acute kidney injury following cardiac surgery, diagnostic value of plasma neutrophil...

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The Egyptian Heart Journal (2011) xxx, xxx–xxx

EHJ 18 No. of Pages 8

10 October 2011

Egyptian Society of Cardiology

The Egyptian Heart Journal

www.elsevier.com/locate/ehjwww.sciencedirect.com

ORIGINAL ARTICLE

Acute kidney injury following cardiac surgery, diagnostic

value of plasma neutrophil gelatinase-associated lipocalin

Mohamed Ali Mohamed Badawy, Hisham Ali Elaasar, Gamal Hamed Ahmed *,

Hamdy Mohamed Saber, Inas Abdellatif Ahmed

Cairo University, Critical Care Medicine Department, Egypt

Received 12 December 2010; accepted 26 January 2011

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KEYWORDS

ICU;

NGAL;

AKI;

RIFLE

Corresponding author.

-mail address: ghamal60@y

10-2608 ª 2011 Egyptian S

sting by Elsevier B.V. All rig

er review under responsibilit

i:10.1016/j.ehj.2011.08.018

Production and h

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Abstract Introduction: Acute kidney injury (AKI) is well recognized for its impact on the out-

come of patients admitted to the intensive care unit (ICU) and the extent of perioperative renal

impairment ranges from subclinical injury to the established renal failure requiring dialysis.

The pursuit of improved biomarkers for the early diagnosis of AKI and its outcomes is an area of

intense contemporary research.

Aim of work is to study the utility of early NGAL (neutrophil gelatinase-associated lipocalin) mea-

surements for predicting clinical outcomes of AKI, following cardiac surgery.

Methodology: Study was conducted on 40 patients scheduled to have either on-pump or off-pump

cardiac surgery during the period from February 2009 till June 2010, with mean age of

54.7 ± 12.3 years, 28 males and the remaining 12 were females. Thirty-two patients were hyperten-

sives, 24 diabetics, 7 known to have COPD, 6 known to have CVD, 14 documented to have recent

myocardial infarction within the previous 6 weeks, and 30 patients of them were routinely receiving

ACEI.

Regarding the type of surgery they were scheduled to, 29 patients were scheduled for CABG, 5 for

valve surgery and 6 for combined surgery, also 6 patients were in need for urgent surgery and 20 of

them were operated using CPB.

Spot plasma samples at (2 and 12 h) intervals after cardiac surgery for measurement of plasma

NGAL and serum creatinine were obtained from all patients and RIFLE criteria were calculated

at baseline and daily during the first five postoperative days taking into consideration the strict

(G. Hamed Ahmed).

Cardiology. Production and

ved.

tian Society of Cardiology.

lsevier

ohamed Badawy MA et al. Acute kidney injury following cardiac surgery, diagnostic value ofiated lipocalin, The Egypt Heart J (2011), doi:10.1016/j.ehj.2011.08.018

mailto:[email protected]

http://dx.doi.org/10.1016/j.ehj.2011.08.018



http://www.sciencedirect.com/science/journal/11102608


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2 M.A. Mohamed Badawy et al.


10 October 2011

Please cite this article in press as: Mplasma neutrophil gelatinase-assoc

measures to avoid postoperative volume depletion and prerenal azotemia through using standard

fluid regimen allowing all patients to receive at least 80% of their maintenance fluid requirements

during the first 24 h after surgery and 100% subsequently.

Results: Exploring the diagnostic yield of NGAL levels in our study, the development of acute kid-

ney injury in our studied population was highly and significantly correlated to 2HNGAL level with

P value (0.0001) and a mean 2HNGAL of 310 ± 65 in AKI patients compared to 140 ± 51 in non-

AKI patients, also it was significantly correlated to 12HNGAL level with P value (0.02) and a mean

12HNGAL of 210 ± 103 in AKI patients compared to 147 ± 53 in non-AKI patients also. Upon

attempting to find out the best cutoff limits of both 2HNGAL and 12HNGAL as diagnostic mark-

ers of AKI using ROC curve analysis, it had been discovered that the best cutoff value for

2HNGAL was 169 that yields a sensitivity of 100% and a specificity of 80%, on the other hand,

the best cutoff value for 12HNGAL was 130 that yields a sensitivity of 80% and a specificity of

55%.

