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This work was supported by Health Data Research UK (HDR-9006; CFC0110) and the Medical Research Council (MR/S027750/1). Health Data Research UK is funded by: UK Medical Research Council; Engineering and Physical Sciences Research Council; Economic and Social Research Council; National Institute for Health Research (England); Chief Scientist Office of the Scottish Government Health and Social Care Directorates; Health and Social Care Research and Development Division (Welsh Government); Public Health Agency (Northern Ireland); British Heart Foundation and Wellcome Trust. Introduction Multimorbidity is widely recognised as the presence of two or more concurrent long-term conditions, yet remains a poorly understood global issue despite increasing in prevalence. We have created the Wales Multimorbidity e-Cohort (WMC) to provide an accessible research ready data asset to further the understanding of multimorbidity. Our objectives are to create a platform to support research which would help to understand prevalence, trajectories and determinants in multimorbidity, characterise clusters that lead to highest burden on individuals and healthcare services, and evaluate and provide new multimorbidity phenotypes and algorithms to the National Health Service and research communities to support prevention, healthcare planning and the management of individuals with multimorbidity. Methods and analysis The WMC has been created and derived from multisourced demographic, administrative and electronic health record data relating to the Welsh population in the Secure Anonymised Information Linkage (SAIL) Databank. The WMC consists of 2.9 million people alive and living in Wales on the 1 January 2000 with follow-up until 31 December 2019, Welsh residency break or death. Published comorbidity indices and phenotype code lists will be used to measure and conceptualise multimorbidity. Study outcomes will include: (1) a description of multimorbidity using published data phenotype algorithms/ontologies, (2) investigation of the associations between baseline demographic factors and multimorbidity, (3) identification of temporal trajectories of clusters of conditions and multimorbidity and (4) investigation of multimorbidity clusters with poor outcomes such as mortality and high healthcare service utilisation. Ethics and dissemination The SAIL Databank independent Information Governance Review Panel has approved this study (SAIL Project: 0911). Study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals. Publisher PDF

Movement of solutes across the peritoneum allows for the use of peritoneal dialysis to treat kidney failure. However, there is a large inter-individual variability in the peritoneal solute transfer rate (PSTR). Here, we tested the hypothesis that common genetic variants are associated with variability in PSTR. Of the 3561 participants from 69 centers in six countries, 2850 with complete data were included in a genome-wide association study. PSTR was defined as the four-hour dialysate/plasma creatinine ratio from the first peritoneal equilibration test after starting PD. Heritability of PSTR was estimated using genomic-restricted maximum-likelihood analysis, and the association of PSTR with a genome-wide polygenic risk score was also tested. The mean four-hour dialysate/plasma creatinine ratio in participants was 0.70. In 2212 participants of European ancestry, no signal reached genome-wide significance but 23 single nucleotide variants at four loci demonstrated suggestive associations with PSTR. Meta-analysis of ancestry-stratified regressions in 2850 participants revealed five single-nucleotide variants at four loci with suggestive correlations with PSTR. Association across ancestry strata was consistent for rs28644184 at the KDM2B locus. The estimated heritability of PSTR was 19%, and a permuted model polygenic risk score was significantly associated with PSTR. Thus, this genome-wide association study of patients receiving peritoneal dialysis bolsters evidence for a genetic contribution to inter-individual variability in PSTR.

There has been growing interest recently in using machine learning techniques as an aid in clinical medicine. Machine learning offers a range of classification algorithms which can be applied to medical data to aid in making clinical predictions. Recent studies have demonstrated the high predictive accuracy of various classification algorithms applied to clinical data. Several studies have already been conducted in diagnosing or predicting chronic kidney disease at various stages using different sets of variables. In this study we are investigating the use of machine learning techniques with blood test data. Such a system could aid renal teams in making recommendations to primary care general practitioners to refer patients to secondary care where patients may benefit from earlier specialist assessment and medical intervention. We are able to achieve an overall accuracy of 88.48% using logistic regression, 87.12% using ANN and 85.29% using SVM. ANNs performed with the highest sensitivity at 89.74 % compared to 86.67 % for logistic regression and 85.51 % for SVM.

