Environmentally sustainable design guide for haemodialysis facilities: An Australian and New Zealand society of Nephrology initiative.

Haemodialysis facilities have a large environmental impact due to high energy, water and consumable usage by haemodialysis equipment. As climate change and natural resource scarcity escalate, all the while the number of people requiring dialysis increases, there is an urgent need for dialysis facilities that meet care needs while minimising environmental impact. To address this, the Australian and New Zealand Society of Nephrology engaged an environmental sustainability consulting practise to develop a best practise guide for the environmentally sustainable design and operation of haemodialysis facilities. Four opportunity areas were considered, namely energy, water, waste and resource recovery, and additional sustainability. A total of 28 environmental improvement initiatives were identified. The majority (n = 23) were general measures that could be applied across all healthcare settings, while five were specific to haemodialysis facilities. Recommendations were made regarding specific measures that should be undertaken and/or standards that must be met to achieve the intent of each initiative. These were stratified to enable their application to both existing dialysis facilities and new builds. The lifecycle stage of a haemodialysis facility to which each initiative applied was highlighted, as was its potential impact. This guide provides a tailored and comprehensive resource for the kidney care community to enable the integration of best practise sustainability considerations into both existing and new facilities. If broadly implemented, it has the potential to markedly improve the environmental impact of haemodialysis provision.

Healthcare professional and community preferences in deceased donor kidney allocation: A best-worst scaling survey.

Deceased donor kidneys are a scarce community resource; therefore, the principles underpinning organ allocation should reflect societal values. This study aimed to elicit community and healthcare professional preferences for principles guiding the allocation of kidneys from deceased donors and compare how these differed across the populations. A best-worst scaling survey including 29 principles in a balanced incomplete block design was conducted among a representative sample of the general community (n = 1237) and healthcare professionals working in transplantation (n = 206). Sequential best-worst multinomial logistic regression was used to derive scaled preference scores (PS) (range 0-100). Thematic analysis of free text responses was performed. Five of the six most valued principles among members of the community related to equity, including priority for the longest waiting (PS 100), difficult to transplant (PS 94.5) and sickest (PS 93.9), and equitable access for men and women (PS 94.0), whereas the top four principles for healthcare professional focused on maximizing utility (PS 89.9-100). Latent class analysis identified unmeasured class membership among community members. There are discordant views between community members and healthcare professionals. These should be considered in the design, evaluation, and implementation of deceased donor kidney allocation protocols.

Mortality After Home Hemodialysis Treatment Failure and Return to In-Center Hemodialysis.

RATIONALE & OBJECTIVE: Patients on home hemodialysis (HHD) may eventually return to in-center hemodialysis (ICHD) for clinical, technical, or psychosocial reasons. We studied the mortality of patients returning to ICHD after HHD, comparing it with the mortality experience among patients receiving HHD and patients receiving ICHD without prior treatment with HHD. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: All patients represented in the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA) who commenced HD during 2005-2015 and were treated for >90 days. EXPOSURE: ICHD and/or HHD, and clinical characteristics at study entry. OUTCOME: Mortality and cause of death. ANALYTICAL APPROACH: A time-varying multivariate Cox proportional hazards analysis with shared frailty was implemented to explore the association between patient treatment states and mortality. Patients were censored at the time of transplantation or change in treatment modality to peritoneal dialysis. RESULTS: A total of 19,306 patients initiated HD and were treated for >90 days. The mean age of patients was 60.8 ± 15.4 (SD) years, 62% were male, and 49% had diabetes. After HHD treatment failure, adjusted mortality was increased compared with continued HHD at 0-30 days (HR, 3.93 [95% CI, 2.09-7.40]; P < 0.001), 30-90 days (HR, 3.34 [95% CI, 1.98-5.62]; P < 0.001), and >90 days (HR, 2.29 [95% CI, 1.84-2.85]; P < 0.001). LIMITATIONS: Covariates recorded at dialysis initiation, residual confounding underlying successful initiation of HHD treatment, and observational data lacking detail on cause of HHD treatment failure. CONCLUSIONS: HHD treatment failure is associated with a significant increase in mortality compared with continued HHD. This risk was present in both the early (first 30 days and 30-90 days) and late (>90 days) periods after HHD treatment failure. Further investigation into the specific causes of treatment failure and death may highlight specific high-risk patients.

