Does the KDIGO CKD risk stratification based on GFR and proteinuria predict kidney graft failure? Cristina Bucs ¸a •Gabriel S ¸ tefan •Dorina Tacu •… [613843]

NEPHROLOGY – ORIGINAL PAPER
Does the KDIGO CKD risk stratification based on GFR
and proteinuria predict kidney graft failure?
Cristina Bucs ¸a •Gabriel S ¸ tefan •Dorina Tacu •
Ioanel Sinescu •Ruxandra Diana Sinescu •
Mihai Ha ˆrza
Received: 18 February 2014 / Accepted: 3 June 2014
/C211Springer Science+Business Media Dordrecht 2014
Abstract
Purpose The 2012 Kidney Disease: Improving Global
Outcomes (KDIGO) guidelines on chronic kidney disease
(CKD) introduced risk classes for adverse outcome based
on estimated glomerular filtration rate (eGFR) and albu-
minuria categories (low—LR, moderately—MR, high—
HR, very high risk—VHR). We aimed to investigate if
such risk stratification is suitable in kidney transplant
(KTx) recipients.
Methods This single-center prospective study enrolled
231 prevalent KTx recipients [36 (34–48) years, 62 %
male, eGFR 53.7 (50.9–56.4) mL/min]. The patients were
stratified in risk classes in January 2011; clinical and lab-
oratory data were collected every 6 months till June 2013.
Individual slope of linear regression of all eGFR and time-
averaged proteinuria (TAP) were computed. The composite
endpoint was defined as [30 % decline in eGFR from6 months after KTx to June 2013, dialysis initiation or
death.
Results Fifty-one patients reached the endpoint. They
were younger, more often female, donor specific anti-HLA
antibodies positive, noncompliant and smokers. TAP was 4
time greater ( p\0.0001) and eGFR abruptly declined
[eGFR slope: -3.17 ( -4.13 to -2.21) vs. 0.81 (0.45–1.3)
mL/min per year, p\0.0001] in the endpoint group. At
baseline: 36 % LR, 23 % MR, 23 % HR and 18 % VHR,
without differences between the groups. In the binary
logistic regression model, VHR as compared to the other
risk classes was an independent risk factor for poorer
outcome. The final model also included female gender,
cardiovascular events, smoking, GFR slope and BK virus
infection.
Conclusions Risk group stratification according to KDI-
GO guideline on CKD may prove useful in predicting graft
outcome, but this should be confirmed in larger cohorts.
Keywords Kidney transplant /C1KDIGO guideline /C1
Estimated glomerular filtration rate /C1Proteinuria /C1Outcome
Introduction
According to the 2012 Kidney Disease: Improving Global
Outcomes (KDIGO) clinical practice guideline on the
evaluation and management of chronic kidney disease
(CKD), kidney transplant (KTx) recipients are defined as
having CKD, regardless of their estimated glomerular fil-
tration rate (eGFR) or the existence of any sign of renal
injury [ 1]. The rationale of this statement resides in pro-
tocol biopsies in renal graft recipients that demonstrated
pathologic abnormalities even in patients with apparently
preserved kidney function [ 2]. Moreover, similarly to
C. Bucs ¸a /C1D. Tacu /C1I. Sinescu /C1M. Ha ˆrza
Center of Uronephrology and Renal Transplantation,
Fundeni Clinical Institute, Bucharest, Romania
C. Bucs ¸a /C1G. S¸ tefan /C1I. Sinescu /C1M. Ha ˆrza
‘‘Carol Davila’’ University of Medicine and Pharmacy,
Bucharest, Romania
G. S¸ tefan (&)
‘‘Dr Carol Davila’’ Teaching Hospital of Nephrology,
Bucharest, Romania
e-mail: [anonimizat]
G. S¸ tefan
Romanian Renal Registry, Bucharest, Romania
R. D. Sinescu
Plastic Surgery and Reconstructive Microsurgery Department,
Elias Emergency University Hospital, Bucharest, Romania
123Int Urol Nephrol
DOI 10.1007/s11255-014-0761-7

patients with native CKD, KTx recipients have increased
comorbid conditions and comparable mortality rates [ 3,4].
