Optimization of sodium removal in paired filtration dialysis by single pool sodium and conductivity kinetic models

Dialysate sodium management in hemodialysis and on-line hemodiafiltration: the single-pool kinetic model revisited

BACKGROUND

Determining the optimal dialysate sodium remains one of the challenges of hemodialysis prescription. Several arguments suggest that the dialysate sodium should be individually adjusted according to the patient's natremia. This strategy is greatly facilitated by using an algorithm. Only three such algorithms have been embedded in hemodialysis machines for the widespread generalization of this strategy in clinical routine: the Diacontrol (Hospal-Baxter Healthcare Corp., Deerfield, IL, USA), the HFR-Aequilibrium (Bellco-Medtronic, Dublin, Ireland) and the Na-control (Fresenius Medical Care, Bad-Homburg, Germany).

METHODS

Model the solute mass-transfer across the dialyzer membrane in online hemodiafiltration and adapt the Diacontrol algorithm based on a single-pool kinetic model of sodium balance for quantifying ionic balance and managing tonicity.

RESULTS

1) Substituting sodium measurements with conductivity measurements allows the control of tonicity which is a more physiological parameter than natremia. 2) Consideration of all ion exchanges as a whole and not just sodium exchange avoids some of the assumptions required by kinetic modeling of sodium balance. 3) Equations provided by the model are applicable to both hemodialysis and online hemodiafiltration. 4) The differences between this model used by Diacontrol and the models on which the other two software's (HFR-Aequilibrium and Na-control) are based are highlighted.

CONCLUSIONS

The single-pool kinetic model validated for the management of natremia in hemodialysis is also valid for the management of tonicity for both conventional hemodialysis and all online hemodiafiltration procedures.

[The different modalities of isonatric hemodialysis]

Setting dialysate sodium allows to adequately adjust sodium balance and plasma sodium at the end of dialysis session. In accordance with the set-point theory based on the concept of restoring cellular hydration, an adequate target for plasma sodium at the end of the session could be the value of predialysis plasma sodium concentration (isonatric hemodialysis). Some recently available dialysis monitors provide an on-line value of plasma-water conductivity usually converted in on-line natremia. There are different modalities of isonatric hemodialysis depending on whether the online value of natremia is used or not. By reviewing the few studies concerning the isonatric hemodialysis, it seems logical to set a target of postdialysis on-line natremia (or plasma-water conductivity) slightly lower than its predialysis value. However this strategy requires specifically designed software not yet available in clinical routine.

A Bayesian approach for the identification of patient-specific parameters in a dialysis kinetic model

Hemodialysis is the most common therapy to treat renal insufficiency. However, notwithstanding the recent improvements, hemodialysis is still associated with a non-negligible rate of comorbidities, which could be reduced by customizing the treatment. Many differential compartment models have been developed to describe the mass balance of blood electrolytes and catabolites during hemodialysis, with the goal of improving and controlling hemodialysis sessions. However, these models often refer to an average uremic patient, while on the contrary the clinical need for customization requires patient-specific models. In this work, we assume that the customization can be obtained by means of patient-specific model parameters. We propose and validate a Bayesian approach to estimate the patient-specific parameters of a multi-compartment model, and to predict the single patient's response to the treatment, in order to prevent intra-dialysis complications. The likelihood function is obtained by means of a discretized version of the multi-compartment model, where the discretization is in terms of a Runge-Kutta method to guarantee convergence, and the posterior densities of model parameters are obtained through Markov Chain Monte Carlo simulation. Results show fair estimations and the applicability in the clinical practice.

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.

