The Impact of Admissions for the Management of End-stage renal disease on hospital bed occupancy

BACKGROUND:

End-stage renal disease (ESRD) is increasingly prevalent but the inpatient costs associated with this condition are poorly defined due to limitations with data extraction and failure to differentiate between hospitalisation for renal and non-renal disease reasons. The impact of admissions primarily for the management of ESRD on hospital bed utilisation was assessed over a 5-year period in a large teaching hospital.

METHODS:

All admission episodes were reviewed and the ESRD group was identified by a primary International Classification of Diseases code for ESRD or a non-specific primary renal failure code with a secondary code for ESRD. The frequency and duration of hospitalisation and contribution to bed day occupancy of this group with ESRD was determined.

RESULTS:

There were 70,808 patients responsible for a total of 116,915 admissions and 919,212 bed days over the study period. Of these, 988 (1.4%) patients were admitted for the management of ESRD, accounting for 2,387 (2.0%) of admissions and utilisation of 23,011 (2.5%) bed days. After adjustment for age and gender, those admitted for ESRD management were significantly more likely to have a prolonged admission exceeding 30 days (odds ratio 1.46, 95% confidence interval 1.23-1.72, p < 0.001). When the admission was an emergency rather than an elective event, the patient was 4.6 times more likely to be hospitalised for over 30 days.

CONCLUSIONS:

Persons admitted for ESRD management are hospitalised more frequently and for longer than the overall inpatient population, occupying a substantial number of bed days.

Evaluation of Five Interleukin Genes for Association with End-Stage Renal Disease in White Europeans

Background: Genetic variation within interleukin genes has been reported to be associated with end-stage renal disease (ESRD). These findings have not been consistently replicated. No study has yet reported the comprehensive investigation of IL1A, IL1B, IL1RN, IL6 and IL10 genes. Methods: 664 kidney transplant recipients (cases) and 577 kidney donors (controls) were genotyped to establish if common variants in interleukin genes are associated with ESRD. Single nucleotide polymorphism (SNP) genotype data for each gene were downloaded for a northern and western European population from the International HapMap Project. Haploview was used to visualize linkage disequilibrium and select tag SNPs. Thirty SNPs were genotyped using MassARRAY (R) iPLEX Gold technology and data were analyzed using the chi(2) test for trend. Independent replication was conducted in 1,269 individuals with similar phenotypic characteristics. Results: Investigating all common variants in IL1A, IL1B, IL1RN, IL6 and IL10 genes revealed a statistically significant association (rs452204 p(empirical) = 0.02) with one IL1RN variant and ESRD. This IL1RN SNP tags three other variants, none of which have previously been reported to be associated with renal disease. Independent replication in a separate transplant population of comparable size did not confirm the original observation. Conclusions: Common variants in these five candidate interleukin genes are not major risk factors for ESRD in white Europeans. Copyright (C) 2010 S. Karger AG, Basel

A literature review of end-stage renal disease and cachexia:Understanding experience to inform evidence-based healthcare

Introduction: Cachexia is a major cause of morbidity and mortality in people who have end-stage renal disease (ESRD). The majority of research into cachexia in ESRD has focused on the biological aspects of the syndrome and potential treatment modalities. While this research is necessary, it predominately focuses on the physical impact of cachexia in ESRD. The multi-dimensional psychosocial ramifications of this syndrome have been highlighted in other end-stage illness trajectories, but have not been systematically explored in persons who have ESRD. Aim: This paper discusses why this research is necessary, alongside further studies to help define the pathophysiology of this syndrome. Conclusion: The rich insightful data gained from understanding the patients' illness experience will positively contribute to the limited knowledge base available and inform future holistic patient-centred care delivery which recognises and responds to not only the biological but also the psychosocial impact of cachexia. © 2013 European Dialysis and Transplant Nurses Association/European Renal Care Association.

