Nghiên cứu giá trị chẩn đoán của tiêu chuẩn KDIGO, RIFLE, AKIN, cystatin C huyết thanh và các yếu tố nguy cơ dự báo tổn thương thận cấp sau mổ tim mở (TT ANH)

M INISTRY OF EDUCATION & TRAINING

M INISTRY OF DEFENCE

108 INS TITUTE OF CLIN ICAL MED ICAL AND
PHARMACEUTICAL S CIENC ES

NGO DINH TRUNG

STUDY ON THE DIAGNOSTIC VALUE OF KDIGO,
RIFLE, AKIN CRITERIA, SERUM CYSTATIN C AND
RISK FACTORS FOR CARDIAC SURGERYASSOCIATED ACUTE KIDNEY INJURY
Specialty: Anesthes ia and Critical Care
Code: 62720122

SUMMARY OF MEDICAL DOCTORAL THESIS

Hanoi – 2020


This study is completed in
108 INSTITUTE OF CLINICAL MEDICAL AND
PHARMACEUTICAL SCIENCES

Supervisor: Assoc. Prof. PhD. Tran Duy Anh

Reviewer 1: ……………………………………………….

Reviewer 2: ……………………………………………….

Reviewer 3: ……………………………………………….

The thesis will be presented at Institute Council of 108 Institute of
Clinical Medical and Pharmaceutical Sciences at
hour
day
month
year
The thesis can be found at:
1. National library
2. Library of the Clinical Medicine Research Institute 108


1
INTRODUCTION
Acute kidney injury (AKI) is a syndrome characterized by the
rapid decline of renal function which leads to homeostatic imbalance.
In the past, the common term of this syndrome was acute renal
failure, and since 2004 it has been replaced by acute kidney injury,
and accompanied with some new diagnostic criteria such as KDIGO,
RIFLE and AKIN.
AKI can occur in many different kinds of patients, such as
infection, trauma, toxicity, surgery… with the incidence ranging from
1 to 80% according to the subjects and definitions applied. Especially,
in cardiac surgery, the AKI rate can be as high as 40% with the
mortality up to 60% in patients requiring renal replacement therapy
(RRT), compared with 2-8% in general cardiac surgery.
Therefore, early predicting and diagnosing is essential for effective
prevention of AKI. To accomplish it, we need first to identify the risk
factors, and then, use prediction scores to calculate the possibility of
AKI occurrence after surgery. Beside that, using some new biological
markers such as cystatin C, NGAL…which have been initially reported

of having ability to early diagnose AKI is also reasonable approach. In
Vietnam, there are only a few research on these issues. Therefore, we
carried out this study for 2 aims:
1. To evaluate the role of KDIGO, RIFLE, AKIN criteria, serum
cystatin C in diagnosing of AKI in the early period after open-heart
surgery
2. To determine the risk factors and the value of Cleveland Clinic,
AKICS and ACEF scores to predict AKI in the early period after openheart surgery


2
Practical significance and new contributions
In Vietnam and also in the world, cardiac surgery using
cardiopulmonary bypass is very popular. The advances in skills,
techniques and equipments have helped to improve the overall
outcomes. However, there have still been some complications, one of
them is AKI, which could lead to higher morbidity and mortality of
these patients. Therefore, early detect and prevent this complication is
very important.
New contributions of the thesis:
1. Applying new criteria, including KDIGO, RIFLE, AKIN, in
diagnosing AKI after cardiac surgery, and giving comparisons and
recommendations for using these criteria in clinica l practice.
2. Determining the value of serum cystatin C in diagnosing
cardiac surgery-associated acute kidney injury, and the possibility of
application in clinical practice
3. Determining the risk factors and the value of some risk scores
(Cleveland Clinic, AKICS and ACEF) in predicting AKI after cardiac
surgery, which could help to early predict, diagnose and so prevent
this complication.

Structure of the thesis
The dissertation has 122 pages, including 2 pages of Introduction,
35 pages of Overview, 21 pages of Subjects and Methods, 31 pages of
Results, 32 pages of Discussion, 2 pages of Conclusion, and 1 page of
Recommendation. There are 34 tables, 16 figures, 4 pictures with 155
references, including 6 in Vietnamese and 149 in English. The
published works related to the thesis, studying protocol and list of
participating subjects are also included.


