Severe Acute Maternal Morbidity and Postpartum Hemorrhage · Severe Acute Maternal Morbidity and...

60Severe Acute Maternal Morbidity andPostpartum HemorrhageA. Vais and S. Bewley

INTRODUCTION

For every woman who dies of postpartum hemorrhage(PPH), many more suffer short- and long-term conse-quences even when well managed. During the 1990s,the concept of severe adverse maternal morbidity(SAMM) emerged in response to the need for a moresensitive marker of quality of maternity care thanmaternal death1,2. This concept and the accompanyingacronym have the advantage of drawing attention tosurviving women’s health and are applicable in bothresource rich and poor countries. As such, SAMM hashad increased interest worldwide over the past 5 years,especially in lower income settings such as Brazil3,Indonesia4 and several African countries5,6; at the sametime, it is highlighted in a WHO report aiming toquantify the global problem7.

The UK is one of the few countries in which everymaternal death has been investigated by the Confiden-tial Enquiry into Maternal Death (CEMD) for sixdecades. In most other developed countries, deathfrom PPH has become too rare for adequate andcontemporaneous surveillance of local services. Forexample, the annual number of maternal deaths fromhemorrhage fell from 40 to three in the UK over thepast 50 years8, and only 14 deaths were attributed tohemorrhage in the 2003–2005 CEMD triennium. Inthe 2006–2008 period which recorded nine deaths,only five were attributable to PPH. Currently, theoverall maternal mortality rate in the UK is around11/100,000 maternities with 0.39 deaths/100,000attributable to hemorrhage, the lowest since theCEMD began in 19529. Obstetric hemorrhagecurrently represents the sixth leading cause of directmaternal deaths in the UK. Despite a rising cesareansection rate, the actual number of deaths from hemor-rhage and genital tract trauma (including ruptureduterus) has declined slightly (although not statisticallyso) or is static. Lower death rates may be due torecommendations made in previous reports.

Within the UK, in 2003 Scotland established anational prospective audit of severe morbidity inparallel to the CEMD. The total SAMM rate variedwith time, ranging from 4.5/1000 births in 2003 to6.2/1000 in 2006, with the rate being 5.88/1000for 2006–200810. This fluctuation is largely due to

changes in the rates of major obstetric hemorrhage(MOH, defined as blood loss of more than 2.5 liters),which initially peaked in 2006 (4.9/1000 live births)and has been declining steadily since to 4.3/1000births. The Scottish authors characterize many cases ofsevere morbidity as ‘great saves’ rather than ‘near-misses’. Although the audit’s threshold for MOH ishigher than most other studies, this survey provides ameans to monitor trends and is more likely to reflectthe burden of severe disease than the extreme ‘tip ofthe iceberg’ represented by death.

WHAT IS SEVERE ADVERSE MATERNAL MORBIDITYAS OPPOSED TO A NEAR-MISS?

The term near-miss was previously used to characterizea case where a woman had a near brush with death; inother words, she would have died were good fortuneand medical care not on her side. This characterizationwas also used for women with severe organ dysfunctionor organ failure who survived11,12 whereby, with inten-sive medical intervention, a maternal death was avoidedand a survival ensued13. The term SAMM was laterintroduced to refer to the morbidity a woman actuallysuffers, rather than focusing on the fact that she nearlydied (which may still be more important from a riskmanagement point of view). Recently, the WHOworking group on Maternal Mortality and Morbidityrecommended a return to the near-miss terminology,referring to the fact that the woman ‘nearly died butsurvived’7. Our review for this chapter shows that thetwo terms, SAMM and near-miss, are currently beingused interchangeably in the literature.

Three different definitions for SAMM have beenproposed by various authors7:

● A severe life-threatening obstetric complicationnecessitating an urgent medical intervention toprevent the likely death of the mother14

● Any pregnant or recently delivered woman, inwhom immediate survival is threatened and whosurvives by chance or due to the hospital care shereceived15

● A very ill woman who would have died had it notbeen that luck and good care was on her side11.

499

Attempting to unify these differences, WHO defines amaternal near-miss as: a woman who nearly died but sur-vived a complication that occurred during childbirth or within42 days of termination of pregnancy7. This simplifies theconcept and attaches a useful time-frame. However, itexcludes complications in pregnancy that do not leadto delivery (such as septicemia, pulmonary embolusor cardiac arrest); moreover, it does not generate auniversal system for case identification which wouldfacilitate cross-country comparisons.