IntroductionAcute Kidney Injury (AKI) effects up to 20% of emergency hospital admissions. It can be identified from serum creatinine (SCr) levels and as such an e-alert system has been introduced to hospitals in England and Wales to identify AKI. This system relies on manual review by pathology laboratory staff to prevent false alerts in dialysis patients. Objectives and ApproachOur aim is to use routinely collected dialysis timeline and dialysis treatment data in order to create dialysis treatment spells using Structured Query Language (SQL), which can then be compared with dialysis prevalence results in the UK renal registry. Furthermore, we will link this data with biochemical results in Secure Anonymised Information Linkage (SAIL) Databank to create an AKI cohort. Through identifying when patients are on renal replacement therapy (RRT) at a specific time we are able to exclude false positive AKI Alerts. This is done in two ways – one from a timeline within the data which is used in the UK renal registry. The other using individual dialysis sessions to get accurate coverage, as short periods of acute dialysis are often not been recorded in UK renal registry data. ResultsUsing the renal dataset in SAIL we were able identify more renal dialysis patients than the UK renal registry between (2009-17). By applying this to Swansea and Bridgend pathology data in SAIL we were able to identify 60,072 SCr tests in dialysis patients between 2011 and 2013 out of 1,776,101 SCr tests. In this cohort, without ruling out dialysis patients there would be 91,140 AKI alerts, however 19.6% (17,855) of the alerts are during dialysis treatments spells. Conclusion / ImplicationsWe were able to recreate the ‘e-Alert’ algorithm using SQL with SAIL and get an accurate picture of RRT in Wales, enabling more accurate AKI analysis.

Background and objectives\ud The inflammation-driven increase in peritoneal solute transport rate that occurs during long-term peritoneal dialysis is associated with higher mortality, hospitalization, and encapsulating peritoneal sclerosis. Because biocompatible solutions were developed to mitigate these effects, we examined the association with their use and longitudinal peritoneal solute transport rate.\ud \ud Design, setting, participants, & measurements\ud We analyzed subjects from the multinational prospective Global Fluid Study with three or more peritoneal solute transport rate measurements >2 months from the start of peritoneal dialysis. Follow-up was for 7.5 years (median, 2.3 years; interquartile range, 1.8–3.6) in biocompatible solutions and 12.8 years (median, 3.2 years; interquartile range, 1.9–4.3) for standard solutions. Using a random intercept/slopes multilevel model, we examined the association of patients using biocompatible solutions and peritoneal solute transport rate over time, adjusting for center effects, dialysate dextrose concentration, baseline dialysate IL-6 concentration, icodextrin use, residual kidney function, and peritonitis.\ud \ud Results\ud Of 366 patients, the 71 receiving biocompatible solutions throughout their time on peritoneal dialysis had a mean adjusted dialysate-to-plasma creatinine ratio of 0.67 compared with 0.72 for standard solutions (P=0.02). With duration of treatment, there was a continuous increase in peritoneal solute transport rate in patients using standard solutions (range, 2 months to 4 years). In contrast, patients using biocompatible solutions had peritoneal solute transport rates that plateaued after 2 years of therapy. These changes in peritoneal solute transport rate were independent of baseline inflammation and time-varying predictors of faster peritoneal solute transport rate. In patients suffering episodes of peritonitis while using standard solutions, there was an associated increase in peritoneal solute transport rate of 0.020 (95% confidence interval, 0.01 to 0.03) per episode, whereas in patients using biocompatible solutions, there was no change in this parameter (−0.014; 95% confidence interval, −0.03 to

