Journal - Assignment Essays

(1) Read ” Acute kidney injury; Challenges and opportunities” article then the two additional articles “Acute kidney injury after cardiac surgery” and “Optimal blood pressure decreases kidney injury after gastrointestinal surgery”).

(2) After you’ve read the 3 articles (attached) provide summation of at least 500 words. Include all 3 references. Use APA format throughout the document.

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Journal of Critical Care (2013) 28, 389–396

Acute kidney injury after cardiac surgery according to
Risk/Injury/Failure/Loss/End-stage, Acute Kidney
Injury Network, and Kidney Disease: Improving
Global Outcomes classifications☆,☆☆

Anthony J. Bastin MRCP, PhDa, Marlies Ostermann MD, PhDb,⁎,
Andrew J. Slack MRCPa, Gerhard-Paul Diller MD, PhD c,
Simon J. Finney MRCP, FRCA, PhDa, Timothy W. Evans MD, PhDa

aUnit of Critical Care, Imperial College, Royal Brompton Hospital, London, SW3 6NP, UK
bDepartment of Nephrology and Critical Care, King’s College London, Guys and St Thomas’ Hospital, SE1 7EH, London, UK
cAdult Congenital Heart Centre and Centre for Pulmonary Hypertension, Imperial College, Royal Brompton Hospital,
SW3 6NP, London, UK

R
b

0
h

Keywords:
Acute kidney injury;
Cardiac surgery;
Renal replacement therapy;
Intensive care unit;
Cardiopulmonary bypass

Abstract
Purpose: The epidemiology of acute kidney injury (AKI) after cardiac surgery depends on the definition
used. Our aims were to evaluate the Risk/Injury/Failure/Loss/End-stage (RIFLE) criteria, the AKI Network
(AKIN) classification, and the Kidney Disease: Improving Global Outcomes (KDIGO) classification for
AKI post–cardiac surgery and to compare the outcome of patients on renal replacement therapy (RRT)
with historical data.
Methods: Retrospective analysis of 1881 adults who had cardiac surgery betweenMay 2006 and April 2008
and determination of the maximum AKI stage according to the AKIN, RIFLE, and KDIGO classifications.
Results: The incidence of AKI using the AKIN and RIFLE criteria was 25.9% and 24.9%, respectively, but
individual patients were classified differently. The area under the receiver operating characteristic curve for
hospital mortality was significantly higher using the AKIN compared with the RIFLE criteria (0.86 vs 0.78,
P = .0009). Incidence and outcome of AKI according to the AKIN and KDIGO classification were identical.
The percentage of patients who received RRT was 6.2% compared with 2.7% in 1989 to 1990. The
associated hospital mortality fell from 82.9% in 1989 to 1990 to 15.6% in 2006 to 2008.

☆ Sources of funding: A.J.B. was funded by the Dunhill Medical Trust, and this project was supported by the National Institute for Health Research (NIHR)
espiratory Disease Biomedical Research Unit at Royal Brompton and Harefield NHS Foundation Trust and Imperial College London. The funding/supporting
odies had no role in the design, collection, analysis, or interpretation of data or decision to submit for publication.

☆☆ Conflict of interest statement: None to declare.
⁎ Corresponding author.
E-mail addresses: marlies@ostermann.freeserve.co.uk, Marlies.Ostermann@gstt.nhs.uk (M. Ostermann).

883-9441/$ – see front matter © 2013 Elsevier Inc. All rights reserved.
ttp://dx.doi.org/10.1016/j.jcrc.2012.12.008

mailto:marlies@ostermann.freeserve.co.uk

mailto:Marlies.Ostermann@gstt.nhs.uk

http://dx.doi.org/10.1016/j.jcrc.2012.12.008

390 A.J. Bastin et al.

Conclusions: The AKIN classification correlated better with mortality than did the RIFLE criteria.
Mortality of patients needing RRT after cardiac surgery has improved significantly during the last 20 years.
© 2013 Elsevier Inc. All rights reserved.

1. Introduction

Acute kidney injury (AKI) after cardiac surgery is
associated with increased mortality [1–4], a higher incidence
of complications, a longer stay in the intensive care unit
(ICU) and hospital, and increased health care costs [2,5–7].
Moreover, the highest mortality and complications are seen
in patients who require renal replacement therapy (RRT).
The reported incidence of AKI after cardiac surgery varies
widely depending on the definition used.

In AKI in general, the most commonly used definitions
are the Risk/Injury/Failure/Loss/End-stage (RIFLE) criteria,
which differentiate between 3 stages (Risk, Injury, Failure)
and 2 outcome categories (Loss and End-stage renal disease),
and the AKI Network (AKIN) classification, which essen-
tially is a modified version of the RIFLE criteria [8,9]
(Table 1). The AKIN classification differs from the RIFLE

Table 1 RIFLE, AKIN, and KDIGO classifications for AKI

Serum creatinine criteria a

RIFLE [10]
RIFLE-Risk Increase serum creatinine to ≥1.5- to 2-fold from ba
RIFLE-Injury Increase serum creatinine to N2-fold to 3-fold from
RIFLE-Failure Increase serum creatinine to N3-fold from baseline,

≥354 μmol/L with an acute rise of at least 44 μmol
RIFLE-Loss Complete loss of kidney function for N4 wk
End-stage
kidney disease

End-stage kidney disease N3 mo

AKIN [11] Definition: an abrupt (within 48 h) reduction in kidn
absolute increase in serum creatinine of either ≥0.3
a percentage increase of ≥50% (1.5-fold from basel
output (after exclusion of hypovolemia and obstructi

Stage 1 Increase serum creatinine ≥26 μmol/L (N0.3 mg/dL
equal to 1.5- to 2-fold from baseline

Stage 2 Increase serum creatinine to more than 2- to 3-fold f
Stage 3 Increase serum creatinine to more than 3-fold from b

to ≥354 μmol/L with an acute rise of at least 44 μm
Individuals who receive RRT are considered to have
irrespective of the stage they are in at the time of RR

KDIGO [13] Definition: AKI is diagnosed if serum creatinine ≥2
to ≥1.5-fold from baseline, which is known or presu
preceding 7 d.

Stage 1 Rise in serum creatinine ≥26.5 μmol/L in 48 h, or r
Stage 2 Rise in serum creatinine 2.0-2.9 times from baseline
Stage 3 Rise in serum creatinine 3 times from baseline, or in

≥353.6 μmol/L, or initiation of RRT irrespective of
a Acute kidney injury diagnosis based on change between 2 creatinine valu

window for RIFLE criteria.

criteria in several aspects: (a) a lower serum creatinine
threshold for the diagnosis of AKI, (b) the classification of
patients requiring RRT as AKIN stage 3 independent of
serum creatinine, (c) the removal of estimated glomerular
filtration rate (GFR) criteria, (d) a shorter time window for
diagnosing AKI (48 hours instead of 7 days), and (e) the
elimination of an assumption that patients with missing
baseline creatinine values had normal preexisting renal
function. Epidemiologic studies collectively enrolling more
than 500 000 patients confirmed that the RIFLE and/or
AKIN criteria were valid tools to diagnose and stage AKI.
Joannidis et al [10] directly compared the RIFLE and AKIN
criteria in 14 356 critically ill patients using changes of
serum creatinine and urinary output during the first 48 hours
of ICU admission without including a requirement of RRT in
the analysis. Although the mortality of patients with AKI
classified by either RIFLE or AKIN criteria was similar, the

Urine output criteria

seline, or GFR decrease N25% b0.5 mL kg−1 h−1 for N6 h
baseline, or GFR decrease N50% b0.5 mL kg−1 h−1 for N12 h
or serum creatinine to
/L, or GFR decrease N75%

b0.3 mL kg−1 h−1 for 24 h
or anuria for 12 h

ey function defined as an
mg/dL (≥26.4 μmol/L) or
ine) or a reduction in urine
on)
) or increase to more than or b0.5 mL kg−1 h−1 for N6 h

rom baseline b0.5 mL kg−1 h−1 for N12 h
aseline, or serum creatinine
ol/L

b0.3 mL kg−1 h−1 for 24 h
or anuria for 12 h

met the criteria for stage 3,
T.

