predicting fluid responsiveness in children: a … fluid responsiveness in children: a systematic...
Post on 21-May-2018
220 Views
Preview:
TRANSCRIPT
1380 www.anesthesia-analgesia.org December 2013 • Volume 117 • Number 6
Copyright © 2013 International Anesthesia Research SocietyDOI: 10.1213/ANE.0b013e3182a9557e
The goal of hemodynamic resuscitation is to achieve adequate oxygen delivery by maintaining ade-quate cardiac output and perfusion pressure.
This is typically attempted initially with intravascular
volume expansion. However, in pediatric studies exam-ining fluid responsiveness, only 40% to 69% of chil-dren responded to intravascular volume expansion.1–9 Appropriate early fluid resuscitation improves sur-vival,10,11 but excessive fluid therapy increases mortal-ity.12–14 Clinical assessment of hemodynamic status based on physical examination and routine monitoring is inadequate, particularly in children.15–17 These findings underline the need for more reliable predictors of fluid responsiveness.
Numerous hemodynamic variables have been proposed as predictors of fluid responsiveness. Static variables are based on a single observation in time. This includes clinical observations such as heart rate and arterial blood pressure, preload pressures such as central venous pressure (CVP) and pulmonary artery occlusion pressure, and preload volume estimates from thermodilution and ultrasound dilution.
BACKGROUND: Administration of fluid to improve cardiac output is the mainstay of hemody-namic resuscitation. Not all patients respond to fluid therapy, and excessive fluid administra-tion is harmful. Predicting fluid responsiveness can be challenging, particularly in children. Numerous hemodynamic variables have been proposed as predictors of fluid responsiveness. Dynamic variables based on the heart–lung interaction appear to be excellent predictors of fluid responsiveness in adults, but there is no consensus on their usefulness in children.METHODS: We systematically reviewed the current evidence for predictors of fluid respon-siveness in children. A systematic search was performed using PubMed (1947–2013) and EMBASE (1974–2013). Search terms included fluid, volume, response, respond, challenge, bolus, load, predict, and guide. Results were limited to studies involving pediatric subjects (infant, child, and adolescent). Extraction of data was performed independently by 2 authors using predefined data fields, including study quality indicators. Any variable with an area under the receiver operating characteristic curve that was significantly above 0.5 was considered predictive.RESULTS: Twelve studies involving 501 fluid boluses in 438 pediatric patients (age range 1 day to 17.8 years) were included. Twenty-four variables were investigated. The only variable shown in multiple studies to be predictive was respiratory variation in aortic blood flow peak velocity (5 studies). Stroke volume index, stroke distance variation, and change in cardiac index (and stroke volume) induced by passive leg raising were found to be predictive in single studies only. Static variables based on heart rate, systolic arterial blood pressure, preload (central venous pressure, pulmonary artery occlusion pressure), thermodilution (global end diastolic volume index), ultrasound dilution (active circulation volume, central blood volume, total end diastolic volume, total ejection fraction), echocardiography (left ventricular end diastolic area), and Doppler (stroke volume index, corrected flow time) did not predict fluid responsiveness in children. Dynamic variables based on arterial blood pressure (systolic pressure variation, pulse pressure variation and stroke volume variation, difference between maximal or minimal systolic arterial blood pressure and systolic pressure at end-expiratory pause) and plethysmography (pulse oximeter plethysmograph amplitude variation) were also not predictive. There were contradicting results for plethymograph variation index and inferior vena cava diameter variation.CONCLUSIONS: Respiratory variation in aortic blood flow peak velocity was the only vari-able shown to predict fluid responsiveness in children. Static variables did not predict fluid responsiveness in children, which was consistent with evidence in adults. Dynamic variables based on arterial blood pressure did not predict fluid responsiveness in children, but the evi-dence for dynamic variables based on plethysmography was inconclusive. (Anesth Analg 2013;117:1380–92)
Predicting Fluid Responsiveness in Children: A Systematic ReviewHeng Gan, MBBCh, MRCPCH, FRCA,*† Maxime Cannesson, MD, PhD,‡ John R. Chandler, MBBCh, FCARCSI, FDSRDS,§ and J. Mark Ansermino, MBBCh, MSc (Inf), FFA (SA), FRCPC*†
From the *Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia; †Department of Anesthesia, BC Children’s Hospital, Vancouver, Canada; ‡Department of Anesthesiology and Periop-erative Care, University of California, Irvine, School of Medicine, Irvine, California; and §Department of Anaesthesia, University College London Trust, London, United Kingdom.
Accepted for publication August 9, 2013.
Funding: Not funded.
Conflict of Interest: See Disclosures at the end of the article.
Reprints will not be available from the authors.Address correspondence to Heng Gan, MBBCh, MRCPCH, FRCA, Depart-ment of Anesthesia, Room V3-317, 950 W. 28th Ave., Vancouver, British Columbia V5Z 4H4 Canada. Address e-mail to heng.gan@gmail.com.
December 2013 • Volume 117 • Number 6 www.anesthesia-analgesia.org 1381
Dynamic variables reflect the variation in preload induced by mechanical ventilation. With positive pres-sure ventilation, the vena cava blood flow is impeded during inspiration, causing a decrease in venous return and pulmonary artery blood flow. This effect on venous return can be quantified as inferior vena cava diameter variation (∆IVCD). Approximately 3 heart beats later (pulmonary transit time), this decrease in blood flow is transmitted to the left heart, resulting in a decrease in left ventricular end diastolic volume and consequently stroke volume.18 This ventilation-induced variation in stroke volume is then observed downstream as variation in aortic blood flow, arterial blood pressure, and plethys-mographic waveform amplitude. The degree of variation observed is larger in hypovolemia19,20 when the heart is functioning at the steep portion of the Frank–Starling relationship. Dynamic variables quantify this variation as the percentage difference between the maximal and the minimal measured value in a single breath, indexed to either the maximum, mean, or midpoint value. For example, one of the earliest dynamic variables, systolic pressure variation (SPV) is calculated as:
SPV (%) = (SAPmax − SPBmin)/[(SAPmax + SAPmin)/2] × 100
where SAP is systolic blood pressure. An average is usually taken over a period of time or a number of respira-tory cycles.
Many of these hemodynamic variables have been consis-tently shown to be the best predictors of fluid responsive-ness in adults. However, in the pediatric population, the predictive value of these variables remains controversial. We systematically reviewed the current evidence for the
value of these static and dynamic variables on predicting fluid responsiveness in children.
METHODSSelection of StudiesPublished studies evaluating the predictive factors of fluid responsiveness in pediatric patients in the periopera-tive and critical care settings were included. Studies were identified by electronic searches of PubMed (from 1947) and EMBASE (from 1974) databases. The final search was performed on 2 July, 2013. Results were limited to stud-ies involving pediatric subjects by using MeSH terms (PubMed) or by setting search limits (EMBASE). Search terms included fluid, volume, response, respond, chal-lenge, bolus, load, predict, and guide. Study selection was performed independently by HG and JMA. Figure 1 illus-trates the full search strategy.