Based on the findings from large collaborative meta-
analyses of general, high-risk and CKD cohorts—the CKDPrognosis Consortium (CKD-PC) provided comprehensive
evidence that eGFR and albuminuria are independent pre-
dictors of both patient and kidney outcome and identifiedrelative risk classes across eGFR and albuminuria catego-
ries for all-cause mortality, cardiovascular disease, and
kidney failure [ 5–7]. These classes of risk were endorsed
by KDIGO in the 2012 guideline on CKD [ 1]. However, if
such risk stratification is suitable in transplanted patients islargely unknown, as there are no studies addressing this
issue.
This study aims to assess the post-transplant evolution in
renal function, to identify the risk factors associated with
the decline in GFR, and to evaluate if the classes of risk
defined according to GFR and proteinuria categories areappropriate to patients with kidney grafts.
Methods
Study designThis is a prospective study on KTx patients prevalent at
January 2011 in ‘‘Fundeni Clinical Institute’’. Clinical andlaboratory data were obtained every 6 months from Janu-
ary 2011 (baseline) till June 2013 (assessment) in all
patients.
Patients were allocated to one of the four risk classes
defined by KDIGO (low, moderate, high, very high)
according to the GFR and proteinuria categories evaluatedat January 2011 (Table 1)[1].
The graft failure was defined by a composite endpoint:
the need to initiate dialysis or a more than 30 % decline ineGFR from 6 months after KTx to June 2013. We used the
30 % decline in eGFR as a surrogate endpoint for kidneyfailure as recently suggested by the US Food and Drug
Administration (FDA) [ 8]. The study protocol was
approved by the local Ethics Committee.
Parameters
The recipient examined characteristics included age, gen-
der, body mass index (BMI), smoking status and primary
renal disease summarized in five categories: diabetic
nephropathy, glomerulonephritis, polycystic kidney dis-
ease, tubulo-interstitial nephropathies, other or unknown.
The determinants of histocompatibility comprised the
presence of HLA antibodies in the recipient serum (class I,
II or both), HLA mismatch and the development of de novo
anti-donor specific HLA antibodies (DSA). The immuno-suppressive therapy and the patients’ noncompliance to
therapy defined as serious deviation from the prescribed
immunosuppressive regimen were also registered.
Rejection episode was defined as any deterioration in
allograft function during the observation period without an
obvious other cause, which was treated with corticoste-roids. Urologic complications related to transplantation and
urinary infections were also recorded.
Glomerular filtration rate (GFR) was estimated from
serum creatinine, using the four variables MDRD equation,
the individual slope of linear regression of all existing GFR
measurements was computed and used in analysis [ 9].
Proteinuria was measured in a 24 h urine collection. Time-
averaged proteinuria—defined as average of the every
6 months proteinuria measurements—was determined.
Other parameters of interest were: high blood pressure
(higher than 140/80 mmHg or antihypertensive medica-
tion), number of cardio-vascular events (myocardialinfarction, unstable angina, stroke, hospitalization for heart
failure), hypercholesterolemia (total cholesterol [240 mg/
dL), positive serology for hepatitis B, C, cytomegalicantigenemia or BK virus infection reactivation.
The donor characteristics examined included donor type
(deceased or living), age, gender and eGFR.
Statistical analyses
Continuous variables are presented as mean or median and
(95 % confidence intervals), according to their distribution,
and categorical variables as percentages. Group compari-sons were performed with Student’s ttest,v
2test and
Mann–Whitney Utest, as appropriate.
Multivariable-adjusted binomial logistic regression was
used to investigate the association between the outcome
(defined as a dichotomous variable—graft failure or not)
and the investigated risk factors.
ApB0.05 was considered statistically significant.
