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Background: The Kidney Failure Risk Equation (KFRE) predicts the 2- and 5-year risk of needing kidney replacement therapy (KRT) using four risk factors – age, sex, urine albumin-to-creatinine ratio (ACR), and creatinine-based estimated glomerular filtration rate (eGFR). Although the KFRE has been recalibrated in a UK cohort, this did not consider minority ethnic groups. Further validation of the KFRE in different ethnicities is a research priority. The KFRE also does not consider the competing risk of death, which may lead to overestimation of KRT risk. This study externally validates the KFRE for patients of South Asian ethnicity and compares methods for accounting for ethnicity and the competing event of death. Methods: Data were gathered from an established UK cohort containing 35,539 individuals diagnosed with chronic kidney disease. The KFRE was externally validated and updated in several ways taking into account ethnicity, using recognised methods for time-to-event data, including the competing risk of death. A clinical impact assessment compared the updated models through consideration of referrals made to secondary care. Results: The external validation showed the risk of KRT differed by ethnicity. Model validation performance improved when incorporating ethnicity and its interactions with ACR and eGFR as additional risk factors. Further, accounting for the competing risk of death improved prediction. Using a criteria of 5 year ≥5% predicted KRT risk, the competing risks model resulted in an extra 3 unnecessary referrals (0.59% increase) but identified an extra 1 KRT case (1.92% decrease) compared to the previous best model. A hybrid criteria of predicted risk using the competing risks model and ACR ≥70mg/mmol should be used in referrals to secondary care. Conclusions: The accuracy of KFRE prediction improves when updated to consider South Asian ethnicity and to account for the competing risk of death. This may reduce unnecessary referrals whilst identifying risks of KRT and could further individualise the KFRE and improve its clinical utility. Further research should consider other ethnicities.

Background Hypertension is common in individuals with chronic kidney disease and both conditions are associated with adverse outcomes including cardiovascular morbidity. Therefore, it is clinically important to identify methods of risk prediction in individuals with chronic kidney disease. Blood pressure variability has recently emerged as a predictor of cardiovascular events and mortality in the general population, with growing evidence indicating that it may play a similar role in individuals with chronic kidney disease. However, there have been no large studies assessing blood pressure variability in individuals with chronic kidney disease in primary care, where the majority of these patients are managed. Method Using a retrospective observational study design, we analyzed routinely collected blood pressure readings from 16 999 individuals in The Leicester and County Chronic Kidney Disease cohort. Standard deviation, coefficient of variation and average real variability of SBP were used to calculate blood pressure variability. Results During a median follow-up of 5.0 (IQR 3.3--5.0) years, 2053 (12.1%) patients had cardiovascular events, death occurred in 5021 (29.6%) individuals and 156 (0.9%) individuals had endstage kidney disease events. In adjusted models, standard deviation and coefficient of variation were associated with cardiovascular events, all-cause mortality and endstage kidney disease. Average real variability was associated with all-cause mortality and cardiovascular events, but not endstage kidney disease. Conclusion Blood pressure variability may be an accessible, routinely collected, noninvasive measure for stratifying the risk of adverse events in individuals with chronic kidney disease in a primary care setting.

Background South Asian (SA) individuals are more likely to develop end-stage renal disease (ESRD), but how chronic kidney disease (CKD) differs in relation to demographics, comorbidities and outcomes has not been studied. We aimed to study differences in SA individuals with CKD compared with White individuals. Methods This was an observational CKD cohort comparing SA with White individuals. Inclusion criteria were ≥18 years of age and two or more Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) eGFRs 3 months apart. Individuals with ESRD at baseline were excluded. Baseline characteristics, including eGFR formulae [CKD-EPI and CKD-EPI-Pakistan (CKD-EPI-PK)], were compared. Analysis using competing risk regression for cardiovascular (CV) and ESRD events and Cox proportional hazard model for mortality was performed. Results From an adult population of 277 248 individuals, 17 248 individuals had CKD, of whom 1990 (11.5%) were of SA ethnicity. Age-adjusted prevalence of CKD was similar between ethnicities. SA individuals were more likely to be male, younger and socioeconomically deprived, and to have diabetes mellitus, CV disease and advanced CKD. Mean CKD-EPI-PK eGFR was 6.5 mL/min/1.73 m2 lower (41.1 versus 47.6, 95% confidence interval for difference 6.47–6.56) than for CKD-EPI. During 5 years of follow-up, 5109 (29.6%) individuals died, 2072 (12.0%) had a CV and 156 (0.90%) an ESRD event. Risk for SA individuals was higher for ESRD, similar to CV events and lower for mortality. Each 1 mL/min/1.73 m2 decrease in CKD-EPI-PK was associated with a 13.1% increased ESRD risk (adjusted subdistribution hazard ratio 0.869, 95% confidence interval 0.841–0.898). Conclusions SA individuals with CKD were younger and had more advanced disease than White individuals. Risk of ESRD was higher and CKD-EPI-PK was associated with ESRD risk in SA individuals. Specific CKD interventions, including the use of CKD-EPI-PK, should be considered in SA populations.

