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Identification and Characterization of Kidney Transplants With Good Glomerular Filtration Rate at 1 Year But Subsequent Progressive Loss of Renal Function

Park, Walter D.1,2; Larson, Timothy S.1,3; Griffin, Matthew D.4; Stegall, Mark D.1,2,5


In the November 15, 2012 issue of Transplantation in the article by Park et al, “Identification and Characterization of Kidney Transplants With Good Glomerular Filtration Rate at 1 Year But Subsequent Progressive Loss of Renal Function”, there is an incorrect study reference and a numeric typographical error. On page 938 in the first full paragraph, the article incorrectly refers to the 5-year analysis of the belatacept Phase II study as the belatacept Phase III BENEFIT study. The quote states “. . . a 5-year analysis of the BENEFIT study included eGFR data on 52% (66/145) of patients originally randomized to belatacept.” The cited reference is “Vincenti F, Blancho G, Durrbach A, et al. Five-year safety and efficacy of belatacept in renal transplantation. J Am Soc Nephrol 2010;21:1587.” It should be noted that this Vincenti et al paper reports findings from the long-term extension of a Phase II belatacept trial, not the Phase III BENEFIT study. Additionally, as shown in Figure 2 of the Vincenti et al. reference, there were 76 patients with cGFR data at year 5, not 66 patients as printed in the Park et al. paper. The correct calculation is 52% (76/145). In addition to this error, there were several lines missing from Table 2 . The correct version of Table 2 is shown in its entirety below.

Transplantation. 95(7):e53, April 15th, 2013.

doi: 10.1097/TP.0b013e3182692b70
Clinical and Translational Research

Background After the first year after kidney transplantation, 3% to 5% of grafts fail each year but detailed studies of how grafts progress to failure are lacking. This study aimed to analyze the functional stability of kidney transplants between 1 and 5 years after transplantation and to identify initially well-functioning grafts with progressive decline in allograft function.

Methods The study included 788 adult conventional kidney transplants performed at the Mayo Clinic Rochester between January 2000 and December 2005 with a minimum graft survival and follow-up of 2.6 years. The modification of diet in renal disease equation for estimating glomerular filtration rate (eGFRMDRD) was used to calculate the slope of renal function over time using all available serum creatinine values between 1 and 5 years after transplantation.

Results Most transplants demonstrated good function (eGFRMDRD ≥40 mL/min) at 1 year with positive eGFRMDRD slope between 1 and 5 years after transplantation. However, a subset of grafts with 1-year eGFRMDRD ≥40 mL/min exhibited strongly negative eGFRMDRD slope between 1 and 5 years suggestive of progressive loss of graft function. Forty-one percent of this subset reached graft failure during follow-up, accounting for 69% of allograft failures occurring after 2.5 years after transplantation. This pattern of progressive decline in estimated glomerular filtration rate despite good early function was associated with but not fully attributable to factors suggestive of enhanced antidonor immunity.

Conclusions Longitudinal analysis of serial estimated glomerular filtration ratemeasurements identifies initially well-functioning kidney transplants at high risk for subsequent graft loss. For this subset, further studies are needed to identify modifiable causes of functional decline.

Supplemental digital content is available in the text.

1 William J von Liebig Transplant Center, Mayo Clinic, Rochester, MN.

2 Division of Transplantation Surgery, Department of Surgery, Mayo Clinic, Rochester, MN.

3 Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN.

4 Regenerative Medicine Institute, College of Medicine, Nursing and Health Sciences, National University of Ireland, Galway, Ireland.

5 Address correspondence to: Mark Stegall, M.D., William J. von Liebig Transplant Center, Mayo Clinic, 200 First Street SW, Rochester, MN 55905.

The study was supported by National Institutes of Health/National Center for Research Resources Clinical and Translational Science Awards Grant number UL1 RR024150. M.D.G. is supported by the Science Foundation Ireland through Grant numbers 06/IN.1/B652 and SFI 09/SRC/B1794.

The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.

The authors declare no conflicts of interest.


W.P., M.G., and M.S. participated in making the research design, performing the research, analyzing the data, and writing the article. T.L. participated in making the research design and analyzing data.

