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      Longitudinal Assessment of Serum Creatinine Levels on Graft Survival After Renal Transplantation: Joint Modeling Approach

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          Abstract

          Background

          Chronic kidney disease (CKD) is a major public health problem. The eventual outcome of CKD is end-stage renal disease (ESRD). Early diagnosis and proper management play an important role in preventing CKD progression to ESRD. Dialysis and kidney transplantation are the only treatment options available for patients suffering from ESRD.

          Objectives

          This study was designed to investigate the etiological role of recipient and donor characteristics on serum creatinine changes within the follow-up period, graft failure risk, and the impact of longitudinal serum creatinine levels on graft survival after renal transplantation.

          Patients and Methods

          This study was carried out at the department of nephrology, Baqiyatallah hospital, Baqiyatallah University, Tehran, Iran, between April 2005 and December 2008. During that time period, 461 patients who had undergone renal transplantation were entered in the current study. Time to graft loss and serum creatinine levels at each visit were the primary data gathered for the study. A joint modeling of survival and longitudinal nonsurvival data was used to assess the association between the two processes and investigate the influential factors.

          Results

          Median follow-up time was 6.80 months. A linear decreasing trend in serum creatinine level over time was found (P < 0.001). The results showed a positive correlation between serum creatinine levels and risk of graft failure (P < 0.001).

          Conclusions

          The major finding of this study is that one unit increase in serum creatinine level suggests an increased risk of graft failure of up to four times.

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          Most cited references30

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          PyMC: Bayesian Stochastic Modelling in Python.

          This user guide describes a Python package, PyMC, that allows users to efficiently code a probabilistic model and draw samples from its posterior distribution using Markov chain Monte Carlo techniques.
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            Strategies to improve long-term outcomes after renal transplantation.

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              Each additional hour of cold ischemia time significantly increases the risk of graft failure and mortality following renal transplantation.

              Although cold ischemia time has been widely studied in renal transplantation area, there is no consensus on its precise relationship with the transplantation outcomes. To study this, we sampled data from 3839 adult recipients of a first heart-beating deceased donor kidney transplanted between 2000 and 2011 within the French observational multicentric prospective DIVAT cohort. A Cox model was used to assess the relationship between cold ischemia time and death-censored graft survival or patient survival by using piecewise log-linear function. There was a significant proportional increase in the risk of graft failure for each additional hour of cold ischemia time (hazard ratio, 1.013). As an example, a patient who received a kidney with a cold ischemia time of 30 h presented a risk of graft failure near 40% higher than a patient with a cold ischemia time of 6 h. Moreover, we found that the risk of death also proportionally increased for each additional hour of cold ischemia time (hazard ratio, 1.018). Thus, every additional hour of cold ischemia time must be taken into account in order to increase graft and patient survival. These findings are of practical clinical interest, as cold ischemia time is among one of the main modifiable pre-transplantation risk factors that can be minimized by improved management of the peri-transplantation period.
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                Author and article information

                Journal
                Nephrourol Mon
                Nephrourol Mon
                10.5812/numonthly
                Kowsar
                Nephro-urology Monthly
                Kowsar
                2251-7006
                2251-7014
                07 June 2016
                July 2016
                : 8
                : 4
                : e37666
                Affiliations
                [1 ]Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, IR Iran
                [2 ]Nephrology and Urology Research Center, Baqiyatallah University of Medical Sciences, Tehran, IR Iran
                [3 ]Department of Statistics, Mathematical Science and Computer Faculty, Shahid Chamran University, Ahvaz, IR Iran
                Author notes
                [* ]Corresponding author: Mohammad Reza Eshraghian, Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, P. O. Box: 14155-6446, Tehran, IR Iran. Tel: +98-2188989127, E-mail: eshraghianm@ 123456tums.ac.ir
                Article
                10.5812/numonthly.37666
                5070485
                27795953
                d08b2d3b-482a-422a-b530-c85bd68d5289
                Copyright © 2016, Nephrology and Urology Research Center

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

                History
                : 28 March 2016
                : 13 April 2016
                : 28 May 2016
                Categories
                Research Article

                end stage renal disease (esrd),graft failure,joint modeling,serum creatinine

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