ObjectivesTo assess the applicability of risk factors for severe COVID-19 defined in the general population for patients on haemodialysis.SettingA retrospective cross-sectional study performed across thirty four haemodialysis units in midlands of the UK.ParticipantsAll 274 patients on maintenance haemodialysis who tested positive for SARS-CoV-2 on PCR testing between March and August 2020, in participating haemodialysis centres.ExposureThe utility of obesity, diabetes status, ethnicity, Charlson Comorbidity Index (CCI) and socioeconomic deprivation scores were investigated as risk factors for severe COVID-19.Main outcomes and measuresSevere COVID-19, defined as requiring supplemental oxygen or respiratory support, or a C reactive protein of ≥75 mg/dL (RECOVERY trial definitions), and its association with obesity, diabetes status, ethnicity, CCI, and socioeconomic deprivation.Results63.5% (174/274 patients) developed severe disease. Socioeconomic deprivation associated with severity, being most pronounced between the most and least deprived quartiles (OR 2.81, 95% CI 1.22 to 6.47, p=0.015), after adjusting for age, sex and ethnicity. There was no association between obesity, diabetes status, ethnicity or CCI with COVID-19 severity. We found no evidence of temporal evolution of cases (p=0.209) or clustering that would impact our findings.ConclusionThe incidence of severe COVID-19 is high among patients on haemodialysis; this cohort should be considered high risk. There was strong evidence of an association between socioeconomic deprivation and COVID-19 severity. Other risk factors that apply to the general population may not apply to this cohort.

Background and ObjectivesRisk factors for cardiovascular disease in chronic kidney disease differ to the general population due to the increased role of inflammation, calcification and arteriosclerosis. Over 350 cardiovascular risk models (“models”) exist in the general population but most have not undergone testing (“external validation”) in other populations, such as cohorts with chronic kidney disease. We aimed to update a previous systematic review of models in chronic kidney disease and then perform external validation of these and general population models in a chronic kidney disease cohort.Design, Setting, Participants and MeasurementsWe searched Medline up to 26th August 2020 for models in chronic kidney disease. We performed external validation of models using a primary care chronic kidney disease cohort of 17,248 individuals with 2,072 (12.0%) cardiovascular events, 5,108 (29.6%) deaths and a median follow-up of 5.0 years. Model discrimination and calibration was assessed and where appropriate models were re-calibrated. Multiple imputation was used to account for missing data.ResultsSeven chronic kidney disease specific models were identified. These models and three general population models underwent external validation. All models had worse discrimination of events than in their original cohorts, particularly in the chronic kidney disease specific models. General population models were miscalibrated and overpredicted risk. The major contributor to this was the high competing risk of death from non-cardiovascular causes.ConclusionsExisting chronic kidney disease cardiovascular risk models performed poorly in external validation. General population cardiovascular disease risk models should be interpreted with caution in individuals with chronic kidney disease as they may overestimate risk due to the competing risk of death. Further development of models to include simultaneous risk prediction for cardiovascular and non-cardiovascular disease risk is required.

Children with end-stage kidney disease (ESKD) requiring renal replacement therapy (RRT) are usually managed in one of the 13 paediatric nephrology centres in the United Kingdom. The UK Renal Registry (UKRR) collects, analyses and reports data on children receiving RRT in these centres.The UKRR annual report presents analyses relating to the attainment of the Renal Association audit measures [1], national averages to enable benchmarking and long-term trends for children on RRT for ESKD. Data are reported by centre to enable between centre comparisons.To improve the timeliness of data reporting, the format of the UKRR 21st Annual Report, which included data to December 31, 2017 [2], differs significantly to that of previous years. For paediatric data, changes include a single chapter reporting demographic and biochemical data, reduced clinical commentary, a higher threshold for data quality control (with data completeness at least 70%) and greater alignment of analyses to the Renal Association guidelines [1].In this article, we summarise the analyses of paediatric data presented in the UKRR 21st Annual Report. The corresponding adult summary is published separately in this issue. The full UKRR 21st Annual Report can be accessed at https://www.renalreg.org/reports/data_to_end_2017/.

Introduction: This retrospective cohort study compares in-centre haemodialysis (ICHD) patients’ outcomes between the 1st and 2nd waves of the COVID-19 pandemic in England, Wales, and Northern Ireland. Methods: All people aged ≥18 years receiving ICHD at 31 December 2019, who were still alive and not in receipt of a kidney transplant at 1 March and who had a positive polymerase chain reaction test for SARS-CoV-2 between 1 March 2020 and 31 January 2021, were included. The COVID-19 infections were split into two “waves”: wave 1 from March to August 2020 and wave 2 from September 2020 to January 2021. Cumulative incidence of COVID-19, multivariable Cox models for risk of positivity, median, and 95% credible interval of reproduction number in dialysis units were calculated separately for wave 1 and wave 2. Survival and hazard ratios for mortality were described with age- and sex-adjusted Kaplan-Meier plots and multivariable Cox proportional models. Results: 4,408 ICHD patients had COVID-19 during the study period. Unadjusted survival at 28 days was similar in both waves (wave 1 75.6% [95% confidence interval [CI]: 73.7–77.5], wave 2 76.3% [95% CI 74.3–78.2]), but death occurred more rapidly after detected infection in wave 1. Long vintage treatment and not being on the transplant waiting list were associated with higher mortality in both waves. Conclusions: Risk of death of patients on ICHD treatment with COVID-19 remained unchanged between the first and second outbreaks. This highlights that this vulnerable patient group needs to be prioritized for interventions to prevent severe COVID-19, including vaccination, and the implementation of measures to reduce the risk of transmission alone is not sufficient.

