Content uploaded by Qiang Wei
Author content
All content in this area was uploaded by Qiang Wei on Apr 21, 2020
Content may be subject to copyright.
Hepatobiliary Pancreat Dis Int,Vol 9,No 3 • June 15,2010 • www.hbpdint.com • 259
Author Affiliations: Department of Hepatobiliary and Pancreatic Surgery,
First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou
310003, China (Xu X, Ling Q, Wei Q, Wu J, Gao F, He ZL, Zhou L and
Zheng SS)
Corresponding Author: Shu-Sen Zheng, MD, PhD, FACS, Department
of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang
University School of Medicine, Hangzhou 310003, China (Tel: 86-571-
87236567; Fax: 86-571-87236567; Email: zyzss@zju.edu.cn)
© 2010, Hepatobiliary Pancreat Dis Int. All rights reserved.
BACKGROUND: Acute kidney injury (AKI) is a common
complication in the early period after liver transplantation
(LT), posing an enormous obstacle to treatment efficiency
and patient survival. However, the exact influencing factors
of AKI are still unclear and a predictive model is desperately
required in the clinic.
METHODS: Data of 102 consecutive LTs were reviewed. A
model for predicting AKI was established and further
validated in a prospective study of 44 patients receiving LT.
RESULTS: The incidence of AKI was 32.4%. AKI patients
showed a significantly lower survival rate than non-AKI
patients. Multivariate analysis demonstrated the independent
influencing factors of AKI were preoperative serum
creatinine >1.2 mg/dl, intraoperative urine output ≤60 ml/h,
intraoperative hypotension status, and intraoperative use of
noradrenaline. A model was then established and showed a
sensitivity of 75.0%, a specificity of 93.8% , and an accuracy of
88.6% in predicting AKI.
CONCLUSIONS: High preoperative serum creatinine, low
intraoperative urine output, and intraoperative hypotension
contribute to the development of AKI, and intraoperative use
of noradrenaline serves as a protective factor. The predictive
model could potentially facilitate early prediction and
surveillance of AKI.
(Hepatobiliary Pancreat Dis Int 2010; 9: 259-263)
KEY WORDS: acute kidney injury;
liver transplantation;
risk factors;
complications;
prognosis
Introduction
Acute kidney injury (AKI) is the loss of renal
function over a period of hours to days and
reflects the entire spectrum of acute renal
failure.[1] It is one of the most common complications
after liver transplantation (LT), especially in the early
postoperative period, and is associated with a high
mortality.[2-8] It is defined as serum creatinine >1.5 mg/dl
with an increase of 50% above the baseline level or/and
the presence of need for renal replacement therapy in
the first week post-LT.[2, 9] The development of AKI has
been associated with markedly increased costs and
consumption of health care resources in the general
hospital population and the LT population.[ 5, 10]
Unfortunately, it seems that the incidence of AKI,
which varies from 17% to 95%[2 -7] has not shown a
significant decline with the remarkable improvement
of surgical technique, the invention of drugs with low
nephrotoxicity and the development of perioperative
management during the past decade, and AKI remains
an unsolved problem.
The difficulties in early intervention contribute
significantly to the poor prognosis of AKI. Serum
creatini ne, which is the most importa nt index of renal
function, is strongly correlated with AKI.[2-5] However, it
is apparent that preoperative renal f unction alone may
be insufficient to elucidate the underlying mechanisms
of AKI and to predic t AKI effect ively. There also have
been many studies concerning the multifactorial etiology
of AKI and a variety of preoperative, intraoperative and
postoperative variables are suggested.[5, 6]
One of the main indications for LT in Asia is HBV-
related liver cirrhosis. Acc ording to an ea rly report on
a relatively small cohort, recipients with HBV-related
liver cirrhosis might be more susceptible to AKI than
others.[7] However, much less is known about the
incidence and the ex act factors influencing AK I in the
mainland of China, where the majority of recipients
receive LT for HBV-related end-stage liver diseases.