Data ExtractionUsing a data extraction spreadsheet, 1 review author (HG) extracted data from included studies, and a second author (JMA) checked the extracted data. Information was extracted from each included study on:
(1) Characteristics of trial participants (age, weight, rel-evant clinical diagnosis, vasoactive therapy)
(2) Characteristics of study (clinical setting, ventilation, fluid bolus type, volume, and duration)
(3) Reference standard used (definition of response, method of assessment)
(4) Variables tested (method of assessment, area under receiver operating characteristic [ROC] curve)
8 articles excluded:5 adult studies
2 not fluid bolus study1 not prediction study
317 records after duplicates removed
297 of records excluded by title
20 articles assessed for eligibility
12 studies included
244 records identified
98 records identified
PubMed database search
(fluid or volume) AND(response* or respond* orchallenge or bolus or load) AND(predict* or guide) AND(hemodynamics[mh] or fluidtherapy[mh]) AND(infant[mh] or child[mh] oradolescent [mh])
EMBASE database search
(((fluid or volume) ADJ3(response* or respond* or challenge or bolus or load)) AND(predict* or guide)).ti,ab.
Limit: (infant <to one year> or child <unspecified age> or preschool child <1 to 6 years> or school child <7 to 12 years> or adolescent <13 to 17 years>)
Figure 1. Flow diagram of literature search and study selection.
1382 www.anesthesia-analgesia.org aNesthesia & aNalgesia
Predicting Fluid Responsiveness in Children
Summary MeasuresThe areas under the ROC curves and their 95% confidence intervals (CIs) were the primary measures for comparison. Standard deviations (SDs) and 95% CI, when not quoted, were reconstructed from P values if available. Any variable with an area under the ROC curve that was significantly above 0.5 (i.e. the lower limit of the 95% CI was above 0.5) was considered predictive. Any variable with a 95% CI overlapping 0.5 is no better than chance and was consid-ered not predictive. No meta-analysis was done due to the limited number of studies and diverse study characteristics.
Risk of BiasUsing an 18-item assessment tool (Appendix), which incor-porated the recommendations from Quality Assessment of Diagnostic Accuracy Studies (QUADAS)21 and the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy,22 the quality and risk of bias of individual studies were assessed by consensus based on joint review by 2 authors (HG and JMA).
To assess for publication bias, we created funnel plots of the area under the ROC curve against sample size for each variable that was investigated by 5 or more studies. The funnel plot is based on the fact that precision increases with sample size. Results from smaller studies will scatter widely at the bottom of the graph, with the spread narrow-ing among larger studies. The funnel plots were assessed visually for symmetry. In the absence of bias the plot will resemble a symmetrical inverted funnel.23 To formally test for asymmetry, we applied Egger regression tests on sec-ondary funnel plots of log (area under ROC/[1-area under
ROC]) against precision, using a significance level of 0.1 because of small sample size.23
RESULTSStudy CharacteristicsWe included 12 studies, totaling 501 fluid boluses in 438 pediatric patients (age range 1.0 day to 17.8 years). All but 29 patients’ lungs were mechanically ventilated. Six studies (156 patients) standardized tidal volume at 10 mL/kg. Positive end-expiratory pressure, where reported, ranged from 0 to 5 cm H2O. Three studies used crystalloid as fluid bolus, 6 studies used colloid, 2 studies used a mixture of fluids, and 1 study did not report type of fluid given. The hemodynamic response to intravascular volume expansion was defined by an increase in stroke volume in 10 studies, cardiac output in 1 study and arterial blood pressure in another. Cardiac diagnoses were present in 176 patients (40%) from 6 studies. Vasoactive drugs were administered during study measure-ments to 92 patients (21%) from 5 studies. All potential pre-dictors studied and their abbreviations are listed in Table 1. Study characteristics are detailed in Table 2.
Static VariablesTwelve static variables were included in this review, although only heart rate and CVP were investigated by >1 study. The area under the ROC curve and its 95% CI for each static variable is illustrated in Figure 2.
Clinical and Preload VariablesThe area under the ROC curve for heart rate was not signifi-cantly >0.5 in 3 pediatric studies.6,8 Similarly, the area under ROC for SAP was not significantly >0.5 in 1 study.24
Table 1. List of Potential Predictors and Their AbbreviationsSTATICClinical Heart rate HR
Systolic arterial blood pressure SAP
Preload pressure Central venous pressurePulmonary artery occlusion pressure
CVPPAOP
Thermodilution Global end diastolic volume index GEDVI
Ultrasound dilution Active circulation volumeCentral blood volumeTotal end diastolic volumeTotal ejection fraction
ACVCBVTEDVTEF
Echocardiography and Doppler Left ventricular end diastolic areaStroke volume indexCorrected flow time
LVEDASVIFTc
DyNAMIC
Arterial pressure Systolic blood pressure variation SPVPulse pressure variation PPVStroke volume variation SVVDifference between minimal SAP and SAP at end-expiratory pause ∆DownDifference between maximal SAP and SAP at end-expiratory pause ∆Up
Plethysmography Pulse oximeter plethysmograph amplitude variationPlethysmograph variability index
∆POPPVI
Echocardiography and Doppler Respiratory variation in aortic blood flow peak velocityStroke distance variationInferior vena cava diameter variation
∆Vpeak
∆VTI∆IVCD
PASSIvE LEG RAISING (PLR)
Echocardiography and Doppler PLR-induced change in cardiac index ∆CIPLR
PLR-induced change in stroke volume ∆SVPLR
December 2013 • Volume 117 • Number 6 www.anesthesia-analgesia.org 1383