The mortality rate as a primary outcome was obviously and significantly related to both

2HNGAL and 12HNGAL levels, particularly 12HNGAL (P= 0.03 for 2HNGAL) and

(P= 0.01 for 12HNGAL).

Development of AKI was significantly associated with the preoperative echocardiographic evi-

dence of lower ejection fractions (LVEF) (P value = 0.001), a significant inverse correlation

between preoperative echocardiographic estimation of LVEF and postoperative NGAL levels,

yet that correlation had more significance in the case of 2HNGAL (r = �0.61, P = 0.001) if com-

pared to 12HNGAL (r = �0.45, P = 0.004).

Diabetes mellitus was not associated with higher incidence of postoperative AKI (P = 0.053),

but perioperative myocardial infarction was associated with higher incidence of AKI (P = 0.004)

and preoperative use of vasopressors showed higher incidence of AKI (P = 0.01) with significantly

higher levels of 2HNGAL (P = 0.01) and 12HNGAL (P = 0.03).

Use of CPB showed no increase of incidence of AKI or levels of 2HNGAL and 12HNGAL,

however there was a significant direct correlation between duration of use of CPB and 2HNGAL

levels (r = 0.45, P = 0.04). Development of AKI was also significantly associated with excessive

intraoperative blood loss represented by the lowest intraoperative Hct value (P value = 0.002) with

significant direct correlation between a number of blood units transfused intraoperatively and

2HNGAL (r = 0.42, P = 0.007), also higher incidence of AKI occurred with lesser amounts of

intraoperative total UOP (P value = 0.008).

No significant relation between the re-exploration of our patients for any cause and both

2HNGAL and 12HNGAL (P = 0.23, 0.25, respectively. Total number of ICU stay days was obvi-

ously and significantly correlated to both 2HNGAL and 12HNGAL levels, particularly 12HNGAL

(r= 0.4, P = 0.01 for 2HNGAL) and (r = 0.43, P= 0.005 for 12HNGAL).

Conclusion: NGAL measurement represents an early and reliable marker of AKI following cardiac

surgery, levels of 2HNGAL and 12HNGAL correlate with mortality rate as a primary outcome.

Perioperative myocardial infarction, use of vasopressors, duration of use of CPB, intraoperative

blood loss are associated with higher levels of 2HNGAL and 12HNGAL and development of

AKI. Monitoring of NGAL could be in the future a therapeutic strategy modifying agent.

ª 2011 Egyptian Society of Cardiology. Production and hosting by Elsevier B.V. All rights reserved.

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1. Introduction

The incidence of perioperative ARF varies according to the eti-ology and definition, and type of surgery undergone; but for allcauses, renal failure is associated with mortality rates of 60–

90%.1

There has been a steady improvement over the last 40 yearsin crude mortality statistics following cardiac surgery, in the

face of increasing number of higher risk patients.2 This is pri-marily as a result of improvements in cardiopulmonary bypass(CPB) technology, operative technique, and postoperativeman-agement.3 However, the incidence of acute renal failure (ARF)

has not changed over this time and renal dysfunction still affectsa significant number of patients in the perioperative period.4

In spite of much research activity in this area there is still no

standardized definition of ARF,5 but it is usually quantified asan increase in serum creatinine, reduction in creatinine clear-

ohamed Badawy MA et al. Acuiated lipocalin, The Egypt Hea

ance or a decrease in urine output. ARF following cardiac sur-gery is associated with an increased early mortality even after

adjusting for co-morbidity and postoperative complications.6

ARF also increases the risk of postoperative morbidity,especially sepsis, gastrointestinal bleeding, neurological distur-bances and postoperative myocardial infarction.7

ARF therefore results in a 2–3-fold increase in total hospi-tal stay, increases the length of time spent in a high dependencyfacility,1 and triples the likelihood of discharge to an extended

care facility.1 All of this increases the overall cost of the proce-dure for patients developing acute renal failure, but also putsthe patient at long-term risk of progressive renal failure.7