Supplemental digital content (SDC) is available for this article. Direct URL citations appear in the printed text, and links to the digital files are provided in the HTML text of this article on the journal’s Web site (

Received 30 March 2012. Revision requested 20 April 2012.

Accepted 9 July 2012.

Kidney transplantation is a successful treatment of end-stage renal disease but remains associated with a graft failure rate of 3% to 5% per year after the first posttransplantation year (1). Early identification of grafts at highest risk for failure is a clear prerequisite for developing strategies to improve long-term outcomes (2–8).

Donor-specific antibody (DSA), subclinical intragraft inflammation, recurrent disease, and polyomavirus infection have been associated with shortened graft survival (2, 7). Regardless of the underlying cause, the path to graft failure is typically preceded by a period of functional decline. Several studies have reported associations between graft function and subsequent loss, but most of these have focused on correlating rates of graft failure with a single functional measurement within the first posttransplantation year (3, 5, 9–11). Although these studies show that low allograft function in the early posttransplantation period (≤1 year) is associated with increased risk of subsequent graft failure, it is unlikely that the ongoing annual loss of 3% to 5% of transplants during long-term follow-up remains closely linked with low initial graft function. For example, Magott-Proceleweska et al. (9) recently showed that although modification of diet in renal disease equation for estimating glomerular filtration rate (eGFRMDRD) less than 40 mL/min at 6 months is associated with increased risk of graft loss, 33% of those grafts demonstrated estimated glomerular filtration rate (eGFR) improvement by 2 years with 94% 5-year graft survival.

We hypothesized that low renal function at 1-year after transplantation would identify recipients at high risk for early graft failure but that risk prediction for graft failures occurring during longer term follow-up would require a more longitudinal analysis of function. We pursued a two-stage approach to analyzing the association between eGFR and graft failure in a large cohort of kidney transplant recipients followed for 5 years or more. A single eGFRMDRD value at 1-year after transplantation was used to determine a level of early graft function, below which subsequent survival was significantly reduced. For recipients with eGFRMDRD above this cutoff value, we used all available eGFRMDRD measurements between 1 and 5 years after transplantation to determine the graft functional stability (slope of eGFR). The results indicate the following: (a) low 1-year eGFR is primarily predictive of graft failure occurring within a short time frame after transplantation; (b) a substantial subset of allografts with high 1-year eGFR undergo progressive decline in eGFR after the first posttransplantation year, and this accounts for most graft failures occurring during extended follow-up; and (c) analysis of eGFR trends by modification of diet in renal disease (and other formula-based approaches) using large numbers of serum creatinine measurements per patient provides important prognostic information despite known discrepancies between estimated and true GFR measurements in kidney transplant recipients (7, 12).

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Correlating Kidney Transplant Survival With 1-Year eGFRMDRD

All adult conventional renal transplantations between 2000 and 2005 that remained functional for 1 year or more were identified. From a total of 953 transplants, 896 (94%) had eGFRMDRD recorded 1-year after transplantation (Fig. 1). Subsequent graft survival rates were determined for different ranges of 1-year eGFRMDRD (<20, 20–29, 30–39, 40–49, and 50–59 mL/min) and were compared with the survival rate for transplants with eGFRMDRD 60 mL/min or greater (data not shown). This analysis indicated that all 1-year eGFRMDRD ranges below 40 mL/min showed significantly lower subsequent graft survival, whereas those with eGFRMDRD between 40 and 59 mL/min showed similar graft survival rates to the 60 mL/min or greater group (Fig. 2A). For subsequent analyses, therefore, transplants with 1-year eGFRMDRD 40 mL/min or greater and less than 40 mL/min were designated as “high GFR” and “low GFR,” respectively (Fig. 2B).





In total, 129 (14.4%) of 896 transplants failed during follow-up of 62.3 (26.9) months after 1-year eGFRMDRD measurement. Between 1 and 2.5-years after transplantation, most graft failures (38/48; 79%) occurred within the low GFR group. In contrast, graft failures later than 2.5 years after transplantation occurred predominantly within the high GFR group (53/81; 65%). Thus, 49% of all graft failures during this follow-up period would have been incorrectly categorized as having a good prognosis based on eGFRMDRD at 1-year after transplantation (Fig. 2C).