The three definitions cited above clearly are similarand illustrate the concept of a continuum of worseningmorbidity in the pregnant population, culminating inmaternal death. The disease pyramid illustrates thisconcept (Figure 1) by which the base represents thegeneral pregnant population, and the ‘tip of the ice-berg’ is maternal death with a spectrum of morbiditybetween11,12,16. A clinical insult may be followed by asystemic response and subsequent organ dysfunction,which leads to organ failure and eventual death2,11.The figure shows the severity continuum of morbidityas well as factors that move women up and down thepyramid. For example, a faulty ambulance or wronglycross-matched blood might lead to an anemic womandying of hemorrhage unnecessarily. If the same patienthad been provided iron supplementation antenatally,was well managed and treated promptly, there may beno residual morbidity. On the other hand, pathologiessuch as placenta previa and uterine rupture woulddrive women up towards the tip of the pyramid. Inter-ventions such as uterotonics might stop bleeding at anearly stage, whereas interventions such as obstetrichysterectomy may be used near the top.

Despite the different definitions of MOH, studieshave used three main approaches for case identifica-tion (outlined in Table 1). Each approach has advan-tages and disadvantages:

(1) Specific disease entities (e.g. eclampsia, PPH)allow relatively easy retrospective data collectionfrom case notes or registers. Quality of care andcomplication rates can be determined for thespecific disease and set against standards of care.However, it is difficult to use this for ongoingaudits. There may be poor documentation in theworst cases and morbidity criteria may have toolow a threshold to be considered a near-miss.

(2) Intervention-based criteria are easily measured andagreed, do not rely on medical diagnosis andcoding, but are affected by local units’ differentfacilities, policies, customs and practices, as well asthresholds for transfer (e.g. use and availability ofhigh dependency/intensive-care beds or inter-ventional radiology).

(3) The main advantage of an organ system dysfunc-tion approach is that it allows mortality and mor-bidity surveys to run in parallel, thus enablingcalculations of morbidity : mortality ratios for var-ious disease processes. The Scottish MorbiditySurvey is an example, and its findings have beenreported in parallel to the CEMD. Trends in dis-eases can be established. This approach alsofocuses on diseases which should not cause death ifappropriately managed (e.g. PPH). However,cases can only reliably be identified prospectivelyand depend on investigative test availability.

500

POSTPARTUM HEMORRHAGE

Figure 1 A representation of the morbidity–mortality continuum. ACOG, American College of Obstetricians and Gynecologists; BMI,body mass index; IVF, in vitro fertilization; NICE, National Institute for Health and Clinical Excellence; RCOG, Royal College ofObstetricians and Gynaecologists2,24

Rates may be biased if ascertainment problems arepresent. A diligent unit may report more cases via theorgan-system approach, and careful recording couldtranslate into a disproportionately higher rate ofSAMM12. On the other hand, a poor-quality unit thatdoes not recognize and treat hemorrhage promptlymay have more severe sequelae as the natural historyprogresses. Thus the true incidence of SAMM may beunderestimated.

HOW COMMON IS ALL-CAUSE SEVERE ADVERSEMATERNAL MORBIDITY?

Because quantification is problematic, with no inter-national definition and haphazard recording, widevariations are present in incidence estimates (summa-rized in Table 2).

High income countries

A recent review including studies from Europe,Canada and USA suggested the incidence of SAMMto approximate to 0.5–1% of all deliveries in highincome countries (3.3–12/1000)35. The rates/1000births ranged from 3.3 in France, through 3.8 inScotland, 4.6 in Canada, 7.2 in The Netherlands, 10.9in South Africa to 12.0 in England.

Low income countries

A 2009 review grouped low income countries intothose of Africa, Latin America and Asia36, andincluded landmark audits of severe morbidity in SouthAfrica11,37. Thirty-seven studies from 24 countries

were examined, ranging from small audits of near-missmorbidity5,11,37,38 in general and teaching hospitals, tolarge population based surveys37,39,40 or surveys ofneed for life-saving surgery (Tanzania, Guinea, Indo-nesia)36. Comparisons are difficult, however, becauseall women do not give birth in health facilities andstandards vary widely (e.g. availability of ITU beds).African studies exemplified these wide variations. Therate of severe morbidity across several West Africanstates was calculated as 59.8/1000 deliveries (almost6%)39, whilst contemporaneous studies in South Africayielded rates of 1%11,37, falling to 0.5% in 200441, arate which is similar to that in high income countries.