Tabl
e 2. C
hara
cter
isti
cs o
f Stu
dies
Pub
licat
ion
Popu
lati
on
Age
, med
ian
(r
ange
), or
mea
n
(SD
), ye
ars
Wei
ght,
med
ian
(r
ange
) or
mea
n
(SD
), k
gPa
tien
ts,
n
Flui
d bo
lus,
n
Flui
d ty
pe
Flui
d vo
lum
e,
mL/
kg
Bol
us
time,
m
in
vent
ilati
on
tida
l vol
ume
(m
L/kg
)P
EEP,
cm
H2O
CvS
sta
tus
Defi
niti
on o
f re
spon
seM
etho
d of
as
sess
men
t
Pre
dict
ors
wit
h
repo
rted
are
as u
nder
th
e R
OC
cur
ves
Tibb
y et
al.2
5C
ardi
ac a
nd
Gen
eral
PIC
U
2.1
(0–1
6)
12 (3
–60)
94
94
FFP,
4.5
% A
lb o
r
PRB
C
10
30
NR
NR
50 h
ad v
asoa
ctiv
e
infu
sion
(s)
∆S
V >10%
TDC
VP, F
Tc
Tran
et al
.26
Car
diac
OR
0.7
(0–1
7.2
)6.2
(2.2
–71.5
)25
44
Blo
odN
RN
RN
RN
RPo
st-C
PB, o
pen
ches
t,
vaso
activ
e dr
ugs
not
cont
rolle
d
∆M
BP
≥80 m
m
Hg/
L/m
2
IAB
PC
VP, S
PV,
PPV
(man
ual),
SVV
(man
ual)
Dur
and
et a
l.1G
ener
al P
ICU
2.4
(IQ
R 1
.3–3
.7)
13 (I
QR
9.8
–15)
26
26
Plas
mio
n or
0.9
%
NaC
l
20
15–3
07.4
(med
ian)
4 (m
edia
n)11
rece
ived
nore
pine
phrin
e
∆S
V ≥1
5%
TTE
SPV
, PPV
(man
ual),
∆V p
eak
Cho
i et al
.2C
ardi
ac P
ICU
2.6
(1.8
)12 (4
)21
21
6%
HES
10
20
10
010 rec
eive
d m
ilrin
one
or
dopa
min
e
∆S
V ≥1
5%
TTE
CVP
, ∆V p
eak,
∆IV
CD
Rau
x et
al.3
Gen
eral
OR
(0–0
.5)
(2.5
–5)
50
50
4%
Alb
, 6%
HES
or
0.9
% N
aCl
10–3
020–4
0N
RN
RC
linic
ally
hyp
ovol
aem
ic,
no v
asoa
ctiv
e dr
ugs
∆S
V ≥1
5%
TED
HR
, MAP
, CI,
SVI
, FTc
, mea
n
acce
lera
tion
Luki
to e
t al
.4G
ener
al P
ICU
(1–1
3)
Mea
n B
SA
(SD
)
0.7
6 (0
.24)
40
40
0.9
% N
aCl
10
NR
29 (s
pont
aneo
us
brea
thin
g)
NR
3 rec
eive
d ep
inep
hrin
e∆
CO
>10%
TTE
Res
pons
e to
PLR
: HR
, MB
P,
SAP
, SV
and
CI
Pere
ira d
e
Sou
za
Net
o et
al.6
Neu
rosu
rgic
al
OR
2 (0
.5–5
) and
11 (6
–14)
11 a
nd 3
230
30
0.9
% N
aCl
20
15
10
0–2
No
vaso
activ
e dr
ugs
∆S
V ≥1
5%
TTE
∆PO
P, PV
I, PP
V (m
anua
l),
PPV
(aut
omat
ed),
LVED
A, ∆
V pea
k
Ren
ner et
al.8
Car
diac
OR
1.4
(1.3
)10.4
(6.3
)27
27
6%
HES
10
NR
10
3–5
Con
geni
tal h
eart
dis
ease
,
pre-
CPB
, clo
sed
ches
t,
no v
asoa
ctiv
e dr
ug
∆S
V ≥1
5%
TEE
PVI,
∆V p
eak,
∆VT
I
Sax
ena
et a
l.9Car
diac
and
Gen
eral
PICU
1N
R47
65
NR
10
NR
11 (m
edia
n)N
RN
R∆
SV
>15%
US
dilu
tion
ACV, C
BV, T
EDV, T
EF, S
PV,
PPV, S
V
Ren
ner et
al.7
Car
diac
OR
1.2
(1)
9.7
(4.3
)26
52
6%
HES
10
NR
10
3–5
Pre-
and
pos
t-CPB
,
clos
ed c
hest
, 18
rece
ived
eno
xim
one
and
epin
ephr
ine
post
-VS
D r
epai
r
∆S
V >15%
TEE
CVP
, PPV
(aut
o), S
VV, G
EDVI
Cha
ndle
r et
al.5
Car
diac
cat
h la
b6.1
(1.2
–17.8
)26.3
(8.9
–74)
19
19
Cry
stal
loid
10
NR
10
5Po
stca
rdia
c ca
th, n
o
resi
dual
shu
nt
∆S
V ≥1
5%
TD∆
POP,
PVI,
PPV
(man
ual),
CVP
, PAO
P
Byo
n et
al.2
4N
euro
surg
ical
OR
6.2
(0.6
–10.0
)24.3
(10.2
)33
33
6%
HES
10
10
10
0N
o va
soac
tive
drug
s∆
SV
≥10%
TTE
SAP, H
R, C
VP, ∆
IVCD
, SPV
,
∆D
own,
∆Up,
PPV
,
∆V p
eak,
PVI
SD
= s
tand
ard
devi
atio
n; n
= n
umbe
r of
sub
ject
s; P
EEP
= p
ositi
ve e
nd-e
xpira
tory
pre
ssur
e; C
VS =
car
diov
ascu
lar
syst
em;
RO
C =
rec
eive
r op
erat
ing
char
acte
ristic
; PI
CU
= p
edia
tric
inte
nsiv
e ca
re u
nit;
FFP
= f
resh
fro
zen
plas
ma;
Alb
= h
uman
alb
umin
sol
utio
n; P
RB
C =
pac
ked
red
bloo
d ce
lls; N
R =
not
rep
orte
d; ∆
SV
= c
hang
e in
str
oke
volu
me;
TD
= the
rmod
ilutio
n; C
VP =
cen
tral
ven
ous
pres
sure
; FTc
= c
orre
cted
flow
tim
e; O
R =
ope
ratin
g ro
om;
CPB
= c
ardi
opul
mon
ary
bypa
ss;
∆M
BP
= c
hang
e in
mea
n bl
ood
pres
sure
; IA
BP
= inv
asiv
e ar
teria
l bl
ood
pres
sure
; S
PV =
sys
tolic
pre
ssur
e va
riatio
n; P
PV =
pul
se p
ress
ure
varia
tion;
IQ
R =
int
er-q
uart
ile r
ange
; N
aCl =
sod
ium
chl
orid
e so
lutio
n; T
TE =
tra
nsth
orac
ic e
choc
ardi
ogra
phy;
TED
= t
rans
esop
hage
al D
oppl
er;
∆Vp
eak
= r
espi
rato
ry v
aria
tion
in a
ortic
blo
od fl
ow p
eak
velo
city
; ∆
IVC
D =
infe
rior
vena
cav
a di
amet
er v
aria
tion;
H
ES =
hyd
roxy
ethy
l sta
rch;
TEE
= tr
anse
soph
agea
l ech
ocar
diog
raph
y; H
R =
hea
rt ra
te; M
AP =
mea
n ar
teria
l blo
od p
ress
ure;
CI =
car
diac
inde
x; S
VI =
str
oke
volu
me
inde
x; B
SA
= b
ody
surf
ace
area
; ∆C
O =
cha
nge
in c
ardi
ac
outp
ut;
PLR
= p
assi
ve le
g ra
isin
g; M
BP
= m
ean
bloo
d pr
essu
re;
SAP
= s
ysto
lic b
lood
pre
ssur
e; S
V =
str
oke
volu
me;
∆PO
P =
pul
se o
xim
eter
ple
thys
mog
raph
am
plitu
de v
aria
tion;
PVI
= p
leth
ysm
ogra
ph v
aria
bilit
y in
dex;
LV
EDA
= le
ft v
entr
icul
ar e
nd d
iast
olic
are
a; ∆
VTI =
str
oke
dist
ance
var
iatio
n; U
S =
ultr
asou
nd;
ACV
= a
ctiv
e ci
rcul
atio
n vo
lum
e; C
BV
= c
entr
al b
lood
vol
ume;
TED
V =
tot
al e
nd d
iast
olic
are
a; T
EF =
tot
al e
ject
ion
frac
tion;
VS
D =
ven
tric
ular
sep
tal d
efec
ts;
SVV
= s
trok
e vo
lum
e va
riatio
n; G
EDVI
= g
loba
l end
dia
stol
ic v
olum
e in
dex;
SAP
= s
ysto
lic a
rter
ial b
lood
pre
ssur
e; ∆
Dow
n =
diff
eren
ce b
etw
een
min
imal
SAP
and
SAP
at
end-
expi
rato
ry
paus
e; ∆
Up
= d
iffer
ence
bet
wee
n m
axim
al S
AP a
nd S
AP a
t en
d-ex
pira
tory
pau
se.
1384 www.anesthesia-analgesia.org aNesthesia & aNalgesia
Predicting Fluid Responsiveness in Children
In eight studies that investigated the predictive value of CVP and 1 study the predictive value of pulmonary artery occlusion pressure, none of the areas under the ROC curves were significantly >0.5.2,5,7–9,24–26
Thermodilution and Ultrasound DilutionIn 1 pediatric study of 26 children with atrial or ventricular septal defects (ASD/VSD), the area under the ROC curve for global end diastolic volume index was not significantly >0.5.7
One pediatric intensive care unit (PICU) study, using ultrasound dilution to measure stroke volume, investigated using measurements derived from ultrasound dilution (total end diastolic volume, active circulation volume, central blood volume, and total ejection fraction) to predict fluid responsiveness.9 The study found that the 95% CI for areas under the ROC curve for these variables overlapped 0.5.