Analyse-it (Analyse-it Software, Ltd., Leeds, UK) andTable 1 Patients’ distribution in classes of risk defined based on
eGFR and proteinuria categories evaluated at baseline (January2011); according to KDIGO criteria
eGFR (mL/
min 1.73
2)
categoriesProteinuria categories
A1 A2 A3
\150 mg/24 h 150–500 mg/24 h [500 mg/24 h
G1 [90 Low Moderate High
G2 60–89 Low Moderate High
G3a 45–59 Moderately High Very high
G3b 30–44 High Very high Very highG4 15–29 Very high Very high Very highG5 \15 Very high Very high Very highInt Urol Nephrol
123

Table 2 Investigated parameters in study groups
All Endpoint No endpoint p*
Recipient patients (number) 231 51 180
Age at transplantation (years) 36 [34–48] 30 [26–33] 37 [35–40] 0.0005Gender (male %) 62 49 65 0.03BMI at baseline (kg/m
2) 23.6 [23.2–24] 22.8 [21.9–23.5] 23.8 [23.5–24.3] 0.005
Smokers (%) 9 18 6 0.009Primary renal disease (%) 0.1
Glomerulonephritis 56 49 58Diabetic nephropathy 7 6 7PKD 11 6 12Interstitial nephropathies 15 21 13Other/NA 11 18 10
Pre-emptive transplantation (%) 22 18 18 0.9
Time from KTx to baseline (months) 57 [54–60] 57 [52–63] 56 [54–60] 0.8Donors
Type (living %) 59 71 56 0.05Gender (male %) 48 31 53 0.006Age (years) 42 [40–46] 46 [41–49] 41.5 [40–45] 0.1eGFR (mL/min 1.73 m
2) 96 [93–98] 92 [90–96] 98 [93–100] 0.3
HLA mismatch 3 [2, 3] 2.4 [2.1–2.6] 2.5 [2.3–2.6] 0.3HLA antibodies (absent; %) 92 90 91 0.6Donor specific HLA antibodies (present; %) 6 18 2 \0.0001
KTx complications
Urologic (%) 16 14 17 0.6Rejection episode (%) 30 31 30 0.8Urinary tract infections (%) 53 61 51 0.1
Immunosuppressive therapy (%) 0.6
CSA ?MMF 22 20 22
RAPA ?MMF 5 4 6
TAC ?RAPA 6 10 5
TAC ?MMF 67 66 67
Compliance to therapy (%) 89 80 92 0.02Co-morbidities
High blood pressure (%) 68 55 72 0.02Cardiovascular events (%) 12 18 11 0.1Hypercholesterolemia (%) 46 31 50 0.01New onset DM after RT (%) 8 4 9 0.2Viral infections (% positive)
HBV 7 4 8 0.3HCV 10 6 12HBV and HCV 1 0 1CMV 30 31 29 0.7BKV 10 17 9 0.1
Proteinuria
6 Months after KTx (mg/24 h) 172.7 [98.8–246.6] 110.2 [15.9–204.5] 190.4 [99.2–281.6] 0.3Baseline (mg/24 h) 222.7 [141.8–303.6] 354.7 [123.7–585.7] 185.2 [103.9–266.6] 0.08Time averaged (mg/24 h per year) 394.7 [267.9–521.4] 874.5 [399.6–1349.3] 258.7 [171.9–345.5] \0.0001
GFR
6 Months after KTx (mL/min 1.73 m
2) 49.6 [46.4–52.7] 56 [49.6–60.2] 48.4 [44.7–50.9] 0.002Int Urol Nephrol
123

SPSS ver. 14 (SPSS Inc., Chicago, IL, USA) software were
used to analyze the data.
Results
Patient characteristicsTwo hundred thirty one prevalent KTx patients were
included (median age at transplantation 36 years; 62 %
men). Glomerulonephritis was the main primary renal
disease (56 %), followed by tubule-interstitial nephropa-thies (15 %) and polycystic kidney disease (11 %), but
diabetic nephropathy was rather rare (7 %) (Table 1). The
median time from KTx to baseline was 57 (54–60) months.
The KTx was pre-emptive in 22 % of cases and hae-
modialysis was the main renal replacement therapy (RRT)
method before transplantation (70 % of cases). The graftwas from a living donor in 59 % of cases; the median age
of the donors was 42 years and the sex ratio was nearly
1:1. Average donor eGFR was 96 (93–98) mL/min1.73 m
2.
The matching was good, as the median mismatch was 3
(95 % CI 2–4), anti-HLA antibodies were absent in 92 %of cases, and anti-donor specific HLA antibodies developed
in only 6 % of patients. After transplantation, 95 % of
patients received corticosteroids and a combined immu-nosuppressive regimen consisting in a calcineurin inhibi-
tor—mainly tacrolimus (76 %) and mycophenolate mofetil
(94 %). The patients’ compliance to therapy was rathergood (89 %) (Table 2).