3
Chapter 1
OVERVIEW
1.1. Anatomical and functional features of kidney
The structural and functional unit of kidney is nephron, which is
composed of a renal corpuscle and a renal tubule. The main function
of nephron is to filter out wastes and toxins from the blood, and return
needed molecules. The renal function is represented by Glomerular
filtration rate (GFR). In clinica l practice, creatinine clearance
rate (Ccr) is commonly used to evaluate the GFR.
1.2. Diagnostic criteria for acute kidney injury
For many years, acute renal failure used to be the term indicating
the rapid decline in renal function; however, there was no consensus
definition for this condition. Therefore, since 2004, the term acute
kidney injury has been proposed to replace “acute renal failure”,
accompanied with some newly developed definitions for AKI such as
RIFLE (2004), AKIN (2007) and KDIGO (2012).
According to the RIFLE criteria, AKI is defined as an increase of
serum creatinine (Scr) with 50%, corresponding to a decrease in GFR,
relative to baseline, of >25% or a urine output (UO) of <0.5 ml/kg per

h for >6h. The RIFLE classification considers three severity classes
of AKI (Risk, Injury and Failure), according to the variations in serum
creatinine and/or urine output, and two outcome classes (loss of
kidney function and end-stage kidney disease).
The AKIN classification is a later version of RIFLE: it only relies on
SCr and not on GFR changes; AKI is defined by the sudden decrease (in 48
h) of renal function, defined by an increase in absolute SCr of at least 26.5
μmol/L (0.3 mg/dl) or by a percentage increase in SCr ≥50% (1.5× baseline


4
value), or by a decrease in the UO (documented oliguria <0.5 ml/kg/h for
more than 6 h); Stage 1 corresponds to the risk class, but it also considers
an absolute increase in SCr ≥26.5 μmol/L (0.3 mg/dl); Stages 2 and 3
correspond to injury and failure classes, respectively; Stage 3 also considers
patients requiring RRT; the two outcome classes were removed from the
classification.
The KDIGO classification is a combination of RIFLE and AKIN.
Therefore, AKI has been defined as an increase in SCr ≥0.3 mg/dL (≥26.5
μmol/L) within 48 h; or an increase in SCr to ≥1.5 times baseline, which is
known or presumed to have occurred within the prior 7 days or a urine
volume of <0.5 mL/kg/h for 6 h. AKI has been staged in severity according
to the AKIN criteria, with a change is that, patients under 18 with a GFR
<35mL/min and patients with a serum creatinine >4.0mg/dL (absolute
value) were added to AKIN stage 3.
At present, three criteria above have been still evaluated to reach the
consensus in for practice and research.
1.3. Pathogenesis of acute kidney injury

The pathogenesis of cardiac surgery associated acute kidney injury

(CSA-AKI) is complex and multifactorial. It likely involved at least six
major injury pathways: 1). exogenous and endogenous toxins; 2).
metabolic factors; 3). ischemia and reperfusion; 4). neurohormonal
activation; 5). Inflammation; and 6). oxidative stress. These mechanisms
of injury are likely to be active at different times (pre, intra, and
postoperative) with different intensity and probably act synergistically.


5

1.4. Risk factors and prediction scores for AKI after cardiac surgery
1.4.1. Risk factos
Preoperative factors: age, heart failure, basal renal function,
anemia, diabetes, COPD, emergency, nephrotoxic drugs, contrast
agents, genetic…
Intraoperative factors: renal hypoperfusion, type of surgery,
cadiopulmonary bypass use (hemodilution, hypothermia, non-pulsatile
flow, inflammation, nephrotoxins, embolism).
Postoperative factors: low cardiac output, IABP, vasoactive agents,
nephrotoxic drugs, volume depletion, sepsis…
1.4.2. Prediction scores
Based on the risk factors above, some risk scores have been
developed to predict AKI after cardiac surgery, such as Cleveland
Clinic, STS, AKICS, ACEF… The aim of these models is to early
identify the patients who are at high risk of developing into cardiac
surgery associated acute kidney injury (CSA-AKI); this may
contribute to prevention and management of this complication.
These scores consists of different factors, for example, Cleveland
Clinic, STS, ACFE are based on preoperative risk factors; meanwhile
AKICS uses the factors of pre, intra, and postoperative periods. Until

now, although some different risk scores have been proposed, there
has been no consensus on applying these scores in predicting AKI
after cardiac surgery. In Vietnam, the research on this kind of model
has not been performed yet.
1.5. Biomarkers of AKI

Serum creatinin is now still the standard for diagnosing of AKI;
however the use of SCr as a marker of AKI has significant limitations.