Echocardiography and DopplerThe use of left ventricular end diastolic area measured by transthoracic echocardiography to predict fluid
responsiveness was investigated in 1 pediatric study and was found not to predict fluid responsiveness.6 Stroke vol-ume index (SVI) predicted fluid responsiveness (95% CI lower limit 0.80) in 1 perioperative study involving 50 chil-dren younger than 6 months.3 One pediatric study found that corrected flow time (FTc) predicted fluid responsive-ness in general PICU patients (95% CI lower limit 0.58) but not in postoperative cardiac patients.25
Dynamic VariablesTen dynamic variables were included in this review. The area under the ROC curve and its 95% CI for each dynamic variable is illustrated as a forest plot in Figure 3.
Arterial PressureFour pediatric studies found that SPV did not accurately predict fluid responsiveness in children.1,9,24,26 Of the 7 studies investigating the use of pulse pressure varia-tion (PPV) to predict fluid responsiveness in children, 6 had negative results.1,5–7,9,24,26 In contradiction, 1 study,
Figure 2. Comparison of the areas under the receiver operating characteristic (ROC) curve for static variables. CI = confidence interval; ̶ · ̶ · ̶ = CI not reported; n = number of subjects; HR = heart rate; SAP = systolic arterial blood pressure; OR = operating room; CVP = central venous pressure; PICU = pediatric intensive care unit; ASD = atrial septal defects; VSD = ventricular septal defects; PAOP = pulmonary artery occlusion pressure; US = ultrasound; GEDVI = global end diastolic volume index; ACV = active circulation vol-ume; CBV = central blood volume; TEDV = total end diastolic volume; TEF = total ejection fraction; LVEDA = left ventricular end diastolic area; SVI = stroke volume index; FTc = corrected flow time; TTE = transesophageal echocardiography; TED = transesophageal Doppler.
December 2013 • Volume 117 • Number 6 www.anesthesia-analgesia.org 1385
involving 26 children aged 0 to 2 years, found that PPV predicted fluid responsiveness both before (95% CI lower limit 0.59) and after (95% CI lower limit 0.58) ASD/VSD closure.7 Three studies investigating the use of stroke vol-ume variation (SVV) in children did not find SVV predic-tive of fluid responsiveness,7,9,26 except in 1 study where
SVV was predictive (95% CI lower limit 0.56) of fluid responsiveness in children after surgical repair of ASD/VSD.7 One study investigated the difference between mini-mal and maximal SAP and SAP at end-expiratory pause (∆Down and ∆Up, respectively) and found neither had areas under the ROC curve that was significantly >0.5.24
Figure 3. Comparison of the areas under the receiver operator curve (ROC) curve for dynamic and passive leg raising (PLR) variables. CI = confidence interval; ̶ ̶ ̶ = CI reported as not significant; ̶ · ̶ · ̶ = CI not reported; n = number of subjects; PPV = pulse pres-sure variation; PICU = pediatric intensive care unit; OR = operating room; ASD = atrial septal defects; VSD = ventricular septal defects; SPV = systolic pressure variation; SVV = stroke volume variation; ∆POP = pulse oximeter plethysmograph amplitude variation; PVI = ple-thysmograph variability index; ∆Vpeak = peak velocity variation; ∆VTI = stroke distance variation; ∆IVCD = inferior vena cava diameter variation; ∆CIPLR = PLR-induced change in cardiac index; ∆SVPLR = PLR-induced change in stroke volume; TTE = transesophageal echocar-diography; TEE = transthoracic echocardiography.
1386 www.anesthesia-analgesia.org aNesthesia & aNalgesia
Predicting Fluid Responsiveness in Children
PlethysmographyTwo pediatric studies involving a total of 49 patients found that pulse oximeter plethysmograph amplitude variation (∆POP) did not predict fluid responsiveness in children.5,6
Two pediatric studies found plethysmograph variability index (PVI) predictive (95% CI lower limit 0.58 and 0.77) of fluid responsiveness.8,24 Two other pediatric studies, however, did not find PVI to predict fluid responsiveness in children.5,6
Echocardiography and DopplerFive studies investigated the use of respiratory variation in aortic blood flow peak velocity (∆Vpeak) to predict fluid responsiveness in children in the operating room6,7,24 and the intensive care unit1,2 and found that ∆Vpeak predicted fluid responsiveness in children (95% CI lower limits 0.64, 0.61, 0.66, 0.82, 0.73, and 0.73). One study found stroke distance variation (∆VTI) measured using transesophageal echocar-diography a predictor of fluid responsiveness (95% CI lower limit 0.65) in children with congenital heart disease.7 ∆IVCD was found to predict fluid responsiveness in children in a study in the PICU (95% CI lower limit 0.69)2 but not in another study in the operating room (95% CI lower limit 0.16).24
Passive Leg RaisingOne study investigated using hemodynamic changes induced by passive leg raising (PLR) to predict fluid respon-siveness in 40 PICU patients, the most which were sponta-neously breathing.4 The study demonstrated that changes in cardiac index and stroke volume induced by PLR (∆CIPLR and ∆SVPLR, respectively) predicted fluid responsiveness (95% CI lower limits 0.55 and 0.59, respectively). However, after multivariate analysis using logistic regression analy-sis, the study concluded that only ∆CIPLR significantly cor-related with fluid responsiveness.
Risk of BiasTable 3 summarizes the assessment of quality and risk of bias of individual studies. Twenty-one of 216 items were initially assessed differently but were resolved by consen-sus. The quality of the most studies was high with low risk of bias, except for the 2 included abstracts,5,9 which lacked detailed description of study methodology. Most studies could not avoid incorporation bias because the same modal-ity (e.g., transthoracic echocardiography) was used both as the reference and as the index variable. None of the studies established cutoff values prospectively because they were using area under the ROC curve as effect measure. Five studies tested for observer variation in echocardiography and Doppler measurements.
Funnel plots of the area under the ROC curve against sam-ple size were constructed for CVP, PPV, and ∆Vpeak (Fig. 4), the only variables investigated by 5 or more studies. The funnel plot for PPV appeared symmetrical, but the funnel plot for CVP and ∆Vpeak appeared asymmetrical. However, Egger regression test for symmetry showed nonsignificant P values (0.46, 0.33, and 0.17, respectively for CVP, PPV, and ∆Vpeak), suggesting low risk of publication bias.
DISCUSSIONStatic VariablesThe studies included in this review failed to demon-strate any predictive value in heart rate, CVP, pulmo-nary artery occlusion pressure, left ventricular end diastolic area, global end diastolic volume index, and ultrasound dilution measurements (total end diastolic volume, active circulation volume, central blood vol-ume, and total ejection fraction). The only static vari-ables that potentially have predictive values are SVI and FTc. SVI was found to be predictive of fluid respon-siveness in 1 study of 50 pediatric patients undergoing general surgery.3 There are, however, no other pediatric studies to support this result.
FTc is derived from transesophageal Doppler mea-surement of blood flow in the descending thoracic aorta. Flowtime is measured from the beginning to end of the aor-tic velocity waveform. FTc controls for varying heart rate using the equation FTc = Flowtime/√cycletime.