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Combining the 1-Year eGFRMDRD and Slope of Renal Function Between 1 and 5 Years to Identify Grafts at High Risk for Graft Loss

In the next stage of the study, longitudinal trends in renal function during the first 2.5 years were analyzed with a view to identification of well-functioning transplants at increased risk for later graft failure. For this analysis, allografts that failed or were lost to follow-up before 2.5 years after transplantation (81/896, 8%) or that showed insufficient eGFR measurements (27/896, 3%) were omitted, leaving 788 transplants eligible for analysis—113 categorized as low GFR and 675 as high GFR (Fig. 1). Characteristics of the total group are summarized in Table 1A; and those of the Low GFR and High GFR subsets, in Table 1B. Of note, although 1-year eGFRMDRD was lower among the 70 allografts from this cohort that failed during follow-up compared with all other outcomes, there was considerable overlap of individual 1-year eGFRMDRD values for all outcomes (see Figure S1A, SDC,



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Plotting Trends in Kidney Transplant Function From 1 to 5 Years After Transplantation

Trends in renal function for the high GFR group were next analyzed between 1 and 5 years after transplantation by plotting mean eGFRMDRD for sequential 6-month intervals. For the entire group, a broad distribution of renal function values was observed across all time intervals with the mean eGFRMDRD remaining constant throughout (see Figure S1B, SDC, The slope of eGFRMDRD was then calculated for each individual high GFR transplant (see Materials and Methods). The mean eGFRMDRD slope for all 675 high GFR transplants was −1.7% (9.0%), corresponding to a change in eGFRMDRD of −0 (5.3) mL/min per yr (range, +18 to −41). However, when the group was subdivided into quintiles based on the distribution of eGFRMDRD slopes (Table 1C), only two of five quintiles demonstrated declining eGFRMDRD (slopes of −15% [10%] and −4 [1.3%]), whereas three demonstrated either increasing or stable eGFRMDRD over time (slopes of 0.0% [0.7%], +2.5% [0.8%], and +7.4% [4.1%]) (see Figure S2, SDC, The quintile with the largest decrease in eGFRMDRD demonstrated a mean change of −8.7 [6.2] mL/min per yr. Strikingly, 27 of the 28 allograft failures that occurred less than 5 years after transplantation in the high GFR group and 42 of the 48 failures during the entire follow-up period were contained within in this quintile. In contrast, the quintile with the second greatest declining slope experienced only three graft losses, each occurring more than 5 years after transplantation. Among the remaining quintiles, only 1 graft loss occurred, which was also less than 5 years after transplantation.

There were no notable differences in follow-up time, donor source, or age across quintiles (Table 1C). In addition, although the frequency of abnormal proteinuria (>150 mg/24 hr) at 1 year after transplantation was higher among low GFR compared with high GFR groups (58% vs. 38%), there was no difference in the frequency of abnormal proteinuria at 1 year among the quintiles (Table 1B, C). The availability of 1-year surveillance biopsies for most transplants within the total high GFR cohort also allowed for comparison of histologic abnormalities among quintiles. The quintile with the greatest decline in eGFRMDRD did have higher proportions of biopsies with some grade of transplant glomerulopathy or interstitial fibrosis with inflammation. However, no quintile showed less than 80% of 1-year biopsies with normal histologic condition or interstitial fibrosis alone. Therefore, it was concluded that the progressive decline in renal function among allografts with apparently good function at 1-year could not be largely accounted for by obvious baseline characteristics, increased rate of development of abnormal proteinuria, or histologic abnormalities during the first posttransplantation year.