In low income settings, major surgical interventionssuch as cesarean section or hysterectomy are likely tobe accurately recorded and may be useful markers ofsevere morbidity. One way to quantify the need forlife-saving surgery is by cesarean section for absolutematernal indications (severe antepartum hemorrhagedue to placenta previa, major cephalopelvic dispropor-tion, transverse lie or brow presentation). In settingswithout ITU facilities, a combination of life-savingsurgery and organ dysfunction approaches are likely towork best, as evidenced by studies in Brazil3 andIndonesia36. Using transfused blood has limitations asthresholds for transfusion vary, blood may not beavailable in low income settings or women may refusetransfusion (e.g. Jehovah’s Witnesses).

RELATIONSHIP OF SEVERE ADVERSE MATERNALMORBIDITY TO MORTALITY

Two methods generally are used to address therelationship between severe morbidity and mortality.

501

Severe Acute Maternal Morbidity and Postpartum Hemorrhage

Criteria for identification ofnear-miss Case definition Study

Related to specific disease Starting point is a specific disease and morbidity is defined for each. For example,pre-eclampsia might be the disease with severe morbidity identified by itscomplications (i.e. renal failure, pulmonary edema, eclampsia, etc.)

Can be prospective or retrospective

Waterstone et al., 200117

Scottish survey, 2003 ongoing18,19

LEMMoN, 200820

UKOSS, 2005 ongoing21

Intervention based Marker for near-miss is an identifiable event or procedure (e.g. admission to ITU,large blood transfusion or emergency hysterectomy) to save the mother’s life

Usually retrospective studies

Bewley & Creighton, 199713

Killpatrick & Matthay, 200222

LEMMoN, 200820


Obstetric hysterectomy studies23,24

Based on organ-systemdysfunction

System is based on the concept of the pyramid of disease from good health to death.A clinical insult is followed by a systemic response syndrome, then organdysfunction, organ failure and death. Near-miss cases are the women with organdysfunction or failure who survive. Markers for dysfunction for each organ systemare specified and criteria for defining a near-miss are given ( e.g. cardiovascularshock from hemorrhage)

Usually prospective studies

Mantel et al., 199811

Pattinson et al., 200312

Waterstone et al., 200117

Scottish survey, 2003 ongoing19

Rare event A rare event allows large, even national, population estimates.UKOSS, for example, has studied risk factors (e.g. BMI >50), specific diseases (e.g.

swine flu, amniotic fluid embolism), complications of obstetric morbidity (e.g.acute fatty liver) or treatment (e.g. extraordinary interventions for massivehemorrhage – hysterectomy, factor VII, intrauterine balloon, brace suture).

The disadvantage is the inability to examine common severe morbidities

BEST study, 1995 (eclampsia)25

Waterstone et al., 2001 (uterinerupture as rare event)17


Obstetric hysterectomy studies23,24

BMI, body mass index; UKOSS, UK Obstetric Surveillance System

Table 1 Different methodological approaches to the identification of cases of SAMM

502


Stud

y,co

untry

and

year

ofpu

blica

tion

Incid

ence

ofSA

MM

per1

000

deliv

erie

s(a

llca

uses

)

Incid

ence

ofhe

mor

rhag

e/10

00de

liver

ies

(%of

tota

lSA

MM

)

Incid

ence

ofhy

perte

nsio

n(%

ofto

tal)

Incid

ence

ofse

vere

seps

is(%

ofto

tal)

Add

ition

alco

mm

ents

Ston

eset

al.1

UK

1991

8.8

3.23

(36.

8%)

2.77

(31.

5%)

Not

avai

labl

eSA

MM

defin

edas

‘pot

entia

llylif

e-th

reat

enin

gep

isode

s’.In

cide

nce

for

tota

l(al

l)m

orbi

dity

267/

1000

.Inc

iden

ceof

alls

epsis

30.5

/100

0(s

ever

ese

psis

nots

epar

ated

).H

emor

rhag

ein

clud

esan

tepa

rtum

and

PPH

ifov

er20

00m

l.O

neca

seof

seco

ndar

yPP

Hdu

eto

seps

is

Bou

vier

-Col

leet

al.26

Fran

ce19

96

3.1

0.62

(20%

)0.