FTc is influenced by preload as well as contractil-ity and systemic vascular resistance.27,28 In individual patients, FTc may increase with fluid administration and increased stroke volume and has been used to guide intraoperative fluid management in adults.29 Studies in adults using FTc to predict fluid responsiveness are inconclusive.30,31 The only pediatric study found that FTc predicted fluid responsiveness in general PICU patients but not in cardiac patients who had comparatively lower cardiac index and higher (and more variable) systemic vascular resistance.25
Dynamic VariablesDynamic preload variables are those which reflect the cyclical changes in left ventricular stroke volume induced by positive pressure ventilation. Several sys-tematic reviews and meta-analyses suggest that in adults, dynamic variables based on arterial blood pres-sure (SPV, PPV, and SVV) and plethysmography (∆POP and PVI) all have excellent predictive value.32–36 The evidence for this in children is disappointingly poor. Dynamic parameters extracted from the arterial pres-sure waveform (SPV, PPV, SVV, ∆Down, and ∆Up) on the whole do not predict fluid responsiveness in chil-dren. PPV and SVV have only been demonstrated in single studies to predict fluid responsiveness in chil-dren with congenital heart disease.7,8 There were con-tradicting results for the predictive value of dynamic parameters based on the plethysmographic waveform. Studies agreed ∆POP did not predict fluid responsive-ness in children, but there were conflicting results for PVI. Only ∆Vpeak appeared to predict fluid respon-siveness in children. We explore a number of possible explanations.
Thoracic/Lung Compliance and VentilationChildren have higher chest wall and lung compliance.37 The variation in intrathoracic pressure with normal tidal volume ventilation may not cause significant circulatory changes in children. In adults, a tidal volume of at least 8 mL/kg is required.38 Most of the pediatric studies in
December 2013 • Volume 117 • Number 6 www.anesthesia-analgesia.org 1387
this review used a tidal volume of 10 mL/kg, although some either did not report or did not control tidal vol-umes used. Four studies investigating ∆Vpeak demon-strated that there is indeed measurable variation in aortic blood flow in children with ventilation tidal volumes of 10 mL/kg.2,6,7,24
Arterial Blood Pressure, Vascular Compliance, and Cardiac ComplianceSPV and PPV are dynamic preload indicators based on arterial blood pressure. They quantify the magnitude of change induced by positive pressure ventilation in SAP and pulse pressure (PP), respectively. SPV is calculated using
Table 3. Methodological Quality Summary
Tibby et al.25
Tran et al.26
Durand et al.1
Choi et al.2
Raux et al.3
Lukito et al.4
Pereira de Souza Neto
et al.6Renner
et al.,20118Saxena et al.9
Renner et al.,20127
Chandler et al.5
Byon et al.24
Representative spectrum?
Yes No No No No Yes No No Unclear No No No
Clear selection criteria?
No Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes
Acceptable reference standard?
Yes No Yes Yes Yes Yes Yes Yes Unclear Yes Yes Yes
Acceptable delay between tests?
Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes
Partial verification avoided?
Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Differential verification avoided?
Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Incorporation avoided?
Yes No No No No No No No No Yes Yes No
Detailed description of index test?
Yes Yes Yes Yes Yes Yes Yes Yes No Yes No Yes
Detailed description of reference standard?
Yes Yes Yes Yes Yes Yes Yes Yes No Yes No Yes
Reference standard results blinded?
Yes Yes No Yes No No Yes Yes No Yes No No
Index test results blinded?
Yes Yes No Yes No No Yes Yes No Yes No No
Same clinical data available?
Yes Yes Yes Yes Yes Yes Yes Yes Unclear Yes No Yes
Interpretable results reported?
Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Withdrawals explained?
Unclear Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Cutoff established before study?
No No No No No No No No No No No No
Clear definition of “positive” result?
No No No Yes Yes Yes Yes Yes No Yes No Yes
Reported and acceptable observer variation?
Yes No Yes Yes No Yes Yes No No No No Yes
No commercial funding?
No Yes Yes Yes Yes Yes Yes Yes Unclear Yes Yes Yes
Yes = high quality; No = low quality.
1388 www.anesthesia-analgesia.org aNesthesia & aNalgesia
Predicting Fluid Responsiveness in Children
the maximal and minimal SAP values measured in a single respiratory cycle:
SPV (%) = (SAPmax − SPBmin)/[(SAPmax + SAPmin)/2] × 100
PPV is calculated with PP using an analogous formula. An average is taken either over 3 consecutive respiratory cycles or over 30 seconds.7,39,40
Respiratory-induced changes in cardiac stroke volume centrally are measured as changes in the arterial blood pres-sure peripherally. Children have a more compliant arterial tree than adults.41,42 The magnitude of the change in arterial blood pressure induced by ventilation is smaller in a more compliant arterial vascular system because the peripherally measured PP is dependent on arterial compliance.43 This may explain why dynamic variables based on arterial blood pressure in general do not predict fluid responsiveness in children.1,5,6,9 The picture is less clear in children with intra-cardiac shunts who may have reduced arterial compliance due to sympathetic upregulation.5,44 Renner et al.7 found PPV to predict fluid responsiveness in a study of children before and after ASD or VSD closure. However, when PPV was examined in children after transcatheter closure of intracardiac shunts, it was not a predictive value of fluid responsiveness.5
Animal studies suggest that immature ventricles are less compliant and have less steep Starling curves.45 A recent study demonstrated PPV values that were lower in immature pigs compared with adult pigs with the same degree of hypovolemia.46 Reduced cardiac compliance may be a possible explanation why PPV and SPV do not predict fluid responsiveness as well in children compared with adults.
Flow VariablesThe most convincing predictor was ∆Vpeak, a direct ultrasound measurement of variations in aortic blood flow induced by small reversible changes in preload due to ventilatory-induced changes in venous return. Unlike variables based on arterial blood pressure or plethysmographic measurements, flow measurements are not affected by arterial compliance or changes in arterial tone.47 ∆Vpeak is measured using Doppler echocardiography, which requires a skilled operator.
This may limit its utility in routine clinical practice, despite being a reliable predictor of fluid responsiveness.
Plethysmographic VariablesThe plethysmographic waveform is the quantity of infra-red light detected by the oximeter photo detector, which varies during the cardiac cycle. The plethysmographic waveform amplitude is measured beat to beat as the vertical distance between peak and preceding valley in the output waveform. ∆POP is then calculated using a formula analogous to that of SPV and PPV. The plethys-mographic gain factor is held constant during record-ing so that the waveform amplitude is not modified by automatic gain adjustment.39,48 Similar to the calculation of PPV, an average is usually taken over 3 consecutive respiratory cycles.39,48
PVI (Masimo Corp., Irvine, CA) is an algorithm for auto-mated and continuous representation of the respiratory
0
10
20
30
40
50
60
70
0 0.5 1
Sam
ple
size
Area under ROC curve
CVP
0
10
20
30
40
50
60
70
0 0.5 1
Sam
ple
size
Area under ROC curve
PPV
0
10
20
30
40
0 0.5 1
Sam
ple
size
Area under ROC curve
∆Vpeak
Figure 4. Funnel plots for central venous pressure (CVP), pulse pressure variation (PPV) and peak velocity variation (∆Vpeak). Plots of area under the receiver operating characteristic (ROC) curve against sample size to assess for publication bias. In the absence of bias, the plot resembles a symmetrical inverted funnel.