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Further Defining and Examining the Clinical Characteristics of High GFR Transplants With Progressive Loss of Function

To further characterize high GFR transplants that subsequently “progressed” to poor function, 13 allografts were excluded from the quintile with the greatest eGFR decline. These demonstrated eGFRMDRD 60 mL/min or greater throughout follow-up (n=3) or demonstrated less than 20% absolute reduction in eGFRMDRD over time (n=10). The remaining 122 grafts were termed “high GFR progressors” (High-P) and were compared with all other high eGFR grafts (high eGFR nonprogressors [High-NP], n=553) (Table 2A). Predictably, the High-P group showed more graft failures (n=41, 34%) than the High-NP group (1%, P<0.0001). In addition, the rate of graft failure among the High-P group was higher than that of the low GFR group during this time frame (19%, P<0.0021) (Fig. 3A). Similar to the initial quintiles analysis, the mean 1-year eGFRMDRD of the High-P and High-NP groups did not differ (Fig. 3B).





To determine whether the High-P and High-NP subgroups differed for relevant clinical, histologic, and laboratory characteristics either at baseline or during subsequent follow-up, univariate and multivariate analyses were conducted. As shown in Table 2A, univariate analysis indicated associations between High-P status and younger recipient age, higher number of transplants, white recipient race, female recipient gender, nonuse of Thymoglobulin induction, transplant glomerulopathy on 1-year surveillance biopsy, and abnormal proteinuria within 1 year of the most recent eGFR measurement. There were also trends toward associations of High-P status with pretransplantation anti–class II DSA and with anti–class II DSA within 1 year of the most recent eGFR measurement, which did not reach significance (although posttransplantation data were available for only a limited number of study subjects). In multivariate analysis (Table 2B), the associations with higher transplant number, female recipient gender, nonuse of Thymoglobulin induction, and abnormal proteinuria within 1 year of the most recent eGFR measurement remained significantly associated with High-P status.

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Alternative Approaches to Assessing Renal Function Trends

Comparisons were performed between the eGFRMDRD 6-m interval approach and alternative methods for estimating or measuring GFR (see Table S1, SDC,

The slope cutoff for progressor status was independently determined for each method. The proportion of failed grafts considered to be progressors was similar for each method (83%–88%; see Table S1A, SDC, However, the formula-based eGFR methods identified higher proportions of progressor grafts that failed during follow-up compared with iothalamate clearance (34%–40% vs. 17%). Overall, the similarity between eGFRMDRD 6-m interval and other methods was 88% to 96% (see Table S1B, SDC,

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Our results agree with existing literature indicating that renal allografts with low eGFRMDRD 1 year or less after transplantation have inferior subsequent graft survival (3, 9, 11) in the first few years after transplantation. However, in the current study, most allograft failures between 2.5 and 7 years after transplantation showed a 1-year eGFRMDRD 40 mL/min or greater (65%; 53/81). Thus, a low 1-year eGFR seems to contribute most of its predictive value during the first few posttransplantation years. Therefore, categorizing transplant recipients into low- and high-risk groups on the basis of a single early GFR estimate would fail to identify a substantial number of recipients who are destined for future graft failure beyond 2.5 years. We believe that this concept is an important and underappreciated finding and questions the validity of using a single measure of early renal function as a primary endpoint for clinical trials in kidney transplantation (13–15). We contend that the current study’s use of sequential eGFR values between 1 and 5 years to create an eGFR slope provides a fuller picture of the fate of renal allografts after transplantation and might provide a useful endpoint for clinical trials designed to improve long-term graft survival.

This study also extends our prior research in chronic injury, which showed that not all renal allografts are affected by chronic injury in the first 5 years after transplantation (8). Indeed, most renal allografts with 1-year eGFRMDRD of 40 mL/min or greater have stable or improving function between 1 and 5 years. Even after excluding all patients with low 1-year eGFR and grafts with limited survival or follow-up during the first 2.5 years after transplantation, 43% of the entire starting population (405/953) would have showed renal functional profiles comparable with healthy people up to 7 years after transplantation. These results are similar to findings reported from the U. S. Renal Data System and single centers using data from exclusively deceased-donor recipients (16, 17). Most notably, in a study by Gill et al. (16), in which the rate of functional decline was assessed for grafts surviving at least 2 years, the overall decline in renal function was slow (−1.66 mL/min/1.73 m2 per yr), and 50% of recipients showed no change or an improvement in eGFRMDRD.