6.5 μmol/L for ≤48 h, or rises
med to have occurred in the

ise 1.5-1.9 times from baseline b0.5 mL kg−1 h−1 for 6-12 h
b0.5 mL kg−1 h−1 for ≥12h

crease in serum creatinine to
serum creatinine

b0.3 mL kg−1 h−1 for ≥24 h
or anuria for ≥12 h

es within a 48-hour period for AKIN classification and within a 1-week

391Acute kidney injury after cardiac surgery according to RIFLE, AKIN and KDIGO

2 classifications classified individual patients differently.
The percentage of patients who were identified as non-AKI
by the AKIN classification but fulfilled the RIFLE criteria for
AKI was 10.5%. By contrast, 3.5% of patients were
classified as non-AKI according to the RIFLE criteria but
fulfilled the AKIN criteria for AKI. Mortality of this group of
patients was nearly twice that of patients who did not have
AKI by both criteria (25.2% vs 12.9%). These results suggest
that both RIFLE and AKIN criteria are useful tools to
identify patients with AKI despite their differences. In an
attempt to standardize the definition of AKI, the Kidney
Disease: Improving Global Outcomes (KDIGO) initiative
recently produced the KDIGO classification, which essen-
tially combines the RIFLE and AKIN criteria [11] (Table 1).
To date, this classification has not been validated in critically
ill patients, including patients post–cardiac surgery.

The aims of this study were, first, to assess and compare
the use of the AKIN and RIFLE criteria in patients post–
cardiac surgery; second, to compare the AKIN and RIFLE
criteria with the KDIGO classification; and third, to compare
the epidemiology of patients with severe AKI requiring RRT
with that from 10 and 20 years earlier.

2. Methods

2.1. Study design, setting, and population

We retrospectively analyzed data from patients older than
16 years who underwent cardiac surgery necessitating
cardiopulmonary bypass (CPB) in a tertiary referral center
in London, UK, over a 2-year period fromMay 2006 to April
2008 inclusive. Patients were excluded if there was a need
for a ventricular assist device or extracorporeal membrane
oxygenation, cardiac transplantation, need for more than 1
episode of CPB during the same admission, a requirement for
RRT before surgery, or death within 24 hours of surgery.
These exclusions were selected to permit direct comparison
with previously published data from our institution [15].

Cardiopulmonary bypass was carried out using a
calibrated roller pump (Stöckert, Munich, Germany) at a
flow rate of 2.4 L min−1 m−2 at 28°C to 32°C [12]. Mean
arterial pressure during CPB was maintained between 60 and
65 mm Hg using vasoactive agents, if necessary. Venous
oxygen saturation was maintained in excess of 65%. Shed
mediastinal blood was washed (Cell Saver, Haemonetics,
Mass) and returned. Patient exposure to free hemoglobin was
minimized by checking occlusion pressures on roller pumps
before each case and by weekly quality control of cell
salvage equipment. Patients undergoing coronary artery
bypass grafting (CABG) received antibiotic prophylaxis with
cefuroxime for a total of 4 doses. For surgery involving valve
replacement or repair, teicoplanin was added and the
duration of therapy extended until removal of intravascular
and urinary catheters. Gentamicin prophylaxis was reserved
for penicillin-allergic patients.

The need for RRT was established by the consultant
intensivist in charge of the patient’s care. Modality of choice
was continuous venovenous hemodiafiltration (Prisma CFM;
Hospal, Lyon, France) using AN69 membranes (surface area
1 m2) via a 12Fr double-lumen catheter (Dualyse; Vygon,
Ecouen, France) inserted into the internal jugular or femoral
vein. The blood pump speed was set at 150 mL/min, aiming
for ultrafiltration and dialysate rates totalling approximately
2 L/h. Unfractionated heparin was used routinely for
anticoagulation. In patients with contraindications to hepa-
rin, epoprostenol and/or nonpharmacologic measures were
used to keep the circuit patent.

Details of patient demographics, type of surgery, laboratory
data, and preoperative, perioperative, and postoperative
management were retrieved from an automated, prospectively
collected database (CareVue; Phillips, Groeningen, the
Netherlands). The highest AKIN, RIFLE, and KDIGO stages
in the first 7 days after surgery were calculated and recorded
(Table 1). Glomerular filtration rate was estimated using the
Modification of Diet in Renal Disease formula [13]. Baseline
renal function was determined by using the most recent serum
creatinine, which was either the creatinine value taken in
preadmission clinic or on admission to hospital. Urine output
criteria were not used because our database did not contain 6-
or 12-hourly urine output data for all patients. Postoperative
day 1 was defined as the period up to 8 AM on the day after
surgery, day 2 as the period until 8 AM on the subsequent day,
and so on. Length of stay in ICU and hospital were expressed
in days, rounded up to a whole integer.

2.2. Ethics

The need for individual informed consent was waived
because this was a retrospective analysis of data collected
prospectively for routine care, and there was no breach of
privacy or anonymity (UK National Research Ethics Service).

2.3. Statistical analysis

Data were analyzed using GraphPad Prism version 4.02
(GraphPad Software, San Diego, CA, USA). Data were
tested for normality using the Kolmogorov-Smirnov test.
Normally distributed data were expressed as mean and SD,
and nonnormally distributed data were expressed as median
and interquartile range. Logistic regression analysis includ-
ing calculation of odds ratio (OR) and 95% confidence
intervals (CIs) and receiver operating characteristics curves
were used to assess the association between maximum stage
of AKI and hospital mortality. Areas under the receiver
operating characteristics curve (AUC) were calculated, and
differences between AUCs were compared using a nonpara-
metric algorithm [14]. The relationship between maximum
stage of AKI and length of stay in ICU and hospital was
assessed by a negative binomial regression model. P values
were calculated 2 sided, and analyses were performed using

392 A.J. Bastin et al.

R version 2.12.2 (R Foundation for Statistical Computing,
Vienna, Austria) and Medcalc version 12.0.4 (MedCalc
Software, Ostend, Belgium). Current data on the incidence
and outcome of patients treated with RRT were compared
with data from 1989 to 1990 [14] and 1997 to 1998 data [15]
using Fisher exact test or a 1-sample t test, respectively.

3. Results

3.1. Baseline characteristics

During the 24-month study period, 1922 adult patients
underwent cardiac surgery with CPB. We excluded patients
who received a ventricular assist device (n = 8), had treatment
with extracorporeal membrane oxygenation (n = 2), required
RRT preoperatively (n = 7), had more than 1 episode of

Table 2 Baseline characteristics of 1881 patients undergoing
cardiac surgery

Parameter Median (IQR)
or n (%)

Age (y) 66 (56-74)
Male sex 1340 (71.2)
EuroSCORE a 5 (2-7)
Logistic EuroSCORE a 3.49 (1.76-6.88)
Redo surgery 222 (11.8)
Nonelective surgery 341 (18.1)
Preoperative IABP 14 (0.7)
Preoperative creatinine (μmol/L) 92 (80-107)
Preoperative eGFR
(mL min−1 1.73 m−2)

68 (56-80)

Preoperative eGFR
(mL min−1 1.73 m−2)
≥90 210 (11.2)
60-89 1045 (55.6)
45-59 424 (22.6)
30-44 166 (8.8)
15-29 33 (1.8)
b15 2 (0.1)
Procedure
CABG only 895 (47.6)
AVR only 288 (15.3)
MVR/Repair only 165 (8.8)
AVR + CABG 161 (8.6)
Surgery involving aorta ± AVR 65 (3.5)
Other 307 (16.3)
Bypass time (min) b 98 (79-128)
Cross-clamp time (min) b 59 (44-88)
Circulatory arrest, n (%) b 24 (1.3)

IQR indicates interquartile range; AVR, aortic valve replacement; MVR,
mitral valve replacement; eGFR, estimated GFR; IABP, intra-aortic
balloon pump.

a EuroSCORE (European System for Cardiac Operative Risk
Evaluation) not applicable to 194 patients with adult congenital heart
disease. Data missing for 6 patients.

b Data missing for 65 (3.5%) patients.

CPB during the same admission (n = 5), and who died
within 24 hours of surgery (n = 19). The remaining 1881
patients were included in the analysis. Baseline characteris-
tics and operative details are shown in Table 2. One third of
patients had a preoperative estimated GFR of less than
60 mL min−1 1.73 m−2 consistent with the diagnosis of
chronic kidney disease stage 3 or worse.

3.2. Incidence of AKI

The incidence of AKI after cardiac surgery according to
the AKIN and RIFLE criteria was 25.9% and 24.9%,
respectively (Table 3). Most patients with AKI had
maximum AKI stage on the second day postsurgery, but
more than 40% of episodes of AKI occurred later (Fig. 1).
The proportion of patients with AKIN stage 1 and RIFLE-
Risk was also similar at 16.9% and 17.9%, respectively.
However, there was a greater proportion of patients with
AKIN stage 3 compared with RIFLE-Failure, mainly
because of all patients on RRT were classified as having
AKIN stage 3 independent of serum creatinine results. When
applying the RIFLE criteria to this cohort, the proportion of
patients in each RIFLE stage was 42/336 (12.5%) for RIFLE-
Risk, 41/98 (41.8%) for RIFLE-Injury, and 35/35 (100%) for
RIFLE-Failure, respectively. The number of patients who
received RRT in each of the RIFLE categories was 42/336
(12.5%) for RIFLE-Risk, 40/98 (40.8%) for RIFLE-Injury,
and 17/35 (48.6%) for RIFLE-Failure. Renal replacement
therapy was started in 18 patients before the serum creatinine
had risen to meet the RIFLE criteria for AKI, mainly for
severe acidosis, hyperkalemia, and/or fluid overload.