December 2013 • Volume 117 • Number 6 www.anesthesia-analgesia.org 1389
variations in the plethysmographic waveform amplitude, using the perfusion index (PI) as a surrogate. PVI is the maximum change in PI over a time interval that includes at least 1 complete respiratory cycle:
PVI = [(PImax − PImin)/PImax] × 100
The plethysmographic waveform reflects the amount of infrared light detected by the pulse oximeter sensor, which is dependent on the blood volume in the tissue where the oximeter sensor is placed. The blood volume depends on vascular distensibility and stroke volume.49 Since vascular distensibility is considered unchanged during the course of 1 mechanical breath, respiratory-induced changes in the arterial pulse pressure become the main determinants of PVI and ∆POP. Indeed, ∆POP has been shown to be corre-lated to SPV50 and PPV39 in adults, and to PPV in children.51 Furthermore, the increased impedance to venous return during a positive pressure inspiration may increase the volume of venous blood, thus exaggerating the decrease in plethysmographic wave amplitude.49 PVI and ∆POP should therefore be expected to be more sensitive to ventilator-induced changes than SPV or PPV. In adult studies, PVI and ∆POP predicted fluid responsiveness, both in the periopera-tive32,48,52–54 and critical care settings.55,56 Disappointingly, in children, ∆POP did not predict fluid responsiveness. PVI was found to predict fluid responsiveness in 2 pediatric studies8,24 but not in 2 other pediatric studies.5,6 This contra-dicting result is difficult to explain. The studies all involved patients of similar ages, and their lungs were ventilated at tidal volumes of 10 mL/kg. The 2 positive studies used col-loid fluid boluses, and the 2 negative studies used crystal-loid, but this should not influence the results, particularly since all 4 studies similarly defined fluid responsiveness as an increase in stroke volume measured using echocardiog-raphy. One of the positive studies was in children with con-genital heart disease,8 which may be explained by reduced vascular compliance due to sympathetic upregulation.5,44 However, this does not explain the other positive study in children undergoing neurosurgery.24
Passive Leg Raising∆CIPLR appeared to be an excellent predictor of fluid respon-siveness in children, which is consistent with findings in adult studies.57 In adults, PLR induces an “autotransfu-sion” of approximately 150 mL.58 Children have a lower leg-length to body-length ratio than adults,59 so the effect of PLR may be smaller. A major advantage of PLR-induced changes in cardiac output as a predictor of fluid respon-siveness is that its accuracy seemed unaffected by venti-lation mode, underlying cardiac rhythm, and technique of measurements.57 ∆CIPLR is also completely reversible,4,60,61 and therefore, any detrimental effects of unnecessary fluid administration are only minimal and temporary.
LimitationsA number of different thresholds were used for fluid respon-siveness. The most common definition of fluid responsive-ness was change in stroke volume of >15% as measured by transesophageal or transthoracic echocardiography. This
seemed reasonable, as 15% is more than the expected error of echocardiographic measurements and is generally consid-ered clinically relevant. Other studies used a 10% increase as threshold, or measured stroke volume differently, using transesophageal Doppler, thermodilution or ultrasound dilution. An increase in mean arterial blood pressure or car-diac output was also used to define fluid responsiveness, which in our opinion was inappropriate. An increase in arte-rial blood pressure or cardiac output would not necessarily reflect increased stroke volume. All studies measured fluid responsiveness within 10 minutes of a fluid bolus, except for 2 studies which did not report a time interval.
There was no uniformity in the type, volume, and rate of fluid bolus across the studies. A slow small volume bolus of crystalloid would have a different impact on intravascu-lar volume expansion compared with a rapid large-volume bolus of colloid. However, the proportion of subjects with a positive fluid response was consistently approximately 50% across the studies.
Most of the studies had subjects with a median age younger than 3 years, but the ranges did vary, and some included subjects in their late teens. It is difficult to inter-pret the validity of pooled results from subjects of diverse weights and physiology (e.g., vascular compliance, stroke volume). One study included 2 separate age groups, but their results did not differ significantly between the age groups.6
All except 1 study involved fewer than 50 fluid boluses. Most variables were only included in single studies. Only CVP, PPV, SPV, PVI, and ∆Vpeak were investigated by 4 or more studies.
Seven studies included patients receiving vasoactive infusions, which would have affected vascular compliance. Eighteen of 26 subjects in the Renner et al.7 study received enoximone and epinephrine after VSD closure. Two of the 5 studies supporting ∆Vpeak as a predictor of fluid responsive-ness included patients receiving norepinephrine, milrinone, or dopamine.1,2
ConclusionsΔVpeak was the only variable to reliably predict fluid respon-siveness in children. Most static variables did not predict fluid responsiveness in children, which was consistent with findings in adults. However, in contrast to adults, dynamic variables based on arterial blood pressure also did not predict fluid responsiveness in children. The evidence for dynamic variables based on plethysmography was incon-clusive. Children have different lung, vascular, and cardiac compliances compared with adults. Research is needed to explain how these affect the ability of dynamic variables to predict fluid responsiveness in children.
RECUSE NOTEMaxime Cannesson is the Section Editor for Technology, Computing, and Simulation for the Journal. This manuscript was handled by Peter Davis, Section Editor for Pediatric Anesthesiology, and Dr. Cannesson was not involved in any way with the editorial process or decision.
1390 www.anesthesia-analgesia.org aNesthesia & aNalgesia
Predicting Fluid Responsiveness in Children
DISCLOSURESName: Heng Gan, MBBCh, MRCPCH, FRCA.Contribution: This author helped design the study, collect and analyze the data, and prepare this manuscript.Attestation: This author approved the final manuscript.Conflicts of Interest: The author has no conflicts of interest to declare.Name: Maxime Cannesson, MD, PhD.Contribution: This author helped design the study and prepare this manuscript.Attestation: This author approved the final manuscript.Conflicts of Interest: Sironis is a biomedical company I cofounded in 2010 to develop closed-loop fluid manage-ment systems and noninvasive hemodynamic monitoring tools. I hold 37% equity interest in Sironis. During the past 5 years, I have consulted and/or have prepared CME materi-als for Covidien, Draeger, Philips Medical System, Edwards Lifesciences, Fresenius Kabi, Masimo Corp., and ConMed. My department has received research fundings from Edwards Lifesciences and Masimo Corp. to support clinical studies for which I act as principal investigator.Name: John R. Chandler, MBBCh, FCARCSI, FDSRDS.Contribution: This author helped prepare this manuscript.Attestation: This author approved the final manuscript.Conflicts of Interest: The author has no conflicts of interest to declare.Name: J. Mark Ansermino, MBBCh, MSc (Inf), FFA (SA), FRCPC.Contribution: This author helped design the study, analyze the data, and prepare this manuscript.Attestation: This author approved the final manuscript.Conflicts of Interest: The author has no conflicts of interest to declare.
ACKNOWLEDGMENTSPartial salary support for HG was received from a Canadian Institutes of Health Research Grant to JMA. The authors wish to thank Dorothy Myers (manuscript presentation) and Guohai Zhou (statistical analysis) for their contributions.