Dialysis modality utilization patterns and mortality in older persons initiating dialysis in Australia and New Zealand.

AIM: The benefits of dialysis in the older population remain highly debated, particularly for certain dialysis modalities. This study aimed to explore the dialysis modality utilization patterns between in-centre haemodialysis (ICHD), peritoneal dialysis (PD) and home haemodialysis (HHD) and their association with outcomes in older persons. METHODS: Older persons (≥75 years) initiating dialysis in Australia and New Zealand from 1999 to 2018 reported to the Australia and New Zealand Dialysis and Transplant (ANZDATA) registry were included. The main aim of the study was to characterize dialysis modality utilization patterns and describe individual characteristics of each pattern. Relationships between identified patterns and survival, causes of death and withdrawal were examined as secondary analyses, where the pattern was considered as the exposure. RESULTS: A total of 10 306 older persons initiated dialysis over the study period. Of these, 6776 (66%) and 1535 (15%) were exclusively treated by ICHD and PD, respectively, while 136 (1%) ever received HHD during their dialysis treatment course. The remainder received both ICHD and PD: 906 (9%) started dialysis on ICHD and 953 (9%) on PD. Different individual characteristics were seen across dialysis modality utilization patterns. Median survival time was 3.0 (95%CI 2.9-3.1) years. Differences in survival were seen across groups and varied depending on the time period following dialysis initiation. Dialysis withdrawal was an important cause of death and varied according to individual characteristics and utilization patterns. CONCLUSION: This study showed that dialysis modality utilization patterns in older persons are associated with mortality, independent of individual characteristics.

Multicenter registry analysis comparing survival on home hemodialysis and kidney transplant recipients in Australia and New Zealand.

BACKGROUND: In the era of organ shortage, home hemodialysis (HHD) has been identified as the possible preferential bridge to kidney transplantation. Data are conflicting regarding the comparability of HHD and transplantation outcomes. This study aimed to compare patient and treatment survival between HHD patients and kidney transplant recipients. METHODS: The Australia and New Zealand Dialysis and Transplant Registry was used to include incident HHD patients on Day 90 after initiation of kidney replacement therapy and first kidney-only transplant recipients in Australia and New Zealand from 1997 to 2017. Survival times were analyzed using the Kaplan-Meier product-limit method comparing HHD patients with subtypes of kidney transplant recipients using the log-rank test. Adjusted analyses were performed with multivariable Cox proportional hazards regression models for time to all-cause mortality. Time-to-treatment failure or death was assessed as a composite secondary outcome. RESULTS: The study compared 1411 HHD patients with 4960 living donor (LD) recipients, 6019 standard criteria donor (SCD) recipients and 2427 expanded criteria donor (ECD) recipients. While LD and SCD recipients had reduced risks of mortality compared with HHD patients [LD adjusted hazard ratio (HR) = 0.57, 95% confidence interval (CI) 0.46-0.71; SCD HR = 0.65 95% CI 0.52-0.79], the risk of mortality was comparable between ECD recipients and HHD patients (HR = 0.90, 95% CI 0.73-1.12). LD, SCD and ECD kidney recipients each experienced superior time-to-treatment failure or death compared with HHD patients. CONCLUSIONS: This large registry study showed that kidney transplant offers a survival benefit compared with HHD but that this advantage is not significant for ECD recipients.

Development and validation of a risk index to predict kidney graft survival: the kidney transplant risk index.