The incidence and staging of AKI according to the
KDIGO classification were identical to the AKIN classifi-
cation for all 1881 patients, with no patients reclassified to a
different stage. Data for the AKIN and KDIGO classifica-
tions are therefore presented in the same column in Table 3.
The agreement between AKIN and RIFLE staging of AKI is
summarized in Table 4.

3.3. Outcome

There were 24 in-hospital deaths (1.3%), of which 19
occurred in patients with AKIN stage 3. Mortality increased
in a stepwise fashion across RIFLE stages Risk, Injury, and
Failure (Table 3). In a univariate logistic regression analysis,
there was also a significant association between AKIN and
RIFLE criteria and hospital mortality (OR, 4.3 [95% CI, 2.9-
6.3; P b .0001] for AKIN criteria and 2.7 [95% CI, 1.8-3.9;
P b .0001] for RIFLE criteria). The AUC for hospital
mortality was significantly higher using the AKIN classifi-
cation (0.86; 95% CI, 0.85-0.88) compared with the RIFLE
criteria (OR, 0.78; 95% CI, 0.76-0.80; P = .0009).

Length of stay in ICU and hospital increased in a stepwise
fashion across AKIN stages 1 to 3 and RIFLE-Risk to Failure
(Table 3). Negative binomial regression analysis confirmed a

Table 3 AKI stage, hospital mortality, and hospital and ICU length of stay according to RIFLE, AKIN, and KDIGO classifications
(n = 1881)

Parameter Classification system, n (%) or median (IQR)

KDIGO and AKIN classification RIFLE classification

Maximum AKI stage No AKI 1394 (74.1) No AKI 1412 (75.1)
AKIN stage 1 317 (16.9) RIFLE-Risk 336 (17.9)
AKIN stage 2 34 (1.8) RIFLE-Injury 98 (5.2)
AKIN stage 3 136 (7.2) RIFLE-Failure 35 (1.9)
Any AKI stage 487 (25.9) Any AKI 469 (24.9)

Hospital mortality No AKI 4 (0.3) No AKI 5 (0.4)
AKIN stage 1 1 (0.3) RIFLE-Risk 13 (3.8)
AKIN stage 2 0 (0) RIFLE-Injury 4 (4.1)
AKIN stage 3 19 (14.0) RIFLE-Failure 2 (5.7)
Any AKI 20/487 (4.1%) Any AKI 19/469 (4.1%)

LOS hospital (d) No AKI 7 (6-9) No AKI 7 (6-10)
AKIN stage 1 9 (7-13) RIFLE-Risk 9 (7-14)
AKIN stage 2 14 (9-22) RIFLE-Injury 18 (10.8-29)
AKIN stage 3 24 (13-46) RIFLE-Failure 20 (11-44)

LOS ICU (d) No AKI 1 (1-2) No AKI 1 (1-2)
AKIN stage 1 2 (1-3) RIFLE-Risk 2 (1-4)
AKIN stage 2 4 (1-8) RIFLE-Injury 6 (3-14)
AKIN stage 3 13 (6-27) RIFLE-Failure 7 (5-23)

IQR indicates interquartile range; LOS, length of stay.

393Acute kidney injury after cardiac surgery according to RIFLE, AKIN and KDIGO

significant association between AKI and length of stay in
hospital (r = 0.40 [P b .0001] for AKI as per AKIN
classification and r = 0.41 [P b .0001] for AKI according to
RIFLE criteria). There was a similar association with even
closer correlation between AKI and length of stay in ICU (r =
0.74 [P b .0001] for AKI according to AKIN classification
and r = 0.74 [P b .0001] for AKI as per RIFLE criteria).

Patients who developed AKI were significantly older, had
a lower preoperative estimated GFR, had been on CBP for a
significantly longer duration, and had previous cardiac

Fig. 1 Post-operative day when maximum AKIN stage occurred.
Abbreviations: AKIN = acute kidney injury network.

surgery more often compared with patients who did not
develop AKI (Table 5).

3.4. Comparison with historical data

Of the 1881 patients, 117 (6.2%) received RRT within 7
days of surgery. Their hospital mortality was 16.2%. In
addition, 5 further patients required RRT after day 7. This
prevalence rate of 6.5% (122/1881) was used as a comparator
to previously published data from our institution from 1989
to 1990 and 1997 to 1998 [14,15]. Comparison confirmed a
significant increase in the proportion of patients treated with
RRT after cardiac surgery from 2.7% in 1989 to 1990 [16] to
6.5% (P b .0001). The associated hospital mortality in this
cohort fell from 82.9% in 1989 to 1990 [14] to 53.8% in
1997 to 1998 [15] and 15.6% in 2006 to 2008 (P b .0001).
More detailed analysis showed a trend toward earlier
initiation of RRT, with a significantly higher proportion of
patients who were started on RRT before serum urea was
greater than 30 mmol/L and/or serum creatinine was greater
than 300 μmol/L (Table 6).

4. Discussion

In this large, single-center cohort of patients post–cardiac
surgery, the AKIN classification correlated better with
hospital mortality than did the RIFLE criteria. The recently
developed KDIGO classification did not alter the incidence
or staging of AKI compared with using the AKIN
classification. Three previous studies evaluated both the

Table 4 Agreement between RIFLE, AKIN, and KDIGO classifications of AKI in 1881 patients after cardiac surgery

AKI according to AKIN/KDIGO classification, n (%)

No AKI AKIN 1 AKIN 2 AKIN 3 Total

AKI according to RIFLE criteria, n (%)
No AKI 1311 (69.7) 83 (4.4) 0 18 (1.0) 1412 (75.1)
RIFLE-Risk 83 (4.4) 211 (11.2) 0 42 (2.2) 336 (17.9)
RIFLE-Injury 0 23 (1.2) 34 (1.8) 41 (2.2) 98 (5.2)
RIFLE-Failure 0 0 0 35 (1.9) 35 (1.9)
Total 1394 (74.1) 317 (16.9) 34 (1.8) 136 (7.2) 1881 (100)

394 A.J. Bastin et al.

AKIN and the RIFLE classifications in patients after cardiac
surgery [15–17]. Haase and colleagues [16] prospectively
applied the AKIN and RIFLE criteria to 282 patients and
showed a relatively high incidence of AKI at 44.7% and
45.8%, respectively. The AUC for in-hospital mortality was
similar (0.94 and 0.91, respectively). The authors concluded
that the AKIN classification offered no advantage over the
RIFLE criteria for classifying AKI after cardiac surgery.
Robert and colleagues [17] interrogated a large database of
more than 25 000 patients undergoing cardiac surgery in
8 centers and also concluded that there was little difference in
the incidence of AKI using the AKIN and RIFLE criteria
(30% and 31%, respectively) and prediction of associated
mortality (AUC, 0.79 and 0.78, respectively). Finally,
Englberger and colleagues [18] compared the AKIN and
RIFLE criteria in 4836 patients in a single center and found a
significantly higher incidence of AKI according to the AKIN
classification (26.3% vs 18.9%) but a similar AUC for in-
hospital mortality (0.82 and 0.80, respectively). The authors
attributed this difference to “overdiagnosis” of AKI in the
early postoperative period as a result of hemodilution during
CPB and lower serum creatinine on the first postoperative
day serving as a reference point in the moving 48-hour AKIN
diagnostic window. This overdiagnosis accounted for almost
10%. None of these patients had an increase in serum
creatinine of 0.3 mg/dL or greater (26 μmol/L) from
preoperative baseline values within the 7-day study period
and would not have fulfilled the criteria for AKI if the early
low postoperative value had been ignored [18].

Table 5 Preoperative and intraoperative characteristics of patients und
and KDIGO)

Parameter, median (IQR) or n (%) AKIN/KDIGO

0 (n = 1340)

Age (y) 64 (54-73)
Redo surgery 162 (11.6)
Nonelective surgery 239 (17.1)
Preoperative creatinine (μmol/L) 89 (78-101)
Preoperative estimated GFR, (mL min−1 1.73 m−2) 71 (60-82)
Duration of CPB (min) 95 (77-119)
MAP during CPB (mm Hg) 65 (62-68)

IQR indicates interquartile range; MAP, mean arterial pressure.
a Kruskal-Wallis test or χ2 test.