Many different risk factors have been identified for periop-erative ARF which include, pre-existing renal dysfunction,8

chronic renal disease,9 reduced creatinine clearance,10 or raised

preoperative serum creatinine or urea11which all predict an in-creased risk of ARF after cardiac surgery.

te kidney injury following cardiac surgery, diagnostic value ofrt J (2011), doi:10.1016/j.ehj.2011.08.018


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Acute kidney injury following cardiac surgery, diagnostic value of plasma neutrophil gelatinase-associated lipocalin 3


10 October 2011

Poor preoperative cardiac status and advanced vascular

disease with greater renal involvement.12

Finally, early postoperative complications such as atrialfibrillation and sepsis are associated with increased renaldysfunction.13

1.1. Aim of the work

� Proving that plasma neutrophil gelatinase-associated lipoc-

alin is an earlier and accurate biomarker in predicting acuterenal injury in post cardiac surgery patients.� Finding correlations between plasma NGAL and need for

dialysis, ICU stay, and overall mortality post cardiac sur-gery with renal impairment.

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Table 1 Basic demographic characteristics.

Variable Number of patients %

Gender

Male 28 70

Female 12 30

HTN 32 80

DM 24 60

COPD 7 18

CVD 6 15

Recent MI 14 35

Preop. ACEI 30 75

Surgery type

CABG 29 73

Valve 5 13

Combined 6 15

Urgent surgery 6 15

CPB 20 50

2. Patients and methods

2.1. Inclusion criteria

A total of 40 patients undergoing cardiac surgery with normalpreoperative renal function, sonographically normal kidneys.

Exclusion criteria

� Pre-existing renal insufficiency.� Extremes of age (>75 and <18).

� Abnormal preoperative renal sonographic findings.� Peripheral vascular disease.� Use of nephrotoxic drugs before or during the study.� Severely impaired left ventricular systolic function

(EF < 20%).

All patients will be subjected to the following:

� Written informed consent entailing all ethical and moralconsiderations.

� Full history taking and clinical systematic review stressingon conditions predisposing to renal impairment.� Full preoperative laboratory investigations including (CBC,

kidney and liver functions, electrolyte review, fasting andpost prandial blood sugar) in addition to abdominal ultra-sonography and echocardiography.� RIFLE criteria will be calculated at baseline and daily dur-

ing the first five postoperative days.� Strict measures to avoid postoperative volume depletionand perennial azotemia through using standard fluid regi-

men allowing all patients to receive at least 80% of theirmaintenance fluid requirements during the first 24 h aftersurgery and 100% subsequently.

� Spot plasma samples at baseline and at frequent intervals (2and 12 h) after cardiac surgery for measurement of plasmaNGAL and serum creatinine.

Table 2 AKI and NGAL levels.

Number 2HNGAL 12 HNGAL

Mean SD P value Mean SD P value

AKI 20 310.65 65.15 0.0001 210.45 103.88 0.02

NO AKI 20 140.8 51.76 147.4 53.86

3. Results

Our study is a prospective randomized controlled observa-tional study that was conducted on 40 patients scheduled tohave cardiac surgery during the period from February 2009 till

June 2010 in Kasr-Elaini hospital – Cairo University, Dar-Elfouad hospital, in addition to Police hospital.

Our results are to be demonstrated under four main

categories:

Please cite this article in press as: Mohamed Badawy MA et al. Acuplasma neutrophil gelatinase-associated lipocalin, The Egypt Hear

A. Basic characteristics.

B. Relation between AKI and NGAL levels.C. Analyzing predictors and outcome of AKI and NGAL

levels.

D. Relations to the use of Cardio Pulmonary bypass (CPB).

3.1. Basic characteristics

The mean age of our studied population was 54.7 ± 12.3years, with 28 of them males and the remaining 12 were fe-

males. Thirty-two patients were hypertensives, 24 diabetics, 7known to have COPD, 6 known to have CVD, 14 documentedto have recent myocardial infarction within the previous

6 weeks and 30 patients of them were routinely receiving ACEI(Angiotensin Converting Enzyme Inhibitor).