However, 30 % of patients experienced rejection epi-
sodes. Urinary tract infections and urologic complicationswere noted in 53 % and in 16 %, respectively.Factors predicting graft outcome
During the 30 months observation period, no patient was
lost to follow up and no death was recorded. Of the 51
patients who reached the composite endpoint, 13 neededdialysis. In univariate analysis, as compared to those with
normally functioning grafts, the patients with graft failure
were younger, mostly female, more often anti-donor spe-cific HLA antibodies positive, and had lower treatment
compliance. Also, they were more frequently smokers, and
had in lower proportion high blood pressure and hyper-cholesterolemia (Table 2).
The patients’ distributions in eGFR and proteinuria
categories did not change during the follow up period(Fig. 1).
Notably, patients with graft failure had lower proteinuria
and higher eGFR at 6 months post transplantation. How-ever, at baseline (January 2011), eGFR and proteinuria
were similar in both groups. During the follow up, time-
averaged proteinuria was higher and eGFR decline steeper(eGFR slope -3.17 mL/min 1.73 m
2per year) in the
patients with graft failure.
At baseline, the distribution of patients in risk classes
according to KDIGO criteria was comparable in those who
reached the end-point and in those who did not: 40/35 %
low risk, 16/26 % moderate risk, 18/24 % high risk and26/15 % very high risk (Fig. 2; Table 2).
In a binomial logistic regression model that accounted
for 42 % of the probability to predict graft failure andcorrectly classified 90 % of cases, risk classes were
retained as independent determinants. The very high risk
class was associated with a significant greater probabilityof graft failure as compared to the other risk classes
(Fig. 3). The final model also included female gender,
cardiovascular events, smoking, steeper GFR slope and BKTable 2 continued
All Endpoint No endpoint p*
Baseline (mL/min 1.73 m2) 53.7 [50.9–56.4] 50.4 [41–61] 54.1 [52–57.3] 0.2
Slope (mL/min per year) 0.21 [ -0.23–0.67] -3.17 [ -4.13–2.21] 0.81 [0.45–1.3] \0.0001
Risk classes at baseline (%)/C1600.1
Low 36 40 35
Moderately increased 23 16 26High 23 18 24Very high 18 26 15
BMI body mass index, BKV BK virus, CSA cyclosporine, CKD chronic kidney disease, GFR estimated glomerular filtration rate, DMdiabetes
mellitus, HBV hepatitis B virus, HCV hepatitis C virus, HLA human leukocyte antigen, MMF mycophenolate mofetil, NAnot available, PKD
polycystic kidney disease, CMV cytomegalovirus, RAPA rapamycin, KTx kidney transplant, TAC tacrolimus
* End point versus no endpoint
/C160According to KDIGO 2012 [ 1]Int Urol Nephrol
123

Fig. 1 a ,bPatients’ distribution in chronic kidney disease eGFR and proteinuria categories at baseline, 18 months and 30 months
Fig. 2 Patients’ distribution at baseline in KDIGO risk classes according to outcome. There is no significant difference in distribution in risk
classes between the outcome groupsInt Urol Nephrol
123

virus infection as independent predictors of a poorer out-
come (Table 3).
Discussion
The present study is the first to investigate the prognostic
utility of risk classes described by 2012 KDIGO guidelineon CKD in prevalent KTx patients. In our data, risk group
stratification using eGFR and 24 h proteinuria seemed to
be in relation to the graft outcome. This might be clini-cally relevant to physicians treating KTx patients, as
patients at risk of graft dysfunction are still difficult to
identify.
Most of the patients in our cohort were in G3 CKD
category, and their distribution in G categories was similar
to other reports [ 3,10,11]. Moreover, the distribution did
not change during the follow-up period. We observed an
increasing trend in GFR 6 months after transplantation
[0.21 (95 % CI -0.23 to 0.67) mL/min per year], which is
in contradiction with the decline reported in other single
centre studies and national registries [ 10,12–14]. This
difference could be explained by the characteristic of ourcohort: younger age at KTx, good donor- recipient
matching and fair compliance to therapy. Additionally, as
most of KTxs were non-pre-emptive, the previously treatedby dialysis patients could have reduced muscle mass, a
process not reversed by KTx, resulting in a low production
of creatinine, which may cause eGFR overestimation [ 15].