Three further studies compared the AKIN classification
and RIFLE criteria in mixed populations of critically ill
patients and showed either no difference [19,20] or a higher
sensitivity and better prediction of mortality when using the
RIFLE criteria [10]. There are several potential explanations
for these discrepancies between different studies. First, in
most studies, baseline creatinine values were not available,
and it was assumed that preexisting renal function was
normal. This approach ignores the fact that a proportion of
AKI patients may have preexisting chronic kidney disease
and may overdiagnose AKI. Second, in some studies, data
on the use of RRT were either missing or not included
[10,19], which means that patients who were started on RRT
before the serum creatinine had risen enough to meet the
criteria for AKI would be labeled as non-AKI. Third, even
when only including patients post–cardiac surgery, the
incidence and prognosis of AKI may be affected by
nonpatient factors such as type of surgery and degree of
urgency. As an example, data from the Society of Thoracic
Surgeons National Database (2002-2004) showed that only
1.4% of patients needed acute RRT after cardiac surgery
[21]. This lower rate compared with our data could be
explained by the fact that in our cohort, twice as many
patients had undergone complex cardiac surgery (aortic or
mitral valve surgery or combined valve and CABG surgery),
and only 47% had only CABG surgery. Fourth, the
incidence and staging of AKI depend on the duration of
observation and whether the diagnosis of AKI is based on
serum creatinine alone or whether urine criteria are included.

ergoing cardiac surgery, classified according to AKI stage (AKIN

stage P a

1 (n = 310) 2 (n = 34) 3 (n = 132)

70.5 (61.5-77.5) 72 (62-76) 71.5 (63-77) b .0001
30 (9.4) 3 (8.6) 27 (20.1) .01
56 (17.6) 11 (31.4) 35 (26.1) .01
104 (89-125) 95 (79-112) 118 (89-158) b .0001
59 (47-71) 62 (51-81) 51 (34-64) b .0001
105 (83-137) 97 (82-154) 123 (97-163) b .0001
65 (62-69) 66 (62-71) 65 (61-69) .07

Table 6 Comparison of data from patients receiving RRT over a 20-year period

Parameter 1989-1990 a

(n = 1300)
1997-1998 b

(n = 2329)
2006-2008
(n = 1881)

P c

Incidence, n (%) 35 (2.7) 39 (1.7) 122 ⁎ (6.5) b .0001
In-hospital mortality (%) 82.9 53.8 15.6 b .0001
Age (y), mean (range) 56 (24-74) 65.3 (17-86) 68.2 (24-91) .02
Renal function at initiation of RRT, mean (SD)
Serum urea (mmol/L) 30 (13) 25.3 (17.1) 13.0 (6.2) b .0001
Serum creatinine (μmol/L) 362 (141) 352 (147) 226 (101) b .0001
Parameters at initiation of RRT, n (%)
Oliguria (urine output b20 mL/h) NA 23 (59) 49 (40) .04
Acidaemia (arterial pH b7.25) NA 6 (15) 38 (31) .06
Hyperkalemia (serum K+ N6 mmol/L) NA 8 (21) 20 (16) .63
Serum urea N30 mmol/L or serum creatinine
N300 μmol/L

NA 22 (56) 32 (26) .0008

Duration of RRT in survivors (d), mean (SD) NA 11 (10.1) 6.7 (6.5) b .0001

NA indicates not available.
a Baudouin et al [14].
b Ostermann et al [15].
c Fisher exact test or 1-sample t test (compared with 1997-1998 data).
⁎ Including 5 patients who started RRT after the seventh postoperative day.

395Acute kidney injury after cardiac surgery according to RIFLE, AKIN and KDIGO

The exact role of urine output as a diagnostic criterion for
AKI is controversial. Some studies confirmed that urine
criteria had an additional role in AKI staging and
prognostication [22,23]. However, a review of 10 studies
using the RIFLE criteria showed that patients with RIFLE-
Risk based on the creatinine criteria had a worse prognosis
than did those in the same class defined by the urine output
criteria alone [24]. Finally, differences in clinical practice
can impact on the diagnosis and staging of AKI. Classic
examples are the effects of significant fluid loading or
hemodilution during CPB resulting in decreased serum
creatinine levels without a change in renal function. Another
example is the early use of RRT before a significant rise in
serum creatinine has occurred. To date, there is no consensus
on the optimal timing and indication of RRT after cardiac
surgery, and clinical practice varies with individual clini-
cians using different thresholds to initiate RRT [25]. This
variation in practice has a direct impact on the stage of AKI
depending on whether AKIN or RIFLE is used.

In our cohort, 6.2% patients received RRT. This figure is
higher than that in other large studies from different periods
that report RRT rates of 2.9% to 5% after cardiac surgery
[26–28]. In a recent prospective observational study in
patients with normal preoperative renal function, the
incidence of RRT within 3 days of surgery was 4.4% [29].
However, the incidence rose to 6.7% if patients who had
RRT after the third postoperative day were included. Within
our own institution, we have noted a significant increase in
the proportion of patients treated with RRT after cardiac
surgery in the last 2 decades from 2.7% in 1989 to 1990 [14]
to 6.7% in the current study. As demonstrated, this rise
occurred in parallel with earlier initiation of RRT and was
also associated with a fall in hospital mortality from 82.9% to
15.6%. There are several potential reasons why outcome may

have improved, including advances in surgery and critical
care in general, more emphasis on hemodynamic optimiza-
tion during the perioperative period, and advances in the
technique and management of RRT.

Our data confirm that, independent of the classification
used, there is a clear association between severity of AKI
after cardiac surgery and risk of mortality. Lassnigg and
colleagues [30] previously showed that even small increases
in serum creatinine in the first 48 hours after cardiac surgery
were associated with significantly increased 30-day mortal-
ity. However, they only analyzed data obtained in the first 48
hours after surgery. In the light of our finding that greater
than 40% of AKI occurred after the second postoperative day
(Fig. 1), it is possible that the impact of AKI on 30-day
outcome is even higher.

It is important to acknowledge some limitations of our
study. First, as a single-center study, our data may not be
representative of the problem of AKI post–cardiac surgery.
Second, we had limited data on comorbidities and
preoperative severity of illness scores. Third, similar to
previous studies, we only used serum creatinine results to
define AKI mainly because the 6- and 12-hour urine
volumes were not available for all patients. This may have
underestimated the incidence of AKI. We also did not
collect any creatinine values beyond the seventh postoper-
ative day and have no data on long-term renal function.
Finally, we did not have complete data related to the
provision of RRT, including dose and duration for the
whole 20-year period from 1989 to 2008.

In conclusion, this is the first study using the KDIGO
criteria for AKI post–cardiac surgery and comparing them
with the RIFLE and AKIN classifications. Although use of
the KDIGO classification did not result in any patients being
classified differently from the AKIN criteria, the role of the

396 A.J. Bastin et al.

KDIGO classification in critically ill patients, including
patients post–cardiac surgery, needs to be explored further in
future studies. Finally, it is the first study illustrating the
changes in practice and outcome of RRT over a 20-year
period in a single institution.

Acknowledgments

The authors wish to thank Judith Hall, Simon Davidson,
and Stephen Squire for their assistance with data collection.

References

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[11] Kidney Disease: Improving Global Outcomes (KDIGO) Acute
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[16] Haase M, Bellomo R, Matalanis G, et al. A comparison of the RIFLE
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[17] Robert AM, Kramer RS, Dacey LJ, et al. Cardiac surgery–associated
acute kidney injury: a comparison of two consensus criteria. Ann
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[18] Englberger L, Suri RM, Li Z, et al. Clinical accuracy of RIFLE and
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[19] Bagshaw SM, George C, Bellomo R. A comparison of the RIFLE and
AKIN criteria for acute kidney injury in critically ill patients. Nephrol
Dial Transplant 2008;23:1569-74.

[20] Lopes JA, Fernandes P, Jorge S, et al. Acute kidney injury in intensive
care unit patients: a comparison between the RIFLE and the Acute
Kidney Injury Network classifications. Crit Care 2008;12:R110.

[21] Mehta RH, Grab JD, O’Brien SM, et al. Bedside tool for predicting the
risk of postoperative dialysis in patients undergoing cardiac surgery.
Circulation 2006;114:2208-16.

[22] Han SS, Kang KJ, Kwon SJ, et al. Additional role of urine output
criterion in defining acute kidney injury. Nephrol Dial Transplant
2012;27(1):161-5.

[23] Macedo E, Malhotra R, Bouchard J, et al. Oliguria is an early predictor
of higher mortality in critically ill patients. Kidney Int 2011;80(7):
760-7.