Regarding the type of surgery, 29 patients were scheduled

for CABG, 5 for valve surgery and 6 for combined surgery,also 6 patients were in need for urgent surgery and 20 of themwere operated using CPB.

The mean weight of patients was 80.5 ± 10.7 kg, their

mean LVEF prior to surgery was 51.2 ± 10.5% and their pre-operative serum albumin had a mean of 3.7 ± 0.44 g/dl asshown in Table 1.

3.2. Relationship between AKI and NGAL levels

Exploring the diagnostic yield of NGAL levels in our study,the development of acute kidney injury was highly and signif-icantly correlated to 2HNGAL level with P value (0.0001),also it was significantly correlated to 12HNGAL level with P

value (0.02) as demonstrated in Table 2 and Fig. 1.

te kidney injury following cardiac surgery, diagnostic value oft J (2011), doi:10.1016/j.ehj.2011.08.018


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Figure 1 Relation between AKI and NGAL levels.



10 October 2011

Receiver operating characteristic (ROC) was carried out for

both 2HNGAL and 12HNGAL levels to test for the diagnosticyield of each of them as an early marker of AKI and to findout the best cutoff limits of these levels as shown in Table 3

and Fig. 2.Two HNGAL levels represent an accurate and early diag-

nostic marker of AKI as evidenced by a leftward and upward

shift of its curve, AUC of 0.973 and a P value of 0.0001. Onthe other hand, 12HNGAL did not show the same diagnosticyield as 2HNGAL as evidenced by a less leftward and upward

shift, AUC of 0.671 and a P value of 0.06.The best cutoff value for 2HNGAL was 169 that yields a

sensitivity of 100% and a specificity of 80%, on the otherhand, the best cutoff value for 12HNGAL was 130 that yields

a sensitivity of 80% and a specificity of 55%.

Table 3 AUC for NGAL levels.

Variable Area P value

2HNGAL 0.973 0.0001

12NGAL 0.671 0.06

Figure 2 ROC curve analysis.

Please cite this article in press as: Mohamed Badawy MA et al. Acuplasma neutrophil gelatinase-associated lipocalin, The Egypt Hea

3.3. Analyzing predictors and outcome of AKI and NGAL levels

These include preoperative factors, intraoperative factors, andpostoperative factors.

3.3.1. Preoperative factors

3.3.1.1. Left ventricular ejection fraction. The development ofAKI was significantly associated with preoperative echocar-diographic evidence of lower ejection fractions with a P va-lue = 0.001 as shown in Fig. 3.

3.3.1.2. Diabetes mellitus. Although diabetic patients werefound to be more susceptible to the postoperative development

of AKI, yet with no statistical significance with a Pvalue = 0.053.

3.3.1.3. Preoperative use of vasopressors. The development ofAKI in our studied population was significantly associatedwith the preoperative use of vasopressor drugs with a P va-

lue = 0.01 as shown in Fig. 4.

3.3.1.4. Perioperative myocardial infarction. Documented peri-operative MI was significantly associated with the develop-

ment of AKI with a P value (0.004) as shown in Fig. 5.

Figure 3 Relation between LVEF and AKI.

Figure 4 Relation between pre-operative use of vasopressors

and AKI.



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186Figure 6 Relation between CPB duration and AKI.

Figure 8 Relation between total intra-operative UOP and AKI.Figure 5 Relation between pre-operative MI and AKI.



10 October 2011

3.3.1.5. Intraoperative factors. The use of cardiopulmonary by-pass per se had no significant relation to the development ofAKI but prolonged CPB times were associated with, high inci-

dence of AKI P = 0.01, Fig. 6.3.3.1.5.1. Intra-operative blood transfusion. AKI was signif-

icantly associated with the amount of intraoperative bloodtransfusion units with a P value = 0.008 as shown in Fig. 7.

Total intraoperative UOP: The development of AKI wassignificantly associated with lesser amounts of intraoperativetotal UOP with a P value = 0.008 as shown in Fig. 8.

Figure 7 Relation between transfused blood units and AKI.