We believe that these findings have important therapeutic implications. First, most well-functioning grafts at 1 year that have stable or improved function suggest that sweeping changes in immunosuppression are not needed to prevent chronic injury in most allografts in the first 5 years after transplantation. In contrast, if we are to improve overall long-term graft survival, we cannot focus solely on improving 1-year GFR but also must identify the causes of renal functional decline in grafts that have good function at 1 year.

For the 122 allografts identified as having progressive renal dysfunction, we investigated the possible causes using both univariate and multivariate analyses. Only a small proportion of progressors exhibited specific characteristics previously associated with increased risk of graft failure such as overt complications (BK nephropathy, recurrent disease, and calcineurin inhibitor), abnormal histologic condition (glomerulopathy and fibrosis+inflammation), and deceased-donor source (2, 4, 7). The relatively low frequency of these well-defined risks among the High-P group suggests that different factors may contribute to the progressive loss of function in these grafts compared with low GFR grafts. The significant associations with progressor status observed included female gender, retransplantation, and lack of Thymoglobulin induction, perhaps implicating a role for antidonor sensitization. Interestingly, despite a trend toward higher frequency of pretransplantation anti–class II DSA among the High-P compared with High-NP group (16% vs. 8%), this did not reach significance indicating that pretransplantation sensitization was not highly enriched among the progressors. Although the amount of data available to interrogate the role of time-dependent posttransplantation variables in this cohort was relatively limited, it is of interest that the most recent 24-hr urine protein measurements indicated that the frequency of abnormal proteinuria became higher over time in the High GFR progressors having been no different to nonprogressors at 1 year after transplantation. Clearly, more comprehensive, prospective analysis will be necessary to determine whether the emergence of de novo proteinuria, DSA, or other abnormalities occurs before, after, or concurrent with declining functional measurements.

A limited number of prior studies have used multiple measures of renal function collected within the first 2 years after transplantation and have determined that the change in function between two measurements can be used to improve the association with eGFR and long-term survival (5, 9, 10). Given the known variability in eGFR values (18), it is likely that the inclusion of additional data points, as we have performed here, adds further accuracy to the estimation of the rate of functional change. For all subjects in the study, we used five or more data points (range, 5–9), each representing the mean of all eGFRMDRD measurements available within the 6-month intervals between 1 and 5 years. On average, 40 (range, 6–242) unique eGFRMDRD measurements were available for the study-eligible grafts. Given the ubiquitous use of frequent serum creatinine and formula-based eGFR measurements in the follow-up of kidney transplant recipients, we believe that this approach can be readily applied both retrospectively and prospectively to routine clinical practice and to clinical trials.

A concern for any long-term prospective study of kidney transplant recipients is the collection of functional measurements in most patients. For example, 3 year follow-up of the Symphony study included eGFR data on only 45% of the original study population (710/1589) (19), and a 5-year analysis of the BENEFIT study included eGFR data on 52% (66/145) of patients originally randomized to belatacept (20). The large proportions of missing subjects from these studies make it difficult to confidently interpret the results. In contrast, our approach resulted in the inclusion of 76% of all adult conventional recipients who underwent transplantation from 2000 to 2005 (788/1039 if 86 grafts lost <1 year are included). To reach such a high inclusion rate in our cohort, we used eGFRMDRD, which is known to underestimate the rate of change in renal function when compared with iothalamate clearance (12). Consistent with this, only 59% of the progressors identified by uncorrected iothalamate were also identified by eGFRMDRD (as opposed to 95% of nonprogressors; see Table S1B, SDC, However, the rate of graft failure among the iothalamate-defined progressors was lower than those identified by eGFRMDRD (17% vs. 34%, see Table S1A, SDC,, suggesting that a formula-based approach using a large number of sequential creatinine measurements has distinct value for identifying transplants at high risk for failure.