Rationale and design of the Sodium Lowering In Dialysate (SoLID) trial: a randomised controlled trial of low versus standard dialysate sodium concentration during hemodialysis for regression of left ventricular mass

BACKGROUND

The current literature recognises that left ventricular hypertrophy makes a key contribution to the high rate of premature cardiovascular mortality in dialysis patients. Determining how we might intervene to ameliorate left ventricular hypertrophy in dialysis populations has become a research priority. Reducing sodium exposure through lower dialysate sodium may be a promising intervention in this regard. However there is clinical equipoise around this intervention because the benefit has not yet been demonstrated in a robust prospective clinical trial, and several observational studies have suggested sodium lowering interventions may be deleterious in some dialysis patients.

METHODS/DESIGN

The Sodium Lowering in Dialysate (SoLID) study is funded by the Health Research Council of New Zealand. It is a multi-centre, prospective, randomised, single-blind (outcomes assessor), controlled parallel assignment 3-year clinical trial. The SoLID study is designed to study what impact low dialysate sodium has upon cardiovascular risk in dialysis patients. The study intends to enrol 118 home hemodialysis patients from 6 sites in New Zealand over 24 months and follow up each participant over 12 months. Key exclusion criteria are: patients who dialyse more frequently than 3.5 times per week, pre-dialysis serum sodium of <135 mM, and maintenance hemodiafiltration. In addition, some medical conditions, treatments or participation in other dialysis trials, which contraindicate the SoLID study intervention or confound its effects, will be exclusion criteria. The intervention and control groups will be dialysed using dialysate sodium 135 mM and 140 mM respectively, for 12 months. The primary outcome measure is left ventricular mass index, as measured by cardiac magnetic resonance imaging, after 12 months of intervention. Eleven or more secondary outcomes will be studied in an attempt to better understand the physiologic and clinical mechanisms by which lower dialysate sodium alters the primary end point.

DISCUSSION

The SoLID study is designed to clarify the effect of low dialysate sodium upon the cardiovascular outcomes of dialysis patients. The study results will provide much needed information about the efficacy of a cost effective, economically sustainable solution to a condition which is curtailing the lives of so many dialysis patients.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Registry number: ACTRN12611000975998.

Measuring plasma conductivity to detect sodium load in hemodialysis patients

BACKGROUND

Sodium thiosulfate therapy has been proposed for calcific uremic arteriolopathy and nephrogenic systemic fibrosis in hemodialysis patients. The treatment brings 3.7 g (161 mmol) of sodium. How to counterbalance this sodium load was studied.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Plasma conductivity (Cp) and mass balance index were compared for 20 sessions without thiosulfate and 20 sessions with thiosulfate infusion. Subsequently, the dialysate conductivity was set to 13.8 mS/cm during the entire session. Next, dialysate conductivity was set to 14 mS/cm for the first 3 h and to 13 mS/cm for the last hour of thiosulfate infusion (n = 25).

RESULTS

The Cp variation between beginning and end was equal to +0.005 +/- 0.13 mS/cm without thiosulfate, +0.24 +/- 0.13 mS/cm with thiosulfate, and 14 mS/cm dialysate conductivity (P < 0.001). The decrease in dialysate conductivity at 13.8 mS/cm did not counterbalance the sodium load. The last program adequately compensated the sodium load with a Cp increase of only +0.05 +/- 0.14 mS/cm (NS versus without thiosulfate). The total of the dialyzed sodium and the sodium load for this last program was equal to 603 mmol compared with 456 mmol for the sessions without thiosulfate, the difference of 147 mmol being close to the known content of 161 mmol in 25 g of infused thiosulfate.

CONCLUSIONS

Thiosulfate infusion requires a decrease of dialysate conductivity of -1 mS/cm during the infusion to counterbalance the added 3.7 g (161 mmol) sodium load.

