parameter is highly sensitive to the number of species modeled, and that the value of Jp_MAX should be interpreted only in relation to this factor.

Individualization of Ultrafiltration in Hemodialysis

OBJECTIVES

There are approximately 660 000 end-stage renal disease patients in the USA, with hemodialysis (HD) the primary form of treatment. High ultrafiltration rates (UFRs) are associated with intradialytic hypotension, a complication associated with adverse clinical outcomes including mortality. Individualized UFR profiles could reduce the incidence of intradialytic hypotension.

METHODS

The patient's fluid dynamics during HD is described by a nonlinear model comprising intravascular and interstitial pools, whose parameters are given by the patient's estimated nominal parameter values with uncertainty ranges; the output measurement is hematocrit. We design UFR profiles that minimize the maximal UFR needed to remove a prescribed volume of fluid within a set time, with hematocrit not exceeding a specified time-varying critical profile.

RESULTS

We present a novel approach to design individualized UFR profiles, and give theoretical results guaranteeing that the system remains within a predefined physiologically plausible region and does not exceed a specified time-invariant critical hematocrit level for all parameters in the uncertainty ranges. We test the performance of our design using a real patient data example. The designed UFR maintains the system below a time-varying critical hematocrit profile in the example.

CONCLUSION

Theoretical results and simulations show that our designed UFR profiles can remove the target amount of fluid in a given time period while keeping the hematocrit below a specified critical profile.

SIGNIFICANCE

Individualization of UFR profiles is now feasible using current HD technology and may reduce the incidence of intradialytic hypotension.

Numerical simulations of the microvascular fluid balance with a non-linear model of the lymphatic system

Fluid homeostasis is required for life. Processes involved in fluid balance are strongly related to exchanges at the microvascular level. Computational models have been presented in the literature to analyze the microvascular-interstitial interactions. As far as we know, none of those models consider a physiological description for the lymphatic drainage-interstitial pressure relation. We develop a computational model that consists of a network of straight cylindrical vessels and an isotropic porous media with a uniformly distributed sink term acting as the lymphatic system. In order to describe the lymphatic flow rate, a non-linear function of the interstitial pressure is defined, based on literature data on the lymphatic system. The proposed model of lymphatic drainage is compared to a linear one, as is typically used in computational models. To evaluate the response of the model, the two are compared with reference to both physiological and pathological conditions. Differences in the local fluid dynamic description have been observed using the non-linear model. In particular, the distribution of interstitial pressure is heterogeneous in all the cases analyzed. The resulting averaged values of the interstitial pressure are also different, and they agree with literature data when using the non-linear model. This work highlights the key role of lymphatic drainage and its modeling when studying the fluid balance in microcirculation for both to physiological and pathological conditions, e.g. uremia.

Does the plasma refilling coefficient change during hemodialysis sessions?

The filtration coefficient in the Starling equation is an important determinant of plasma refilling during hemodialysis. A method for calculating from clinical data an estimate of the filtration coefficient, called the refilling coefficient, was proposed in the past. The assumption behind this method was that the only drive for refilling is the increase in plasma oncotic pressure, and the remaining Starling forces have negligible effect. The refilling coefficient was observed to decrease during hemodialysis, and this was interpreted as a change in the filtration coefficient. The purpose of our study was providing an alternative explanation for the behavior of the refilling coefficient and, using clinical data and mathematical modeling, to predict the values of the immeasurable Starling forces and provide the theoretical basis for the interpretation of the refilling coefficient as the filtration coefficient. Blood volume and bioimpedance data from 23 patients undergoing hemodialysis were used to calculate the refilling coefficient according to the original formulation and to fit a two-compartment model of protein and fluid transport. The changes in the other Starling forces were non-negligible, ranging from 19% to 60% of plasma oncotic pressure. The results showed that the decrease observed in the refilling coefficient is likely caused by neglecting important changes in the Starling forces while deriving the equation for the refilling coefficient. When these Starling forces were taken into account, constant filtration coefficient and dynamic refilling coefficient provided an equivalent description of the data in most cases. However, this was not true for a subgroup of sessions, which suggests that additional factors may also be responsible for the observed decrease in the refilling coefficient.

Changes in Total Protein Concentration Due to Fluid Removal During and Shortly after Hemodialysis

BACKGROUND

Changes in plasma volume during hemodialysis are complex and have been shown to depend on the rate of fluid removal and the degree of fluid overload. We examined changes in total protein concentration during and shortly after a dialysis treatment in archived data from the HEMO study.

METHODS

During follow-up months 4 and 36 of the HEMO study, additional blood samples were obtained during a typical dialysis session at 30 and 60 min after dialysis. In 315 studies from 282 patients where complete data were available, we calculated the concentration change in total protein and compared it to the modeled change in both total body water and extracellular fluid space as derived from 2-pool urea kinetic modeling.

RESULTS

The mean postdialysis modeled urea volume (V) was 31.1 ± 6.18 L. Mean fluid removal was 2.76 ± 1.27 kg, over a session length of 207 ± 28 min. The ratio of predialysis V to postdialysis V averaged 1.090 ± 0.040. The mean TP ratios (post/pre) at 0, 30, and 60 min postdialysis averaged 1.121 ± 0.070 (SD), 1.091 ± 0.090, and 1.091 ± 0.086. The dialysate to serum sodium gradient, studied in a different group of treatments where this information was available, had no impact on these findings, nor did the length of the interdialytic interval.

CONCLUSIONS

On average, after equilibration, the change in plasma volume due to fluid removal is similar to the modeled change in total body water (urea space), irrespective of dialysate to serum sodium gradient. This supports previous observations that during dialysis with ultrafiltration, plasma volume contracts to a lesser degree than the interstitial volume and that some fluid may be removed from spaces other than the extracellular fluid.