6
SCr is a late marker of disease, and alterations are often not apparent
until 48–72 hours post-injury leading to missed early therapeutic
opportunities when treatments may be most effective. For the last
recent years, some new biomarkers have been studied, such as cystatin
C, Neutrophil Gelatinase Associated Lipocalin (NGAL), interleukin18, KIM-1, L-FABP… The initial results suggests that some of them
may help to early detection of AKI than the conventional one of
creatinin.
Cystatin C is a 120 amino acid nonglycosylated basic cysteine
protease inhibitor widely expressed by all nucleated cells in the body,
and is excreted to blood at constant concentration. One of significant
advantages of cystatin C is that The blood levels of cystatin C are not
significantly affected by age, gender, race, overall muscle mass;
inflammation or infection. Cystatin C is directly and freely filtered by
the glomerulus, reabsorbed completely, and is not secreted by the
tubule, and is considered an ideal marker for GFR and better than that
of serum creatinin.
Chapter 2
SUBJECTS AND METHODS
2.1. Subjects

The subjects were adult patients (over 18 years old) undergoing
open heart surgery in 108 Military Central Hospital from January
2015 to December 2017.
Exclusion criteria

- Surgery due to heart injury or massive pulmonary embolism
- Preoperative renal failure requiring RRT
- Preoperative Congenital kidney disease, Urinary Tract stone or
Kidney Stone Disease, Polycystic Kidney Disease…


7
- Patients who were using medications affecting creatinin excretion
(cimetidin, ranintidin, trimethoprim); drugs which interfere
with Jaffe's method (cephalotin, cephalozin, acid ascorbic…)
- Patients who died in the during the operation or right after that
unable to access the kidney function
- Patients and/or families did not consent to participate in
2.2. Methods
2.2.1. Study design: A descriptive, longitudinal combined with casecontrol study
2.2.2. Sample
Sample size: using formula required to estimate a proportion
n = Z2 1-α/2 p(1-p)/d2 ; in which, Z=1.96 for 95% CI, P is expected
true proportion = 36.1% (from the study of Howitt et al (2018); d is
desired precision = 6%. Result: n ≥ 247.
The study subjects were divided into 2 groups: AKI (case) and
non- AKI (control) after surgery
Sampling: all those patients that fulfilled the inclusion criteria
2.2.3. Research variables and conduction
Variables for objective 1

a. AKI diagnosing according to KDIGO, RIFLE and AKIN in the
early period after surgery
After the operation, serum creatinin (sCr) was measured at the
following times: arrival in ICU (T0), 12 hours (T1), 24h (T2), and 48h
(T3) after to evaluate the incidence and severity of AKI according to
three criteria (KDIGO, RIFLE and AKIN).
Variables included:
- The time point of AKI detection
- The AKI proportion and severity according to KDIGO


8
- Comparison of incidence and severity of AKI among KDIGO,
RIFLE and AKIN.
- Relation between AKI and ICU and postoperative hospital stay
- Relation between AKI and death
b. The diagnostic value of serum cystatin C
- Using KDIGO as the diagnostic criteria for AKI
- The serum level of cystatin C was evaluated postoperatively at 4
time points in coincidence with serum creatinin testing times.
- The level of cystatin C was compared between AKI and non-AKI
group.
- The correlation between serum cystatin C and creatinin level was
determined
- The area under the ROC curve ( AUC ) of creatinin and cystatin
C was defined to compare the performance in detecting AKI between
two biomarkers.
Variables for objective 2
Using KDIGO as the diagnostic criteria for AKI
a. Risk factors for AKI

Preoperative:
- Age, gender, body mass index (BMI); body surface area (BSA)
- Comorbidities
- The severity of heart failure based on NYHA classification
- Preoperative renal function (urea, serum creatinin, eGFR)
Intraoperative:
- Cardiopulmonary bypass time (minutes); aortic cross-clamping
time (minutes)
- The lowest body temperature (o C) and highest activated clotting
time (ACT) (second)


9
- The amount blood products (packed RBC, fresh frozen plasma,
plate let) infused during operation.
- Urine output, fluid balance
- Vasoactive agents used in operation
Postoperative:
- Central venous pressure ≥ 12cmH2 O
- Duration of vasoactive use >2 hours
- Numbers of vasoactive agents
- Requiring reopening of the chest
- Mechanical ventilation time > 24 hours
- Low cardiac output syndrome
- Some hematology, biochemistry and blood gas parameters
Using univariate analysis to determine the relation between the
variables with AKI; and then using multivariate analysis to define
independent risk factors to postoperative AKI.
b. Prediction scores for AKI
- Using 3 scores, including Cleveland Clinic, ACEF and AKICS.