Furthermore, glomerulonephritis was the main primary
renal disease in our cohort, and the immunosuppressive
therapy imposed by KTx may prevent the degradation ofkidney function by the primary renal disease. Interestingly,
Mulay et al. [ 16] showed that this is a class effect, since nospecific immunosuppressive agent was superior in reducing
the incidence of recurrence.
In our study, the patients who reached the composite
endpoint had a higher eGFR at 6 months post KTx. Simi-
larly, Gill et al. [ 13] showed that patients with a higher
eGFR at 6 months had a more rapid decline in GFR, which
suggests that the rate of CKD progression in KTx recipi-
ents differ from that observed in non-KTx patients, inwhom a faster rate was associated with a lower eGFR at
baseline [ 13,17–19].
Proteinuria is a common finding after KTx, and it is a
recognized risk factor for CKD progression in graft
recipients [ 20]. The mechanisms of proteinuria in KTx
patients are diverse and not entirely understood: residualproteinuria from native kidneys, immunosuppressive ther-
apy-related, i.e. sirolimus induced proteinuria or hemody-
namic effects of calcineurin inhibitors, glomerular injury,and absorption deficit due to tubular defects [ 21–24].
However, proteinuria and graft histology were independent
predictors of graft outcome [ 25]. The threshold for pro-
teinuria in KTx patients was set at 500 mg/24 h, but even a
level below this cut-off was associated with reduced graft
survival [ 20,26]. In our data, the patients with a poorer
graft outcome had higher proteinuria at baseline, and the
time averaged proteinuria was three times higher in this
group.
In the general population, the combination of eGFR and
albuminuria is the strongest predictor of ESRD known to
date [ 27]. Interestingly, Hernandez et al. [ 28] showed that
the combination of low grade albuminuria ( C100 mg/24 h)
and eGFR C
60 mL/min at 3 months after KTx is an
independent predictor of long-term graft loss and mortality.However, the proposed CKD risk stratification by KDIGO
has not been tested in KTx patients. Prevalent renal graft
Fig. 3 Odds ratios of graft
failure associated in KDIGOrisk classesInt Urol Nephrol
123

recipients with more than 6 months from KTx resemble the
most with the non-KTx CKD patients. Interestingly, Ha-riharn et al. [ 29] demonstrated that 1 year serum creatinine
and the change in creatinine from 6 months to 1 year
correlate best with long term graft survival. Thus, testingthe risk stratification according to KDIGO criteria in this
population could be appropriate. In our data, KDIGO risk
classes were independently associated with a composite
end-point, a surrogate of graft failure. As compared to the
very high-risk class, patients in lower risk classes hadsignificantly lesser odds of an adverse outcome. Therefore,
the risk classes defined by KDIGO criteria seem to be
useful in KTx patients too, allowing identification of ahighly vulnerable category of KTx patients, namely, those
in the high-risk class, which require close monitoring and
appropriate interventions.
Anti-donor specific HLA antibodies have been recog-
nized as an important risk factor for reduced allograft
survival [ 30–32]. Wiebe et al. [ 33] reported that DSA
developed in 15 % of low-risk KTx recipients at a mean of
4.6±3 years and graft survival is reduced by 40 % in
such patients. Furthermore, in those who develop graftdysfunction, the DSA appearance precedes the onset of
proteinuria or the rise in serum creatinine [ 33]. In our
cohort, a significantly higher percentage of patients wasDSA positive in the group with graft failure in the uni-
variate analysis.We found that smoking and cardiovascular events are
important risk determinants for graft failure. This is notsurprising since smoking acts synergistically with the other
traditional and non-traditional factors of atherosclerosis to
greatly increase the risk for cardiovascular disease. Fur-thermore, these risk factors are more often present in KTx
recipients than in the general population [ 34]. Thus, it
seems that most of the negative effects of smoking are
related to increased mortality [ 35]. However, in our pop-
ulation, during the follow-up period no death was recorded.Studies on allograft histology showed that smoking con-
tinued after KTx causes vascular fibrous intimal thickening
and nodular glomerulosclerosis [ 36,37]. Therefore, the
direct effect of smoking could be responsible for graft
dysfunction.
