Measuring intradialyser transmembrane and hydrostatic pressures: pitfalls and relevance in haemodialysis and haemodiafiltration.

BACKGROUND: Post-dilutional haemodiafiltration (HDF) with high convection volumes (HCVs) could improve survival. HCV-HDF requires a significant pressure to be applied to the dialyser membrane. The aim of this study was to assess the pressure applied to the dialysers in HCV-HDF, evaluate the influence of transmembrane pressure (TMP) calculation methods on TMP values and check how they relate to the safety limits proposed by guidelines. METHODS: Nine stable dialysis patients were treated with post-dilutional HCV-HDF with three different convection volumes [including haemodialysis (HD)]. The pressures at blood inlet (Bi), blood outlet (Bo) and dialysate outlet (Do) were continuously recorded. TMP was calculated using two pressures (TMP2: Bo, Do) or three pressures (TMP3: Bo, Do, Bi). Dialysis parameters were analysed at the start of the session and at the end of treatment or at the first occurrence of a manual intervention to decrease convection due to TMP alarms. RESULTS: During HD sessions, TMP2 and TMP3 remained stable. During HCV-HDF, TMP2 remained stable while TMP3 clearly increased. For the same condition, TMP3 could be 3-fold greater than TMP2. This shows that the TMP limit of 300 mmHg as recommended by guidelines could have different effects according to the TMP calculation method. In HCV-HDF, the pressure at the Bi increased over time and exceeded the safety limits of 600 mmHg provided by the manufacturer, even when respecting TMP safety limits. CONCLUSIONS: This study draws our attention to the dangers of using a two-pressure points TMP calculation, particularly when performing HCV-HDF.

Correction: Consequences of increasing convection onto patient care and protein removal in hemodialysis.

[This corrects the article DOI: 10.1371/journal.pone.0171179.].

Consequences of increasing convection onto patient care and protein removal in hemodialysis.

INTRODUCTION: Recent randomised controlled trials suggest that on-line hemodiafiltration (OL-HDF) improves survival, provided that it reaches high convective volumes. However, there is scant information on the feasibility and the consequences of modifying convection volumes in clinics. METHODS: Twelve stable dialysis patients were treated with high-flux 1.8 m2 polysulphone dialyzers and 4 levels of convection flows (QUF) based on GKD-UF monitoring of the system, for 1 week each. The consequences on dialysis delivery (transmembrane pressure (TMP), number of alarms, % of achieved prescribed convection) and efficacy (mass removal of low and high molecular weight compounds) were analysed. RESULTS: TMP increased exponentially with QUF (p<0.001 for N >56,000 monitoring values). Beyond 21 L/session, this resulted into frequent TMP alarms requiring nursing staff interventions (mean ± SEM: 10.3 ± 2.2 alarms per session, p<0.001 compared to lower convection volumes). Optimal convection volumes as assessed by GKD-UF-max were 20.6 ± 0.4 L/session, whilst 4 supplementary litres were obtained in the maximum situation (24.5 ± 0.6 L/session) but the proportion of sessions achieving the prescribed convection volume decreased from 94% to only 33% (p<0.001). Convection increased high molecular weight compound removal and shifted the membrane cut-off towards the higher molecular weight range. CONCLUSIONS: Reaching high convection volumes as recommended by the recent RCTs (> 20L) is feasible by setting an HDF system at its optimal conditions based upon the GKD-UF monitoring. Prescribing higher convection volumes resulted in instability of the system, provoked alarms, was bothersome for the nursing staff and the patients, rarely achieved the prescribed convection volumes and increased removal of high molecular weight compounds, notably albumin.

The use of SDS-PAGE scanning of spent dialysate to assess uraemic toxin removal by dialysis.