ObjectivesTo explore how people with chronic kidney disease who are pre-dialysis, family members and healthcare professionals together navigate common shared decision-making processes and to assess how this impacts future treatment choice.DesignCoproductive qualitative study, underpinned by the Making Good Decisions in Collaboration shared decision-model. Semistructured interviews with a purposive sample from February 2019 - January 2020. Interview data were analysed using framework analysis. Coproduction of logic models/roadmaps and recommendations.SettingFive Welsh kidney services.Participants95 participants (37 patients, 19 family members and 39 professionals); 44 people supported coproduction (18 patients, 8 family members and 18 professionals).FindingsShared decision-making was too generic and clinically focused and had little impact on people getting onto home dialysis. Preferences of where, when and how to implement shared decision-making varied widely. Apathy experienced by patients, caused by lack of symptoms, denial, social circumstances and health systems issues made future treatment discussions difficult. Families had unmet and unrecognised needs, which significantly influenced patient decisions. Protocols containing treatment hierarchies and standards were understood by professionals but not translated for patients and families. Variation in dialysis treatment was discussed to match individual lifestyles. Patients and professionals were, however, defaulting to the perceived simplest option. It was easy for patients to opt for hospital-based treatments by listing important but easily modifiable factors.ConclusionsShared decision-making processes need to be individually tailored with more attention on patients who could choose a home therapy but select a different option. There are critical points in the decision-making process where changes could benefit patients. Patients need to be better educated and their preconceived ideas and misconceptions gently challenged. Healthcare professionals need to update their knowledge in order to provide the best advice and guidance. There needs to be more awareness of the costs and benefits of the various treatment options when making decisions.

It is not clear whether the association of increased peritoneal protein clearance (PPCl) with worse survival on peritoneal dialysis (PD) is a consequence of either local or systemic inflammation or indicative of generalized endothelial dysfunction associated with comorbidity. To investigate this we determined the relationship of PPCl to comorbidity, membrane area (equivalent to low molecular weight peritoneal solute transport rate), local and systemic inflammation and hypoalbuminaemia, and for each of these with patient survival. 257 incident patients from three GLOBAL Fluid Study centers were included in this analysis. Clinical profiles were collected at baseline along with a peritoneal equilibration test, 24-h dialysate protein and paired plasma and dialysate cytokine measurements. Although peritoneal protein clearance was associated with increased age and severe comorbidity on univariate analysis, only dialysate IL-6, peritoneal solute transport rate, plasma albumin and cardiac comorbidities (ischaemic heart disease and left ventricular dysfunction) were independent explanatory variables on multivariate analysis. While peritoneal protein clearance and daily peritoneal protein loss were associated with survival in univariate analysis, on multivariate analysis only plasma IL-6, age, residual kidney function, comorbidity, and plasma albumin were independent predictors. Peritoneal protein clearance is primarily a function of peritoneal membrane area and local membrane inflammation. The association with comorbidity and survival is predominantly explained by its inverse relationship to hypoalbuminaemia, especially in diabetics.

IntroductionAcute Kidney Injury (AKI) is a common, serious condition effecting up to 20% of all hospital admissions in the UK. AKI has an agreed definition for its recognition, however there is no consensus for the duration of an AKI episode. Objectives and ApproachWe aimed to describe four different potential definitions of an AKI episode. AKI was identified using an SQL (Structured Query Language) based algorithm (an implementation of the NHS England eAlert algorithm) applied to serum creatinine (SCr) results from a South Wales population of ~518,000 people, held in the Secure Anonymised Information Linkage (SAIL) Databank. Using a person’s index AKI case, we applied four different rules to define an episode of AKI. These definitions are: ALERTS - until they no longer trigger an AKI eAlert, 90 DAYS - until 90 days post first AKI test and

