Dataset Information

Risk Factors for Graft Failure and Death following Geriatric Renal Transplantation.

ABSTRACT:

Background

Population aging is a major health concern in Asian countries and it has affected the age distribution of patients with end-stage renal disease (ESRD). As a consequence, the need for kidney transplantation in the geriatric population has increased, but the shortage of donors is an obstacle for geriatric renal transplantation. The aim of this study was to evaluate risk factors for graft failure and death in geriatric renal transplantation.

Methods

Kidney transplantations performed in a tertiary hospital in South Korea from May 1995 to December 2014 were retrospectively reviewed. Recipients younger than 60 years of age or who underwent other organ transplantations were excluded. The Kaplan-Meier method was used to assess patient and graft survival. A Cox regression analysis was used to evaluate risk factors for graft failure and patient death.

Results

A total of 229 kidney transplantation patients were included. Graft survival at 1, 5, and 10 years were 93.2%, 82.9%, and 61.2% respectively. Patient survival at 1, 5, and 10 years were 94.6%, 86.9%, and 68.8%, respectively. According to the Cox multivariate analysis, ABO incompatibility (hazard ratio [HR] 3.91, p < 0.002), DGF (HR 3.544, p < 0.004), CMV infection (HR 2.244, p < 0.011), and HBV infection (HR 6.349, p < 0.015) were independent risk factors for graft survival. Recipient age (HR 1.128, p < 0.024), ABO incompatibility (HR 3.014, p < 0.025), CMV infection (HR 2.532, p < 0.010), and the number of HLA mismatches (HR 1.425, p < 0.007) were independent risk factors for patient death.

Conclusion

Kidney transplantation in the geriatric population showed good clinical outcomes. ABO incompatibility, DGF, CMV infection, and HBV infection were risk factors for graft failure and the recipient age, ABO incompatibility, CMV infection, and the number of HLA mismatches were risk factors for patient death in geriatric renal transplantation.

SUBMITTER: Cho H

PROVIDER: S-EPMC4830585 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Risk Factors for Graft Failure and Death following Geriatric Renal Transplantation.

Cho Hyungjin H Yu Hoon H Shin Eunhye E Kim Young Hoon YH Park Su-Kil SK Jo Min-Woo MW

PloS one 20160413 4

<h4>Background</h4>Population aging is a major health concern in Asian countries and it has affected the age distribution of patients with end-stage renal disease (ESRD). As a consequence, the need for kidney transplantation in the geriatric population has increased, but the shortage of donors is an obstacle for geriatric renal transplantation. The aim of this study was to evaluate risk factors for graft failure and death in geriatric renal transplantation.<h4>Methods</h4>Kidney transplantations ...[more]

PMID: 27074003

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Project description:Background and objectivesHypophosphatemia is common in the first year after kidney transplantation, but its clinical implications are unclear. We investigated the relationship between the severity of post-transplant hypophosphatemia and mortality or death-censored graft failure in a large cohort of renal transplant recipients with long-term follow-up.Design, setting, participants, & measurementsWe performed a longitudinal cohort study in 957 renal transplant recipients who were transplanted between 1993 and 2008 at a single center. We used a large real-life dataset containing 28,178 phosphate measurements (median of 27; first to third quartiles, 23-34) serial measurements per patient) and selected the lowest intraindividual phosphate level during the first year after transplantation. The primary outcomes were all-cause mortality, cardiovascular mortality, and death-censored graft failure.ResultsThe median (interquartile range) intraindividual lowest phosphate level was 1.58 (1.30-1.95) mg/dl, and it was reached at 33 (21-51) days post-transplant. eGFR was the main correlate of the lowest serum phosphate level (model R2 =0.32). During 9 (5-12) years of follow-up, 181 (19%) patients developed graft failure, and 295 (35%) patients died, of which 94 (32%) deaths were due to cardiovascular disease. In multivariable Cox regression analysis, more severe hypophosphatemia was associated with a lower risk of death-censored graft failure (fully adjusted hazard ratio, 0.61; 95% confidence interval, 0.43 to 0.88 per 1 mg/dl lower serum phosphate) and cardiovascular mortality (fully adjusted hazard ratio, 0.37; 95% confidence interval, 0.22 to 0.62) but not noncardiovascular mortality (fully adjusted hazard ratio, 1.33; 95% confidence interval, 0.9 to 1.96) or all-cause mortality (fully adjusted hazard ratio, 1.15; 95% confidence interval, 0.81 to 1.61).ConclusionsPost-transplant hypophosphatemia develops early after transplantation. These data connect post-transplant hypophosphatemia with favorable long-term graft and patient outcomes.

Project description:Background: A mechanism to predict graft failure before the actual kidney transplantation occurs is crucial to clinical management of chronic kidney disease patients. Several kidney graft outcome prediction models, developed using machine learning methods, are available in the literature. However, most of those models used small datasets and none of the machine learning-based prediction models available in the medical literature modelled time-to-event (survival) information, but instead used the binary outcome of failure or not. The objective of this study is to develop two separate machine learning-based predictive models to predict graft failure following live and deceased donor kidney transplant, using time-to-event data in a large national dataset from Australia. Methods: The dataset provided by the Australia and New Zealand Dialysis and Transplant Registry will be used for the analysis. This retrospective dataset contains the cohort of patients who underwent a kidney transplant in Australia from January 1 st, 2007, to December 31 st, 2017. This included 3,758 live donor transplants and 7,365 deceased donor transplants. Three machine learning methods (survival tree, random survival forest and survival support vector machine) and one traditional regression method, Cox proportional regression, will be used to develop the two predictive models (for live donor and deceased donor transplants). The best predictive model will be selected based on the model's performance. Discussion: This protocol describes the development of two separate machine learning-based predictive models to predict graft failure following live and deceased donor kidney transplant, using a large national dataset from Australia. Furthermore, these two models will be the most comprehensive kidney graft failure predictive models that have used survival data to model using machine learning techniques. Thus, these models are expected to provide valuable insight into the complex interactions between graft failure and donor and recipient characteristics.

Dataset Information

Risk Factors for Graft Failure and Death following Geriatric Renal Transplantation.

Background

Methods

Results

Conclusion

Publications

Risk Factors for Graft Failure and Death following Geriatric Renal Transplantation.

Similar Datasets

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