Effectiveness of sodium and conductivity kinetic models in predicting end-dialysis plasma water sodium concentration: Preliminary results of a single-center experience

The attainment of a neutral sodium balance represents a major objective in hemodialysis patients. It requires that at the end of each dialysis session, total body water volume (V(f)) and total plasma water sodium concentration (Na(pwf)) are constant. Whereas to achieve a constant V(f) it is sufficient that ultrafiltration equals the interdialytic increase in body weight, it is impossible to predict the value of Na(pwf) and calculate the dialysate sodium concentration needed to obtain it without making use of kinetic mathematical models. The effectiveness of both sodium and conductivity kinetic models in predicting Na(pwf) has already been validated in previous clinical studies. However, applying the sodium kinetic model appears to be poorly feasible in the everyday clinical practice, due to the need for blood samples at the start of each dialysis session for the determination of predialysis plasma water sodium concentration. The conductivity kinetic model appears to be more easily applicable, because no blood samples or laboratory tests are needed to determine plasma water conductivity (C(pw)) and ionic dialysance (ID), used in place of plasma water sodium concentration and sodium dialysance, respectively. We applied the 2 models in 69 chronic hemodialysis patients using the Diascan Module for the automatic determination of C(pw) and ID, and using the latter as an estimate of sodium dialysance in the sodium kinetic model. The conductivity kinetic model was shown to be more accurate and precise in predicting Na(pwf) as compared with the sodium kinetic model. Both accuracy and imprecision of the 2 models were not significantly affected by the method used to estimate total body water volume. These findings confirm the conductivity kinetic model as being an effective and easily applicable instrument for the achievement of a neutral sodium balance in chronic hemodialysis patients.

Predicting Dialysate Sodium Composition in Sorbent Dialysis Using Single Point and Multiple-Dilution Conductivity Measurement

This research establishes the ability to predict the sodium composition in dialysate from a single conductivity measurement over the wide range of concentrations of chloride, bicarbonate, and acetate that occur during sorbent dialysis. The ranges explored in mEq/L were sodium 100-180, chloride 76-143, bicarbonate 16-31, and acetate 4-11. Through mathematical optimization using a pattern search method, a single point measurement technique was shown to predict the total sodium concentration within approximately +/- 4.2 mEq/L in solutions with varying relative concentrations of chloride, bicarbonate, and acetate. The data analysis showed that the total sodium concentration can be predicted within +/- 2.1 mEq/L in most cases. Another potential approach to determining sodium concentration, a multiple-dilution measurement method, was tested and is also described. It is based on the varying relationship of activity to concentration for each of the sodium-anion pairs. This technique has practical limitations because of interactions between the various ions in solution at normal concentrations of dialysis along with the complexities involved in creating high dilutions of dialysate for on-line assays during dialysis.

Haemodialysis with on-line monitoring equipment: tools or toys?

BACKGROUND

On-line monitoring of chemical/physical signals during haemodialysis (HD) and bio-feedback represents the first step towards a 'physiological' HD system incorporating adaptive and logic controls in order to achieve pre-set treatment targets.

METHODS

Discussions took place to achieve a consensus on key points relating to on-line monitoring and bio-feedback, focusing on the clinical applications.

RESULTS

The relative blood volume (BV) reduction during HD can be monitored by optic devices detecting the variations in concentration of haemoglobin/haematocrit. BV changes result from an equilibrium between ultrafiltration and the refilling capacity. However, BV reduction has little power in predicting intra-HD hypotensive episodes, while the combination of the patient-dialysate sodium gradient, the relative BV reduction between the 20th and 40th minute of HD, the irregularity of the profile of BV reduction over time and the heart rate decrease from the start to the 20th minute of HD predict intra-HD hypotension with a sensitivity of 82%, a specificity of 73% and an accuracy of 80%. A bio-feedback system drives the relative BV reduction according to desired values by instantaneously changing the ultrafiltration rate and the dialysate conductivity. This system has proved to reduce the incidence of intra-HD hypotension episodes significantly. Ionic dialysance and the patient's plasma conductivity can be calculated easily from on-line inlet and outlet dialysate conductivity measurements at two different steps of dialysate conductivity. Ionic dialysance is equivalent to urea clearance corrected for recirculation and is a tool for continuously monitoring the dialysis efficiency and detecting early problems with the delivery of the prescribed dose of dialysis. Given the strict and linear relationship between conductivity and sodium content, the conductivity values replace the sodium concentration values and this permits the development of a conductivity kinetic model, by means of which sodium balance can be achieved at each dialysis session. The conductivity kinetic model has been demonstrated to improve intra-HD cardiovascular stability in hypotension-prone patients significantly. Ionic dialysance is also a useful tool to monitor vascular access function, as it can be used to obtain serial measurements of vascular access blood flow. On-line urea monitors provide detailed information on intra-HD urea kinetics and delivered dialysis dose, but they are not in widespread use because of the costs related to the disposable materials (e.g. urease cartridge). The body temperature monitor measures the blood temperature at the arterial and venous lines of the extra-corporeal circuit and, thanks to a bio-feedback system, is able to modulate the dialysate temperature in order to influence the patient's core body temperature, which can be kept at constant values. This is associated with improved intra-HD cardiovascular stability. The module can also be used to quantify total recirculation.