CD2AP is associated with end-stage renal disease in patients with type 1 diabetes

CD2-associated protein (CD2AP) is essential for podocyte function. CD2AP mutations have been found in patients with focal segmental glomerulosclerosis, a disease histologically resembling diabetic nephropathy and often progressing to end-stage renal disease (ESRD). We hypothesised that variations in the CD2AP gene may contribute to susceptibility to glomerular injury in diabetes and investigated if single-nucleotide polymorphisms (SNPs) in CD2AP are associated with diabetic nephropathy in patients with type 1 diabetes. The discovery cohort consisted of 2,251 Finnish patients with type 1 diabetes. SNPs were selected from the HapMap database to cover the CD2AP gene. The associations between genotyped SNPs and diabetic nephropathy or ESRD were analysed with the chi-squared test and logistic regression. Three SNPs were selected for replication in cohorts from Denmark, Italy, the United Kingdom and Ireland. None of the 15 successfully genotyped SNPs were associated with diabetic nephropathy when compared to patients with normal albumin excretion rate. However, when genotype frequencies in patients with ESRD were compared with all other patients, two CD2AP SNPs, rs9369717 and rs9349417, were found to be associated with ESRD. The meta-analysis of the original and two additional European cohorts resulted in significant p values

Novel genetic susceptibility loci for diabetic end-stage renal disease identified through robust naive Bayes classification

Aims/hypothesis: Diabetic nephropathy is a major diabetic complication, and diabetes is the leading cause of end-stage renal disease (ESRD). Family studies suggest a hereditary component for diabetic nephropathy. However, only a few genes have been associated with diabetic nephropathy or ESRD in diabetic patients. Our aim was to detect novel genetic variants associated with diabetic nephropathy and ESRD. Methods: We exploited a novel algorithm, ‘Bag of Naive Bayes’, whose marker selection strategy is complementary to that of conventional genome-wide association models based on univariate association tests. The analysis was performed on a genome-wide association study of 3,464 patients with type 1 diabetes from the Finnish Diabetic Nephropathy (FinnDiane) Study and subsequently replicated with 4,263 type 1 diabetes patients from the Steno Diabetes Centre, the All Ireland-Warren 3-Genetics of Kidneys in Diabetes UK collection (UK–Republic of Ireland) and the Genetics of Kidneys in Diabetes US Study (GoKinD US). Results: Five genetic loci (WNT4/ZBTB40-rs12137135, RGMA/MCTP2-rs17709344, MAPRE1P2-rs1670754, SEMA6D/SLC24A5-rs12917114 and SIK1-rs2838302) were associated with ESRD in the FinnDiane study. An association between ESRD and rs17709344, tagging the previously identified rs12437854 and located between the RGMA and MCTP2 genes, was replicated in independent case–control cohorts. rs12917114 near SEMA6D was associated with ESRD in the replication cohorts under the genotypic model (p < 0.05), and rs12137135 upstream of WNT4 was associated with ESRD in Steno. Conclusions/interpretation: This study supports the previously identified findings on the RGMA/MCTP2 region and suggests novel susceptibility loci for ESRD. This highlights the importance of applying complementary statistical methods to detect novel genetic variants in diabetic nephropathy and, in general, in complex diseases.

Advances in joint modelling: A review of recent developments with application to the survival of end stage renal disease patients

The use of joint modelling approaches is becoming increasingly popular when an association exists between survival and longitudinal processes. Widely recognized for their gain in efficiency, joint models also offer a reduction in bias compared with naïve methods. With the increasing popularity comes a constantly expanding literature on joint modelling approaches. The aim of this paper is to give an overview of recent literature relating to joint models, in particular those that focus on the time-to-event survival process. A discussion is provided on the range of survival submodels that have been implemented in a joint modelling framework. A particular focus is given to the recent advancements in software used to build these models. Illustrated through the use of two different real-life data examples that focus on the survival of end-stage renal disease patients, the use of the JM and joineR packages within R are demonstrated. The possible future direction for this field of research is also discussed. © 2013 International Statistical Institute.