REFERENCES 1. Durand P, Chevret L, Essouri S, Haas V, Devictor D. Respiratory
variations in aortic blood flow predict fluid responsiveness in ventilated children. Intensive Care Med 2008;34:888–94
2. Choi DY, Kwak HJ, Park HY, Kim YB, Choi CH, Lee JY. Respiratory variation in aortic blood flow velocity as a predic-tor of fluid responsiveness in children after repair of ventricular septal defect. Pediatr Cardiol 2010;31:1166–70
3. Raux O, Spencer A, Fesseau R, Mercier G, Rochette A, Bringuier S, Lakhal K, Capdevila X, Dadure C. Intraoperative use of transoesophageal Doppler to predict response to volume expansion in infants and neonates. Br J Anaesth 2012;108:100–7
4. Lukito V, Djer MM, Pudjiadi AH, Munasir Z. The role of passive leg raising to predict fluid responsiveness in pediatric intensive care unit patients. Pediatr Crit Care Med 2012;13:e155–60
5. Chandler JR, Cooke E, Hosking M, Froese N, Karlen W, Ansermino JM. Volume responsiveness in children, a compari-son of static and dynamic variables. Proceedings of the IARS 2011 Annual Meeting 2011:S–200
6. Pereira de Souza Neto E, Grousson S, Duflo F, Ducreux C, Joly H, Convert J, Mottolese C, Dailler F, Cannesson M. Predicting fluid responsiveness in mechanically ventilated children under general anaesthesia using dynamic parameters and transtho-racic echocardiography. Br J Anaesth 2011;106:856–64
7. Renner J, Broch O, Duetschke P, Scheewe J, Höcker J, Moseby M, Jung O, Bein B. Prediction of fluid responsiveness in infants and neonates undergoing congenital heart surgery. Br J Anaesth 2012;108:108–15
8. Renner J, Broch O, Gruenewald M, Scheewe J, Francksen H, Jung O, Steinfath M, Bein B. Non-invasive prediction of fluid responsiveness in infants using pleth variability index. Anaesthesia 2011;66:582–9
9. Saxena R, Durward A, Puppala NK, Murdoch I, Tibby S. A comparison between novel static and dynamic markers of fluid responsiveness: preliminary data from 47 children. Proceedings of the 22nd Annual Congress of the ESPNIC 2011;37 Suppl 2:S315–442
10. Rivers E, Nguyen B, Havstad S, Ressler J, Muzzin A, Knoblich B, Peterson E, Tomlanovich M; Early Goal-Directed Therapy Collaborative Group. Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med 2001;345:1368–77
11. Han YY, Carcillo JA, Dragotta MA, Bills DM, Watson RS, Westerman ME, Orr RA. Early reversal of pediatric-neonatal septic shock by community physicians is associated with improved outcome. Pediatrics 2003;112:793–9
APPENDIXRepresentative spectrum? Was the spectrum of patients representative of the patients who will receive the test in practice?Clear selection criteria? Were selection criteria clearly described?Acceptable reference standard? Is the reference standard likely to classify the target condition correctly?Acceptable delay between tests? Is the time period between reference standard and index test short enough to be reasonably sure
that the target condition did not change between the 2 tests?Partial verification avoided? Did the whole sample or a random selection of the sample, receive verification using the intended
reference standard?Differential verification avoided? Did patients receive the same reference standard irrespective of the index test result?Incorporation avoided? Was the reference standard independent of the index test (i.e. the index test did not form part of the
reference standard)?Detailed description of index test? Was the execution of the index test described in sufficient detail to permit its replication?Detailed description of reference standard? Was the execution of the reference standard described in sufficient detail to permit its replication?Reference standard results blinded? Were the index test results interpreted without knowledge of the results of the reference standard?Index test results blinded? Were the reference standard results interpreted without knowledge of the results of the index test?Same clinical data available? Were the same clinical data available when test results were interpreted as would be available when
the test is used in practice?Interpretable results reported? Were uninterpretable/ intermediate test results reported?Withdrawals explained? Were withdrawals from the study explained?Cutoff established before study? Were cutoff values established before the study was started?Clear definition of “positive” result? Did the study provide a clear definition of what was considered to be a ‘positive’ result?Reported and acceptable observer variation? Were data on observer variation reported and within an acceptable range?No commercial funding? Was the study free of commercial funding?
December 2013 • Volume 117 • Number 6 www.anesthesia-analgesia.org 1391
12. Rosenberg AL, Dechert RE, Park PK, Bartlett RH; NIH NHLBI ARDS Network. Review of a large clinical series: association of cumulative fluid balance on outcome in acute lung injury: a retrospective review of the ARDSnet tidal volume study cohort. J Intensive Care Med 2009;24:35–46
13. Murphy CV, Schramm GE, Doherty JA, Reichley RM, Gajic O, Afessa B, Micek ST, Kollef MH. The importance of fluid man-agement in acute lung injury secondary to septic shock. Chest 2009;136:102–9
14. Boyd JH, Forbes J, Nakada TA, Walley KR, Russell JA. Fluid resuscitation in septic shock: a positive fluid balance and ele-vated central venous pressure are associated with increased mortality. Crit Care Med 2011;39:259–65
15. Tibby SM, Hatherill M, Marsh MJ, Murdoch IA. Clinicians’ abilities to estimate cardiac index in ventilated children and infants. Arch Dis Child 1997;77:516–8
16. Egan JR, Festa M, Cole AD, Nunn GR, Gillis J, Winlaw DS. Clinical assessment of cardiac performance in infants and children following cardiac surgery. Intensive Care Med 2005;31:568–73
17. Vincent JL, Weil MH. Fluid challenge revisited. Crit Care Med 2006;34:1333–7
18. Michard F. Changes in arterial pressure during mechanical ven-tilation. Anesthesiology 2005;103:419–28; quiz 449–5
19. Perel A, Pizov R, Cotev S. Systolic blood pressure variation is a sensitive indicator of hypovolemia in ventilated dogs subjected to graded hemorrhage. Anesthesiology 1987;67:498–502
20. Rick JJ, Burke SS. Respirator paradox. South Med J 1978;71:1376–8, 1382
21. Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol 2003;3:25
22. Reitsma H, Rutjes A, Whiting P, Vlassov V, Leeflang MMG, Deeks J. Chapter 9: assessing methodological quality. In: Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy Version 1.0.0., 2009
23. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629–34
24. Byon HJ, Lim CW, Lee JH, Park YH, Kim HS, Kim CS, Kim JT. Prediction of fluid responsiveness in mechanically ven-tilated children undergoing neurosurgery. Br J Anaesth 2013;110:586–91
25. Tibby SM, Hatherill M, Durward A, Murdoch IA. Are transo-esophageal Doppler parameters a reliable guide to paediatric haemodynamic status and fluid management? Intensive Care Med 2001;27:201–5
26. Tran H, Froese N, Dumont G, Lim J, Ansermino JM. Variation in blood pressure as a guide to volume loading in children follow-ing cardiopulmonary bypass. J Clin Monit Comput 2007;21:1–6
27. Singer M, Bennett ED. Noninvasive optimization of left ven-tricular filling using esophageal Doppler. Crit Care Med 1991;19:1132–7
