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Contamination of water use points in health establishments is a frequent and concerning problem. Maintenance and disinfection of water systems can be inefficient. Sterilizing filters are commonly used at selected taps. We report diagnostic and corrective approaches that have succeeded in making a contaminated health facility sustainably compatible with its activity without restriction in taps use. The zones contaminated with pseudomonas as well as those, along the water networks, at risk of biofilm development were identified. Corrective measures on the network and various types of decontamination were carried out. At the end of this work, the bacterial load in the water significantly decreased and 219 out of 223 controls were negative for P. aeruginosa over 3 years of follow-up. Four positive results were linked to three taps not used for care which were satisfactorily treated locally. Errors at the design and setup phases of health facilities may result in resistant bacterial contamination. P. aeruginosa contamination of newly built healthcare facilities is an underreported problem. Guidelines on design, disinfection, and monitoring procedures of water networks of healthcare facilities should be adapted consequently and would certainly improve the offered care limiting patients’ risk and avoid many unwanted financial situations for the providers.

BACKGROUND AND AIM Post-dilutional haemodiafiltration (HDF) with high convection volumes are suggested to improve survival. However, a large increase in convection flow (QUF) is associated with high transmembrane pressure (TMP) which, when exceeding limits advised by guidelines, acts as a limiting factor and prevents achieving the prescription. Our aim is to predict the TMP needed to reach any given convection flow for a patient and dialysis session. METHOD The TMP necessary to obtain a desired convection was predicted from the automatic determination of the maximum ultrafiltration coefficient (KUF max, HDF machine Dialog iQ, BBraun, Melsungen, Germany) and compared to the actual value for 16 patients and 29 dialysis sessions. KUF max was determined at the start of the session and the coefficients of the quadratic regression of the ultrafiltration coefficient (KUF) on convection flow (KUF = a*(QUF)² + b* QUF + c) were obtained and used to predict the TMP needed to obtain a convection of 30% of QB (QUF max), knowing that TMP = QUF/KUF. Then, infusion rate was set at QUF max and the observed TMP was recorded after 8 minutes stabilization. Dialyses were performed with the patient's usual dialyzer (Diacap pro for 28 sessions, Nephral 400 for 1 session) and blood flow [363 ± 30 mL/min (300–400 mL/min)]. Observed and estimated TMPs were compared. RESULTS There was a high correlation between both TMPs (Pearson's R = 0.98; P CONCLUSION KUF max determination allows estimating TMP at any QUF prescription with an acceptable error (3%). Therefore, the KUF on QUF parabolic curve may be of help in the clinical setting to prescribe the most suitable convection in post-dilutional HDF by predicting the TMP the filtrating system will be submitted to. Based on this principle, automatic systems to aid personalized convection flow prescriptions can be developed.

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.

International audience; Background: Recent randomized controlled trials suggest that sufficiently high convection post-dilutional haemodiafiltration (HC-HDF) improves survival in dialysis patients, consequently this technique is increasingly being adopted. However, when performing HC-HDF, rigorous control systems of the ultrafiltration setting are required. Assessing the global ultrafiltration coefficient of the dialysis system [GKD-UF; defined as ultrafiltration rate (QUF)/transmembrane pressure] or water permeability may be adapted to the present dialysis settings and be of value in clinics.Methods:GKD-UF was determined and its reproducibility, variability and influencing factors were specifically assessed in 15 stable patients routinely treated by high-flux haemodialysis or HC-HDF in a single unit.Results:GKD-UF invariably followed a parabolic function with increasing QUF in dialysis and both pre- and post-dilution HC-HDF (R2 constantly >0.96). The vertex of the parabola, GKD-UF-max and related QUF were very reproducible per patient (coefficient of variation 3.9 ± 0.6 and 3.3 ± 0.3%, respectively) and they greatly varied across patients (31–42 mL/h−1/mmHg and 82–100 mL/min, respectively). GKD-UF-max and its associated QUF decreased during dialysis treatment (P < 0.01). The GKD-UF-max decrease was related to weight loss (R2 = 0.66; P = 0.0015).Conclusions: GKD-UF is a reliable and accurate method to assess the water permeability of a system in vivo. It varies according to dialysis setting and patient-related factors. It is an objective parameter evaluating the forces driving convection and identifies any diversion of the system during the treatment procedure. It is applicable to low- or high-flux dialysis as well as pre- or post-dilution HDF. Thus, it may be used to describe the characteristics of a dialysis system, is suitable for clinical use and may be of help for personalized prescription.