The present study consisted of a retrospective
An effective model for predicting acute kidney
injury after liver transplantation
Xiao Xu, Qi Ling, Qiang Wei, Jian Wu, Feng Gao, Zeng-Lei He, Lin Zhou and Shu-Sen Zheng
Hangzhou, China
Original Article /
Transplantation
Hepatobiliary & Pancreatic Diseases International
260 • Hepatobiliary Pancreat Dis Int,Vol 9,No 3 • June 15,2010 • www.hbpdint.com
review and a prospective identification in two cohorts
of patients with end-stage liver disease who received
LT in our center. The aim of the study was to evaluate
the current status of AKI in the first week post-LT and
its impact on patient survival, to identify the factors
critical to the presence of AKI, and to establish a valid
predictive model. The ultimate goal of the present study
was to identify patients at great risk for developing AKI
so that effective rescue or protective strategies can be
promptly undertaken.
Methods
Retrospective cohort
The records of all patients (88 males and 14 females)
with benign end-stage liver disease who had undergone
cadaveric related LT at the First Affiliated Hospital,
Zhejiang University School of Medicine, f rom January
2004 until September 2005 were retrospectively
analyzed. Their main indication for LT was HBV-
related cirrhosis. All of the patients received a triple
immunosuppression regimen consisting of a calcineurin
inhibitor, prednisolone and mycophenolate mofetil.
Patient characteristics are shown in Table 1. Informed
consent was given by all donors and recipients before
transplantation. Each organ donation or transplant
complied with t he g uidelines of the Eth ics Committee
of the hospital, the Organ Transplant Committee of
Zhejiang Province, and the Declaration of Helsinki.
All patients underwent orthotopic LT without veno-
venous bypass. To maintain an intraoperative mean
arterial pressure above 60 mmHg, some vasoactive drugs
were used. In some patients, continuous infusion of
noradrenalin was initiated at 1 μg/min and subsequently
raised to a maximum of 50 μg/min according to the
clinical response during the anhepatic phase or extended
to the neohepatic phase. In general, adrenalin was used
when noradrenalin or high-dose dopamine failed to
work. Intraoperative hypotension status was defined as a
systolic blood pressure <90 mmHg for >15 minutes.
AKI was determined by a serum creatinine >1.5 mg/dl
with an increase of 50% above the baseline level or/and
the presence of need for renal replacement therapy in
the first week post-LT.[11] According to the definition of
AKI, the patients were divided into an AKI group and a
non-AKI group. All patients were routinely followed up
closely at the outpatient clinic.
Validation cohort
To further evaluate the clinical predictive ability of
the model established in a previous retrospective study,
we prospectively investigated another cohort of 44
adult patients with benign end-stage liver di sease who
had undergone LT from November 2005 to July 2006
at our center. Different from the retrospective cohort,
the validation cohort were treated with the piggyback
technique and tacrolimus. Other perioperative strategies
were the same as i n the retrospective study. The main
parameters of the two cohorts are compared in Table 1.
Statistical analysis
The data were analyzed statistically using SPSS,
version 11.0 (SPSS Inc, Chicago, IL). Descriptive variables
were expressed as mean±SD or median and range. The
Kaplan-Meier method and the log-rank test were used
to assess the impact of AKI on the survival. Appropriate
cutoff levels for all potential influencing factors were
selected for their clinical significance. All the variables
were detected by univariate analysis and a P value of
less than 0.05 was considered statistically significant.
Variables with statistical significance were taken for a
forward stepwise multivariate logistic regression analysis.
The area under the receiver operating characteristic (ROC)
curve was generated to assess the model’s discrimination,
and the method of Hosmer and Lemeshow was used to
assess its goodness of fit.