PURPOSE: A laboratory-based acute kidney injury (AKI) electronic-alert (e-alert) system, with e-alerts sent to the UK Renal Registry (UKRR) and collated in a master patient index (MPI), has recently been implemented in England. The aim of this study was to determine the degree of correspondence between the UKRR-MPI and AKI International Classification Disease-10 (ICD-10) N17 coding in Hospital Episode Statistics (HES) and whether hospital N17 coding correlated with 30-day mortality and emergency re-admission after AKI.METHODS: AKI e-alerts in people aged ≥18 years, collated in the UKRR-MPI during 2017, were linked to HES data to identify a hospitalised AKI population. Multivariable logistic regression was used to analyse associations between absence/presence of N17 codes and clinicodemographic features. Correlation of the percentage coded with N17 and 30-day mortality and emergency re-admission after AKI were calculated at hospital level.RESULTS: In 2017, there were 301 540 adult episodes of hospitalised AKI in England. AKI severity was positively associated with coding in HES, with a high degree of inter-hospital variability-AKI stage 1 mean of 48.2% [SD 14.0], versus AKI stage 3 mean of 83.3% [SD 7.3]. N17 coding in HES depended on demographic features, especially age (18-29 years vs. ≥85 years OR 0.22, 95% CI 0.21-0.23), as well as sex and ethnicity. There was no evidence of association between the proportion of episodes coded for AKI with short-term AKI outcomes.CONCLUSION: Coding of AKI in HES is influenced by many factors that result in an underestimation of AKI. Using e-alerts to triangulate the true incidence of AKI could provide a better understanding of the factors that affect hospital coding, potentially leading to improved coding, patient care and pharmacoepidemiologic research.

Background Chronic kidney disease (CKD) is a recognised risk factor of poor outcomes from COVID-19. Methods This retrospective cohort study used the UK Renal Registry (UKRR) database of people on kidney replacement therapy (KRT) at the end of 2019 in England and who tested positive for SARS-CoV-2 between 01/03/2020 and 31/08/2020, to analyse incidence and outcomes of COVID-19 among different KRT modalities. Comparisons with 2015-2019 mortality data were used to estimate excess deaths. Results 2,783 individuals on KRT tested positive for SARS-CoV-2. Patients from more deprived areas (most deprived vs least deprived HR 1.20, 95% CI 1.04-1.39) and those with diabetes compared to those without (HR 1.51, 95% CI 1.39-1.64) were more likely to test positive. Approximately 25% of in-centre haemodialysis and transplanted patients died within 28 days of testing positive, compared to 36% of those on home therapies. Mortality was higher in those aged ≥80 years compared to those aged 60-79 years (OR 1.71, 95% CI 1.34-2.19) and much lower in those listed for transplantation compared to those not listed (OR 0.56, 95% CI 0.40-0.80). Overall, excess mortality in 2020 for people on KRT was 36% higher than the 2015-2019 average. Excess deaths peaked in April 2020 at the height of the pandemic and were characterised by wide ethnic and regional disparities. Conclusions The impact of COVID-19 on the English KRT population highlights their extreme vulnerability and emphasises the need to protect and prioritise this group for vaccination. COVID-19 has widened underlying inequalities in people with kidney disease making interventions that address health inequalities a priority., Graphical Abstract Graphical Abstract

Background and Aims Acute kidney injury (AKI) is a common and serious condition associated with longer length of hospital stay (LOS) for affected patients; leading to increased morbidity, emotional distress and higher healthcare costs. Implementation of AKI care quality improvement interventions have consistently been shown to reduce patient LOS, suggesting its measurement may serve as a valuable AKI care quality indicator for hospitals. In this study, we set out to explore, for the first time, unwarranted centre variation in case-mix adjusted LOS for patients who develop hospital acquired AKI (HA-AKI) across England. Method Analysis was undertaken using a routinely collected national database of patients with biochemically detected AKI, linked with hospitals administrative data. 250,504 HA-AKI episodes were studied in total, across 103 hospitals between 01/01/2017 – 31/12/2018. LOS was defined as the number of days between first AKI alert and discharge. A negative binomial model was used to generate predicted LOS for patients with HA-AKI at each hospital trust using age, sex, diagnosis group, comorbidity score, AKI severity, admission method, month of AKI alert and critical care attendance. Variation in “observed LOS – predicted LOS” values across centres were then compared using a funnel plot. Additional analyses were undertaken to investigate potential associations between centre LOS and readmission rates as well as variation in LOS amongst patients in the most common diagnosis groups. Results The overall median LOS following HA-AKI alert was 8 days (Interquartile range, 3-17). There was significant variation seen in “observed - predicted LOS” values across hospitals, with 55/103 trusts classed as outliers (99.8% control limits). When analysis was limited to patients with more severe AKI (stages 2 or 3) at presentation this number fell to 10/103 (99.8% control limits). Risk factors for longer LOS included male sex, advancing age, higher comorbidity score, more severe AKI at presentation, emergency admission and critical care attendance. Patients admitted due to fracture neck of femur were at highest risk of longer LOS and exhibited considerably more variation in “observed - predicted LOS” values compared to patients with congestive heart failure, pneumonia or septicaemia. Just over 1/5 of patients with HA-AKI went on to have an emergency re-admission within 30 days of discharge, with no association observed between a trusts “observed – predicted LOS” values and readmission rates (Figure). Conclusion There was considerable centre-variation in LOS for patients with HA-AKI across England. Further interrogation of patient and centre-level factors underlying the observed variation is now necessary to better understand why this variation exists and to inform development of future targeted quality improvement interventions to address this.