81(2

6.2%

)0.

14(4

.36%

)T

hird

high

estc

ause

ofm

orbi

dity

isem

bolic

even

tsat

0.38

/100

0.H

emor

rhag

ein

clud

esut

erin

eru

ptur

e.H

yper

tens

ive

dise

ase

incl

udes

cere

bral

hem

orrh

age

Bew

ley

&C

reig

hton

13

UK

1997

4.97

2.3

(46.

7%)

1.98

(40%

)0.

49(1

0%)

SAM

M=

ITU

adm

issio

n.T

otal

30ca

ses

ofSA

MM

.14

case

scl

asse

das

hem

orrh

age

(blo

odlo

ss>

2000

mlb

uta

furt

her

2ca

ses

DIC

/HE

LLP

sopr

opor

tion

due

tohe

mor

rhag

eco

uld

be>

50%

)

Bas

kett

&St

erna

del27

USA

1998

0.72

0.16

(22%

)0.

18(2

5%)

0.1

(14.

5%)

SAM

M=

ITU

adm

issio

n

Man

tele

tal.11

Sout

hA

fric

a19

98

10.9

6.1

(55.

8%)

2.82

(25.

8%)

2.16

(19.

7%)

Seps

isin

corp

orat

esse

ptic

abor

tion,

chor

ioam

nion

itis

and

puer

pera

lsep

sis.H

emor

rhag

ein

corp

orat

esan

tepa

rtum

and

PPH

and

emer

genc

yhy

ster

ecto

my;

PPH

alon

eis

1.8/

1000

Prua

leta

l.15

Wes

tAfr

ica

2000

50.8

29.6

(49.

5%)

6.15

(10.

3%)

0.9

(1.5

%)

Obs

truc

ted

labo

ris

signi

fican

tcau

sefo

rse

vere

mor

bidi

ty(2

0.5/

1000

ofw

hich

1.2/

1000

uter

ine

rupt

ure)

Wat

erst

one

etal

.17

UK

2001

12.0

6.7

(55.

7%)

4.6

(38%

)0.

35(2

.89%

)C

linic

ally

base

dde

finiti

ons,

noti

nclu

ding

man

agem

entp

roce

sses

.Est

imat

edbl

ood

loss

>15

00m

lpic

ked

up55

%of

case

sof

SAM

Mdu

eto

hem

orrh

age

Bra

ceet

al.18

Scot

land

2004

3.8

1.9

(50%

)1.

15(3

0%)

0.09

(3%

)Se

ptic

shoc

kis

the

only

cate

gory

for

seps

is.N

umbe

rof

SAM

Mdu

eto

hype

rten

sive

dise

ase

deri

ved

byad

ding

the

num

ber

ofca

ses

with

ecla

mps

ia,r

enal

dysfu

nctio

nan

dpu

lmon

ary

edem

a.O

nly

one-

thir

dof

patie

nts

with

SAM

Mw

ere

adm

itted

toIT

U

Zha

ng28

MO

MS-

BE

urop

e20

05

9.48

4.6

(48.

8%)

4.33

(45.

7%)

0.8

(8.2

%)

Mul

tinat

iona

lstu

dy,r

ates

diffe

ring

wid

ely

betw

een

coun

trie

s.R

ange

ofSA

MM

6–14

.7%

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hest

rate

sin

Finl

and,

Bel

gium

,UK

and

low

estr

ates

inIt

aly,

Irel

and,

Fran

ce

Min

kaus

kien

eet

al.29

Lith

uani

a20

06

7.91

2.83

(35.

8%)

4.47

(56.

6%)

0.3

(3.8

%)

13,3

99de

liver

ies,

106

case

sSA

MM

,1de

ath

60ca

ses

hype

rten

sion

(57

seve

rePE

T,3

ecla

mps

ia),

38se

vere

hem

orrh

age,

4ca

ses

seve

rese

psis,

3ca

ses

uter

ine

rupt

ure

Tab

le2

SAM

Mst

udie

ssh

owin

gin

cide

nce

and

prop

ortio

nre

late

dto

hem

orrh

age

503


Zw

arte

tal.20

LeM

MoN

Net

herla

nds

2008

7.1

4.5

(63%

ofto

tal,

47%

ofIT

Uad

miss

ions

)

0.62

(ecl

amps

ia8.