Results
Prevalence of AKI and patient survival
The mean postoperative follow-up for the retrospective
cohort was 304±214 days (range 7-686 days). During
Characteristics Cohort 1*
(n=102)
Cohort 2#
(n=44) P
Age (yr) 45±9 48±10 NS
Gender (male/female) 88/14 41/3 NS
Surgical technique (piggyback/classic) 59/43 44/0 <0.001
MELD score pre-LT 25±9 25±11 NS
Indication
HBV-related liver cirrhosis 93 41 NS
HCV-related liver cirrhosis 2 0 NS
Alcohol-related liver cirrhosis 4 1 NS
Other 3 2 NS
Immunosuppressive regimen
Anti-IL2 receptor antibody induction 70 35 NS
Tacrolimus/Cyclosporine 61/41 44/0 <0.001
Table 1. Patient characteristics
*: Cohort 1, population of retrospective study; #: Cohort 2, population
of prospective validation. NS: not significant; MELD: model for end-
stage liver disease; LT: liver transplantation.
An effective model for predicting acute kidney injury after liver transplantation
Hepatobiliary Pancreat Dis Int,Vol 9,No 3 • June 15,2010 • www.hbpdint.com • 261
the first week post-LT, 33 patients (32.4%) developed AKI
including 10 (9.8%) requiring renal replacement therapy.
The median time for appearance of AKI was 2 days post-
LT. The median duration of AKI was 17 days (range 7-481
days). The difference in the 1-year overall survival rates
between patients in the AKI and non-AKI groups was
statistically significant (70.1% vs. 92.3%, P=0.001, Fig. 1).
Clinical features pre-LT
The pre-LT clinical features of the AKI and non-AKI
groups showed differences in a ge, MELD s core, seru m
creatinine, blood urea nitrogen, serum sodium, and
serum potassium (all P<0.01; Table 2).
Risk factors of AKI
In our cohort, norepinephrine was used intra-
operatively as a protective drug. Statistically significant
variables associated with AKI were revealed by the
univariate analysis. Fourteen parameters were significantly
associated with a high risk of AKI (Table 2). Of the
25 patients with preoperative serum creatinine >1.2
mg/dl, 10 including 2 who needed renal replacement
therapy developed hepatorenal syndrome as defined by
the International Ascites Club and the other 15 had a
slight elevation of serum creatinine (<2 mg/dl) without
intrinsic kidney disease.
Predictive model for AKI
Preoperative model
Six preoperative parameters were subject to multi-
variate logistic regression analysis. Serum creatinine >1.2
mg/dl (odds ratio (OR)=8.603, P<0.001) and serum
sodium ≤
137 mmol/L (OR=3.349, P=0.015) were indepen-
dent risk factors of AKI. The preoperative model for
the prediction of AKI was established as: -1.961+2.152×
(serum creatinine >1.2 mg/dl)+1.209×(serum sodium
≤137 mmol/L). For predicting patients at ris k for A KI,
the area under the ROC curve was 0.765 (Fig. 2).
Postoperative model
The results of multivariate logistic regression analysis
are shown in Table 3. Of all 14 potential influencing
factors analyzed, preoperative serum creatinine >1.2 mg/
dl, intraoperative hypotension status, intraoperative urine
output ≤60 ml/h and intraoperative use of noradrenaline
proved to have the best fit in our predictive model: risk
score=[-2.128+1.109×(preoperative serum creatinine
>1.2 mg/dl)+2.243×(intraoperative urine output ≤60
Variables AKI P
Yes (n=33) No (n=69)
Preoperative
Age >50 yr (vs. ≤50 yr) 16 20 0.045
MELD score >25 (vs. ≤25) 21 24 0.006
Serum creatinine >1.2 mg/dl
(vs. ≤1.2 mg/dl)
17 8 <0.001
Blood urea nitrogen >23 mg/dl
(vs. ≤23 mg/dl)
14 11 0.004
Serum sodium ≤137 mmol/L
(vs. >137 mmol/L)
21 25 0.009
Serum potassium >5.0 mmol/L
(vs. ≤5.0 mmol/L)
5 1 0.013
Intraoperative
Red blood cells >15 U (vs. ≤15 U) 26 34 0.005
Fresh-frozen plasma >3000 ml
(vs. ≤3000 ml)
18 21 0.019
Platelets >10 U (vs. ≤10 U) 20 25 0.020
Blood loss >5000 ml (vs. ≤5000 ml) 16 13 0.002
Urine output ≤60 ml/h (vs. >60 ml/h) 23 14 <0.001
Adrenaline >2.3 mg (vs. ≤2.3 mg) 19 16 0.001
Hypotension status
(vs. no hypotension status)
17 11 <0.001
Use of noradrenaline
(vs. no use of noradrenaline)
2 22 0.004
Table 2. Univariate analysis of influencing factors for AKI
MELD: model for end-stage liver disease.
