METHODS:BACKGROUND:The use of haemodiafiltration (HDF) for the management of patients with end-stage kidney failure is increasing worldwide. Factors associated with HDF use have not been studied and may vary in different countries and jurisdictions. The aim of this study was to document the pattern of increase and variability in uptake of HDF in Australia and New Zealand, and to describe patient- and centre-related factors associated with its use. METHODS:Using the Australian and New Zealand Dialysis and Transplant Registry, all incident patients commencing haemodialysis (HD) between 2000 and 2014 were included. The primary outcome was HDF commencement over time, which was evaluated using multivariable logistic regression stratified by country. RESULTS:Of 27 433 patients starting HD, 3339 (14.4%) of 23 194 patients in Australia and 810 (19.1%) of 4239 in New Zealand received HDF. HDF uptake increased over time in both countries but was more rapid in New Zealand than Australia. In Australia, HDF use was more likely in males (odds ratio (OR) 1.13, 95% confidence interval (CI) = 1.03-1.24, P = 0.009) and less likely with older age (reference <40 years; 40-54 years OR = 0.85; 95% CI = 0.72-0.99; 55-69 years OR = 0.79; 95% CI = 0.67-0.91; >70 years OR = 0.48; 95% CI = 0.41-0.56); higher body mass index (body mass index (BMI) < 18.5 kg/m2 OR = 0.62; 95% CI = 0.46-0.84; 18.5-29.9 kg/m2 reference; >30 kg/m2 OR = 1.46; 95% CI = 1.33-1.61), chronic lung disease (OR = 0.84; 95% CI = 0.76-0.94; P < 0.001), cerebrovascular disease (OR = 0.76; 95% CI = 0.67-0.85; P < 0.001) and peripheral vascular disease (OR = 0.77; 95% CI = 0.70-0.85; P < 0.001). No association was identified with race. In New Zealand, HDF use was more likely in Maori and Pacific Islanders (OR = 1.32; 95% CI = 1.05-1.66) and Asians (OR = 1.75; 95% CI = 1.15-2.68) compared to Caucasians, and less likely in males (OR = 0.76; 95% CI = 0.62-0.94; P = 0.01). No association was identified with BMI or co-morbidities. In both countries, centres with a higher ratio of HD to peritoneal dialysis (PD) were more likely to prescribe HDF. Larger Australian centres were more likely to prescribe HDF (36-147 new patients/year OR = 26.75, 95% CI = 18.54-38.59; 17-35/year OR = 7.51, 95% CI = 5.35-10.55; 7-16/year OR = 3.00; 95% CI = 2.19-4.13; ≤6/year reference). CONCLUSION:Haemodiafiltration uptake is increasing, variable and associated with both patient and centre characteristics. Centre characteristics not explicitly captured elsewhere explained 36% of variability in HDF uptake in Australia and 48% in New Zealand.

METHODS:AIM:Clinical interpretation of B-type natriuretic peptide (BNP) levels in haemodialysis (HD) patients for fluid management remains elusive. METHODS:We conducted a retrospective observational monocentric study. We built a mathematical model to predict BNP levels, using multiple linear regressions. Fifteen clinical/biological characteristics associated with BNP variation were selected. A first cohort of 150 prevalent HD (from September 2015 to March 2016) was used to build several models. The best model proposed was internally validated in an independent cohort of 75 incidents HD (from March 2016 to December 2017). RESULTS:In cohort 1, mean BNP level was 630 ± 717 ng/mL. Cardiac disease (CD - stable coronary artery disease and/or atrial fibrillation) was present in 45% of patients. The final model includes age, systolic blood pressure, albumin, CD, normo-hydrated weight (NHW) and the fluid overload (FO) assessed by bio-impedancemetry. The correlation between the measured and the predicted log-BNP was 0.567 and 0.543 in cohorts 1 and 2, respectively. Age (β = 3.175e-2 , P < 0.001), CD (β = 5.243e-1 , P < 0.001) and FO (β = 1.227e-1 , P < 0.001) contribute most significantly to the BNP level, respectively, but within a certain range. We observed a logistic relationship between BNP and age between 30 and 60 years, after which this relationship was lost. BNP level was inversely correlated with NHW independently of CD. Finally, our model allows us to predict the BNP level according to the FO. CONCLUSION:We developed a mathematical model capable of predicting the BNP level in HD. Our results show the complex contribution of age, CD and FO on BNP level.

METHODS:AIM:The removal of cysteine during a dialysis procedure may affect glutathione (GSH) concentration, allowing haemodialysis (HD) patients to become more susceptible to oxidative damage. This study was performed to determine whether the change of GSH/glutathione disulfide (GSSG) redox state and GSH redox potential were linked with the change of cysteine or oxidative stress in patients receiving HD treatment. METHODS:Sixty-seven HD patients who had received regular HD treatment were recruited. Plasma GSH, GSSG, cysteine and malondialdehyde (MDA) were measured at both pre- and post-HD. RESULTS:Plasma cysteine, GSH and GSSG levels significantly decreased after the completion of HD, compared to the levels at pre-HD. Plasma MDA concentration, GSH/GSSG ratio and GSH redox potential remained constant during the dialysis session. Plasma GSH and GSSG were positively associated with plasma MDA at post-HD, while GSH redox potential was negatively associated with plasma MDA at post-HD. However, plasma GSH, GSSG, GSH/GSSG ratio and GSH redox potential were not associated with plasma cysteine at either pre- or post-HD. CONCLUSION:The GSH and GSSG levels were significantly utilized during a HD session, and their levels were significantly associated with increased oxidative stress. HD patients may require higher GSH demands to cope with increased oxidative stress during an HD session.