predicting fluid responsiveness in children: a … fluid responsiveness in children: a systematic...

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 [email protected].

mailto:[email protected]

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


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.



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.


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.



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


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?


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?


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.



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


PPV

0

10

20

30

40

0 0.5 1

Sam

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∆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.


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.



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.

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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

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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?


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