BACKGROUND: Kidney graft failure risk prediction models assist evidence-based medical decision-making in clinical practice. Our objective was to develop and validate statistical and machine learning predictive models to predict death-censored graft failure following deceased donor kidney transplant, using time-to-event (survival) data in a large national dataset from Australia. METHODS: Data included donor and recipient characteristics (n = 98) of 7,365 deceased donor transplants from January 1st, 2007 to December 31st, 2017 conducted in Australia. Seven variable selection methods were used to identify the most important independent variables included in the model. Predictive models were developed using: survival tree, random survival forest, survival support vector machine and Cox proportional regression. The models were trained using 70% of the data and validated using the rest of the data (30%). The model with best discriminatory power, assessed using concordance index (C-index) was chosen as the best model. RESULTS: Two models, developed using cox regression and random survival forest, had the highest C-index (0.67) in discriminating death-censored graft failure. The best fitting Cox model used seven independent variables and showed moderate level of prediction accuracy (calibration). CONCLUSION: This index displays sufficient robustness to be used in pre-transplant decision making and may perform better than currently available tools.

Paediatric deceased donor kidney transplant in Australia: A 30-year review-What have paediatric bonuses achieved and where to from here?

BACKGROUND: In this 30-year national review, we describe trends in DD transplantation for paediatric recipients, assess the impact of paediatric allocation bonuses and identify outstanding areas of need for this population. METHODS: A retrospective review of all DD kidney only transplants to paediatric recipients (<18 years old) in Australia between 1989 and 2018 was conducted using deidentified extracts from the ANZDATA. RESULTS: Of the 1011 kidney only transplants performed in paediatric recipients during the study period, 426 (42%) were from deceased donors. Paediatric candidates on the DD waiting list had consistently higher rates of transplantation and shorter time from dialysis initiation to transplantation compared with adult candidates (median 372 vs 832 days in 2018, for example). Donor characteristics remained more favourable for paediatric recipients, despite a decline in the overall quality of the donor pool. The mean number of HLA antigen mismatches for paediatric recipients of DD transplants increased each decade (2.86 [1989-1998], 3.85 [1999-2008], 4.01 [2009-2018]). Both patient and graft survival have improved for paediatric DD transplant recipients in the most recent era (5-year graft and patient survival 85% vs 65% and 99% vs 94%, respectively, for 2009-2018 vs 1999-2008). CONCLUSIONS: The current DD kidney allocation system in Australia provides rapid access to high-quality organs for paediatric recipients, and early graft loss has decreased significantly in recent years; however, additional targeted interventions to address HLA matching may improve long-term outcomes in this population.

Incidence and predictors of vascular events following end-stage kidney disease in childhood.

AIM: Cardiovascular death is a leading cause of mortality in paediatric end-stage kidney disease (ESKD). There is however little known about the clinically relevant vascular disease in this population. We aimed to describe the incidence of new onset vascular disease and vascular death in Australian children receiving renal replacement therapy (RRT). We also aimed to identify demographic or childhood risk factors for these endpoints, and whether vascular disease predicts mortality. METHODS: Data on Australian patients who commenced RRT at <18 years of age from 1991 to 2017 were extracted from the Australian and New Zealand Dialysis and Transplant Registry (ANZDATA). Multivariable competing risks regression was used to identify factors associated with vascular events. RESULTS: A cohort of 1268 patients were followed up for a median of 10.31 years. Vascular disease was reported in 5.4%, and vascular death in 4.1%. The cumulative incidence of any vascular event, that is, disease or death, at 10 and 20 years was 5.5% and 12.8%, respectively. Childhood vascular events were associated with non-Caucasian, non-Indigenous ethnicity, and for the 804 patients followed up after 18 years of age, vascular events were associated with lack of childhood transplantation, longer childhood dialysis duration and Indigenous ethnicity. Vascular disease was only reported for 25.49% of patients who had a vascular death, and although a significant risk factor for mortality, it had limited ability to predict mortality. CONCLUSION: Cumulative incidence of vascular events is significant after commencing RRT during childhood and is associated with ethnicity, longer childhood dialysis duration and lack of childhood transplantation.

Dialysis initiation in older persons across centres and over time in Australia and New Zealand.