Fig. 1. Comparison of cumulative patient survival between the
AKI group (broken line) and the non-AKI group (solid line); the
log-rank test, P=0.001.
Fig. 2. Area under ROC curve of the preoperative model (broken
line, 0.765) and postoperative model (solid line, 0.908).
Hepatobiliary & Pancreatic Diseases International
262 • Hepatobiliary Pancreat Dis Int,Vol 9,No 3 • June 15,2010 • www.hbpdint.com
ml/h)+1.542×(intraoperative hypotension status)-2.463×
(intraoperative use of noradrenaline)]. Probability of
AKI=EXP (risk score)/[1+EXP (risk score)].
The model discriminated well (area under ROC
curve: 0.908, Fig. 2) and fitted excellently (P=0.971
to reject model fit). Considering both sensitivity and
specificity, we selected the risk score as a cutoff of -0.2 to
predict AKI. This implied that patients with a risk score
≥-0.2 (at high risk) were more likely to develop AKI
than those with a risk score <-0.2 (at low risk).
The consequent prospective evaluation using the
established model showed good predictive results.
According to the predictive rule, 9 of 11 patients at high
risk developed AKI, and 30 of 33 patients at low risk
did not develop AKI. This model obtained a sensitivity
of 75.0% (9/12), a specificity of 93.8% (30/32) and an
accuracy of 88.6% (39/44).
Discussion
In this study, we examined renal function in the early
period post-LT in patients most of whom had hepatitis B
related liver disease. Our retrospective study confirmed
the previous studies that AKI has a relatively high
incidence (32.4%) and has a marked negative impact on
the short-term and long-term survival of patients. Thus it
would be better if there were an effective model for early
prediction of AKI.
A preoperative model could identify patients going
into LT who are at risk for AKI. However, we found it was
difficult to predict the development of AKI based on the
preoperative data alone, as the predictive ability of the
preoperative model was far from desirable (area under
ROC curve <0.8). The etiology of AKI is multifactorial
and the potential risk factors include preoperative,
intraoperative and postoperative factors.[2-7] Our finding
that most AKI cases appeared within 3 days post-LT
suggested that it might be mainly associated with the
preoperative and intraoperative conditions. This study
demonstrated that patients at high risk could be clearly
discriminated from those at low risk for developing
AKI by a predictive model established on the basis of
one preoperative variable (high serum creatinine level)
and three intraoperative variables (low urine output,
hypotension status and nonuse of noradrenalin). Using
this model, we can rapidly and simply assess the natural
course of renal function post-LT and take prompt
strategies for the prevention and treatment of AKI.
It has frequently been mentioned in Western reports
that preoperative impairment of renal function plays
a crucial role in the occurrence of AKI.[2-5] Serum
creatinine has traditionally been considered as a simple
and cheap marker for assessing renal function in clinical
practice. Nevertheless, patients with end-stage liver
disease always present high levels of serum creatinine.[3, 12]
Even a mild elevation of preoperative serum creatinine
level (1.0-1.5 mg/dl) may forebode poor renal function
post-LT.[13] To better evaluate preoperative renal function,
we tried different serum creatinine levels between 1.0
and 1.5 mg/dl for analysis and finally selected >1.2 mg/dl
as the best cutoff value for the threshold of preoperative
renal dysfunction.