Background and Aims Routine monitoring of outcomes for patients with Acute Kidney Injury (AKI) is necessary to drive quality improvement in AKI care. In this study, we describe development of a case-mix adjusted 30-day mortality indicator for patients with hospital acquired AKI (H-AKI), to facilitate identification of unwarranted variation in outcomes across hospitals in England. Method We utilised a routinely collected national dataset of biochemically defined AKI cases, linked with hospitals administrative and mortality data. 250,504 H-AKI episodes were studied in total, across 103 hospitals between January 2017 - December 2018. Standardised mortality ratios were calculated for each hospital using logistic regression; adjusting for age, sex, primary diagnosis, comorbidity score, AKI severity, month of AKI, and admission method. Results Mean 30-day mortality rate was high at 28.6% and varied considerably between hospitals (22.3%-35.5%), with 23/103 trusts classed as outliers (95% control limits). Patients with H-AKI had mortality rates more than 5 times higher than the overall hospitalized population in 90/136 diagnosis groups and over 10 times higher in 60/136 groups. Increasing age, male sex, deprivation, higher comorbidity burden, more severe AKI stage at detection, emergency admission and admission during winter months were all associated with a higher risk of death Presentation at hospitals with on-site specialist nephrology services and Asian or Black ethnicity, however, were linked to a lower risk of death. Conclusion This is the largest multi-centre analysis of mortality for patients with biochemically ascertained H-AKI to date, once again highlighting development of AKI as an important patient safety concern across hospital settings. Centres identified as having poor outcomes will need to carefully interrogate their AKI care pathways to understand and explore reasons underlying the observed variation to guide future quality improvement interventions.

Background Routine monitoring of outcomes for patients with acute kidney injury (AKI) is important to drive ongoing quality improvement in patient care. In this study we describe the development of a case mix-adjusted 30-day mortality indicator for patients with post-hospitalization AKI (PH-AKI) across England to facilitate identification of any unwarranted centre variation in outcomes. Methods We utilized a routinely collected national dataset of biochemically detected AKI cases linked with national hospitals administrative and mortality data. A total of 250 504 PH-AKI episodes were studied across 103 National Health Service hospital trusts between January 2017 and December 2018. Standardized mortality ratios (SMRs) were calculated for each trust using logistic regression, adjusting for age, sex, primary diagnosis, comorbidity score, AKI severity, month of AKI and admission method. Results The mean 30-day mortality rate was high, at 28.6%. SMRs for 23/103 trusts were classed as outliers, 12 above and 11 below the 95% confidence limits. Patients with PH-AKI had mortality rates >5 times higher than the overall hospitalized population in 90/136 diagnosis groups and >10 times higher in 60/136 groups. Presentation at trusts with a co-located specialist nephrology service was associated with a lower mortality risk, as was South Asian or Black ethnicity. Deprivation, however, was associated with higher mortality. Conclusions This is the largest multicentre analysis of mortality for patients with biochemically ascertained PH-AKI to date, demonstrating once again the considerable risk associated with developing even mild elevations in serum creatinine. Mortality rates varied considerably across centres and those identified as outliers will now need to carefully interrogate local care pathways to understand and address the reasons for this, with national policy required to tackle the identified health disparities.

As Munro and Faust point out, there appears a stark contrast in the case and mortality rates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among children compared with the adult population.1 Whether infection in children is generally mild or asymptomatic, which goes undetected, or children are less susceptible to contracting the infection is unclear until screening programmes are introduced. What also remains uncertain is the risk of severe infection for children with significant underlying health concerns, including those with chronic kidney disease (CKD). The few studies reported have so far shown reassuringly low numbers and complication rates in children with coexisting diseases such as cancer and liver transplant recipients.2 3 The NHS England COVID-19 service evaluation (https://www.rcpch.ac.uk/resources/covid-19-service-evaluation-audit-care-needs-children-admitted-hospital-england), to date, has identified 220 confirmed cases in England of whom 44.4% of cases have coexisting disease; two children are reported to have CKD. At the UK Renal Registry (UKRR) and in collaboration with the British Association for …

Background The Kidney Failure Risk Equation (KFRE) uses the 4 variables of age, sex, urine albumin-to-creatinine ratio (ACR), and estimated glomerular filtration rate (eGFR) in individuals with chronic kidney disease (CKD) to predict the risk of end stage renal disease (ESRD), i.e., the need for dialysis or a kidney transplant, within 2 and 5 years. Currently, national guideline writers in the UK and other countries are evaluating the role of the KFRE in renal referrals from primary care to secondary care, but the KFRE has had limited external validation in primary care. The study’s objectives were therefore to externally validate the KFRE’s prediction of ESRD events in primary care, perform model recalibration if necessary, and assess its projected impact on referral rates to secondary care renal services. Methods and findings Individuals with 2 or more Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) eGFR values < 60 ml/min/1.73 m2 more than 90 days apart and a urine ACR or protein-to-creatinine ratio measurement between 1 December 2004 and 1 November 2016 were included in the cohort. The cohort included 35,539 (5.6%) individuals (57.5% female, mean age 75.9 years, median CKD-EPI eGFR 51 ml/min/1.73 m2, median ACR 3.2 mg/mmol) from a total adult practice population of 630,504. Overall, 176 (0.50%) and 429 (1.21%) ESRD events occurred within 2 and 5 years, respectively. Median length of follow-up was 4.7 years (IQR 2.8 to 6.6). Model discrimination was excellent for both 2-year (C-statistic 0.932, 95% CI 0.909 to 0.954) and 5-year (C-statistic 0.924, 95% 0.909 to 0.938) ESRD prediction. The KFRE overpredicted risk in lower (, In this cohort study, Rupert Major and colleagues evaluate the performance of the Kidney Failure Risk Equation in chronic kidney disease patients in primary care settings and project impact of a recalibrated equation on referral practices and patient outcomes., Author summary Why was this study done? The Kidney Failure Risk Equation (KFRE) has been developed in multinational chronic kidney disease (CKD) cohorts to predict end stage renal disease (ESRD) events (the need for dialysis or a kidney transplant) over 2- and 5-year time periods. The performance of the KFRE has not been extensively tested in UK and European primary care CKD populations. The projected impact of the KFRE on referrals from primary to secondary care has not been studied, and it is unclear what criteria for referrals should be used. What did the researchers do and find? Our study suggests that the KFRE has largely accurate performance (discrimination) for predicting ESRD, but requires adjustment (recalibration) for a primary care setting. Compared to current referral criteria, using hybrid criteria of a ≥5% risk of ESRD over 5 years from the recalibrated KFRE and/or a urine albumin-to-creatinine ratio (ACR) of ≥70 mg/mmol would reduce the number of individuals eligible for referral without increasing the number who later develop ESRD and are not initially eligible for referral. What do these findings mean? The recalibrated KFRE can be used to predict the risk of ESRD over 2 and 5 years in primary care CKD. The KFRE, in conjunction with the ACR criterion, can be used to triage CKD referrals from primary to secondary care.