- Cleveland Clinic and ACEF were calculated preoperatively,
meanwhile AKICS was used after surgery.
- Objectives of prediction: total AKI, AKI stage I, II, and III
(according to KDIGO criteria).
- AUC of each prediction, cut-off values, sensitivity and specificity
were calculated
Data analysis: using SPSS 20.0 software; some main statistical
analysis included uni and multivariate, correlation and area under
the ROC curve analysis.


10
Chapter 3
RESULTS
3.1. Characte ristics of the subjects
The study included 247 patients undergoing cardiac surgery using
cardiopulmonary bypass.
- Mean age: 53.32 ± 12.76 years old. Male: 59.9%.
- Type of surgery: valve 72.8%, coronary artery bypass grafting
(CABG) 9.7%; valve combined with CABG 1.6%...
- Severe heart failure (NYHA III-IV) accounted for 19.84%;
2.83% having an ejection fraction less than 40%. 40.91% having
systolic pulmonary artery pressure over 40mmHg.
- Preoperatively, the mean serum creatinin level was 80.47 ±
25.63µmol/L, and mean eGFR was 89.79±24.18ml/min/1.73m2 .
3.2. Diagnostic value of KDIGO, RIFLE, AKIN and serum cystatin C
3.2.1. Diagnosing AKI based on KDIGO, RIFLE and AKIN
- The postoperative AKI incidence, based on KDIGO criteria, was
48.58%, in which, stage I accounted for 73.33%, stage II 18.33% and
stage III 8.33%. Among the AKI patients, 6.67% needed renal

replacement therapy.
Table 3.8. Comparison of AKI incidence among KDIGO, RIFLE
and AKIN
Criteria

KDIGO(1)

RIFLE(2)

AKIN(3)

AKI n (%)

120(48.58%)

98(39.67%)

116(46.96%)

p

p1-2 = 0.04

p2-3 =0.10

p1-3 =0.71


11
- The AKI incidence, according to KDIGO, was higher than those

of AKIN and RIFLE (48.58% vs. 46.96% and 39.67% respectively).
Significant difference was seen between KDIGO and RIFLE (p<0,05)
- KDIGO helped to detect 22 AKI cases who were diagnosed by
RIFLE; and 4 cases more who not were diagnosed by AKIN.
Table 3.12. Relation between AKI and hospitals stays
Stage
ICU stay
(days)
Postoperative
stay (days)
Total hospital
stay (days)

Non-AKI

I

II

III

p

(n=127)

(n=88)

(n=22)

(n=10)

2,44±1,08

3,57±3,40

5,09±4,98 6,00±3,71 <0,001

14,02±7,57 16,86±8,62 20,36±10,37 27,90±12,5 <0,01
27,89±12,9 28,47±13,8 33,77±19,5 37,8±24,2 < 0,05

- The ICU and postoperative stay were longer in the AKI group than
those of non-AKI; and increased according to the severity of AKI
Table 3.13. Relation between AKI and mortality
AKI
Death

Non-AKI1

AKI2

Total

(n=127)

(n=120)

(n=247)

2 (1,57%)

9 (7,5%)

11 (4,45%)

p1-2
0,030

- The total mortality rate after surgery was 4.45%; in AKI group
was 7.5%, higher than that of non-AKI (p=0.03).
- The survival over time (for the first 30 days after surgery) was
also lower in the AKI group.
3.2.2. Diagnostic value of serum cystatin C


12
Table 3.14. Comparison of mean serum cystatin C levels among the
postoperative time points
Time points

Serum cystatin C (mg/L)

pt-test

AKI (n=120)

Non-AKI (n=127)