IntroductionAcute Kidney Injury (AKI) is a serious condition associated with increased mortality/morbidity and occurs in approximately 20% of hospital admissions. A Welsh AKI alert (e-alert) system has been in place since 2014, aiming to improve patient outcomes and care standards through early recognition of AKI using a retrospective dataset. Objectives and ApproachThe e-alert algorithm was re-produced in SQL (structured query language) and applied to serum creatinine (SCr) values for patients from pathology departments in Abertawe Bro Morgannwg health board (ABMUHB) 2011-2014, held in the Secure Anonymised Information Linkage (SAIL) databank. The algorithm utilises ratios between current SCr value (C1) to lowest SCr value within the previous 7 days (RV1), SCr median values from the previous 8-365 days (RV2), and lowest SCr within 48hrs (D). >50% increase in RV1 or RV2 or >26µmol/L above D triggers an alert. Using a renal dataset to create a timeline we created a temporal AKI cohort. Results2,407,590 SCr tests were performed on adult patients with 2,077,493 of these coming from people in the local area who were not on renal replacement during the time-period. The average ABMUHB population for 2011-2014 was 520,293 (2011: 517,981; 2012: 519,481; 2013: 520,710; 2014: 523,001). 85,272 (4.1%) of these tests triggered alerts for AKI. The incidence per 100,000 population of AKI for 2011-2014 were 1767, 1723, 1717, 1660 (average 1,717). The first AKI episodes per year for 2011-2014 respectively were stage 1 (least severe): 78.9%, 79.3%, 79.3%, 79.4% (average 79.2%); stage 2: 13.3%, 13.7%, 13.1%, 13.7% (average 13.5%); stage 3 (most severe): 7.8%, 7.0%, 7.6%, 6.9% (average 7.3%). Conclusion/ImplicationsThe AKI e-alert algorithm can be effectively reproduced using standard query language. The AKI findings in this population are comparable to others published. The use of a renal dataset using both records of renal replacement timeline and individual dialysis session may identify and rectify where alerts have not been generated.

Aims Chronic kidney disease (CKD) is common in type 2 diabetes and limits the treatment choices for glycaemic control. Our aim was to examine real-world prescribing for managing hyperglycaemia in the presence of CKD. Methods The SAIL (Secure Anonymised Information Linkage) databank was used to examine prescribing during the period from the 1st of January to 30th December 2014. CKD was defined as:- none or mild CKD, eGFR ≥60 mL/min/1.73m2; moderate CKD eGFR Results We identified 9585 subjects who received any form of glucose lowering therapy (8363 had no/mild CKD; 1137 moderate CKD; 85 severe CKD). There was a linear association between insulin use and CKD severity with approximately 54% of those with severe CKD receiving insulin. Sulphonylureas use did not differ among the CKD groups and was approximately 40%. Metformin showed a linear decrease across the groups, however approximately 21% in the severe CKD group received metformin. The use of dipeptidyl peptidase 4 inhibitors (DPP-4i) was approximately 20% and did not differ among groups. The DPP-4 inhibitor choice was:- 1% vildagliptin, 9% saxagliptin, 58% sitagliptin, and 32% linaglitpin. With respect to sitagliptin and saxagliptin, 72% and 62% received an inappropriately high dose in the setting of CKD. Conclusions We observed that a considerable proportion of patients with type 2 diabetes and CKD were receiving metformin and non dose-adjusted DPP-4 inhibitors. Careful consideration of medication use and dosaging is required in the setting of CKD and type 2 diabetes.

ObjectivesPatients with chronic kidney disease (CKD ≥3) and diabetes mellitus comprise approximately 25% patients with diabetes. These patients are at a higher risk of cardiovascular morbidity and mortality and furthermore therapies targeting glucose control are limited. The management of glycaemic control in type 2 diabetes and chronic renal disease is difficult with limited therapeutic choices. This issue has been a matter of longstanding debate. Following a number of joint Diabetes-Renal meetings between the Diabetes and Renal teams based in Hywel Dda and ABM University Health Boards, a proposal was put forward to the SAIL team to examine the relationship between diabetes therapies in relation to eGFR, as this may influence further practice and guidance for patients with type 2 diabetes and renal impairment. ApproachLinkage and re-use of routinely collected anonymised clinical data held in the SAIL databank was employed, to identify a cohort of adult patients in Abertawe Bro Morgannwg Health Board (ABMU) having type 2 diabetes (excluding type 1 diabetes). Diagnosis of diabetes was achieved by use of National Health Service ‘Read’ codes. Creatinine, eGFR, age, gender, weight, height, cholesterol, LDL, HDL, TG, systolic blood pressure, diastolic blood pressure, diabetes medication prescriptions, the use of statins, ACEis, aspirin, CHD status, CVD status, duration of diabetes were identified in primary care GP and pathology datasets. Results42170 (6.0%) of adults in ABMU were identified as having type 2 (excluding type 1) diabetes , 13369 of which had good GP registration coverage. The gender split was male 56%, female 44%. Duration of diabetes (years) was (mean/median/SD/IQR) 9.96/8.97/6.78/8.10; weight (Kg) was 86.94/85.00/21.23/28.19; age (years) 65.49/66.74/13.75/19.03; BMI 31.57/30.70/6.62/7.99. Incidence of CKD as defined by GP coded data was 24%, renal replacement therapy 0.4%, Ischaemic Heart Disease 22%. Prevalence of prescriptions during 2014 was: Anti-diabetic medication 72%, statins 75%, aspirin 34%, ACEi/ARB 61%. The import of pathology laboratory data into SAIL is currently pending, and is anticipated before April 2016. This will allow the accurate stratification of CKD status and detailed description of use of anti-diabetic agents. ConclusionThe project methods and coding structure are well place to provide anticipated results as soon as pathology data arrives. The percentage of ABMU patients having type 2 diabetes is in line with other literature for adults in the UK.