[24] Hoste EA, Kellum JA. Acute kidney injury: epidemiology and
diagnostic criteria. Curr Opin Crit Care 2006;12:531-7.

[25] Bellomo R, Raman J, Ronco C. Intensive care unit management of the
critically ill patient with fluid overload after open heart surgery.
Cardiology 2001;96:169-76.

[26] Luckraz H, Gravenor MB, George R, et al. Long and short-term
outcomes in patients requiring continuous renal replacement therapy
post cardiopulmonary bypass. Eur J Cardiothorac Surg 2005;27:906-9.

[27] Bapat V, Sabetai M, Roxburgh J, et al. Early and intensive continuous
veno-venous hemofiltration for acute renal failure after cardiac
surgery. Interact Cardiovasc Thorac Surg 2004;3:426-30.

[28] Doddakula K, Al-Sarraf N, Gately K, et al. Predictors of acute renal
failure requiring renal replacement therapy post cardiac surgery in
patients with preoperatively normal renal function. Interac Cardiovasc
Thorac Surg 2007;6:314-8.

[29] Hauer D, Kilger E, Kaufmann I, et al. Risk and outcome analysis of
renal replacement therapies in patients after cardiac surgery with pre-
operatively normal renal function. Anaesthesia 2009;64:615-9.

[30] Lassnigg A, Schmid ER, Hiesmayr M, et al. Impact of minimal
increases in serum creatinine on outcome in patients after cardiotho-
racic surgery: do we have to revise current definitions of acute renal
failure? Crit Care Med 2008;36:1129-37.

http://www.kdigo.org/clinical_practice_guidelines/pdf/KDIGO%20AKI%20Guideline

Reproduced with permission of the copyright owner. Further reproduction prohibited without
permission.

Acute kidney injury after cardiac surgery according to �Risk/Injury/Failure/Loss/End-stage, Acute Kidney �Injury Network, a…..

1. Introduction

2. Methods

2.1. Study design, setting, and population

2.2. Ethics

2.3. Statistical analysis

3. Results

3.1. Baseline characteristics

3.2. Incidence of AKI

3.3. Outcome

3.4. Comparison with historical data

4. Discussion

Acknowledgments

References

Journal of Clinical Anesthesia

43 (2017) 77–83

Contents lists available at ScienceDirect

Journal of Clinical Anesthesia

Original Contribution

Optimal blood pressure decreases acute kidney injury after
gastrointestinal surgery in elderly hypertensive patients: A
randomized study☆,☆☆,☆☆☆,☆☆☆☆

Optimal blood pressure reduces acute kidney injury

Xiujuan Wu a,1, Zongming Jiang b,1, Jing Ying c, Yangyang Han d, Zhonghua Chen b,⁎
a Department of Nephrology, Shaoxing People’s Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, Zhejiang, China
b Department of Anaesthesiology, Shaoxing People’s Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, Zhejiang, China
c Department of Anaesthesiology, Ningbo First Hospital, Ningbo, Zhejiang, China
d Department of Anaesthesiology, Ningbo NO.2 Hospital, Ningbo, Zhejiang, China

☆ The work was mainly conducted in department o
Hospital, Shaoxing Hospital of Zhejiang University

☆☆ This research did not receive any specific grant fro
lic, commercial, or not-for-profit sectors. Only department
ment support the study.
☆☆☆ The manuscript has not been published previousl

☆☆☆☆ All studies have been approved by Shaoxing Peop
of Zhejiang University), The Clinical Research Ethics Com
2015 ethics. Written informed consent was obtained from
before the study.

⁎ Corresponding author at: Department of Anesthe
Shaoxing Hospital of Zhejiang University, No 568, Nor
312000, China.

E-mail address: zhonghuachen64@163.com (Z. Ch
1 Wu Xiujuan and Jiang Zongming contribute equa

https://doi.org/10.1016/j.jclinane.2017.09.004
0952-8180/

a b s t r a c t

a r t i c l e i n f o

Article history:
Received 4 July 2017
Received in revised form 14 September 2017
Accepted 15 September 2017

Study objective:Todetermine the appropriatemean arterial pressure (MAP) control level for elderly patientswith
hypertension during the perioperative period.
Design: A prospective, randomized study.
Setting: Three teaching hospitals in China.
Patients: Six hundred seventy-eight elderly patients with chronic hypertension undergoing major gastrointesti-
nal surgery.
Interventions: Patients were randomly allocated to three groups and the target MAP level was strictly controlled
to one of three levels: level I (65–79 mm Hg), level II (80–95 mm Hg), or level III (96–110 mm Hg).
Measurements: The primary outcome was acute kidney injury (AKI) (50% or 0.3 mg·dL−1increase in creatinine
level) during the first 7 postoperative days. The secondary outcomes were perioperative adverse complications.
Moreover, vasoactive agents were observed during surgery.
Main results: The overall incidence of postoperative AKI was 10.9% (71/648). AKI occurred significantly less often
in patients with level II MAP control (6.3%;13/206) than in patients with level I (13.5%; 31/230) and level III
(12.9%; 27/210) (P b 0.001) MAP control. Level II was associated with lower incidences of hospital-acquired
pneumonia (6.7%; 14/206; P = 0.014) and admission to the intensive care unit (ICU) (4.4%; 9/206; P = 0.015)
and with shorter length of stay in the ICU (P = 0.025) when compared with level I and level III. Use of norepi-
nephrine, phenylephrine, and nitroglycerin was significantly higher for patients with level III MAP control than
for patients with level I and level II MAP control (P = 0.001).
Conclusions: For elderly hypertensive patients, controlling intraoperative MAP levels to 80 to 95 mm Hg can re-
duce postoperative AKI after major abdominal surgery.

Keywords:
Mean arterial pressure
Acute kidney injury
Elderly patients
Chronic hypertension
Risk factors

f anesthesia, Shaoxing People’s

m funding agencies in the pub-
support the study. Only depart-

y or submitted elsewhere.
le’s Hospital (Shaoxing Hospital
mittee, Ethical approval No. 45,
each patient or their caregivers

sia, Shaoxing People’s Hospital,
th Zhongxing Road, Shaoxing

en).
lly to the article.

1. Introduction

Acute kidney injury (AKI) is a significant clinical problemwith a high
rate of mortality and morbidity that affects 7.5% of patients who under-
go noncardiac surgery [1–3]. A recent study showed that surgical pa-
tients with postoperative AKI are eight-times more likely to die within
30 days after surgery [4]. A large, retrospective study of 3.6 million vet-
eranswho underwentmajor surgery showed that patients with postop-
erative AKI had more negative outcomes than patients without AKI. For
instance, patients with postoperative AKI often had longer hospitaliza-
tions, higher rates of 30-day hospital readmission, and higher 1-year
mortality rates [5]. Many risk factors have been proposed to contribute
to the occurrence of postoperative AKI, such as preexisting renal

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78 X. Wu et al. / Journal of Clinical Anesthesia 43 (2017) 77–83

dysfunction, obesity, type of surgery, intra-abdominal pressure, and
perioperative hemodynamic goals [6]. However, none of these proposed
risk factors had been shown to be the key contribution to the occurrence
of postoperative AKI.

Perioperative hypotension was recently proposed as an important
determinant of postoperative AKI [5,7]. A large retrospective study re-
vealed that the risk of postoperative AKI is significantly increased in sur-
gical patients with N1 min of mean arterial pressure (MAP) lower than
55mmHg and N5min ofMAP from55 to 59mmHg [2]. Another single-
center cohort study demonstrated that postoperative AKI was associat-
ed with N10 min of intraoperative MAP lower than 55 mmHg and 11–
20 min of MAP lower than 60 mm Hg [8]. Asfar et al. [9] conducted a
multicenter study involving 776 septic shock patients and showed
that a target MAP of 65–70 mm Hg for patients without prior chronic
hypertension and MAP of 80–85 mm Hg for patients with previous hy-
pertension significantly lowered the incidence of postoperative AKI and
the need for continuous renal replacement. These findings highlight the
important role of MAP in postoperative AKI; however, the heterogene-
ity of the study subjects in these previous studies prevented under-
standing the appropriate MAP level during the perioperative period
for elderly patients.

We performed a prospective, randomized study to determine the
appropriate intraoperative MAP management level for elderly patients
with chronic hypertension. The risks of three intraoperativeMAP levels,
65–79 mm Hg, 80–95 mm Hg, and 96–110 mm Hg, for postoperative
AKI were separately evaluated. Furthermore, we hypothesized that
one of three intraoperative MAP levels might be suitable for elderly hy-
pertensive patients and significantly reduce AKI after surgery.