BK virus infection has emerged as an important cause of
graft loss in KTx recipients [ 38]. Several different mani-
festations have been described: BKV associated nephrop-
athy (BKVAN), ureteric stenosis, hemorrhagic cystitis,transient renal dysfunction [ 39]. Moreover, a specific
antiviral therapy is not available and the accepted man-
agement is immunosuppression reduction with closemonitoring for rejection [ 38]. Recently, BKVAN incidence
in KTx patients has increased, reaching rates as high as
10 % [ 40]. We observed a similar incidence of BK virus
reactivation in our data, and the presence of infection was
associated with a poorer outcome of the graft.Table 3 Predictors of graft failure (relationship between the composite endpoint and the investigated parameters in a model of multivariable
binary logistic regression)
Variable B SE Exp ( B) (95 % CI) p
Male versus female -1.69 0.53 0.18 (0.04–0.82) 0.001
Cardiovascular events 2.36 0.77 10.66 (2.32–48.94) 0.002Smoker 2.02 0.76 7.59 (1.69–33.99) 0.008Risk class at baseline (vs. very high risk) 0.016
Low-mild -2.16 0.70 0.11 (0.02–0.46) 0.002
Moderate -1.60 0.76 0.20 (0.04–0.89) 0.035
High -1.66 0.75 0.18 (0.04–0.82) 0.027
GFR slope (mL/min per year) -0.63 0.09 0.52 (0.43–0.64) \0.001
BKV 1.45 0.72 4.29 (1.03–17.79) 0.044CMV 0.92 0.55 2.51 (0.85–7.40) 0.095Age at KTx (years) -0.04 0.02 0.96 (0.92–1.00) 0.059
BMI at baseline -0.13 0.07 0.87 (0.76 -1.00) 0.064
Constant 3.63 1.74 37.86 0.037
Cox and Snell R
2=0.42 (v2=126.1; df=11;p\0.001)
Hosmer–Lemeshow goodness-of-fit: v2=3.129; df=8;p=0.926
Variables entered on step 1: gender, age at KTx, primary renal disease, BMI (body mass index) at baseline, GFR slope, time averaged
proteinuria, pre-emptive KTx, donor type, donor gender, donor age, HLA antibodies, HLA mismatch, donor specific HLA antibodies, rejection
episode, VHB/VHC serology, urologic complications, urinary tract infections, high blood pressure, cardiovascular events, hypercholesterolemi a,
immunosuppressive therapy, compliance to therapy, smokers, risk classes at baseline, BKV BK virus, CMV cytomegalovirus, time (months) from
KTx to baselineInt Urol Nephrol
123

Consistently with other studies, female recipients in our
study had an unfavourable evolution of the graft, probably
due to a greater sensitization [ 10,12,13].
Considering all these factors associated with graft out-
come, KTx recipients seem to be a unique subset of CKD
patients. The comorbidities and complications related to
CKD and dialysis prior to transplantation [ 4] are com-
pounded by a new set of complications related to immu-
nosuppression, which increase the risk for infections,
malignancy and cardiovascular disease [ 41].
Our study has some limitations. First, this was a single-
centre observational study on a not so large population ofCaucasian KTx recipients, so larger multicentre trials are
needed to confirm our results. Second, the interval between
KTx and study initiation was variable in our cohort;however, time from KTx to baseline was not retained in the
multivariable regression model. Moreover, at baseline the
investigated patients were more similar to non-transplantedCKD patients. Third, we used 24 h proteinuria and not
albuminuria for CKD KDIGO risk stratification; to over-
come this, albumin to protein excretion rate equivalencedescribed by the same guideline was employed [ 1].
The risk stratification based on eGFR and proteinuria
according to KDIGO guideline seems useful in predictingkidney graft outcome, but this should be confirmed in
larger cohorts.
Conflict of interest The authors have no conflict of interest to
declare.
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