IntroductionKidney disease is common, affecting up to 1 in 10 of the adult population, and the numbers are expected to rise over the next decade. There are three main treatments that are available to patients with kidney disease: transplantation, dialysis and supportive care without dialysis. Dialysis can occur in a dialysis unit or in a person’s home, but unit-based dialysis remains the most common initial treatment for patients in Wales. This is a cause for concern as most studies suggest that it is associated with the lowest quality of life and the highest mortality, and is a more expensive treatment option.This study aims to identify the factors that lead to patients choosing unit-based haemodialysis rather than home-based dialysis with a view to informing future changes in patient education and service commissioning in Wales. A secondary aim is to determine if the co-production of research leads to more sustainable services.Methods and analysisThis mixed-method study taking place between October 2018 and September 2020 will use a sequential explanatory design whereby the descriptive quantitative cross-sectional analysis of linked health and administrative data sets inform qualitative data collection from patients, carers and health and care professionals. Qualitative findings will be used to interpret or explain quantitative descriptive results. Additional strands to the study include a review of materials and education provided to patients and an economic review of treatment modalities.Ethics and disseminationThe study will be conducted in accordance with the principles expressed in the Declaration of Helsinki. It has full approval from Health and Care Research Wales Research Ethics Committee #5. As a co-productive study involving patients, clinicians, third sector partners and academics, findings from this study will be shared on a continual basis. Study results will be published in peer-reviewed journals and presented at national and international conferences.

Background Encapsulating peritoneal sclerosis (EPS) is an uncommon condition, strongly associated with a long duration of peritoneal dialysis (PD), which is itself associated with increased fibrosis in the peritoneal membrane. The peritoneal membrane is inflamed during PD and inflammation is often associated with fibrosis. We hypothesized that patients who subsequently develop EPS might have a more inflamed peritoneal membrane during PD. Methods We performed a nested, case–control study identifying all EPS cases in the UK arm of the GLOBAL Fluid Study and matching them by centre and duration of PD with two to three controls. Dialysate and plasma samples were taken during repeated peritoneal equilibration tests prior to cessation of PD from cases and controls. Samples were assayed by electrochemiluminescence immunoassay for interleukin-1β (IL-1β), tumour necrosis factor α (TNF-α), interferon-γ (IFN-γ) and IL-6. Results were analysed by linear mixed models adjusted for age and time on PD. Results Eleven EPS cases were matched with 26 controls. Dialysate TNF-α {0.64 [95% confidence interval (CI) 0.23, 1.05]} and IL-6 [0.79 (95% CI 0.03, 1.56)] were significantly higher in EPS cases, while IL-1β [1.06 (95% CI −0.11, 2.23)] and IFN-γ [0.62 (95% CI −0.06, 1.29)] showed a similar trend. Only IL-6 was significantly higher in the plasma [0.42 (95% CI 0.07, 0.78)]. Solute transport was not significantly different between cases and controls but did increase in both groups with the duration of PD. Conclusions The peritoneal cavity has higher levels of inflammatory cytokines during PD in patients who subsequently develop EPS, but neither inflammatory cytokines nor peritoneal solute transport clearly discriminates EPS cases. Increased systemic inflammation is also evident and is probably driven by increased peritoneal inflammation.