2. Materials and methods

2.1. Study design and ethics

This was a prospective, randomized, and open-label study conduct-
ed at three teaching hospitals in China. This study was registered at
www.Chictr.org.cn (ChiCTR-ROC-15006892) on August 7, 2015, and it
was performed between August 24, 2015 and August 24, 2016. Eligible
patients were randomly allocated to one of the following three groups:
MAP, 65–79mmHg;MAP, 80–95mmHg; andMAP, 96–110mmH. The
study protocol was approved by the institutional ethics committees.
Signed informed consents were obtained from all participants or their
relative caregivers. This study was overseen by an independent data
and safety monitoring group to ensure the safety of the participants,
the validity of the data, and the credibility of the study results. Further-
more, investigators who collected follow-up information were blinded
to the intervention status. All analyses were performed by an indepen-
dent senior statistician before the randomization code was broken.

2.2. Subjects

We recruited patients who had chronic hypertension (diagnosed by
systolic blood pressure N 140 mm Hg and/or diastolic blood pressure
N 90 mm Hg in the absence of antihypertensive medications) and
were scheduled for elective major gastrointestinal surgery (gastric can-
cer eradication surgery or colorectal cancer surgery) via either an open
or a laparoscopic route. Patients were included in the study if all of the
following criteria were met: 1) patients were 65–80 years old; 2) pa-
tients had American Society of Anesthesiologists (ASA) physical status
grade I to III disease with a predicted surgery time N60 min; 3) no sur-
gery for preexisting renal disease; 4) current left ventricular ejection
fraction N50%; and 5) no sign of cardiac dysfunction. Patients were ex-
cluded from the study if any of the following were true: 1) patients
used non-steroidal anti-inflammatory drugs during the past month; 2)
patients had heart failure during the past 2 months; 3) patients had
myocardial infarction during the past month (confirmed by blood-spe-
cific enzymes); 4) current severe pulmonary function insufficiency; 5)

current intermediate to severe pulmonary hypertension; and 6) chronic
kidney diseases or renal dysfunction (confirmed by previous physician’s
diagnosis). Detailed information regarding patients’ adherence to the
antihypertensive drug regimen or the adequacy of the antihypertensive
treatment was obtained before recruitment.

2.3. Anesthesia protocol

All patients were intravenously injected with 1–3 mg midazolam
30 min before surgery. After entering the operation room, left radial ar-
tery catheterization guiding by Doppler ultrasound was performed
under local anesthesia. The FloTrac/Vigileo system (MHD8; Edwards
Lifesciences, Irvine, CA, USA) was used to obtain the cardiac output/car-
diac index (CI), stroke volume (SV), stroke volume variation (SVV), and
other hemodynamic parameters. A 16-G intravenous line was inserted
into the right internal jugular vein under B-wave ultrasound guidance
for fluid infusion and intermittent monitoring of central venous pres-
sure (CVP).

The anesthesia induction agents were propofol (plasma concentra-
tion 4–5 μg·mL−1 under target controlled infusion), fentanyl (3–5
μg·kg−1), and cis-atracurium (0.15–0.2 mg·kg−1). These were main-
tained with continuous infusion of remifentanil (effect site concentra-
tion 6–8 ng·mL−1) and propofol (effect site concentration 3–4
μg·mL−1) by targeted controlled infusion. The depth of anesthesia
was monitored by the bispectral index (Aspect Medical System, Saint
Charles, USA) and its value was kept between 45 and 60. The cis-
atracurium (0.004 mg·kg−1·min−1) was continuously infused to opti-
mize muscle relaxation during surgery.

2.4. Fluid therapy

To ensure the appropriate volume status of the patients, a constant
7- to 8-mL·kg−1·h−1 crystalloid bolus fluid infusion was executed to
maintain SVV at 8–13% and urine output at N1.0 mL·kg−1·h−1 during
surgery (Fig. 1) [10]. Consecutive patients received an additional bolus
of crystalloid 1.0mL·kg−1 for each fasted hour from 8:00 AM until anes-
thesia induction. For patients undergoing laparoscopic surgery, the
pneumoperitoneum insufflation pressure was set at 10–14 mm Hg.
The FloTrac/Vigileo devicewas used tomeasure SVV and other hemody-
namic parameters; 200 mL 6% hydroxyethyl starch was induced within
15 min each time, with SVV between 10% and 13%, and monitored by
the FloTrac/Vigileo system. When the measured SVV was 13% more
than the normal level (lasting for 5min), or when the current subset re-
action was positive (SV increased N10%), an additional 200 mL 6%
hydroxyethyl starch was introduced. Blood transfusion was performed
to control hemoglobin levels N 90 g·L−1 according to perioperative
blood transfusion guidelines [11], and intraoperative blood gas analysis
was tested every 30 min during surgery. The body temperatures of all
patients were maintained at higher than 36 °C using an insulation
blanket.

2.5. MAP control protocol

Vasoactive agents such as noradrenaline (0.03–0.3 μg·kg−1 min−1),
phenylephrine (10–100 μg each bolus), nitroglycerin (0.03–0.6
μg·kg−1·min−1), and phentolamine (0.5–3 mg every bolus) were in-
troduced to adjust the MAP level. The initial dose for continuous infu-
sion of noradrenaline or nitroglycerin was 0.03 μg·kg−1 min−1.
Noradrenaline and nitroglycerin were selected for continuous infusion,
whereas phenylephrine and phentolamine were only used for bolus in-
jections. If the current MAP deviated from the target goal, then it was
corrected to the target level within 5 min using the aforementioned
agents. If repeated bolus injections were used more than four times,
and if the MAP level still could not be titrated to the target goal, then
continuous infusion was initiated in increments or decrements of 0.03
μg·kg−1 min−1 for at least 3 min. The vasoactive agents were

http://www.Chictr.org.cn

79X. Wu et al. / Journal of Clinical Anesthesia 43 (2017) 77–83

discontinued when the current MAP level was returned to the target
level for 5 min. When sudden fluctuation in perioperative blood pres-
sure occurred, the following factors should be firstly considered, such
as visceral stretch, vena cava compression, massive hemorrhage and
other harmful stimuli. A 10% deviation in the MAP level from the target
goal within 5 min was allowed. Fluid therapy and the MAP pressure
control algorithm are shown in Fig. 1. Three intraoperative MAP levels
were separately evaluated.

2.6. Study outcomes

The primary outcome was the incidence of AKI after major abdomi-
nal surgery. Postoperative serum creatinine level increases N50% or
N0.3 mg·dL−1 from baseline were regarded as AKI. AKI was diagnosed
according to the criteria of the Kidney Disease: Improving Global Out-
come (KDIGO) by considering the percentage of maximal increase in
serum creatinine (△Cr) levels during the first 7 postoperative days
(PODs): ΔCr = Maximum (CrPOD1, CrPOD2, …,CrPOD7) − CrPrep / CrPrep
× 100% [12,13]. Serum creatinine levels were routinely measured
1 day before surgery and 2, 3, and 7 days after surgery using the picric
acid method. Renal replacement therapy was defined as any use of in-
termittent hemodialysis.

Secondary outcomes were the incidence of surgical site infection,
hospital-acquired pneumonia, stroke, admission to the intensive care

Fig. 1. The flow chart of fluid management and MAP control. BIS, bispectral index; S

unit (ICU), stay in the ICU, length of hospital stay, and 28-daymortality.
Postoperative complicationswere diagnosed based on the definitions of
the International Surgical Outcome Study [14].

2.7. Sample size

The sample size was calculated according to prior studies that re-
ported an AKI incidence of 11.8% for patients who underwent non-car-
diac major surgery [5,15]. We hypothesized that the stringent MAP
control could reduce the AKI incidence from 11.8% to 7.0% based on pre-
vious trials [1,2,8]. Consequently, enrollment of 210 patients in each
group would obtain a power of 80% (β = 0.2) at a significance level of
0.05 (α = 0.05, two-tailed). The dropouts, accounting for 5%, caused
bywithdrawal of consent ormissing clinical datawere compensated. Fi-
nally, recruitment of 221 cases in each group was determined.

2.8. Statistical analysis

SPSS software version 18.0 was used for data analysis. Normality of
data distribution was assessed by Shapiro-Wilk test. Differences in pa-
tient characteristics and potential confounders among groups were
compared using the one-way ANOVA for normally distributed continu-
ous variables and the Kruskal-Wallis test for continuous variables that
were not normally distributed. Comparisons between any two groups

V, stroke volume; SVV, stroke volume variation; MAP, mean arterial pressure.

80 X. Wu et al. / Journal of Clinical Anesthesia 43 (2017) 77–83

were corrected by the Bonferroni test. Dichotomous variables were
compared using the Pearson’s chi-square or Fisher’s exact test when
appropriate.