CONCLUSIONS

On-line monitoring devices and bio-feedback systems have evolved from toys for research use to tools for routine clinical application, particularly in patients with clinical complications. Conductivity monitoring appears the most versatile tool, as it permits quantification of delivered dialysis dose, achievement of sodium balance and surveillance of vascular access function, potentially at each dialysis session and without extra cost.

Optimal composition of the dialysate, with emphasis on its influence on blood pressure

Introduction. From the beginning of the dialysis era, the most appropriate composition of the dialysate has been one of the central topics in the delivery of dialysis treatment.

METHODS

A discussion is employed to achieve a consensus on key points relating to the composition of the dialysate, focusing on the relationships with blood pressure behaviour.

RESULTS

Sodium balance is the cornerstone of intra-dialysis cardiovascular stability and good inter-dialysis blood pressure control. Hypernatric dialysis carries the risk of positive sodium balance, with the consequent possibility of the worsening sense of thirst and hypertension. Conversely, hyponatric dialysis may lead to negative sodium balance, with the possibility of intra-dialysis cardiovascular instability and 'disequilibrium' symptoms including fatigue, muscle cramps and headache. The goal is to remove with dialysis the exact amount of sodium that has accumulated in the inter-dialysis interval. The conductivity kinetic model is applicable on-line at each dialysis session and has been proved to be able to improve intra-dialytic cardiovascular stability in hypotension-prone patients. Therefore, it should be regarded as a promising tool to be implemented in everyday clinical practice. Serum potassium concentration and variations during dialysis treatment certainly play a role in the genesis of cardiac arrhythmia. Potassium profiling, with a constant gradient between plasma and dialysate, should be implemented in clinical practice to minimize the arrhythmogenic potential of dialysis. Calcium plays a role both in myocardial contractility and in peripheral vascular resistance. Therefore, an increase in dialysate calcium concentration may be useful in cardiac compromised hypotension-prone patients. Acid-buffering by means of base supplementation is one of the major roles of dialysis. Bicarbonate concentration in the dialysate should be personalized in order to reach a midweek pre-dialysis serum bicarbonate concentration of 22 mmol/l. The role of convective dialysis techniques in cardiovascular stability is still under debate. It has been demonstrated that dialysate temperature and sodium balance play a role and this should be taken into account. Whether removal of vasoactive, middle-sized compounds by convection plays an independent role in improving cardiovascular stability is still uncertain.

CONCLUSIONS

The prescription of dialysis fluid is moving from a pre-fixed, standard dialysate solution to individualization of electrolyte and buffer composition, not only during the dialysis session, but also within the same session (profiling) in order to provide patients with an optimal blood purification coupled with a high degree of tolerability.