ICU arrival

0,939 ± 0,316

0,706±0,210

<0,001

12h

1,052 ±0,447

0,802±0,244

0,005

24h

1,183±0,564

0,802±0,229

<0,001

48h

1,202±0,515

0,788±0,208

<0,001

- At all time points after the operation, the serum cystatin C

concentrations in the AKI patients were much higher than those of nonAKI, and increased from T0 to T3.
- Also at all time points, there was a strong positive correlation
between serum creatinin and cystatin levels ( with r value was 0.54; 0.70;
0.83 and 0.77 respectively). The correlation between cystatin based GFR
and creatinin based GFR was the similar (r value was 0.56; 0.69; 0.74 and
0.74 respectively).
- At the time of T0 (ICU arrival): the AUC for diagnosing of AKI
of cystatin C was good (0.73), better than that of serum creatinin
(AUC 0.66).
- At the time of T2 (the second days after surgery), the AUC of
creatinin was higher than that of cystatin C ( 0.81 vs. 0.72, respectively
with p<0,001).
- At the time of T3 (the third day): diagnostic value of all three
parameters was good and equivalent (AUC of creatinin, cystatin C
was 0.80 and 0.78 respectively).


13
Table 3.15. Cut-off value and diagnostic strengths of serum cystatin
C at T0
Diagnotic

Cut-off

parameters
Cystatin C

(mg/L)

0.765

Youden

Se

Sp

PPV

NPV

index

(% )

(% )

(% )

(% )

0.404

80.35

61.29

71.4

69.0

- At the cut-off of 0.76mg/L, the sensitivity and specificity of serum
cystatin C in diagnosing AKI were 80.35% and 61.29% respectively.
- The negative and positive predictive values were relatively high.
3.3. Risk factors and prediction scores for AKI
3.3.1. Univariate and multivariate analysis of risk factors
Preoperative variables
- Age ≥ 65 (years) related to increase of AKI after surgery; on the
contrary, age < 40 contributed to decrease of AKI. No difference was
seen between two groups of AKI and Non-AKI in term of gender, BMI,
and BSA.
- The

comorbidities,

including

diabetes, hypertension and

Angiotensin converting enzyme inhibitors (ACE inhibitors) use had
relation to postoperative AKI (p<0,01).
- In terms of type of surgery, multiple valve surgery (>1valves),
coronary artery bypass grafting (CABG) and thoracic aorta surgery
were seen to have relation to increased AKI postoperatively.
- In terms of preoperative kidney function and some laboratory
tests, we found that, the eGFR less than 60ml/min/1.73m2 , serum
creatinin greater than 106µmol/L and serum glucose >7mmol/L were
more seen in AKI group.

14
Intraoperative variables
- Some factor was found to relate to AKI including CPB time ≥
120 minutes, aortic cross clamping time ≥ 60 minutes, packed red
blood cell infusion, frozen plasma infusion ≥ 2 units, lowest body
temperature <35o C và intraoperatively vasoactive use.
Postoperative variables
- Some factors were shown to be different between the 2 groups:
central venous pressure (CVP) ≥ 12cmH2 O, multiple vasoactive use,
low cardiac output syndrome, mechanical ventilation duration > 24
hours, serum lactate ≥ 4mmol/L and arterial blood pH <7.35.
The variables above were analyzed by logistic regression model to
define independent risk factors for AKI
Table 3.22. Multivariate analysis of risk factos for AKI
Variables

OR

95% CI

p

Age ≥ 65

1.72

0.59 – 4.97 > 0.05

Diabetes

5.07 1.02– 25.11 < 0.05

Hypertension

2.24

1.17 – 4.29 < 0.05

ACE inhibitors use

1.13

0.51 – 3.17 > 0.05

Preoperative blood glucose > 7mmol/L

1.47

0.61 – 3.58 > 0.05

Multiple valve surgery

2.57

1.41 – 4.67 < 0.01

Thoracic aortic surgery

5.36

1.08 – 6.49 < 0.05

CABG

1.81

0.92 – 5.13 > 0.05

Preoperative eGFR <60ml/min/1.73m2

2.20

1.02 – 3.81 < 0.05

Preoperative serum creatinin ≥ 106µmol/l 2.03

0.91 – 5.24 > 0.05


15
- The preoperative risk factors were preoperative eGFR <
60ml/min/1.73m2 , diabetes, hypertension, thoracic aortic surgery, and
multiple valve surgery
Table 3.23. Multivariate analysis of risk factors for AKI (continued)
Variables