Intraoperative injury to the kidneys could be induced
by unstable hemodynamics (massive blood loss, hypo-
tension status, low urine output, and large requirement
for blood products), surgical technique or nephrotoxic
drugs.[14-16] Our data indicated that massive blood loss,
major blood product transfusion, hypotension status,
low urine output and moderate or even high doses of
vasopressors were significantly related to AKI. To some
extent, intraoperative massive blood loss is inevitable
in patients with refractory disturbance of coagulation
and severe varices.[17] Large amounts of blood loss result
in unstable hemodynamics and inadequate vital organ
perfusion, reflected by hypotension and low urine
output. Fluid transfusion and vasopressors are definitely
required under these conditions, and some drugs might
aggravate poor kidney perfusion. Of particular interest,
noradrenaline, an available and common agent in clinic
use, was found to be significantly associated with a
reduced incidence of AKI, which has not been reported.
Recently, both clinical and animal studies have indicated
that noradrenaline functions are effective not only in
elevating arterial blood pressure, but also in improving
renal blood flow and urine output in vasodilated
conditions such as septic shock.[18-20] Recipients with
cirrhosis present characteristic hemodynamic changes,
including low arterial blood pressure and increased
cardiac output before and during operation, which might
be similar to septic shock.[20, 21] Further studies such as a
randomized and double-blind clinical trial are desperately
required to certify the potential renal protective
function of noradrenalin in LT.
Variables P OR 95% CI
Preoperative serum creatinine >1.2 mg/dl
(vs. ≤1.2 mg/dl)
0.045 3.031 0.896-10.25
Intraoperative urine output ≤60 ml/h
(vs. >60 ml/h)
<0.001 9.423 2.932-30.28
Intraoperative hypotension status 0.016 4.673 1.335-16.36
Intraoperative use of noradrenaline
(vs. no use of noradrenaline)
0.010 0.085 0.013-0.548
Table 3. Multivariate analysis of influencing factors for AKI
OR: odds ratio; CI: confidence interval.
An effective model for predicting acute kidney injury after liver transplantation
Hepatobiliary Pancreat Dis Int,Vol 9,No 3 • June 15,2010 • www.hbpdint.com • 263
The actual impact on the development of AKI of
other potential influencing factors such as age, serum
sodium and serum potassium is still not well defined.
Although the univariate analysis did not find that the
immunosuppressive regimen is a r isk factor of AKI, in
our experience the application of calcineurin inhibitors
should be postponed if the calculated risk score is above
-0.2 according to this predictive model. Veno-venous
bypass has been abandoned since 2001 at our center
because our previous study did not find any positive
effect from this technique on renal function.[22]
In conclusion, AKI remains a common complication
after LT with a poor prognosis among patients with
HBV-related liver diseases. In China, the preoperative
serum creatinine, intraoperative urine flow, intra-
operative hypotension status and intraoperative use
of noradrenalin are strongly associated with AKI.
The predictive model established on the basis of
these four independent influencing factors may be a
reliable and effective tool to identify patients at high
risk for developing AKI, and thus prompt salvaging
interventions are required. Further well-designed
studies are needed to clearly describe the strengths and
limitations of this predictive model.
Funding: This study was supported by a grant from the Projects of
Ministry of Public Health (No. 20082006).
Ethical approval: Not needed.
Contributors: XX proposed the study and wrote the first draft.
All authors contributed to the design and interpretation of the
study and to further drafts. ZSS is the guarantor.
Competing interest: No benefits in any form have been received
or will be received from a commercial party related directly or
indirectly to the subject of this article.
References
1 Mehta RL, Kellum JA, Shah SV, Molitoris BA, Ronco C,
Warnock DG, et al. Acute Kidney Injury Network: report of
an initiative to improve outcomes in acute kidney injury. Crit
Care 2007;11:R31.
2 Niemann CU, Walia A, Waldman J, Davio M, Roberts JP,
Hirose R, et al. Acute kidney injury during liver transplantation
as determined by neutrophil gelatinase-associated lipocalin.
Liver Transpl 2009;15:1852-1860.
3 Lima EQ, Zanetta DM, Castro I, Massarollo PC, Mies S,
Machado MM, et al. Risk factors for development of acute renal
failure after liver transplantation. Ren Fail 2003;25:553-560.
4 Lebrón Gallardo M, Herrera Gutierrez ME, Seller Pérez G,
Curiel Balsera E, Fernández Ortega JF, Quesada García G. Risk
factors for renal dysfunction in the postoperative course of
liver transplant. Liver Transpl 2004;10:1379-1385.
