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Background Chronic kidney disease (CKD) is a major public health problem that may lead to end-stage renal disease (ESRD). Renal transplantation has become the treatment modality of choice for the majority of patients with ESRD. It is therefore necessary to monitor the disease progression of patients who have undergone renal transplantation. In order to monitor the disease progression, the continuous assessment of kidney function over time is considered. Objectives This study aimed to investigate the etiological role of recipient characteristics in serum creatinine changes within the follow-up period and in relation to the graft failure risk, as well as to evaluate whether or not the serum creatinine level represents an indicator of graft failure following renal transplantation. Methods This retrospective cohort study was conducted at the department of nephrology, Baqiyatallah Hospital, Baqiyatallah University of Medical Sciences, between April 2005 and December 2008. The study involved 413 renal transplantation patients. The primary outcomes were the determination of the serum creatinine levels at each attendance and the time to graft failure. Robust joint modeling of the longitudinal measurements (serum creatinine level) and time-to-event data (time to graft failure) were used for the analysis in the presence of outliers in the serum creatinine levels. The data analysis was implemented in WinBUGS 1.4.3. Results There was a positive association between the serum creatinine level and graft failure (HR = 5.13, P < 0.001). A one unit increase in the serum creatinine level suggests an increased risk of graft failure of up to 5.13 times. The serum creatinine level significantly decreased over time (95% CI: (-1.58, -1.08)). The recipient’s age was negatively associated with the serum creatinine level (95% CI: (-0.02, -0.001)). Conclusions Graft failure is more likely to occur in patients with higher serum creatinine levels.

nephro-urology monthly

Longitudinal Serum Creatinine Levels in Relation to Graft Loss Following Renal Transplantation: Robust Joint Modeling of Longitudinal Measurements and Survival Time Data