Systemic inflammation, as evidenced by elevated inflammatory cytokines, is a feature of advanced renal failure and predicts worse survival. Dialysate IL-6 concentrations associate with variability in peritoneal small solute transport rate (PSTR), which has also been linked to patient survival. Here, we determined the link between systemic and intraperitoneal inflammation with regards to peritoneal membrane function and patient survival as part of the Global Fluid Study, a multinational, multicenter, prospective, combined incident and prevalent cohort study (n=959 patients) with up to 8 years of follow-up. Data collected included patient demographic characteristics, comorbidity, modality, dialysis prescription, and peritoneal membrane function. Dialysate and plasma cytokines were measured by electrochemiluminescence. A total of 426 survival endpoints occurred in 559 incident and 358 prevalent patients from 10 centers in Korea, Canada, and the United Kingdom. On patient entry to the study, systemic and intraperitoneal cytokine networks were dissociated, with evidence of local cytokine production within the peritoneum. After adjustment for multiple covariates, systemic inflammation was associated with age and comorbidity and independently predicted patient survival in both incident and prevalent cohorts. In contrast, intraperitoneal inflammation was the most important determinant of PSTR but did not affect survival. In prevalent patients, the relationship between local inflammation and membrane function persisted but did not account for an increased mortality associated with faster PSTR. These data suggest that systemic and local intraperitoneal inflammation reflect distinct processes and consequences in patients treated with peritoneal dialysis, so their prevention may require different therapeutic approaches; the significance of intraperitoneal inflammation requires further elucidation.

Background and Objectives Glucose control is a significant predictor of mortality in diabetic peritoneal dialysis (PD) patients. During PD, the local toxic effects of intra-peritoneal glucose are well recognized, but despite large amounts of glucose being absorbed, the systemic effects of this in non-diabetic patients are not clear. We sought to clarify whether dialysate glucose has an effect upon systemic glucose metabolism. Methods and Materials We analysed the Global Fluid Study cohort, a prospective, observational cohort study initiated in 2002. A subset of 10 centres from 3 countries with high data quality were selected (368 incident and 272 prevalent non-diabetic patients), with multilevel, multivariable analysis of the reciprocal of random glucose levels, and a stratified-by-centre Cox survival analysis. Results The median follow up was 5.6 and 6.4 years respectively in incident and prevalent patients. On multivariate analysis, serum glucose increased with age (β = -0.007, 95%CI -0.010, -0.004) and decreased with higher serum sodium (β = 0.002, 95%CI 0.0005, 0.003) in incident patients and increased with dialysate glucose (β = -0.0002, 95%CI -0.0004, -0.00006) in prevalent patients. Levels suggested undiagnosed diabetes in 5.4% of prevalent patients. Glucose levels predicted death in unadjusted analyses of both incident and prevalent groups but in an adjusted survival analysis they did not (for random glucose 6–10 compared with

Diabetes mellitus, in particular type 2, has become more common, and the trend is likely to continue.1 Associated comorbidity is also more common—for example, diabetes is now the most common cause of dialysis dependent renal failure in the Western world.2 In the United Kingdom between 1991 and 1998, the incidence of new patients on dialysis increased from 67 to more than 90 patients per million population, and the prevalence of diabetes in people receiving dialysis has increased from 16% to 19%.3 The increasing demand for dialysis and slower growth in capacity for haemodialysis has reinforced the need for an integrated approach to providing dialysis. Peritoneal dialysis is the preferred option for a proportion of patients with end stage renal failure.4 A subgroup of patients has difficulties with removing fluid. This can be improved with an alternative osmotic agent based on a polymer of glucose—icodextrin.5 We report a severe potentially clinical consequence of using icodextrin in a diabetic patient, which although mentioned in a specialist journal is still not widely recognised. This issue is even more important given the increasing number of diabetic patients with end stage renal failure. About 500 patients in …