Background and Aims Acute kidney injury (AKI) refers to an abrupt decline in the glomerular filtration rate (GFR) which may be associated with significant morbidity and mortality. Since April 2015, an automated real-time electronic alert system for AKI has been introduced and progressively implemented in England, with alert data being sent to the UK Renal Registry (UKRR) for collection into a master patient index (MPI). Historically, the only way to routinely measure AKI incidence in hospital was to analyse the Hospital Episode Statistics (HES). The introduction of the MPI allows for the first time a comparison between warning-test score defined AKI and clinical coding. This project aims to determine whether episodes of AKI identified in the UKRR MPI correspond to coded diagnoses on the discharge record held in HES. Method The UKRR MPI of all AKI electronic alerts (AKI stages 1, 2 and 3) in patients ≥18 years of age, between 01/01/2017 and 31/12/2017 were linked to HES data to identify a hospitalised AKI population. Descriptive analyses were conducted to describe the demographics and to investigate whether those with electronic AKI alert also had an International Classification of Diseases (ICD)-10 code for AKI (N17) in HES. Results From 01/01/2017 to 31/12/2017, 301,504 hospitalised adults received an AKI electronic alert. AKI severity was positively associated with the percentage of AKI alerts which were coded in HES. There was also a significant variation in HES coding between hospitals, but generally, variation was most pronounced for AKI stage 1, with a mean of 48.2% [SD 14], versus AKI stage 3, with a mean of 83.3 % [SD 7.3] (figures 1, 2 and 3). There was an inverse trend with age in that younger adults AKI staging warning scores were less often coded in HES and this was true for all the three AKI stages (33% of AKI episodes coded in HES for people aged 18-29 versus 64% for people ≥ 85 years old) (Table 1). Conclusion In 2017, earlier stages AKI warning scores were poorly coded in HES. There was also high degree of inter-hospital variability, particularly for AKI warning score 1, reflecting potentially poor clinical recognition and documentation in medical record and subsequent clinical coding. AKI warning scores were poorly captured in HES for younger adults in comparison to those of older age; reasons for which need to be identified. Use of HES to identify cases of AKI is likely to underestimate the incidence of AKI, especially for AKI stage 1, though a high proportion of the most severe cases will be captured.

Introduction: Diabetes is a major cause of CKD and of mortality in patients on renal replacement therapy (RRT). Auditing the care of patients with diabetes on RRT against published guidelines relies on robust data collection. Objective: This article assesses the completeness of data items collected by the UK Renal Registry (UKRR) that are required to audit the care of patients with diabetes on RRT. Methods: The UKRR receives data on all patients receiving RRT in the UK. Patients with diabetes, diabetes type, and method of renal diagnosis were identified from primary renal disease (PRD) codes and comorbidity data for patients commencing RRT at one of the 57 renal centres in England and Wales between 2010 and 2016. The completeness of demographic and clinical data (blood pressure, cholesterol, glycated haemoglobin [HbA1c], and smoking status) was assessed for the first year of RRT. Results: Ninety-three per cent of all patients on RRT irrespective of diagnosis had a PRD code, but only 28/57 renal centres had comorbidity data completeness ≥70%; 34.9% of patients with diabetic nephropathy (DN) had type 1 diabetes, but this varied between centres (9.2–100%). Overall, 4.2% of DN diagnoses were by biopsy. Data completeness in the first year of RRT for cardiovascular risk factors ranged between 50.0 and 80.0%, with HbA1c data completeness being 63.0%. Of 57 centres, 20 had HbA1c data for ≥70% of patients in the first year of RRT. Conclusions: There is persistent variation between renal centres in the completeness of data collected on patients with diabetes on RRT, impacting on the ability to undertake robust audit. Data linkages and expanded data permissions could see registry data play a key role in ongoing audit and research into patients with diabetes and CKD, provided adequate data can be collected.