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 (p56,000 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 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.

International audience; 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 (p56,000 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 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.

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 signif icant 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.

Although a wide range of physical principles capable of separating different solutes exist in biochemistry (such as affinity, or size as well as charge retaining columns and others), the removal of uraemic solutes has been almost exclusively performed up to the present with membrane-based systems. Sir Thomas Graham, in the second half of the 1800s, defined the method of separating various fluids by diffusion through a membrane with the term ‘dialysis’[1]. Galen in the second century of our era already claimed that the skin resembles a sieve and ‘sweating purifies the body, … by low-effort exercise, baths and the summer heat’ [De Symptomatum Causis Libri III, Claudii Galeni Opera Omnia (II)][2], and ancient Romans used the skin as a natural membrane to rid their bodies of poisonous urinal substances in the Therms and public baths. Well into the 20th century, artificial kidneys, based on membrane devices were adopted and the pioneer work by Abel, Rowntree and Turner [3], as well as that of Haas [4], was followed by the rotatory drum dialyser of Willem Kolff [5] and the vertical drum one of Nils Alwall [6]. Finally, the hollow fibre dialysers gained adepts and a widespread use of cuprophane membranes for a very long period of time (from the 1970s to the 1990s) has been followed by the introduction of high-flux membranes that have invaded most of the dialysis units worldwide to the present. It became quite clear from the very beginning that membranes differ in their clearance capacities of the different solutes, basically depending on thickness and pore size. However, increasing the pore size and reducing thickness is almost forcedly associated to a water permeability increase. The open dialysate circuit settings used during the era of low-permeability membranes had to be secured by the addition of ultrafiltration controllers, which closed the dialysis circuit [7], and are mandatory when using high-flux membranes (highly permeable to water) particularly if convective techniques are utilized. Defining water permeability of a dialyser was considered important from the beginning and is even more important with the high-flux dialysers. Water permeability of a dialyser was defined by its ultrafiltration coefficient, which is displayed in the notice of the given dialyser. The coefficient of ultrafiltration (KUF) was first defined by the amount of fluid (V) in mL crossing the dialyser membrane per time (T) in hours and pressure (P) in mmHg: KUF=VT×P The perception that renal physicians have of KUF has changed over time. Senior nephrologists considered KUF as a constant and took it into account in dialysis prescription in the low-permeability era [8]; it was common to hear comments on the different KUF or ‘slope’ of one dialyser in regard to another one in clinics and the consequences that this might have to the treatment and to the patient. Among senior physicians, only those particularly interested on the topic knew that KUF was not always a constant as its value may vary over a certain range of filtration rate. Young nephrologists, who have only lived the ultrafiltration controller era, have just ignored KUF. They simply did not need it. Nevertheless, the importance of KUF of the early times has remained in many aspects, including the approval of new devices by the regulatory agencies such as the US Food and Drugs Administration (FDA) [9] or its equivalent in Europe, the European Medicines Agency (EMA), a prerequisite to use them in clinics in all these countries. Indeed, the recent randomized, controlled trials on haemodiafiltration [10–12] and particularly that of Maduell et al. [12] providing evidence that high convective volume may improve survival has given a renewed protagonism to KUF, as it influences the convective capacities of the dialysis setting. KUF remains, though, the old ‘grand inconnu’. In the present editorial comment, we want to present a refurbished KUF to society, going in-depth into the factors influencing KUF and its calculation, and then coming back with as simple as possible methods to obtain it for easy clinical use.

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 (β2m), retinol-binding protein (RBP) and albumin were measured. The reduction rates of serum urea, creatinine, β2m, 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 β2m, 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.

To the Editor: Real-time measurement of dialysis efficacy is sought by all practicing renal physicians in charge of dialysis patients. Thus, we were very interested in the article by Gross et al.,1 entitled 'Online clearance measurement in high-efficiency hemodiafiltration'. We were surprised to discover that the paper reported the use of ionic dialysance to estimate urea clearance, as we consider this method to be widely accepted and that it was made commercially available quite a long time ago.