AIM: With improved life expectancy over time, the burden of kidney failure resulting in kidney replacement therapy (KRT) in older persons is increasing. This study aimed to describe the age distribution at dialysis initiation in Australia and New Zealand (ANZ) across centres and over time. METHODS: Adults initiating dialysis as first KRT in ANZ from 1999 to 2018 reported to the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry were included. The primary outcomes were the age distribution and the proportion of older persons (75 years and older) initiating dialysis across centres and over time. Secondary outcomes were characterization of the older population compared with younger people and differences in dialysis modality and treatment trajectories between groups. RESULTS: Over the study period, 55 382 people initiated dialysis as first KRT, including 10 306 older persons, in 100 centres. Wide variation in age distribution across states/countries was noted, although the proportion of older persons at dialysis initiation did not significantly change over time (from 13% in 1999 to 19% in 2003, then remaining stable thereafter). Older persons were less likely to be treated with home therapies compared with younger people. Older persons were mostly Caucasians; had higher socioeconomic position, more cardiovascular comorbidities and higher eGFR at baseline; and resided in major cities. Higher proportions of older persons per centre were noted in privately funded facilities. CONCLUSION: Wide variations were noted in the proportions of older persons initiating dialysis across centres and states/country, which were associated with different case-mix across regions, particularly in terms of ethnicity, remoteness and socioeconomic advantage.

Insights into the labeling effect of Kidney Donor Performance Index reporting: The Australian experience.

In 2016, Australia began reporting the Kidney Donor Performance Index (KDPI) with all deceased donor kidney transplant offers despite this not being used in organ allocation rules, offering a unique opportunity to explore the "labeling effect" of KDPI reporting. We reviewed all kidneys retrieved for transplant in Australia from 2015 to 2018 and analyzed the association of KDPI reporting with organ nonutilization, number of offer declines, and donor/recipient age and longevity matching. Analyses were stratified by organ failure risk: higher risk (KDPI > 80%), standard risk (KDPI 20% to 79%), and lower risk (KDPI 0% to 20%). There was no significant difference in organ nonutilization post KDPI reporting either overall or for higher-risk kidneys. KDPI reporting was associated with an increase in offer declines for both higher-risk (incidence risk ratio 1.45, P = .007) and standard-risk (incidence risk ratio 1.22, P = .021) kidneys but not for lower-risk organs. There was a significant increase in recipient age and expected posttransplant survival score for higher-risk kidneys but no differences among other groups. We conclude that although KDPI reporting in Australia has been associated with an increased number of offer declines for higher-risk kidneys, this has not resulted in increased nonutilization and may have contributed to more appropriate use of these organs.

Effect of patient- and center-level characteristics on uptake of home dialysis in Australia and New Zealand: a multicenter registry analysis.

BACKGROUND: Home-based dialysis therapies, home hemodialysis (HHD) and peritoneal dialysis (PD) are underutilized in many countries and significant variation in the uptake of home dialysis exists across dialysis centers. This study aimed to evaluate the patient- and center-level characteristics associated with uptake of home dialysis. METHODS: The Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry was used to include incident dialysis patients in Australia and New Zealand from 1997 to 2017. Uptake of home dialysis was defined as any HHD or PD treatment reported to ANZDATA within 6 months of dialysis initiation. Characteristics associated with home dialysis uptake were evaluated using mixed effects logistic regression models with patient- and center-level covariates, era as a fixed effect and dialysis center as a random effect. RESULTS: Overall, 54 773 patients were included. Uptake of home-based dialysis was reported in 24 399 (45%) patients but varied between 0 and 87% across the 76 centers. Patient-level factors associated with lower uptake included male sex, ethnicity (particularly indigenous peoples), older age, presence of comorbidities, late referral to a nephrology service, remote residence and obesity. Center-level predictors of lower uptake included small center size, smaller proportion of patients with permanent access at dialysis initiation and lower weekly facility hemodialysis hours. The variation in odds of home dialysis uptake across centers increased by 3% after adjusting for the era and patient-level characteristics but decreased by 24% after adjusting for center-level characteristics. CONCLUSION: Center-specific factors are associated with the variation in uptake of home dialysis across centers in Australia and New Zealand.

Donor Kidney Quality and Transplant Outcome: An Economic Evaluation of Contemporary Practice.