Item does not contain fulltext BACKGROUND: Change in albuminuria as a surrogate endpoint for progression of chronic kidney disease is strongly supported by biological plausibility, but empirical evidence to support its validity in epidemiological studies is lacking. We aimed to assess the consistency of the association between change in albuminuria and risk of end-stage kidney disease in a large individual participant-level meta-analysis of observational studies. METHODS: In this meta-analysis, we collected individual-level data from eligible cohorts in the Chronic Kidney Disease Prognosis Consortium (CKD-PC) with data on serum creatinine and change in albuminuria and more than 50 events on outcomes of interest. Cohort data were eligible if participants were aged 18 years or older, they had a repeated measure of albuminuria during an elapsed period of 8 months to 4 years, subsequent end-stage kidney disease or mortality follow-up data, and the cohort was active during this consortium phase. We extracted participant-level data and quantified percentage change in albuminuria, measured as change in urine albumin-to-creatinine ratio (ACR) or urine protein-to-creatinine ratio (PCR), during baseline periods of 1, 2, and 3 years. Our primary outcome of interest was development of end-stage kidney disease after a baseline period of 2 years. We defined an end-stage kidney disease event as initiation of kidney replacement therapy. We quantified associations of percentage change in albuminuria with subsequent end-stage kidney disease using Cox regression in each cohort, followed by random-effects meta-analysis. We further adjusted for regression dilution to account for imprecision in the estimation of albuminuria at the participant level. We did multiple subgroup analyses, and also repeated our analyses using participant-level data from 14 clinical trials, including nine clinical trials not in CKD-PC. FINDINGS: Between July, 2015, and June, 2018, we transferred and analysed data from 28 cohorts in the CKD-PC, which included 693 816 individuals (557 583 [80%] with diabetes). Data for 675 904 individuals and 7461 end-stage kidney disease events were available for our primary outcome analysis. Change in ACR was consistently associated with subsequent risk of end-stage kidney disease. The adjusted hazard ratio (HR) for end-stage kidney disease after a 30% decrease in ACR during a baseline period of 2 years was 0.83 (95% CI 0.74-0.94), decreasing to 0.78 (0.66-0.92) after further adjustment for regression dilution. Adjusted HRs were fairly consistent across cohorts and subgroups (ie, estimated glomerular filtration rate, diabetes, and sex), but the association was somewhat stronger among participants with higher baseline ACR than among those with lower baseline ACR (pinteraction

Background/Introduction: Acute kidney injury (AKI) is common in acute hospital admission and associated with worse patient outcomes. Aim: To measure incidence, care quality and outcome of AKI in admitted hospital care. Design: Forty-six of 168 acute NHS healthcare trusts in UK caring for 2 million acute hospital admissions per annum collected information on adults identified with AKI stage 3 (3-fold rise in serum creatinine or creatinine >354 µmol/l) through routine biochemical testing over a 5-month period in 2012. Methods: Information was collected on patient and care characteristics. Primary outcomes were survival and recovery of kidney function at 1 month. Results: A total of 15 647 patients were identified with biochemical AKI stage 3. Case note reviews were available for 7726 patients. In 80%, biochemical AKI stage 3 was confirmed clinically. Among this group, median age was 75 years, median length of stay was 12 days and the overall mortality within 1 month was 38%. Significant factors in a multivariable model predicting survival included age and some causes of AKI. Dipstick urinalysis, medication review, discussion with a nephrologist and acceptance for transfer to a renal unit were also associated with higher survival, but not early review by a senior doctor, acceptance for transfer to critical care or requirement for renal replacement therapy. Eighteen percent of people did not have their kidney function checked 1 month after the episode had resolved. Discussion/Conclusions: This large study of in-hospital AKI supports the efficacy of biochemical detection of AKI in common usage. AKI mortality remains substantial, length of stay comparable with single-centre studies, and much of the variation is poorly explained (model Cox and Snell R 2 = 0.131) from current predictors.

Kidney disease is a recognised risk factor for poor COVID-19 outcomes. Up to 30 June 2020, the UK Renal Registry (UKRR) collected data for 2,385 in-centre haemodialysis (ICHD) patients with COVID-19 in England and Wales. Overall unadjusted survival at 1 week after date of positive COVID-19 test was 87.5% (95% CI 86.1–88.8%); mortality increased with age, treatment vintage and there was borderline evidence of Asian ethnicity (HR 1.16, 95% CI 0.94–1.44) being associated with higher mortality. Compared to the general population, the relative risk of mortality for ICHD patients with COVID-19 was 45.4 and highest in younger adults. This retrospective cohort study based on UKRR data supports efforts to protect this vulnerable patient group.

Background. Chronic kidney disease (CKD) is a major challenge for health care systems around the world, and the prevalence rates appear to be increasing. We estimate the costs of CKD in a universal health care system. Methods. Economic modelling was used to estimate the annual cost of Stages 3–5 CKD to the National Health Service (NHS) in England, including CKD-related prescribing and care, renal replacement therapy (RRT), and excess strokes, myocardial infarctions (MIs) and Methicillin-Resistant Staphylococcus Aureus (MRSA) infections in people with CKD. Results. The cost of CKD to the English NHS in 2009–10 is estimated at £1.44 to £1.45 billion, which is ∼1.3% of all NHS spending in that year. More than half this sum was spent on RRT, which was provided for 2% of the CKD population. The economic model estimates that ∼7000 excess strokes and 12 000 excess MIs occurred in the CKD population in 2009–10, relative to an age- and gender-matched population without CKD. The cost of excess strokes and MIs is estimated at £174–£178 million. Conclusions. The financial impact of CKD is large, with particularly high costs relating to RRT and cardiovascular complications. It is hoped that these detailed cost estimates will be useful in analysing the cost-effectiveness of treatments for CKD.