Sodium balance in hemodialysis therapy

Water and sodium overload is the predominant factor in the pathogenesis of hypertension in dialysis patients. In many dialysis patients, dry weight is not reached because of an imbalance between the interdialytic accumulation of water and sodium and the brief and discontinuous nature of routine dialysis therapy. During dialysis, sodium is removed by convection and to a lesser degree by diffusion. However, with supraphysiologic dialysate sodium concentrations, diffusive influx from dialysate may occur, especially in patients with low predialytic plasma sodium concentrations. Measuring sodium removal during dialysis is difficult and hampered by the variability in conventional sodium measurements. Ionic mass removal by continuous measurement of conductivity in the dialysate ports appears to be a promising tool for the approximation of sodium removal during dialysis. While the beneficial effects of concomitant water and sodium removal on blood pressure control in dialysis patients are undisputed, it is less well known whether a change in hydrosodium balance solely by reducing dialysate sodium is beneficial. Considering the inherent dangers of such an approach (intradialytic hemodynamic instability), the beneficial effects of strict dietary sodium restriction appear to be of much larger clinical benefit. It has become possible to individualize dialysate sodium concentration by means of online measurements of plasma conductivity and adjustment of dialysate conductivity by feedback technologies. The clinical benefits of this approach deserve further study. Still, reducing dietary sodium intake remains the most important tool in improving blood control in dialysis patients.

Role of sodium in hemodialysis

Sodium chloride is the most abundant salt in extracellular fluid. In normal individuals, the tonicity exerted by dissolved sodium chloride determines plasma osmolality and indirectly determines intracellular tonicity and cell volume. Uremic patients retain nitrogenous wastes and have an elevated plasma osmolality. While urea exhibits osmotic activity in serum, no sustained gradient can be established across cell boundaries because it readily diffuses through cell membranes. Thus, sodium remains the major indicator of body tonicity and determines the distribution of water across the intracellular-extracellular boundary, subsequent cell volume, thirst, and, among patients with renal insufficiency, systemic blood pressure. As a result of highly conserved plasma tonicity control systems, uremic subjects demonstrate remarkable stability of their serum sodium. Dialysate is a synthetic interstitial fluid capable of reconstituting extracellular fluid composition through urea extraction and extremely efficient solute and solvent (salt and water) transfer to the patient. Subtle transdialyzer gradients deliver and remove large quantities of trace elements, solvent, and solute to patients, creating a variety of dialysis "disequilibrium" syndromes manifest as cellular and systemic distress. Every dialysis patient uses dialysate, and the most abundant chemicals in dialysate are salt and water. Despite its universal use, no consensus on dialysate composition or tonicity exists. This can only be explained if we believe that dialysate composition is best determined by matching unique dialysis delivery system characteristics to specific patient requirements. Such a paradigm treats dialysate as a drug and the dialysis system as a delivery device. Understanding the therapeutic and toxic profiles of this drug (dialysate) and its delivery device (the dialyzer) is important to safe, effective, goal-directed modifications of therapy. This article explores some of the historical rationale behind choosing specific dialysate tonicities.

Relevance of the conductivity kinetic model in the control of sodium pool

Changes in the body sodium pool caused by dialytic treatment have very important clinical implications, mainly in terms of intradialytic cardiovascular instability and interdialytic hyperhydration and hypertension with long-term cardiac hypertrophy and dilation. A kinetic model could be helpful in order to define the dialysate sodium concentration needed to match intradialytic hydrosodium removal with interdialytic sodium and water intake, but unfortunately, none of the sodium kinetic models are suitable for routine clinical application. Two conductivity kinetic models (one for hemodialysis and one for paired filtration dialysis) have been developed on the basis of the linear relationship between the sodium content and conductivity of every saline solution and plasma water and according to basic theory for ionic dialysance determination. These models make it possible to know at the start of each session the dialysate conductivity needed to obtain the desired final plasma water conductivity or to know the latter when the former is known. Clinical evaluations showed that conductivity kinetic models are very precise and accurate and may be used instead of sodium kinetic models. Furthermore, they are suitable for routine use because they do not require blood sampling or laboratory determinations. Clinical application of the conductivity kinetic model has shown that the reduced variability of end-dialysis plasma water conductivity obtained when using the model to identify dialysate conductivity significantly reduces cardiovascular instability, even without any changes in average sodium removal. Given that ionic dialysance can be easily, inexpensively, and repeatedly measured at each dialysis session, it seems realistic to expect that conductivity kinetic modeling will soon become a part of everyday clinical practice.