OBJECTIVES: The study had two main aims. First, we assessed the cost-effectiveness of transplanting deceased donor kidneys of differing quality levels based on the Kidney Donor Profile Index (KDPI). Second, we assessed the cost-effectiveness of remaining on the waiting list until a high-quality kidney becomes available compared to transplanting a lower-quality kidney. METHODS: A decision analytic model to estimate cost-effectiveness was developed using a Markov process. Separate models were developed for 4 separate KDPI bands, with higher values indicating lower quality. Models were simulated in 1-year cycles for a 20-year time horizon, with transitions through distinct health states relevant to the kidney recipient from the healthcare payer's perspective. Weibull regression was used to calculate the time-dependent transition probabilities in the base analysis. The impact uncertainty arising in model parameters was included by probabilistic sensitivity analysis using the Monte Carlo simulation method. Willingness to pay was considered as Australian $28 000. RESULTS: Transplanting a kidney of any quality is cost-effective compared to remaining on a waitlist. Transplanting a lower KDPI kidney is cost-effective compared to a higher KDPI kidney. Transplanting lower KDPI kidneys to younger patients and higher KDPI kidneys to older patients is also cost-effective. Depending on dialysis in hopes of receiving a lower KDPI kidney is not a cost-effective strategy for any age group. CONCLUSION: Efforts should be made by the health systems to reduce the discard rates of low-quality kidneys with the view of increasing the transplant rates.

Human leukocyte antigen eplet mismatches and long-term clinical outcomes in pediatric renal transplantation: A pragmatic, registry-based study.

BACKGROUND: HLA epitope-based matching offers the potential to improve immunological risk prediction and management in children receiving renal allografts; however, studies demonstrating the association between systems for defining epitope mismatches and clinical end-points are lacking in this population. METHODS: We conducted a pragmatic, retrospective, registry-based study of pediatric recipients of primary renal allografts in Victoria, Australia between 1990 and 2014 to determine the association between HLA EpMM and clinical outcomes including graft failure, re-transplantation and dnDSA formation. RESULTS: A total of 196 patients were included in the analysis with a median age of 11 years. Median follow-up period was 15 years during which time 108 (55%) primary grafts failed and 72 patients were re-transplanted. HLA class I but not class II EpMM was a significant predictor of graft failure on univariate analysis but not in adjusted models. EpMM was associated with reduced likelihood of re-transplantation in univariate but not adjusted analysis. Within the limitations of the study, class-specific EpMM was a strong predictor of dnDSA formation. Associations were stronger when considering only the subset of antibody-verified EpMM. CONCLUSION: Associations between HLA EpMM and clinical outcomes in pediatric renal allograft recipients seen on univariate analysis were attenuated following adjustment for confounders. These findings are inconclusive but suggest that HLA EpMM may provide one tool for assessing long-term risk in this population while highlighting the need for further clinical studies.

Use of patient-reported outcome measures and patient-reported experience measures in renal units in Australia and New Zealand: A cross-sectional survey study.

AIM: Patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) are increasingly used in research to quantify how patients feel and function, and their experiences of care, however, knowledge of their utilization in routine nephrology is limited. METHODS: The Australia and New Zealand Dialysis and Transplant Registry (ANZDATA) PROMs working group conducted a prospective cross-sectional survey of PROMs/PREMs use among renal 'parent hospitals'. One survey per hospital was completed (August-November 2017). Descriptive statistics reported type and frequency of measures used and purpose of use. RESULTS: Survey response rate was 100%. Fifty-five of 79 hospitals (70%) used at least one PROMs or PREMs for specific patient groups. PROMs were more likely to be collected from patients receiving comprehensive conservative care (45% of hospitals) than dialysis patients (32%, 31% and 28% of hospitals for home haemodialysis, peritoneal dialysis and facility dialysis, respectively). Few renal transplanting hospitals (3%) collected PROMs. The Integrated Palliative Outcome Scale-Renal (IPOS-Renal) (40% of units), and the Euro-Qol (EQ-5D-5 L) (25%), were most frequently used. The main reason for collecting PROMs was to inform clinical care (58%), and for PREMs was to fulfil private dialysis/hospital provider requirements (25%). The most commonly reported reason for not using PROMs in 24 hospitals was insufficient staff resources (79%). Sixty-two hospitals (78%) expressed interest in participating in a registry-based PROMs trial. CONCLUSION: Many renal hospitals in Australia and New Zealand collect PROMs and/or PREMs as part of clinical care with use varying by treatment modality. Resources are a key barrier to PROMs use.