3.3.1.5.2. ICU stay. The total number of ICU stay days hada significant correlation with the development of AKI with a Pvalue = 0.001 as shown in Fig. 9.

3.3.1.5.3. Mortality. The development of AKI in our stud-ied population was significantly associated with a higher mor-tality rate with a P value = 0.01 as shown in Fig. 10.

3.3.2. NGAL levels

3.3.2.1. Left ventricular ejection fraction. There was a signifi-

cant inverse correlation between preoperative echocardio-graphic estimation of LVEF and postoperative NGAL levels,yet that correlation had more significance in the case of

Figure 9 Relation between ICU stay and AKI.

Figure 10 Relation between mortality and AKI.



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Figure 14 Relation between ICU stay and NGAL levels.



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2HNGAL (r = �0.61, P = 0.001) if compared to 12HNGAL

(r = �0.45, P = 0.004) as demonstrated in Fig. 11.CPB duration: There was a significant direct correlation be-

tween duration of use of CPB and 2HNGAL levels (r = 0.45,P = 0.04), yet there was no such significant correlation be-

tween the use of CPB and 12HNGAL levels (r = 0.36,P = 0.12) as shown in Fig. 12.

Intraoperative blood transfusion: There was a significant di-

rect correlation between number of blood units transfusedintraoperatively and 2HNGAL (r= 0.42, P = 0.007), yetthere was no such significant correlation with 12HNGAL

(r = 0.24, P = 0.13) as shown in Fig. 13.ICU stay: The total number of ICU stay days was obvi-

ously and significantly correlated to both 2HNGAL and

12HNGAL levels, particularly 12HNGAL (r = 0.4, P = 0.01for 2HNGAL) and (r = 0.43, P = 0.005 for 12HNGAL) asshown in Fig. 14.

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Figure 11 Relation between LV ejection fraction and NGAL.

Figure 12 Relation between CPB duration and NGAL.

Figure 13 Relation between intra-operative blood units and

NGAL.

Figure 15 Relation between mortality and NGAL.


Mortality: The mortality rate as a primary outcome was

obviously and significantly related to both 2HNGAL and12HNGAL levels, particularly 12HNGAL (P = 0.03 for2HNGAL) and (P = 0.01 for 12HNGAL) as shown inFig. 15.

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4. Discussion

Acute kidney injury is well recognized for its impact on theoutcome of patients admitted to the intensive care unit(ICU). Illness severity scores, such as the Acute Physiology

and Chronic Health Evaluation version III (APACHE III)scoring system14, and the Sequential Organ Failure Assess-ment score (SOFA)15 both weight kidney dysfunction heavily

(20% and 16.6% of the total scores for acute physiology).Yet there is no consensus on the amount of dysfunction thatdefines acute kidney injury.16 The variety of definitions usedin clinical studies may be partly responsible for the large vari-

ations in the reported incidence (1–31%)17–19 and the associ-ated mortality (19–83%)19–22 of acute kidney injury. Acutekidney injury is generally defined as ‘an abrupt and sustained

decrease in kidney function’. Until recently there has not beena consensus on how best to assess kidney function; namely,what markers best reflect kidney function, and what values

of those markers discriminate normal from abnormal kidneyfunction.23

So this study was done to prove that NGAL is an earlier

and accurate biomarker in predicting acute renal injury in postcardiac surgery patients, and its correlations with need fordialysis, ICU stay, and overall mortality post-cardiac surgerywith renal impairment.



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10 October 2011

In the present study patients post cardiac surgery showed a

mortality rate of 25% (5 cases died out of 20 with AKI), thisresult was comparable to reports of similar studies whereacute renal failure has been reported to affect from 1% to25% of patients and has led to mortality rates from 15% to

60%.24–26

Also, the development of AKI in our study was signifi-cantly associated with lesser amounts of intraoperative total

UOP with a P value = 0.008, this coincides with data fromprevious studies where Nonoliguria is associated with an im-proved likelihood of recovery of renal function and approxi-

mately half the mortality of oliguric ARF (50%).27

Co-morbid conditions were found to be extremely influen-tial in developing AKI, the present study showed higher inci-

dence with evidence of the preoperative reduction of LVEF(P = 0.001), perioperative myocardial infarction (P = 0.01)and preoperative use of vasopressors (P = 0.004). Other stud-ies have shown that even within the group of patients with