Hemofiltration and double high flux dialysis: risks and benefits

Convective therapies such as hemofiltration, hemodiafiltration and double high flux dialysis have been shown to improve treatment delivered and treatment tolerance when compared to conventional dialysis therapies. The risk associated with these treatments is primarily in the quality of the substitution fluid. Technological advances now permit on-line produced substitution fluid, thereby significantly reducing the cost associated with hemofiltration and hemodiafiltration. The quality of the substitution fluid is only assured when the quality of the RO water used is within the guidelines set by the Association for the Advancement of Medical Instrumentation (AAMI). Therefore, the success of the application of this therapy is dependent on the water treatment protocols in the dialysis units. The success of this modality as a treatment for chronic renal failure is dependent on identifying those patient groups who will benefit most from this more efficient but more expensive treatment.

Effect of on-line conductivity plasma ultrafiltrate kinetic modeling on cardiovascular stability of hemodialysis patients

The aim of this multicenter, prospective, randomized cross-over study was to clarify whether on-line conductivity ultrafiltrate kinetic modeling (treatment B), as a substitute for sodium kinetic modeling, is capable of reducing intradialytic cardiovascular instability in comparison with standard treatment (treatment A), by reducing the sodium balance variability. Both treatments were performed by means of a modified hemodiafiltration technique. Treatment A was performed using fixed dialysate conductivity; treatment B made use of the dialysate conductivity derived from a conductivity kinetic model, in order to obtain an end-dialysis ultrafiltrate conductivity at each dialysis session that was equal to the mean value determined in the same patient during the four-week run-in period. Thus, during treatment B, the expected end-dialysis ultrafiltrate conductivity value of each patient should have been constant. The study was carried out according to a multicenter cross-over design of 16 weeks with two treatments (A or B), two sequences (1 = ABB and 2 = BAA), a run-in period of four weeks (period 1, treatment A), and three consecutive experimental periods of four weeks each. Analysis of variance for a cross-over design was used for the statistical analysis. Forty-nine hemodialysis patients prone to intradialytic hypotension (> 25% of sessions) were enrolled from 16 participating centers, and randomly assigned to either sequence 1 (26 patients) or sequence 2 (23 patients). Six patients dropped out and four were protocol violators, which left 39 patients selected for statistical analysis. There was no difference in the average dialysate conductivity, predialysis and end-dialysis plasma water ultrafiltrate conductivity or body weight between treatment A and treatment B. Thus, the observed mean sodium balance was not different and, as expected, only the intra-patient variability of end-dialysis ultrafiltrate conductivity (index of sodium balance variability) was reduced (21%). During treatment A, systolic blood pressure decreased by 23 mm Hg (95% confidence intervals 21 to 24 mm Hg) at the end of dialysis with respect to the pre-dialysis values. Treatment B reduced this intradialytic decrease (P = 0.001) with a maximum effect at the third hour of dialysis (4.4 mm Hg, 95% confidence intervals 1.9 to 6.9 mm Hg, 23% less than during treatment A, P 0.0005) without any period or carry-over effect (P = 0.53 and 0.08, respectively). There was no treatment effect on intradialytic diastolic blood pressure (P = 0.291). In conclusion, intradialytic cardiovascular stability was significantly improved by matching the interdialytic sodium load with intradialytic sodium removal using on-line conductivity ultrafiltrate kinetic modeling as an alternative to sodium kinetic modeling. Although highly significant, this effect was clinically not very large. By applying this conductivity kinetic model to patients with a more variable sodium intake from one session to another, a greater benefit can be expected.