Deceased donor kidney allocation: an economic evaluation of contemporary longevity matching practices.

BACKGROUND: Matching survival of a donor kidney with that of the recipient (longevity matching), is used in some kidney allocation systems to maximize graft-life years. It is not part of the allocation algorithm for Australia. Given the growing evidence of survival benefit due to longevity matching based allocation algorithms, development of a similar kidney allocation system for Australia is currently underway. The aim of this research is to estimate the impact that changes to costs and health outcomes arising from 'longevity matching' on the Australian healthcare system. METHODS: A decision analytic model to estimate cost-effectiveness was developed using a Markov process. Four plausible competing allocation options were compared to the current kidney allocation practice. Models were simulated in one-year cycles for a 20-year time horizon, with transitions through distinct health states relevant to the kidney recipient. Willingness to pay was considered as AUD 28000. RESULTS: Base case analysis indicated that allocating the worst 20% of Kidney Donor Risk Index (KDRI) donor kidneys to the worst 20% of estimated post-transplant survival (EPTS) recipients (option 2) and allocating the oldest 25% of donor kidneys to the oldest 25% of recipients are both cost saving and more effective compared to the current Australian allocation practice. Option 2, returned the lowest costs, greatest health benefits and largest gain to net monetary benefits (NMB). Allocating the best 20% of KDRI donor kidneys to the best 20% of EPTS recipients had the lowest expected incremental NMB. CONCLUSION: Of the four longevity-based kidney allocation practices considered, transplanting the lowest quality kidneys to the worst kidney recipients (option 2), was estimated to return the best value for money for the Australian health system.

External validation of the US and UK kidney donor risk indices for deceased donor kidney transplant survival in the Australian and New Zealand population.

BACKGROUND: The US Kidney Donor Risk Index (KDRI) and the UK KDRI were developed to estimate the risk of graft failure following kidney transplantation. Neither score has been validated in the Australian and New Zealand (ANZ) population. METHODS: Using data from the Australia and New Zealand Organ Donor (ANZOD) and Dialysis and Transplant (ANZDATA) Registries, we included all adult deceased donor kidney-only transplants performed in ANZ from 2005 to 2016 (n = 6405). The KDRI was calculated using both the US donor-only and UK formulae. Three Cox models were constructed (Model 1: KDRI only; Model 2: Model 1 + transplant characteristics; Model 3: Model 2 + recipient characteristics) and compared using Harrell's C-statistics for the outcomes of death-censored graft survival and overall graft survival. RESULTS: Both scores were strongly associated with death-censored and overall graft survival (P < 0.0001 in all models). In the KDRI-only models, discrimination of death-censored graft survival was moderately good with C-statistics of 0.63 and 0.59 for the US and UK scores, respectively. Adjusting for transplant characteristics resulted in marginal improvements of the US KDRI to 0.65 and the UK KDRI to 0.63. The addition of recipient characteristics again resulted in marginal improvements of the US KDRI to 0.70 and the UK KDRI to 0.68. Similar trends were seen for the discrimination of overall graft survival. CONCLUSIONS: The US and UK KDRI scores were moderately good at discriminating death-censored and overall graft survival in the ANZ population, with the US score performing slightly better in all models.

Comparison of cause of death between Australian and New Zealand Dialysis and Transplant Registry and the Australian National Death Index.