ARF due to renal hypoperfusion, mortality varied between9% in patients with volume depletion and 100% in patientswith cardiogenic shock.28

The need for dialysis in our patients showed a mortalityrate of 60% (out of 5 pts subjected to dialysis 3 died). Thesedata explain why dialysis therapy fails to dramatically improve

the survival rates in ARF. Patients with multisystem condi-tions, in particular, fail to show any benefit from dialysis ther-apy. An analysis of survival in ARF in the ICU demonstratedthat certain comorbid factors, acute respiratory distress syn-

drome, requirement for antibiotics, and ventilatory failurecaused lower survival.29 Ventilatory failure, in particular,was associated with 100% mortality in patients who also re-

quired dialysis. The particularly high mortality in ARF com-plicating multiorgan system failure and the associatedincrements in hospital costs have led some to call for a re-anal-

ysis of the use of dialytic procedures in critically ill patients.In the present study NGAL levels were found to be of high

diagnostic yield for the development of AKI both at 2 h

(P = 0.0001) and 12 h (P = 0.02). These data coincide withdata from the study of Dent et al., 2007 where patients under-going cardiac surgery, the 2-h post-operative plasma NGALlevels were strongly correlated with duration and severity of

AKI, and length of hospital stay. In addition, the 12-h plasmaNGAL strongly correlated with mortality.

ROC curve analysis had been carried out for both

2HNGAL and 12HNGAL levels to test for the diagnosticyield of each of them as an early marker of AKI and to findout the best cutoff limits of these levels.

What can be extrapolated from both the plot in Fig. 3 andTable 3 is that 2HNGAL level represents an excellent, accurateand early diagnostic marker of AKI as evidenced by a leftward

and upward shift of its curve, AUC of 0.973 and a P value of0.0001. On the other hand, 12HNGAL used as a diagnosticmarker of AKI does not have the same diagnostic yield as2HNGAL as evidenced by a less leftward and upward shift,

AUC of 0.671 and a P value of 0.06.Upon attempting to find out the best cutoff limits of both

2HNGAL and 12HNGAL as diagnostic markers of AKI using

ROC curve analysis, it had been discovered that the best cutoffvalue for 2HNGAL was 169 that yields a sensitivity of 100%and a specificity of 80%, on the other hand, the best cutoff va-

lue for 12HNGAL was 130 that yields a sensitivity of 80% anda specificity of 55%.


Finally, acute kidney injury (AKI) is a complex disorder for

which currently there is no accepted definition. Having a uni-form standard for diagnosing and classifying AKI would en-hance our ability to manage these patients. Future clinicaland translational research in AKI will require collaborative

networks of investigators drawn from various disciplines, dis-semination of information via multidisciplinary joint confer-ences and publications, and improved translation of

knowledge from pre-clinical research.

5. Conclusions

NGAL measurement represents an early and reliable markerof AKI following cardiac surgery, levels of 2HNGAL and

12HNGAL correlate with mortality rate as a primary out-come. Perioperative myocardial infarction, use of vasopres-sors, duration of use of CPB, intraoperative blood loss are

associated with higher levels of 2HNGAL and 12HNGALand development of AKI. Monitoring of NGAL could be inthe future a therapeutic strategy modifying agent.

References

1. Mangano CM et al. Renal dysfunction after myocardial revascu-

larization: risk factors, adverse outcomes, and hospital resource

utilization. The Multicenter Study of Perioperative Ischemia

Research Group. Ann Intern Med 1998;128(3):194–203.

2. Ostermann ME et al. Acute renal failure following cardiopulmo-

nary bypass: a changing picture. Intensive Care Med

2000;26(5):565–71.

3. Hamada Y et al. N-acetyl-beta-D-glucosaminidase is not a

predictor, but an indicator of kidney injury in patients with

cardiac surgery. J Med 1999;30(5–6):329–36.