OR

95% CI

p

CPB time ≥ 120 minutes

2.18

1.12 – 4.21

< 0.05

Aortic clamping time ≥ 60minutes

3.26

1.57 – 6.77

< 0.01

Frozen plasma infusion ≥ 2 units

1.14

0.41 – 3.21

> 0.05

Lowest body temperature <35o C

0.54

0.17 – 1.68

> 0.05

CVP ≥ 12cmH2O

2.01

1.16 – 3.49

< 0.05

Low cardiac output syndrome

3.74

1.34 – 7.59

< 0.05

Mechanical ventilation > 24 hours

3.63

1.35 – 9.76

< 0.05

Arterial blood pH <7.35

0.48

0.24 – 0.97

> 0.05

Serum lactate ≥ 4mmol/L

1.64

0.92 – 2.93

> 0.05

The intra and postoperative independent risk factors for AKI included
CPB time ≥ 120 minutes, aortic clamping time ≥ 60 minutes low
cardiac output syndrome, mechanical ventilation > 24 hours, and CVP
≥ 12cmH2 O,.
3.3.2. Prediction scores for AKI
- For the prediction of total AKI: the AUC of Cleveland Clinic and
AKICS scores was good (0.82 and 0.79 respectively). AUC of ACEF
was lower (0.63).
- For the prediction of mild AKI (stage I), the AUC of three scores
were all lower than those of total AKI.


16
- For the prediction of severe AKI (stage III), AUC of Cleveland
Clinic was the highest of 0.83, and then of AKICS (0,73). ACEF
shown no value to predict this stage of AKI.

From these results, we calculated the cut-off value and strength of
Cleveland Clinic and AKICS for the prediction of total AKI and AKI-III
Table 3.25. Prediction valued of Cleveland Clinic and AKICS for
AKI
Diagnotic

Cut-off

Youden
index

Se

Sp

PPV

NPV

(%)

(%)

(%)

(%)

3

0,49

82,5

63,7

73,4

85,5

3,3

0,50

80,8

69,2

70,1

78,1

5

0,56

80

76,7

54,6

78,1

7,6

0,41

70

78,0

58,9

87,2

parameters

Total AKI
Cleveland
Clinic
AKICS
AKI - III
Cleveland
Clinic
AKICS

- The cut-off values for total AKI and AKI-III of Cleveland Clinic
were 3 and 5; of AKICS were 3.3 and 7.6 , respectively. The
sensitivity and specificity were rather good.
Chapter 4

DISCUSSION
4.1. Diagnostic value of KDIGO, RIFLE, AKIN and se rum
cystatin C


17
4.1.1. Diagnosing AKI based on KDIGO, RIFLE and AKIN
a. Incidence of cardiac surgery-associated AKI
At present, in research and practice, some new criteria such as
KDIGO, RIFLE and AKIN are used to diagnose AKI. In this study,
we used KDIGO – the latest definition of AKI introduced in 2012.
The results were that, the proportion of AKI after cardiac surgery was
48,58%, in which the stage I accounted for 73.335, stage II was
18,33% and stage III was 8.33%. RRT was required in 6,67% of AKI
patients.
There are some differences in cardiac surgery-associated AKI
incidence among studies, both domestically and overseas. Comparing
with a research of Nguyen Quoc Kinh (2002), in which 47.57% of
cardiac surgery patients had renal dysfunction (defined as creatinin
clearance less than 60ml/min). This result was similar to ours,
however, there was a difference in diagnostic criteria applied.
Compared with some other studies in the world, the incidence of AKI
in our study was similar. In a study of Howitt (2018), this figure was
36.1%; meanwhile in another study of Machado (2014) on 2804
cardiac surgery patients, the incidence was 42% (stage I 35%, stage II
and III was much lower); 2% of AKI needed RRT.
b. Comparison of AKI definitions
Comparing KDIGO with RIFLE, the AKI patients detected by
KDIGO were significantly higher (48.58% versus 39.67%, p<0.05).
KDIGO helped to diagnose 22 AKI cases who still normal by RIFLE.