5 Smith JO, Shif fman ML, Behn ke M, Strav itz RT, Luketic VA,
Sanyal AJ, et al. Incidence of prolonged length of stay after
orthotopic liver transplantation and its influence on outcomes.
Liver Transpl 2009;15:273-279.
6 Pawarode A, Fine DM, Thuluvath PJ. Independent risk factors
and natural history of renal dysfunction in liver transplant
recipients. Liver Transpl 2003;9:741-747.
7 Chuang FR, Lin CC, Wang PH, Cheng YF, Hsu KT, Chen
YS, et al. Acute renal failure after cadaveric related liver
transplantation. Transplant Proc 2004;36:2328-2330.
8 Peeters P, Van Laecke S, Vanholder R. Acute kidney injury in
solid organ transplant recipients. Acta Clin Belg Suppl 20 07:
389-392.
9 Rimola A, Gavaler JS, Schade RR, el-Lankany S, Starzl TE, Van
Thiel DH. Effects of renal impairment on liver transplantation.
Gastroenterology 1987;93:148-156.
10 Chertow GM, Burdick E, Honour M, Bonventre JV, Bates DW.
Acute kidney injury, mortality, length of stay, and costs in
hospitalized patients. J Am Soc Nephrol 2005;16:3365-3370.
11 Barri YM, Sanchez EQ, Jennings LW, Melton LB, Hays S, Levy
MF, et al. Acute kidney injury following liver transplantation:
definition and outcome. Liver Transpl 2009;15:475-483.
12 Sharma P, Schaubel DE, Guidinger MK, Merion RM. Effect of
pretransplant serum creatinine on the survival benefit of liver
transplantation. Liver Transpl 2009;15:1808-1813.
13 Bilbao I, Charco R, Balsells J, Lazaro JL, Hidalgo E, Llopart L,
et al. Risk factors for acute renal failure requiring dialysis after
liver transplantation. Clin Transplant 1998;12:123-129.
14 Sural S, Sharma RK, Singhal M, Sharma AP, Kher V, Arora P,
et al. Etiology, prognosis, and outcome of post-operative acute
renal failure. Ren Fail 2000;22:87-97.
15 Cabezuelo JB, Ramirez P, Acosta F, Torres D, Sansano T, Pons
JA, et al. Does the standard vs piggyback surgica l technique
affect the development of early acute renal failure after
orthotopic liver transplantation? Transplant Proc 2003;35:1913-
1914.
16 Park Y, Hirose R, Dang K, Xu F, Behrends M, Tan V, et al.
Increased severity of renal ischemia-reperfusion injury with
venous clamping compared to arterial clamping in a rat model.
Surgery 2008;143:243-251.
17 Findlay JY, Rettke SR. Poor prediction of blood transfusion
requirements in adult liver transplantations from preoperative
variables. J Clin Anesth 2000 ;12:319-323.
18 Di Giantomasso D, Morimatsu H, May CN, Bellomo R.
Intrarenal blood flow distribution in hyperdynamic septic
shock: Effect of norepinephrine. Crit Care Med 2003;31:2509-
2513.
19 Martin C, Viviand X, Leone M, Thirion X. Effect of
norepinephrine on the outcome of septic shock. Crit Care Med
2000;28:2758-2765.
20 Albanèse J, Leone M, Delmas A, Martin C. Terlipressin or
norepinephrine in hyperdynamic septic shock: a prospective,
randomized study. Crit Care Med 2005;33:1897-1902.
21 Møller S, Bendtsen F, Henriksen JH. Splanchnic and systemic
hemodynamic derangement in decompensated cirrhosis. Can
J Gastroenterol 2001;15:94-106.
22 Zheng SS, Liang TB, Wang WL, Huang DS, Shen Y, Zhang
M, et al. Clinical experience in liver transplantation from an
organ transplantation center in China. Hepatobiliary Pancreat
Dis Int 2002;1:487-491.
Received May 14, 2009
Accepted after revision November 6, 2009