We conclude that a single GFR measurement at 1 year (or any time point), although associated with graft failure risk in the short term, is insufficient to provide long-term risk stratification of renal transplant recipients. Instead, a combination of early and repeated estimates of GFR can be used to identify grafts at high risk for failure out to 7 or more years after transplantation. This approach also more accurately identifies the 40% to 60% of all kidney transplant recipients who achieve good early function and maintain it for a prolonged period. The progressive decline in eGFR observed among a subset of grafts with good early function was associated with higher frequency of characteristics that are linked to immune-mediated injury. However, the poor outcome for this subset cannot be fully explained by these associations, and investigation of other candidate factors such as patient compliance, late development of antidonor antibody, and genetic variability is merited (21–23). Finally, we contend that to improve long-term renal allograft survival, attention must be focused on refining methods to accurately identify progressive loss of graft function as early as possible, with the goal of elucidating and treating the causes.

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Study Subjects

The study protocol was approved by the Mayo Clinic institutional review board. All adult recipients of kidney transplants performed at Mayo Clinic, Rochester, MN, between January 2000 and December 2005 were identified. The following groups were excluded from further study: (1) pediatric (<18 years), (2) positive pretransplantation antidonor T- and B-cell flow cytometric crossmatch, (3) ABO blood group incompatibility, (4) combined solid organ transplants, and (4) nonconsent to research.

Seventy-eight percent of study subjects received calcineurin inhibitor–based immunosuppression, 3% received mammalian target of rapamycin inhibitor, and 19% received a combination of both classes. Eighty-one percent received induction with Thymoglobulin.

One-year surveillance biopsies were obtained from 75% of study subjects. Biopsies were performed as previously described and were interpreted by a consultant renal pathologist using the Banff ’97 classification (24). Proteinuria was assessed by 24-hr urine total protein measurements at 1 year after transplantation and annually thereafter, with abnormal proteinuria defined as greater than 150 mg/24 hr (25). Pretransplantation DSA screening was performed on stored serum samples by single antigen bead assay as previously described (6). Graft failure was defined as return to dialysis or eGFRMDRD consistently less than 20 mL/min for 6 months or more.

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Assessment of Renal Function

Uncorrected iothalamate clearance and serum creatinine measurements were extracted from the Mayo Clinic Transplant database for all study subjects. Serum creatinine values were converted to eGFR using eGFRMDRD and other formula-based calculations (see Table S1, SDC, A total of 2783 iothalamate clearances and 34,376 serum creatinine measurements between 1 and 5 years after transplantation were obtained for 953 subjects. Forty-five percent of the creatinine measurements were performed by Mayo Clinic laboratories; and 55%, by external laboratories. For the Mayo laboratory data, both the pre–isotope dilution mass spectrophotometry (IDMS) (26) and IDMS (27) equations were used, whereas for external laboratory values, only the pre-IDMS (26) formula was used.

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Calculation of Slope of Renal Function

Change in estimated renal function over time was determined by linear regression of all eGFRMDRD values between 1 and 5 years. To reduce variation across time, individual eGFRMDRD values were combined into means within 6-month posttransplantation intervals (i.e., 1–1.5, 1.5–2 yr). Data for a minimum of five 6-month intervals were required equating to a minimum renal transplant follow-up of 2.6 years. The log10 of the 6-month averaged eGFRMDRD values was plotted over time for each study subject; and the slope of each plot, calculated. After this, the subjects were divided into quintiles based on the values for eGFRMDRD slope.

Subsequently, categorization as progressor status was based on the following criteria: (1) located in the quintile with the most negative eGFRMDRD slope, (2) absolute eGFRMDRD decline of 20% or greater between 1 year and most recent less than 5-year eGFRMDRD, and (3) average eGFRMDRD less than 60 mL/min for at least one 6-month interval.

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Statistical Analyses

Results are expressed throughout as means (SD). The proportions of nominal data were tested using chi-square (Pearson) test. Continuous variables were tested using the Student t test for parametric data and Wilcoxon test for nonparametric data. Univariate and multivariate logistic regression analyses were used to analyze clinical variables associated with unstable graft function between 1 and 5 years, and a receiver operating characteristic curve analysis was performed to determine if any combination of factors could predict outcomes. A P value of <0.05 was considered statistically significant. The JMP statistical software system (SAS, Cary, NC) was used to perform calculations.

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Kidney transplantation; Glomerular filtration rate; Graft survival; Chronic allograft nephropathy; Proteinuria

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