28. Singer M, Allen MJ, Webb AR, Bennett ED. Effects of alterations in left ventricular filling, contractility, and systemic vascular resistance on the ascending aortic blood velocity waveform of normal subjects. Crit Care Med 1991;19:1138–45
29. Abbas SM, Hill AG. Systematic review of the literature for the use of oesophageal Doppler monitor for fluid replacement in major abdominal surgery. Anaesthesia 2008;63:44–51
30. Lee JH, Kim JT, Yoon SZ, Lim YJ, Jeon Y, Bahk JH, Kim CS. Evaluation of corrected flow time in oesophageal Doppler as a predictor of fluid responsiveness. Br J Anaesth 2007;99:343–8
31. Monnet X, Rienzo M, Osman D, Anguel N, Richard C, Pinsky MR, Teboul JL. Esophageal Doppler monitoring predicts fluid responsiveness in critically ill ventilated patients. Intensive Care Med 2005;31:1195–201
32. Cannesson M, Desebbe O, Rosamel P, Delannoy B, Robin J, Bastien O, Lehot JJ. Pleth variability index to monitor the respiratory variations in the pulse oximeter plethysmographic waveform amplitude and predict fluid responsiveness in the operating theatre. Br J Anaesth 2008;101:200–6
33. Cannesson M, Musard H, Desebbe O, Boucau C, Simon R, Hénaine R, Lehot JJ. The ability of stroke volume variations
obtained with Vigileo/FloTrac system to monitor fluid respon-siveness in mechanically ventilated patients. Anesth Analg 2009;108:513–7
34. Michard F, Boussat S, Chemla D, Anguel N, Mercat A, Lecarpentier Y, Richard C, Pinsky MR, Teboul JL. Relation between respiratory changes in arterial pulse pressure and fluid responsiveness in septic patients with acute circulatory failure. Am J Respir Crit Care Med 2000;162:134–8
35. Marik PE, Cavallazzi R, Vasu T, Hirani A. Dynamic changes in arterial waveform derived variables and fluid responsiveness in mechanically ventilated patients: a systematic review of the literature. Crit Care Med 2009;37:2642–7
36. Sandroni C, Cavallaro F, Marano C, Falcone C, De Santis P, Antonelli M. Accuracy of plethysmographic indices as predic-tors of fluid responsiveness in mechanically ventilated adults: a systematic review and meta-analysis. Intensive Care Med 2012;38:1429–37
37. Papastamelos C, Panitch HB, England SE, Allen JL. Developmental changes in chest wall compliance in infancy and early childhood. J Appl Physiol 1995;78:179–84
38. Backer D De, Heenen S, Piagnerelli M, Koch M, Vincent J. Pulse pressure variations to predict fluid responsiveness: influence of tidal volume. Intensive Care Med 2005;31:517–23
39. Cannesson M, Besnard C, Durand PG, Bohé J, Jacques D. Relation between respiratory variations in pulse oximetry ple-thysmographic waveform amplitude and arterial pulse pres-sure in ventilated patients. Crit Care 2005;9:R562–8
40. Aboy M, McNames J, Thong T, Phillips CR, Ellenby MS, Goldstein B. A novel algorithm to estimate the pulse pressure variation index deltaPP. IEEE Trans Biomed Eng 2004;51:2198–203
41. Senzaki H, Akagi M, Hishi T, Ishizawa A, Yanagisawa M, Masutani S, Kobayashi T, Awa S. Age-associated changes in arte-rial elastic properties in children. Eur J Pediatr 2002;161:547–51
42. ROACH MR, BURTON AC. The effect of age on the elasticity of human iliac arteries. Can J Biochem Physiol 1959;37:557–70
43. Chemla D, Hébert JL, Coirault C, Zamani K, Suard I, Colin P, Lecarpentier Y. Total arterial compliance estimated by stroke volume-to-aortic pulse pressure ratio in humans. Am J Physiol 1998;274:H500–5
44. Leimbach WN Jr, Wallin BG, Victor RG, Aylward PE, Sundlöf G, Mark AL. Direct evidence from intraneural recordings for increased central sympathetic outflow in patients with heart failure. Circulation 1986;73:913–9
45. Spotnitz WD, Spotnitz HM, Truccone NJ, Cottrell TS, Gersony W, Malm JR, Sonnenblick EH. Relation of ultrastructure and function. Sarcomere dimensions, pressure-volume curves, and geometry of the intact left ventricle of the immature canine heart. Circ Res 1979;44:679–91
46. McCrea K, Girling L, Graham R. Pulse pressure variability in pigs: effect of age and tidal volume. Proceedings of the Canadian Anesthesiologists’ Society Annual Meeting 2012:1312346
47. Slama M, Masson H, Teboul JL, Arnould ML, Nait-Kaoudjt R, Colas B, Peltier M, Tribouilloy C, Susic D, Frohlich E, Andréjak M. Monitoring of respiratory variations of aortic blood flow velocity using esophageal Doppler. Intensive Care Med 2004;30:1182–7
48. Cannesson M, Attof Y, Rosamel P, Desebbe O, Joseph P, Metton O, Bastien O, Lehot JJ. Respiratory variations in pulse oximetry plethysmographic waveform amplitude to predict fluid responsiveness in the operating room. Anesthesiology 2007;106:1105–11
49. Dorlas JC, Nijboer JA. Photo-electric plethysmography as a monitoring device in anaesthesia. Application and interpreta-tion. Br J Anaesth 1985;57:524–30
50. Shamir M, Eidelman LA, Floman Y, Kaplan L, Pizov R. Pulse oximetry plethysmographic waveform during changes in blood volume. Br J Anaesth 1999;82:178–81
51. Chandler JR, Cooke E, Petersen C, Karlen W, Froese N, Lim J, Ansermino JM. Pulse oximeter plethysmograph variation and its relationship to the arterial waveform in mechanically venti-lated children. J Clin Monit Comput 2012;26:145–51
52. Zimmermann M, Feibicke T, Keyl C, Prasser C, Moritz S, Graf BM, Wiesenack C. Accuracy of stroke volume varia-tion compared with pleth variability index to predict fluid
1392 www.anesthesia-analgesia.org aNesthesia & aNalgesia
Predicting Fluid Responsiveness in Children
responsiveness in mechanically ventilated patients undergoing major surgery. Eur J Anaesthesiol 2010;27:555–61
53. Hood JA, Wilson RJ. Pleth variability index to predict fluid responsiveness in colorectal surgery. Anesth Analg 2011;113:1058–63
54. Solus-Biguenet H, Fleyfel M, Tavernier B, Kipnis E, Onimus J, Robin E, Lebuffe G, Decoene C, Pruvot FR, Vallet B. Non-invasive prediction of fluid responsiveness during major hepatic surgery. Br J Anaesth 2006;97:808–16
55. Feissel M, Teboul JL, Merlani P, Badie J, Faller JP, Bendjelid K. Plethysmographic dynamic indices predict fluid respon-siveness in septic ventilated patients. Intensive Care Med 2007;33:993–9
56. Loupec T, Nanadoumgar H, Frasca D, Petitpas F, Laksiri L, Baudouin D, Debaene B, Dahyot-Fizelier C, Mimoz O. Pleth variability index predicts fluid responsiveness in critically ill patients. Crit Care Med 2011;39:294–9
57. Cavallaro F, Sandroni C, Marano C, La Torre G, Mannocci A, De Waure C, Bello G, Maviglia R, Antonelli M. Diagnostic accuracy
of passive leg raising for prediction of fluid responsiveness in adults: systematic review and meta-analysis of clinical studies. Intensive Care Med 2010;36:1475–83
58. Rutlen DL, Wackers FJ, Zaret BL. Radionuclide assessment of peripheral intravascular capacity: a technique to measure intra-vascular volume changes in the capacitance circulation in man. Circulation 1981;64:146–52
59. Fredriks AM, van Buuren S, van Heel WJ, Dijkman-Neerincx RH, Verloove-Vanhorick SP, Wit JM. Nationwide age references for sitting height, leg length, and sitting height/height ratio, and their diagnostic value for disproportionate growth disor-ders. Arch Dis Child 2005;90:807–12
60. Boulain T, Achard JM, Teboul JL, Richard C, Perrotin D, Ginies G. Changes in BP induced by passive leg raising pre-dict response to fluid loading in critically ill patients. Chest 2002;121:1245–52
61. Wong DH, Tremper KK, Zaccari J, Hajduczek J, Konchigeri HN, Hufstedler SM. Acute cardiovascular response to passive leg raising. Crit Care Med 1988;16:123–5
top related