On the contrary, no patients were detected more by RIFLE. All of
these 22 patients met the requirement of absolute increase of creatinin
≥26.5µmol/L (in KDIGO) but not 1.5 times higher than the baseline. 2


18
patients, classified as Injury in RIFLE, but they had indication of
RRT, so were in stage III of KDIGO.
Comparing KDIGO with AKIN, the AKI proportion based on
KDIGO was higher (48.58% vs. 46.96%) but it was not significant
(p>0.05). Only 4 AKI patients were detected more by KDIGO than
AKIN; all these 4 cases had serum creatinin increase of 1.5 times
higher than the baseline but not greater than 26,5µmol/L. The reason
was that, KDIGO uses the lowest level of preoperative creatinin as the
baseline, this level was lower than that in 48 hours prior to operation
which used in AKIN.
Those results have shown that, the sensitivity of diagnosing AKI of
KDIGO was better than that of RIFLE and AKIN. This conclusion
was also seen in many studies in the world. The reason of it is that,
KDIGO was developed to combine both RIFLE and AKIN. At
present, KDIGO was recommended by Acute Dialysis Quality
Initiative Group to apply in cardiac surgery patients.
4.1.2. Diagnostic value of serum cystatin C
In this study, we found a significant difference of serum cystatin C
levels between postoperative AKI and non-AKI patients. At the time
point of ICU arrival, the concentration of cystatin C of AKI group was
0.93 mg/L compared with 0.70 of non-AKI one. At the following time,
cystatin C level rapidly increased in AKI patients, but still almost not
unchanged in non-AKI ones. This resutls could demonstrate the ability of
serum cystatin C in diagnosing AKI after cardiac surgery.

To compare the diagnostic value of cystatin C with serum creatinin,
we found that at the time of ICU arrival, the AUC of cystatin C was 0.73,
higher than that of serum creatinin (AUC 0.64). At the following time


19
points (12, 24, 48 hours after), when AKI considerably developed, AUC
of cystatin C and creatinin was equivalent. This result was similar to
some other studies.
The cut-off value of serum cystatin C for diagnosing AKI was
0.76ml/; with the diagnostic parameters were quite high. At present,
serum cystatin C test has been available in many healthcare facilities in
Vietnam; so convenient for applying in cardiac surgery and also other
patients.
4.2. Risk factors and prediction scores for AKI
4.2.1. Risk factors
Preoperative:
Aging has been considered to be a risk factor for all surgeries,
which contributes to higher severity and mortality. In our study, with
AKI after cardiac surgery, the factor of age ≥ 65 years old was found
to be different between AKI and non AKI groups (24.61% versus
11.02%, p = 0.006); but it had not shown significant difference in
multivariate analysis. This might be explained that, in our study
subjects, the number of over 65 year old patients was not much (just
43/247), so maybe did not show a significant result.
In investigating the comorbidities of AKI patients, we found that
the rate of diabetes in AKI group was higher than that of non AKI.
Moreover, AKI was seen to be the independent risk factor for AKI
(OR 5.078; 95% CI 1.027 – 25.11, p<0.05). This result was also seen
in other studies. Diabetic nephropathy is characterized by glomerular

hypertrophy, thickness of the basement, tubular and glomerular
membranes and accumulation of extracellular matrix in these
membranes that finally cause tubulointerstitial and glomerular fibrosis


20
and sclerosis. In diabetes patients, under condition of low ejection
fraction and cardiopulmonary bypass, will be at high risk for kidney
injury.
Hypertension have been proven to be an risk factor for AKI after
surgery. In this study, hypertension was seen to be a independent risk
for AKI (OR 2.24; 95%CI 1.17-4.29, p<0.05). The explanation was
that, in hypertension, there would be increased pulse pressure
reflexing increase in arterial stiffness and decrease in arterial
elastance. The hemodynamic disorders during operation, especially in
cardiac surgery will lead to reduction in blood flow and causing injury
to kidney.
One of preoperative risk factors for AKI was prior renal
dysfunction. In this study, using some indicators of renal function
such as blood urea, serum creatinin and GFR. The results were that,
serum creatinin greater than 106µmol/L and GFR lower than <
60ml/min/1.73m2 were different between AKI and non-AKI groups.
And also in multivariate analysis, preoperative GFR <
60ml/min/1,73m2 was defined as an independent factor of AKI. Some
domestic and abroad studies have also proven that; for example,
according to Nguyen Quoc Kinh, prior renal dysfunction (creatinin
clearance <60ml/minute) had OR of 9.67 as a risk factor for AKI after
open heart surgery.
Intraoperative:
In

almost

all

studies

about

AKI

in

cardiac

surgery,

cardiopulmonary byass has been proven to be the leading cause of
AKI. The mechanism is complicated with many factors which badly
affecting renal function, such as ischemia-reperfusion injury,