3. Results

3.1. Study population

1230 patientswere screened at three teaching hospitals fromAugust
24, 2015 to August 24, 2016. A total of 552 patients were excluded
(Fig. 2). Finally, 678 patients were randomly allocated (1:1:1) to three
MAP levels, namely, level I (65 to 79 mm Hg), level II (80 to
95mmHg), and level III (96 to 110mmHg), and 646patientswith com-
plete data sets were included in the final analysis (level I = 230, level II
= 206, level III = 210) (Fig. 2). All patients were older than 65 years,

Fig. 2. CONSORT flow c

and the demographics and baseline inpatient characteristics among
the three groups were similar (Table 1).

3.2. Intraoperative data and management

Intraoperative data were not significantly different among the three
groups, includingduration of anesthesia and surgery, volume of intrave-
nous fluids, amount of plasma and red blood cells, blood loss, and intra-
operative urine output (Table 2). Patients with MAP level III were
administered larger doses of norepinephrine (3.9 ± 1.0 mg), phenyl-
ephrine (700 ± 202 μg), and nitroglycerin (5.4 ± 1.6 mg) compared
with patients with MAP level I and level II (P b 0.01) (Table 2). The
time weighted average-mean arterial pressure (TWA-MAP) for the
three MAP control levels (I, II and level III) were 72 ± 5 mm Hg, 88 ±
7 mm Hg and 100 ± 6 mmHg respectively, which implied that the ac-
tual MAP control level were within the preset targeted MAP level. And

hart of the study.

Image of Fig. 2

Table 1
Demographic data and baseline characteristics of all patients.

I (n = 230) II (n = 206) III (n = 210)

Age (years) 73 ± 7 73 ± 6 74 ± 5
Gender (male) 124 (60.2%) 157 (68.3%) 143 (65.6%)
Body weight (kg) 69.8 ± 4.7 69.9 ± 5.1 70.1 ± 5.0
ASA grade

I 28 (12.2%) 28 (13.6%) 27 (12.9%)
II 169 (73.8%) 140 (67.9%) 159 (75.7%)
III 32 (14%) 38 (14.5%) 24 (11.4%)

NYHA grade
I 26 (10.7%) 26 (12.6%) 22 (10.5%)
II 189 (83.7%) 165 (80.1%) 174 (82.9%)
III 15 (5.6%) 15 (7.3%) 14 (6.7%)

Past history
Smoke 102 (44.3%) 98 (47.5%) 95 (45.2%)
Alcohol 87 (37.8%) 80 (38.8%) 83 (39.5%)
Stroke 8 (3.5%) 6 (2.9%) 9 (4.28%)
TIA 11 (4.78%) 13 (6.31%) 7 (3.59%)
COPD 4 (1.74%) 3 (1.45%) 4 (1.9%)
Diabetes mellitus 56 (24.3%) 48 (23.3%) 52 (24.7%)
Hyperthyroidism 3 (0.9%) 2 (0.9%) 4 (1.2%)

Antihypertensive agents
ACEI 54 (23.5%) 48 (23.3%) 52 (24.8%)
ARB 90(39.1%) 82(39.8%) 87 (41.4%)
β-Blockers 60 (26.1%) 53 (25.7%) 58 (27.6%)
CCB 42 (18.3%) 36 (17.5%) 40 (19.0%)
Diuretics 30(13.0%) 27(13.1%) 28(13.3%)
Others 34 (14.8%) 39 (17.4%) 33 (15.7%)

Hb (g/L) 123.7 ± 22.0 124.9 ± 21.6 120.6 ± 17.9
WBC (×109/L) 5.8 ± 1.7 6.3 ± 2.2 5.5 ± 2.0
BUN (mmol/L) 4.95 ± 1.65 4.88 ± 1.66 5.25 ± 1.65
SCr (mmol/L) 54.3 ± 7.9 52.9 ± 5.7 53.8 ± 6.7
FBS (mmol/L) 5.5 ± 1.5 5.5 ± 1.4 5.3 ± 1.7
EF (%) 65 ± 4 66 ± 5 64 ± 6
Baseline BP

SBP (mm Hg) 146 ± 20 150 ± 18 145 ± 17
DBP (mm Hg) 84 ± 10 86 ± 11 82 ± 9
MAP (mm Hg) 102 ± 23 104 ± 22 103 ± 21

Data are expressed as mean (SD) or number (%).
Baseline BP is calculated as the average of all radial cuff pressure 2 to 3 days (at least 3 times)
before surgery in the ward. Definitions of smoke and alcohol were based onWHO issued in
1997. The diagnosis of COPD in terms of international GOLD guideline published in 2015.
ASA, American Association of Anesthesiologists; NYHA, New York Heart Association; TIA,
transient ischemic attack; COPD, chronic obstructive pulmonary disease; ACEI, angiotensin
converting enzyme inhibitor; ARB, angiotensin receptor blocker; CCB, calcium channel
blocker;WBC, white blood cell; Hb, hemoglobin; BUN, blood urine nitrogen; SCr, serum cre-
atinine; BP, blood pressure; FBS, fasting blood sugar; EF, ejection fraction; SBP, systolic blood
pressure; DBP, diastolic blood pressure; MAP, mean arterial pressure.

Table 2
Intraoperative data among three groups.

I (n = 230) II (n = 206) III (n = 210) P value

Anesthetic time (min) 220.6 ± 71.0 212.9 ± 73.6 218.9 ± 69.2 0.89
Surgical time (h)

≦2 110 (47.8%) 100 (48.5%) 103 (49.0%) 0.67
2–4 105 (45.7%) 94 (45.6%) 94 (44.8%)
≧4 15 (6.5%) 12 (5.9%) 13 (6.2%)

Surgical route
Open 102 (44.3%) 94 (45.6%) 100 (47.6%)
Laparoscopy 108 (46.9%) 96 (46.6%) 93 (44.3%) 0.35
Laparoscopy to open 20 (8.8%) 16 (7.8%) 17 (8.1%)

Fluid management
Crystalloids (mL) 2102 ± 632 2153 ± 707 2260 ± 649 0.13
Colloids (mL) 756 ± 350 698 ± 332 715 ± 305 0.36
Plasma (mL) 320 ± 160 310 ± 150 325 ± 162 0.08
RBC (mL) 150 ± 150 170 ± 120 160 ± 150 0.22

Estimate blood loss (mL)
≦100 110 (47.8%) 102 (49.5%) 112 (53.3%) 0.56
101–500 112 (48.7%) 96 (46.5%) 88 (42.0%)
501–800 5 (2.2%) 6 (3.0%) 7 (3.3%)
801–1000 3 (1.3%) 2 (1.0%) 3 (1.4%)

Urine output (mL)
≦500 30 (13.0%) 26 (12.6%) 28 (13.3%) 0.21
501–1000 188 (81.7%) 169 (82.0%) 172 (81.9%)
N1000 12 (5.3%) 9 (4.4%) 10 (4.8%)

Vasoactive agents
Norepinephrine (mg) 2.2 ± 1.2 2.1 ± 1.5 3.9 ± 1.0 0.001
Phenylephrine (μg) 450 ± 155 507 ± 165 700 ± 202 0.001
Nitroglycerin (mg) 3.1 ± 1.2 3.3 ± 1.5 5.4 ± 1.6 0.001
Phentolamine (mg) 6.6 ± 4.2 7.3 ± 3.8 7.0 ± 3.5 0.14
Esmolol (mg) 65 ± 32 60 ± 40 69 ± 38 0.35
Atropine (mg) 0.8 ± 0.4 0.9 ± 0.4 0.8 ± 0.4 0.09

TWA-MAP (mm Hg) 72 ± 5 88 ± 7 100 ± 6 0.001

Data are expressed as mean (SD) or number (%).
RBC, red blood cell; TWA-MAP, time weighted average-mean arterial pressure.
TWA-MAP is calculated as theMAPmeasurements divided by totalmeasurement time (all
measurements are equidistant of 1 min interval since we placed arterial line in every case
and easy to extract MAP data from the electronic record system) [16].

Table 3
Perioperative occurrence of AKI, and other adverse outcomes.