The Chronic Kidney Disease (CKD) Prognosis Consortium is a collaborative author of the above-mentioned article. The CKD Prognosis Consortium investigators/collaborators are as follows: • African American Study of Kidney Disease and Hypertension (AASK): Brad Astor, Lawrence J. Appel; British Columbia CKD Study (BC CKD): Adeera Levin, Ognjenka Djurdjev; Canadian Study of Prediction of Death, Dialysis and Interim Cardiovascular Events (CanPREDDICT): Adeera Levin, Mila Tang, Ognjenka Djurdjev; Cleveland Clinic CKD Registry Study (CCF): Sankar D. Navaneethan, Stacey E. Jolly, Jesse D. Schold, Joseph V. Nally Jr; Chronic Renal Impairment in Birmingham (CRIB): David C. Wheeler, Jonathan Emberson, John Townend, Martin Landray; Chronic Renal Insufficiency Cohort Study (CRIC): Harold I. Feldman, Chi-yuan Hsu, James P. Lash, Lawrence J. Appel; Chronic Renal Insufficiency Standards Implementation Study (CRISIS): Philip A. Kalra, James P. Ritchie, Raman Maharajan, Helen Alderson, Beverly Lane; German Chronic Kidney Disease Study (GCKD): Kai-Uwe Eckardt, Markus P. Schneider, Anna Kottgen, Florian Kronenberg, Barbara Barthlein; Geisinger Health System: Alex R. Chang, Jamie A. Green, H. Lester Kirchner, Kevin Ho; Grampian Laboratory Outcomes, Morbidity and Mortality Studies – 2 (GLOMMS2): Angharad Marks, Corri Black, Gordon J. Prescott, Nick Fluck; Gonryo Study: Masaaki Nakayama, Mariko Miyazaki, Tae Yamamoto, Gen Yamada; Hong Kong CKD Studies: Angela Yee-Moon Wang, Sharon Cheung, Sharon Wong, Jessie Chu, Henry Wu; Maccabi Health System: Varda Shalev, Gabriel Chodick; Multifactorial Approach and Superior Treatment Efficacy in Renal Patients with the Aid of a Nurse Practitioner (MASTERPLAN): Peter J. Blankestijn, Jack F.M. Wetzels, Arjan D. van Zuilen, Jan A. van den Brand; Modification of Diet in Renal Disease Study (MDRD): Andrew S. Levey, Lesley A. Inker, Mark J. Sarnak, Hocine Tighiouart; Nanjing CKD Network Cohort Study (Nanjing CKD): Haitao Zhang; NephroTest Study: Benedicte Stengel; National Renal Healthcare Program – Uruguay (NRHP-URU): Pablo G. Rios, Nelson Mazzuchi, Liliana Gadola, Veronica Lamadrid, Laura Sola; New Zealand Diabetes Cohort Study (NZDCS): John F. Collins, C. Raina Elley, Timothy Kenealy; Parcours de Soins des Personnes Agees (PSPA): Olivier Moranne, Cecile Couchoud, Cecile Vigneau; Primary-Secondary Care Partnership to Prevent Adverse Outcomes in Chronic Kidney Disease (PSP CKD): Nigel J. Brunskill, Rupert W. Major, David Shepherd, James F. Medcalf; Racial and Cardiovascular Risk Anomalies in CKD Cohort (RCAV): Csaba P. Kovesdy, Kamyar Kalantar-Zadeh, Miklos Z. Molnar, Keiichi Sumida, Praveen K. Potukuchi; Reduction of Endpoints in Non-insulin Dependent Diabetes Mellitus with the Angiotensin II Antagonist Losartan (RENAAL): Hiddo J.L. Heerspink, Dick de Zeeuw, Barry Brenner; Stockholm CREAtinine Measurements Cohort (SCREAM): Juan Jesus Carrero, Peter Barany, Abdul Rashid Qureshi, Carl-Gustaf Elinder; Second Manifestations of ARTerial Disease Study (SMART): Frank L.J. Visseren, Yolanda van der Graaf; Swedish Renal Registry CKD Cohort (SRR CKD): Marie Evans, Maria Stendahl, Staffan Schon, Marten Segelmark, Karl-Goran Prutz; Sunnybrook Cohort: David M. Naimark, Navdeep Tangri; West of Scotland CKD Study: Patrick B. Mark, Jamie P. Traynor, Colin C. Geddes, Peter C. Thomson.• CKD Prognosis Consortium Steering Committee: Alex R. Chang, Josef Coresh (Chair), Ron T. Gansevoort, Morgan E. Grams, Anna Kottgen, Andrew S. Levey, Kunihiro Matsushita, Mark Woodward, Luxia Zhang.• CKD Prognosis Consortium Data Coordinating Center: Shoshana H. Ballew (Assistant Project Director), Jingsha Chen (Programmer), Josef Coresh (Principal Investigator), Morgan E. Grams (Director of Nephrology Initiatives), Lucia Kwak (Programmer), Kunihiro Matsushita (Director), Yingying Sang (Lead Programmer), Aditya Surapaneni (Programmer), Mark Woodward (Senior Statistician).• Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference on Prognosis and Optimal Management of Patients with Advanced CKD: Kai-Uwe Eckardt (Conference Co-Chair), Brenda R. Hemmelgarn (Conference Co-Chair), David C. Wheeler (KDIGO Co-Chair), Wolfgang C. Winkelmayer (KDIGO Co-Chair), John Davis (CEO), Danielle Green (Managing Director), Michael Cheung (Chief Scientific Officer), Tanya Green (Communications Director), Melissa McMahan (Programs Director).