BACKGROUND: Uraemic toxins in the 8 to 60 kDa molecular weight range have been attracting increasing attention in dialysis therapy. However, there are no available standardized methods to evaluate their removal. Using new filtering membranes, we evaluated SDS-PAGE of spent dialysate to assess cut-off ranges and removal capacities into dialysate, while also measuring classical markers of dialyser function. METHODS: Eighteen dialysis patients were washed out for 2 weeks with FX 100 (Helixone(®)), followed by randomization to Xevonta Hi 23 (Amembris(®)) or FX dialysers for 2 weeks, then crossed over for an additional 2 weeks, and finally placed on Xenium 210 (Purema(®)) for 2 weeks. SDS-PAGE scanning of the removed proteins contained in the spent dialysate was performed during all dialysis sessions. Total mass of urea, creatinine, total proteins, beta 2 microglobulin (ß2m), retinol-binding protein (RBP) and albumin were measured. The reduction rates of serum urea, creatinine, ß2m, leptin, RBP, alpha 1-antitrypsin, albumin and total proteins were also determined. RESULTS: SDS-PAGE scanning identified four major protein peaks (10-18, 20-22.5, 23-30 and 60-80 kDa molecular weight) and showed clear differences in the amounts of removed proteins between the dialysers, particularly in the 20-22.5, 23-30 and 60-80 kDa ranges. Total mass of removed ß2m, RBP and albumin were in agreement with SDS-PAGE, while serum assays showed differing results. CONCLUSIONS: SDS-PAGE scanning provided a good characterization of protein patterns in the spent dialysate; it extended and agreed with protein determinations and allowed a better assessment of dialyser performance in removing 10 to 80 kDa molecular weight substances. It also identified differences between the three mainly filtrating polysulfone dialysers that were not detected with blood measurements.

The ultrafiltration coefficient of a dialyser (KUF) is not a fixed value, and it follows a parabolic function: the new concept of KUF max.

BACKGROUND: Hydraulic permeability (KUF) is an intrinsic characteristic of dialysers, reported by the manufacturer as a single value, which drives and limits fluid removal. High-flux dialysers have been introduced with the appearance of convective techniques, aiming to increase fluid and solute removal. High convective volumes are being employed, although their advantages have not been fully demonstrated. METHODS: We assessed KUF over a pre-selected range of ultrafiltration rates (QUF) in post-dilutional haemodiafiltration and high-flux haemodialysis. RESULTS: KUF vs QUF was neither a fixed value nor a linear function but followed a parabolic function with a vertex der (y)=0, which we have called KUF max. This also held true in high-flux routine dialysis. CONCLUSIONS: These findings are completely new and have clear applications in clinics. The vertex point might be used to define the optimal QUF of a dialysis system, which would be that obtained at KUF max and corresponds to the best QUF/transmembrane pressure ratio, as opposed to the maximum QUF (which corresponds to the highest possible QUF), frequently associated with haemoconcentration, clotting, loss in dialyser surface area, and treatment problems. Determining KUF max in vivo could be of help in dialysis prescription and control with automatic systems.

Use of spent dialysate analysis to estimate blood levels of uraemic solutes without blood sampling: urea.

BACKGROUND: Urea kinetic modelling-based methods are widely used to assess dialysis efficacy. However, they require blood sampling and are susceptible to a number of errors, mainly from the calculated parameters (particularly V). Spent dialysate determinations have been used and have been shown to be reliable and simple to use. In this study, we associated dialysate-based and clearance determinations along with Kt/V to estimate blood urea levels. METHODS: Urea kinetic modelling, continuous sampling of spent dialysate and ionic dialysance were determined in 18 stable dialysis patients during 126 dialysis sessions. Mean blood urea levels were estimated as follows: mean urea level = spent dialysate - urea mass/(dialysance T). Blood urea levels before and after dialysis were calculated based on the same determinations and extended formulae. RESULTS: Estimated mean urea level was significantly correlated with measured mean blood urea level (R(2) = 0.957; P < 0.0001), and Bland and Altman analysis showed significant agreement between estimated and measured levels. Estimated and measured blood urea levels were also correlated before and after dialysis (R(2) = 0.972 , P < 0.0001 and R(2) = 0.903 , P < 0.0001, respectively), with good agreement for both blood urea before and after dialysis and their respective estimates. CONCLUSIONS: Blood urea levels may be reliably estimated from the total mass of urea removed in the dialysate and the dialysance measured during dialysis. Coupling both measurements allows a precise monitoring of dialysis efficacy and a specific evaluation of the patient's urea metabolism status. Technical dysfunctions and patient variations may be easily identified using this approach without blood sampling.