I (n = 230) II (n = 206) III (n = 210) P value

Primary outcome
Incidence of AKI n(%) 31 (13.5%) 13 (6.3%) 27 (12.9%) 0.033

KDIGO stage1 n(%) 20 (8.7%) 9 (4.4%) 20 (9.5%)
KDIGO stage2 n(%) 11 (4.5%) 4 (1.9%) 7 (3.4%)
KDIGO stage3 n(%) 0 (−) 0 (−) 0 (−)

Secondary outcome
Surgical site infection n(%) 9 (3.9%) 7 (3.4%) 7 (3.4%) 0.542
Hospital acquired
pneumonia n(%)

26 (11.3%) 14 (6.7%) 22 (10.4%) 0.014

Stroke n(%) 1 (0.43%) 1 (0.48%) 1 (0.47%) 0.341
Admission to ICU n(%) 19 (8.4%) 9 (4.4%) 16 (7.6%) 0.015
Stay in ICU d(IQR) 2 (1–7) 1 (1–3) 2 (1–6) 0.025
Mortality of 28 day n(%) 7 (3.0%) 6 (2.9%) 8 (3.8%) 0.671

Data are expressed as mean (SD) or number (%).
ICU = intensive care unit; IQR = interquartile range.
KDIGO stage 1 =△Cr 50% to 99%; KDIGO stage 2 =△Cr 100% to 199%; KDIGO stage 3 =
△Cr 200% to 299% or serum creatinine above 353.6 μmol/L or initiate renal replacement
therapy.

81X. Wu et al. / Journal of Clinical Anesthesia 43 (2017) 77–83

the actualMAP control level was the essential determinant of success in
this study.

3.2.1. Perioperative occurrence of AKI and other adverse outcomes
AKI was observed for 10.9% (71/646) of patients after surgery. Pa-

tients with MAP level II exhibited a lower rate of AKI (6.3%) compared
to the patients with MAP level I (13.5%) and level III (12.9%) (Table 3).
When divided according to AKI stage, the numbers of patients with
KDIGO stage 1 or KDIGO stage 2 were also significantly different
among the three groups (P b 0.01). We did not find any patients with
KDIGO stage 3 among the three groups. The incidence of ICU admission
was significantly lower for patients withMAP level II (4.4%) than for pa-
tients withMAP level I (8.4%) and level III (7.6%; P=0.015). Therewere
no significant differences in 28-day mortality among the three groups
(level I, 3.0%; level II, 2.9%; level III, 3.8%) (Table 3).

4. Discussion

In this prospective and randomized study,we characterized the inci-
dence of postoperative AKI and other clinical complications in elderly
patients with chronic hypertension who underwent major gastrointes-
tinal surgery at three rigorously controlled intraoperative MAP levels. It

was revealed that intraoperative MAP controlled at 80–95 mm Hg can
significantly reduce the incidence of postoperative AKI and other post-
operative complications in elderly patients with chronic hypertension.

Our reported results as regards to postoperative AKI occurrence
are consistent with previous study [5]. The overall incidence of post-
operative AKI was 10.9% in the current study, however, it was 6.3%
for patients for MAP control of 80-95 mm Hg, which is significantly
lower than that for patients with MAP control of 65–79 mm Hg
(13.5%) and 96–110 mm Hg (12.9%). In fact, there is a broad range

82 X. Wu et al. / Journal of Clinical Anesthesia 43 (2017) 77–83

of incidence (1.0% to 7.5%) of postoperative AKI for noncardiac surgery
patients owing to the heterogeneity of study subjects, criteria for AKI di-
agnosis and stage, type of surgery, comorbidity, preoperative renal func-
tion status, and others factors [17–19]. In this study, we enrolled elderly
patients from 65 to 80 years and also focused on elderly patients with
chronic hypertension, which might be the reason for the high incidence
of postoperative AKI in our study.

A novel aspect of our study was that we found a middle MAP level
(80–95 mm Hg), but not a low (65–79 mm Hg) or high (96–
110 mm Hg) MAP level, can decrease the incidence of AKI and other
postoperative complications. Although the exact mechanism for this
phenomenon remains elusive, we postulated that a middle MAP level
might be appropriate for themajority of elderly patients with hyperten-
sion, below or above this level will cause abnormal perfusion renal tis-
sue, which involving autoregulation mechanism and other factors in
organ preserved process, further decreases glomerular filtration rate
and eventually jeopardizes kidney function based on the following liter-
ature [2,8,20–22]. Intuitively, abruptly fluctuating MAP, even briefly,
can be deleterious and can lead to increased postoperative cardiovascu-
lar complications and mortality [23,24]. In our study, a strict MAP con-
trol protocol was used with a view to reducing the impact of MAP
variation (5min) on AKI, of whichmay be the one of the factors contrib-
uting the decreased occurrence of AKI in middle MAP level. Another
large retrospective study demonstrated that intraoperative MAP
b 60 mm Hg significantly increased the risk of AKI [25], which means
that MAP level I inevitably causes insufficient renal perfusion in elderly
patients with hypertension. Additionally, too high blood pressure is also
deleterious to vital organ [26]. Therefore, we conclude that a MAP level
between 80 and 95mmHg is the appropriate pressure for the low inci-
dence of AKI.

As shown in Table 3, the rate of hospital-acquired pneumonia was
higher for level I and level III; furthermore, lengths of stay in the ICU
for level I and level III were longer than that for level II. The exact reason
for the higher occurrence of pneumonia remains undetermined in this
trial, partially because patients with level I and level III had longer ICU
stays. During the whole observation period, patients with level II had a
lower incidence of admission to the ICU. This could not be simply attrib-
uted to the contribution of the MAP level because the causes for enter-
ing the ICU are multifactorial. Unfortunately, we only recorded the
duration of stay in the ICU and neglected the exact reason for admitting
or readmitting to the ICU in this study.

The following studies, such as saline [27], chloride-restricted fluid
[28], colloid solutions [29] and fluid balance [30], suggested that both
the type and the amount of fluids are thought to affect the incidence
of AKI. In our study, crystalloids and colloids were used to volume ex-
pansion, and real-timemonitoring of SVV was used to evaluate volume
status andmake rapid adjustments of the volume to eliminate the effect
of volume status on AKI. No significant difference in the amount of crys-
talloid and colloid solutions was observed for the three MAP control
goals, suggesting that the significant differences in the incidence of
AKI and other complications were not caused by fluid therapy.

In the current trial, level III required larger doses of vasopressors
(norepinephrine and phenylephrine) and also larger doses of vasodila-
tors like nitroglycerin. The reason for this phenomenon is that at differ-
ent stages of surgery, the intensity of noxious stimulation varied,
furthermore, under the samedepth of anesthesia, a higherMAP level re-
quires larger doses of vasoactives.Whether the larger doses of vasopres-
sors aggravate renal function and further promote the occurrence of AKI
in level III remains to be unknown. In septic patients, vasopressor may
have a beneficial effect on renal function [31], whereas, administration
of vasopressor was associated with renal vasculature constriction and
renal tissue hypoperfusion which may compromise kidney function in
non-septic patients [32].

There are several shortcomings in this study. First, the randomization
per se created the possibility of exposing them to renal injury. Because it
was a randomized study, we could not allocate patients according to

preoperative baseline blood pressure, and some patients were random-
ized to the low MAP levels, which might not have been suitable for
pre-determined MAP levels. Second, renal blood flow using ultrasound-
tagged technology and cerebral oxygenation using the near-infrared
spectroscopy technique under different MAP levels have not been mon-
itored; therefore, the best suitable MAP level for the kidney or brain re-
mains to be further solved. Third, the MAP control status after surgery,
blood management, and antibiotic selection were left to the discretion
of the attending surgeon; it was unknown whether these factors had
effects on AKI. Finally, in the study, we only observed 28-day postopera-
tive mortality and solely concentrated on a specific population of elderly
patients with hypertension. Therefore, the results should be cautiously
extrapolated to other patients.

In conclusion, in elderly patients with chronic hypertension under-
going major gastrointestinal surgery, a MAP level ranging from 80 to
95 mm Hg confers a protective role in the renal function, reduces post-
operative AKI after major gastrointestinal surgery, and decreases the
likelihood of other complications.

Clinical trial registration

Registry URL: http://www.Chictr.org.cn. Clinical trial number:
ChiCTR-ROC-15006892.

Acknowledgments

We thank all patients who participated in this study. The authors
thank Prof. Haiyan Xing, PhD, a statistician at Shaoxing University, for
her assistance analyzing and explaining the data.

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Reproduced with permission of copyright owner. Further reproduction
prohibited without permission.

Optimal blood pressure decreases acute kidney injury after gastrointestinal surgery in elderly hypertensive patients: A ran…

1. Introduction

2. Materials and methods

2.1. Study design and ethics

2.2. Subjects

2.3. Anesthesia protocol

2.4. Fluid therapy

2.5. MAP control protocol

2.6. Study outcomes

2.7. Sample size

2.8. Statistical analysis

3. Results

3.1. Study population

3.2. Intraoperative data and management

3.2.1. Perioperative occurrence of AKI and other adverse outcomes

4. Discussion

Clinical trial registration

section17

Acknowledgments

References

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