SUMMARY: Technique survival of peritoneal dialysis is seriously limited by the development of peritoneal fibrosis. the mesothelial cell layer lining the peritoneum is important in the pathogenesis of peritoneal fibrosis. Mesothelial cells are able to produce transforming growth factor beta (TGF-β), and respond to stimulation by this cytokine. In this review, we will detail the evidence available so far for the role of the complex interaction between TGF-β and mesothelial cells in the development of peritoneal fibrosis.

Background End-of-life care for people with chronic kidney disease (CKD) has been identified as an area of great clinical need internationally. We estimate causes and place of death and cost of hospital care for people with CKD in England in the final 3 years of life. Methods Hospital Episode Statistics data were linked to Office for National Statistics mortality data to identify all patients in England aged ≥18 years who died 1 April 2006-31 March 2010, and had a record of hospital care after 1 April 2003 (the study group). The underlying cause and place of death were examined in Office for National Statistics data, for patients without and with CKD (identified by International Classification of Diseases version 10 codes N18, I12 and I13). Costs of hospital admissions and outpatient attendances were estimated using National Health Service Reference Cost data. Associations between CKD and hospital costs, and between place of death and hospital costs in those with CKD, were examined using multivariate regressions. Results There were 1 602 105 people in the study group. Of these, 13.2% were recorded as having CKD. The proportion of deaths at home was 10.7% in people with CKD and 17.2% in the age- and gender-matched non-CKD group. Regression analysis suggests that CKD was associated with an increase in hospital costs of £3380 in the last 12 months of life, holding constant place of death, comorbidities and other variables. For the CKD group, home death was associated with a reduction in hospital costs of £2811 in the 12 months before death. The most commonly recorded cause of death in people with CKD was heart disease. CKD was not mentioned on the death certificate in two-thirds of deaths in people with the condition. Conclusions People with CKD are less likely to die at home than those without CKD. The condition is associated with increased hospital costs at the end of life regardless of place of death. Home death in CKD is associated with a substantial reduction in hospital costs at the end of life.

The letter to the editor from Kosmadakis et al.1 references our findings of 25-hydroxyvitamin D (25OHD) levels in the National Health Examination Survey (NHANES III).2 In their subjects, no significant differences in 25OHD levels between stage III and IV chronic kidney disease (CKD) were observed, although both levels were consistent with 25OHD insufficiency.3 These findings are contrary to what was observed in NHANES III where the major decline in 25OHD was observed in stage IV CKD.

BACKGROUND Dialysate glucose has been implicated in the loss of peritoneal membrane function seen in long-term CAPD patients. METHODS In order to investigate this in vitro, human peritoneal mesothelial cells (HPMC) were cultured in a 50:50 mix of dialysis solution and M199 for 12 h. The dialysate was laboratory manufactured and designed to be identical in composition to PD4 (LAB). The final glucose concentration ranged between 5 and 40 mmol/l. Experiments were conducted in the presence and absence of an anti-transforming growth factor-beta (TGF-beta) antibody. Cell viability was measured by lactate dehydrogenase (LDH) release. Fibronectin (FN) and TGF-beta protein were measured by ELISA, and FN gene expression was measured by Northern analysis. Separately, the effects of recombinant TGF-beta(1) added to M199: dialysate at 5 mmol/l glucose were investigated. RESULTS Forty millimoles per litre d-glucose LAB caused a decrease in cell viability, as evidenced by an increase in LDH release (6.0+/-1.3 vs 2.6+/-0.7%). This effect was dependent on osmolality. Forty millimoles per litre d-glucose LAB stimulated a 15.4+/-4.6% increase in FN, a 46.5+/-18.3% increase in TGF-beta protein (both P

Role of diuretics in the preservation of residual renal function in patients on continuous ambulatory peritoneal dialysis. Background Patients on continuous ambulatory peritoneal dialysis (CAPD) are dependent on residual renal function for solute and water clearances, and this declines with time on dialysis. Loop diuretics have been postulated to slow this decline. Methods Sixty-one patients new to dialysis were randomly assigned to either furosemide 250mg every day or no furosemide at the time of CAPD training and were followed prospectively. Urine volume (UV), urea clearance (C Urea ), and creatinine clearance on cimetidine (C Cr ) were measured at randomization at six months and at one year. Patients underwent a standard four-hour peritoneum equilibrium test, and total body water was measured by bioelectrical impedance. Results were expressed on an intention-to-treat basis. Results UV, C Cr , and C Urea were similar at randomization (1020 ± 104 vs. 1040 ± 130mL/24 hours, 4.95 ± 0.51 vs. 4.07 ± 0.40mL/min/1.73m 2 , 0.91 ± 0.09 vs. 0.84 ± 0.08, diuretic vs. control). UV in the diuretic-treated group increased, whereas in the control group, it declined (+176 vs. -200mL/24 hours at 6 months and +48.8 vs. -305mL/24 hours at 1 year, P Cr and C Urea declined at a constant rate and were unaffected by diuretic administration (0.12 ± 0.05 vs. 0.071 ± 0.04mL/min/1.73m 2 /month, 0.020 ± 0.01 vs. 0.019 ± 0.01 per month). Urinary sodium excretion increased in the diuretic group and declined in the control group (+0.72 ± 0.85 vs. -2.56 ± 1.31 mmol/24 hours/month, P = 0.04). Body weight rose in both groups (4.3 vs. 3.0 kg), but the percentage of total body weight rose in the control group and remained constant in the diuretic group (52 ± 2.4 vs. 64 ± 6.6%, P = 0.10). Conclusions Long-term furosemide produces a significant increase in UV over 12 months when on CAPD and may result in clinically significant improvement in fluid balance. However, furosemide has no effect on preserving residual renal function.