21
exogenous and endogenous agents, hemolysis, inflammatory
responses, oxidase stress… The strong relation between prolonged
cardiopulmonary bypass time with AKI was seen in many studies.
Also in our study, the aortic cross-clamping time over > 60 minutes
was a risk factor for AKI with OR = 3.26; and then was the
cardiopulmonary bypass time greater than 120 minutes (OR = 2.18).
The similar results were shown in a study of Nguyen Quoc Kinh,

cardiopulmonary bypass time greater than 120minutes and aortic
cross-clamping time over > 60 minutes had OR of 6.35 and 4.16
respectively.
Postoperative:
In this study, some postoperative variables such as CVP ≥
12cmH2 O, mechanical ventilation time >24hours and low cardiac
output was shown to be risk factors for AKI. In general, the
postoperative factors for AKI after cardiac surgery was similar to
those of AKI in other ICU patients, including vasoactive drug use,
unstable hemodynamics (shock or low cardiac output), hypovolemia,
nephrotoxic drugs and infection.
In conclusion, some AKI risk factors in this study included
preoperative
renal
dysfunction,
diabetes,
hypertension,
cardiopulmonary bypass time greater than 120minutes, aortic crossclamping time over > 60 minutes, postoperative CVP ≥ 12cmH2 O,
mechanical ventilation time >24hours and low cardiac output… Those
factors would help to predict the risk of AKI after cardiac surgery,
based on the prediction scores.
4.2.2. Prediction scores for AKI


22
a. Cleveland Clinic score
In our study, the predictive value of Cleveland Clinic was similar
to some other author’s that, AUC for total AKI was 0.82, for stage I
and III of AKI was 0.72 and 0.83 respectively. This result was
acceptable for a prediction score. The cut-off values for total AKI and

severe AKI were 3 and 5 respectively, with quite good sensitivity and
specificity. However, we also found differences between our subjects
and those of the original study of this score. In our study, the valve
surgery made up a high proportion (76%), and CABG was only 10%.
On the contrary, in the study used to developed Cleveland Clinic
score, CABG patients accounted up to 53%; on the other hand, some
comorbidities like COPD, IABP use... were more frequently seen. On
the other hand, there were some other difference such as gender, body
weight, baseline serum creatinin… Due to these differences, more
studies are needed in greater amount of patients to evaluate its
application in practice.
b. ACEF score
ACEF score consists of 3 variables : age, preoperative serum
creatinin and left ventricular ejection fraction. We found that the
prediction value of ACEF was rather low (AUC for total AKI was
0.63 and for stage III was 0.43. However, ACEF is simple and easy to
calculate, so maybe suitable for emergent situations. Still need more
studies to confirm the value of this score in the prediction of AKI after
cardiac surgery.
c. AKICS score
There are fewer scores consisting of pre, intra and postoperative
factors; one of them is AKICS whose aims to predict total AKI and


23
severe AKI. In our study, the prediction performance of AKICS was
quite high. For prediction of total AKI, the AUC was 0.79, just lower
than that of Cleveland Clinic. AUC for stage I was 0.66), and went up
to 0.73 for prediction of stage III. The cut-off values for total and
severe AKI were 3.3 and 7.6 respectively with acceptable sensitivity

and specificity. But, a limitation of this kind of score like AKICS is
that, despite of consisting of some factor in the whole pathology
process of AKI, the prediction is given just after surgery when AKI
may be already occur, so might affect the early prevention for AKI.
Therefore, more studies are needed to get the appropriate application
of this study in clinical practice.
CONCLUSIONS
1. The cardiac surgery – associated acute kidney injury
incidence diagnoses by KDIGO criteria was higher than that by
RIFLE and AKIN. Serum cystatin C might have good ability in
diagnosing AKI after open heart surgery:
- Using KDIGO criteria, the AKI incidence after cardiac surgery
was 48.58%, higher using RIFLE (39.67%) and AKIN (46.96%). The
stages of AKI according to KDIGO inluded: I (73.33%), II (18.33%)
and III (8.33%).
- The concentration of serum cystatin C had a strong and positive
correlation with serum creatinin after surgery. Serum cystatin C had a
quite good value in diagnosing AKI after cardiac surgery at the time
point of ICU arrival with AUC 0.73, compared with AUC 0.66 of
creatinin. The cut-off value of cystatin C was 0.76mg/L (sensitivity
80.35% and specificity 61,29%).
2. Main risk factors for AKI in cardiac surgery included
preoperative renal failure, prolonged cardiopulmonary bypass