4. Conlon PJ et al. Acute renal failure following cardiac surgery.

Nephrol Dial Transplant 1999;14(5):1158–62.

5. Mangos GJ et al. Acute renal failure following cardiac surgery:

incidence, outcomes and risk factors. Aust N Z J Med

1995;25(4):284–9.

6. Chertow GM et al. Independent association between acute renal

failure and mortality following cardiac surgery. Am J Med

1998;104(4):343–8.

7. Lema G et al. Effects of extracorporeal circulation on renal

function in coronary surgical patients. Anesth Analg

1995;81(3):446–51.

8. Lema G, Canessa R, Urzua J. Renal preservation in cardiac

surgery. Curr Opin Anaesthesiol 1998;11(1):9–13.

9. Durmaz I et al. Cardiac surgery with cardiopulmonary bypass in

patients with chronic renal failure. J Thorac Cardiovasc Surg

1999;118(2):306–15.

10. McCullough PA et al. Acute renal failure after coronary inter-

vention: incidence, risk factors, and relationship to mortality. Am

J Med 1997;103(5):368–75.

11. Yeboah ED, Petrie A, Pead JL. Acute renal failure and open heart

surgery. Br Med J 1972;1(5797):415–8.

12. Conlon PJ et al. Acute renal failure following cardiac surgery.

Nephrol Dial Transplant 1999;14(5):1158–62.

13. Llopart T et al. Acute renal failure in open heart surgery. Ren Fail

1997;19(2):319–23.

14. Kellum JA. Acute kidney injury. Crit Care Med 2008;36(4

):S141–5.

15. Bellomo R et al. Acute renal failure – definition, outcome

measures, animal models, fluid therapy and information technol-

ogy needs: the Second International Consensus Conference of the

Acute Dialysis Quality Initiative (ADQI) Group. Crit Care

2004;8(4):R204–12.



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380

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16. Mehta RL et al. Acute kidney injury network: report of an

initiative to improve outcomes in acute kidney injury. Crit Care

2007;11(2):R31.

17. Vaidya VS, Ferguson MA, Bonventre JV. Biomarkers of acute

kidney injury. Annu Rev Pharmacol Toxicol 2008;48:463–93.

18. Bonventre JV. Pathophysiology of acute kidney injury: roles of

potential inhibitors of inflammation. Contrib Nephrol

2007;156:39–46.

19. Thurau K, Boylan JW. Acute renal success. The unexpected logic

of oliguria in acute renal failure. Am J Med 1976;61(3):308–15.

20. Bagshaw SM et al. A systematic review of urinary findings in

experimental septic acute renal failure. Crit Care Med

2007;35(6):1592–8.

21. Bagshaw SM, Langenberg C, Bellomo R. Urinary biochemistry

and microscopy in septic acute renal failure: a systematic review.

Am J Kidney Dis 2006;48(5):695–705.

22. Kellum JA. Prerenal azotemia: still a useful concept? Crit Care

Med 2007;35(6):1630–1.

23. Kellum JA et al. Developing a consensus classification system for

acute renal failure. Curr Opin Crit Care 2002;8(6):509–14.


24. Liano F, Pascual J. Epidemiology of acute renal failure: a

prospective, multicenter, community-based study. Madrid Acute

Renal Failure Study Group. Kidney Int 1996;50(3):811–8.

25. Brivet FG et al. Acute renal failure in intensive care units – causes,

outcome, and prognostic factors of hospital mortality; a prospec-

tive, multicenter study. French Study Group on Acute Renal

Failure. Crit Care Med 1996;24(2):192–8.

26. Uchino S et al. Acute renal failure in critically ill patients: a

multinational, multicenter study. JAMA 2005;294(7):813–8.

27. Dixon BS, Anderson RJ. Nonoliguric acute renal failure. Am J

Kidney Dis 1985;6(2):71–80.

28. Ympa YP et al. Has mortality from acute renal failure decreased?

A systematic review of the literature. Am J Med

2005;118(8):827–32.

29. Spiegel DM et al. Determinants of survival and recovery in acute

renal failure patients dialyzed in intensive-care units. Am J Nephrol

1991;11(1):44–7.



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