Novel Insights into the Pathogenesis and Prevention of Intradialytic Hypotension

BACKGROUND

Intradialytic hypotension (IDH) is a common complication of haemodialysis (HD) and associated with adverse outcomes, especially when a nadir definition (systolic blood pressure <90 mm Hg) is used. The pathogenesis of IDH is directly linked to the discontinuous nature of the HD treatment, in combination with patient-related factors such as age, diabetes mellitus and cardiac failure.

SUMMARY

Although the decline in blood volume due to removal of fluid by ultrafiltration is the prime mover, thermally induced reflex vasodilation compromises the haemodynamic response to hypovolemia. Recent studies have stressed the relevance of changes in tissue perfusion during HD, which may translate in long-term organ damage. Monitoring changes in tissue perfusion, for which emerging evidence becomes available, appears to have great promise in the fine-tuning of the dialysis procedure. Key Messages: While it is unlikely that IDH can be completely prevented, reduction in inter-dialytic weight gain, prevention of an increase in core temperature by adjusting the dialysate temperature and more frequent or prolonged dialysis treatment remain cornerstones in providing a more comfortable and safe treatment.

Techniques for assessing fluids status in patients with kidney disease

PURPOSE OF REVIEW

The aim of this article is to present current information on techniques for fluid status assessment in patients with kidney disease. The methods can be broadly categorized into biomarkers, ultrasound, blood volume monitoring, and bioimpedance.

RECENT FINDINGS

Biomarkers including atrial natriuretic peptide and B-type natriuretic peptide have been shown to provide information about relative changes in fluid status. Ultrasound is applied to measure inferior vena cava indices, pulmonary indicators, and vascular indicators of fluid overload. Relative blood volume monitoring is used to measure change in intravascular fluid during hemodialysis. While in principle appealing, measurement of absolute blood volume has seen limited use to date. Bioimpedance techniques such as vector analysis, whole body, and regional bioimpedance spectroscopy, have shown their ability to estimate fluid status.

SUMMARY

The interpretation of biomarkers is complicated by the presence of cardiac disease. All ultrasound methods have some correlation with fluid status; however, operator dependency limits their routine use. Bioimpedance methods and relative blood volume monitoring are increasingly used to assess fluid status in patients with acute or chronic kidney disease. Measurement of absolute blood volume holds promise for the future.

Modelling Transcapillary Transport of Fluid and Proteins in Hemodialysis Patients

Background

The kinetics of protein transport to and from the vascular compartment play a major role in the determination of fluid balance and plasma refilling during hemodialysis (HD) sessions. In this study we propose a whole-body mathematical model describing water and protein shifts across the capillary membrane during HD and compare its output to clinical data while evaluating the impact of choosing specific values for selected parameters.

Methods

The model follows a two-compartment structure (vascular and interstitial space) and is based on balance equations of protein mass and water volume in each compartment. The capillary membrane was described according to the three-pore theory. Two transport parameters, the fractional contribution of large pores (α_LP) and the total hydraulic conductivity (LpS) of the capillary membrane, were estimated from patient data. Changes in the intensity and direction of individual fluid and solute flows through each part of the transport system were analyzed in relation to the choice of different values of small pores radius and fractional conductivity, lymphatic sensitivity to hydraulic pressure, and steady-state interstitial-to-plasma protein concentration ratio.

Results

The estimated values of LpS and α_LP were respectively 10.0 ± 8.4 mL/min/mmHg (mean ± standard deviation) and 0.062 ± 0.041. The model was able to predict with good accuracy the profiles of plasma volume and serum total protein concentration in most of the patients (average root-mean-square deviation < 2% of the measured value).

Conclusions

The applied model provides a mechanistic interpretation of fluid transport processes induced by ultrafiltration during HD, using a minimum of tuned parameters and assumptions. The simulated values of individual flows through each kind of pore and lymphatic absorption rate yielded by the model may suggest answers to unsolved questions on the relative impact of these not-measurable quantities on total vascular refilling and fluid balance.

Patient-Specific Modeling of Multicompartmental Fluid and Mass Exchange during Dialysis

Background

Dialysis is associated with a non-negligible rate of morbidity, requiring treatment customization. Many mathematical models have been developed describing solute kinetics during hemodialysis (HD) for an average uremic patient. The clinical need can be more adequately addressed by developing a patient-specific, multicompartmental model.

Materials and Methods

The data from 148 sessions (20 patients), recorded at the Regional Hospital of Lugano, Switzerland, were used to develop and validate the mathematical model. Diffusive and convective interactions among patient, dialysate and substitution fluid were considered. Three parameters, related to mass transfer efficiency at the cell membrane, at the dialyzer and at the capillary wall, were used to tune the model. The ability of the model to describe the clinical evolution of a specific HD session was evaluated by comparing model outputs with clinically acquired data on solutes and catabolite concentrations.

Results

The model developed in this study allows electrolyte and catabolite concentration trends during each HD session to be described. The errors obtained before the estimation of the patient-specific parameters drastically decrease after their identification. With the optimized model, plasmatic concentration trends can be described with an average percent error lower than 2.1% for Na+, CI-, Ca2+ and HCO3-, lower than 5% for K+ and lower than 8% for urea.

Conclusions

The peculiarity of the proposed model is the possibility it offers to perform a real-time simulation enabling quantitative appraisal of hematochemical quantities whose direct measurement is prohibitive. These will be beneficial to dialysis therapy planning, reducing intradialysis complications and improving patients’ quality of life.