AIM: The aim of the present study was to understand the differences in how cause of death for patients receiving renal replacement therapy in Australia is recorded in The Australian and New Zealand Dialysis and Transplant Registry (ANZDATA) compared to the National Death Index (NDI). METHODS: Data linkage was performed between ANZDATA and NDI for all deaths in the period 1980-2013. Cause of death was classified according to ICD-10 chapter. Overall and chapter specific agreement were assessed using the Kappa statistic. Descriptive analysis was used to explore differences where there was disagreement on primary cause of death. RESULTS: The analysis cohort included 28 675 patients. Ninety five percent of ANZDATA reported deaths fell within +/- 3 days of the date recorded by NDI. Circulatory death was the most common cause of death in both databases (ANZDATA 48%, NDI 32%). Overall agreement at ICD chapter level of primary cause was poor (36%, kappa 0.22). Agreement was best for malignancy (kappa 0.71). When there was disagreement on primary cause of death these were most commonly coded as genitourinary (35%) and endocrine (25.0%) in NDI, and circulatory (39%) and withdrawal (24%) in ANZDATA. Sixty-nine percent of patients had a renal related cause documented as either primary or a contributing cause of death in the NDI. CONCLUSION: There is poor agreement in primary cause of death between ANZDATA and NDI which is in part explained by the absence of diabetes and renal failure as causes of death in ANZDATA and the absence of 'withdrawal' in NDI. These differences should be appreciated when interpreting epidemiological data on cause of death in the Australian end stage kidney disease population.

Access to waitlisting for deceased donor kidney transplantation in Australia.

AIM: A detailed analysis of waitlisting for deceased donor kidney transplantation in Australia has not previously been reported. We aimed to determine if patient characteristics associated with waitlisting identify areas of potential inequality in access to transplantation in Australia. METHODS: A competing risk time-to-event model was used to determine predictors of waitlisting for all adult incident renal replacement therapy patients in Australia between 2006 and 2015. Secondary analysis was performed to determine predictors of overall access to transplantation (using a combined outcome of waitlisting and living donor transplantation). RESULTS: The cohort consisted of 21 231 patients with a median age of 63 years. Overall, 4361 (20.5%) were waitlisted and 1239 (5.8%) received a living donor transplant without being previously waitlisted. Primary analysis revealed that medical comorbidities, older age, smoking status and body mass index were all significant predictors of waitlisting and that and there was variation in waitlisting practice across states Despite adjustment for the above factors, demographic characteristics, including Indigenous ethnicity (subdistribution hazard ratios (SHR) 0.46 (95% confidence interval (CI) 0.38-0.55)), female gender (SHR 0.85 (95% CI 0.80, 0.91)) and residence in a regional area (SHR 0.88 (95% CI 0.81-0.95)) were also associated with a lower likelihood of waitlisting. Secondary analysis showed younger age and higher socio-economic advantage were additional predictors of overall access to transplantation, driven by higher rates of living donor transplantation. CONCLUSION: Demographic as well as clinical characteristics are associated with reduced likelihood of waitlisting for kidney transplantation in Australia. Further analysis and auditing should be considered to determine if this reflects other unmeasured factors or highlights a need to address inequality.

HLA Epitope Matching in Kidney Transplantation: An Overview for the General Nephrologist.

Rapid changes in tissue-typing technology, including the widespread availability of highly specific molecular typing methods and solid-phase assays for the detection of allele-specific anti-HLA antibodies, make it increasingly challenging to remain up to date with developments in organ matching. Terms such as epitopes and eplets abound in the transplantation literature, but often it can be difficult to see what they might mean for the patient awaiting transplantation. In this review, we provide the historical context for current practice in tissue typing and explore the potential role of HLA epitopes in kidney transplantation. Despite impressive gains in preventing and managing T-cell-mediated rejection and the associated improvements in graft survival, the challenge of the humoral alloresponse remains largely unmet and is the major cause of late graft loss. Describing HLA antigens as a series of antibody targets, or epitopes, rather than based on broad seroreactivity patterns or precise amino acid sequences may provide a more practical and clinically relevant system to help avoid antibody-mediated rejection, reduce sensitization, and select the most appropriate organs in the setting of pre-existing alloantibodies. We explain the systems proposed to define HLA epitopes, summarize the evidence to date for their role in transplantation, and explore the potential benefits of incorporating HLA epitopes into clinical practice as this field continues to evolve toward everyday practice.