7%of

tota

l)

0.23

(3.3

%of

tota

l,10

%w

ere

due

togr

oup

Ast

rept

ococ

cus)

5ca

tego

ries

for

SAM

M(I

TU

adm

issio

n,ut

erin

eru

ptur

e,ne

edin

gce

sare

an/h

yste

rect

omy

orla

paro

tom

y,ec

lam

psia

/HE

LLP,

maj

orhe

mor

rhag

ene

edin

gtr

ansfu

sion

orhy

ster

ecto

my

and

grou

pof

othe

rse.

g.se

psis,

pre-

ecla

mps

ia).

27%

ofM

OH

adm

itted

toIT

U.M

OH

coun

ted

asse

para

tegr

oup

buta

lsoa

surg

ery

grou

p(s

ome

for

rupt

ure

orhy

ster

ecto

my,

i.e.i

mpl

ies

hem

orrh

age,

sora

teof

MO

Hm

aybe

unde

rest

imat

e)

UK

OSS

19,3

0

UK

2005

–201

1

0.41

peri

part

umhy

ster

ecto

my

0.26

2nd

line

trea

tmen

t

0.27

(in20

05)

Not

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ofra

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–sy

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udie

dat

diffe

rent

times

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isno

tcon

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lcau

ses.

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nd-l

ine

trea

tmen

tsfo

rM

OH

are

com

pres

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ssel

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ion,

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Indo

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2009

141.

612

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ngsu

rger

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;34%

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32(1

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rura

land

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ery

(e.g

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ordy

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aco

mm

onca

use

for

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ngsu

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ybu

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etal

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New

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4.99

12(4

1.4%

)8

(27.

6%)

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ptic

emia

(17.

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SAM

M=

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adm

issio

n.St

udy

duri

ng20

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days

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otal

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ses

inte

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usin

gor

gan-

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case

s,9

hyst

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ies.

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erte

nsio

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clud

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ghbl

ood

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case

sbu

tthe

rear

eal

soso

me

CV

As

coun

ted

sepa

rate

ly.S

ame

crite

ria

asB

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ight

on13

,cas

esco

uld

have

mor

eth

anon

em

orbi

dity

Alm

erie

etal

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Syri

a20

10

32.9

11(3

4.4%

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(52%

)0.

9(2

.8%

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etro

spec

tive

revi

ewof

near

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and

mat

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lmor

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ate

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ryho

spita

lin

Dam

ascu

s20

06–2

007.

28,0

25de

liver

ies,

15de

aths

,901

near

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case

s.M

MR

=54

.8/1

00,0

00liv

ebi

rths

,mor

talit

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dex

1.7%

.Mos

tcas

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ferr

edin

criti

calc

ondi

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from

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(tra

ditio

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ts,h

omes

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vate

prac

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imar

yan

dse

cond

ary

care

units

).26

%of

near

-miss

case

sad

mitt

edto

ITU

.Hem

orrh

age

acco

unte

dfo

r60

%of

mor

talit

yca

ses.

Rat

esar

egi

ven

per

1000

live

birt

hsra

ther

than

deliv

erie

s.Se

psis

and

dyst

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are

unco

mm

onca

uses

ofne

ar-m

issbu

thig

hm

orta

lity

indi

ces

(7.4

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9%,r

espe

ctiv

ely)

Lenn

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These are the mortality-to-morbidity ratio and the mortal-ity index. The mortality-to-morbidity ratio simplydescribes the number of severe morbidity cases foreach maternal death2,17. The mortality index, on theother hand, is defined as the number of maternaldeaths divided by the sum of women with SAMM andmaternal deaths, and is expressed as a percentage12,37.Both can be expressed as totals (all-cause) or by condi-tion. Both reflect the fatality of a condition and iden-tify those conditions that are more or less amenable tointervention. Recently WHO have introduced a newset of definitions (see text box below).

In general, the risk of mortality depends on (1) theprior health of the mother, (2) the severity of theparticular condition, (3) access to skilled help, and (4)the availability and quality of medical intervention.PPH is the morbidity par excellence for assessing theseparameters. It is common and has a high morbidity-to-mortality ratio (or low mortality index)2,12,17,37. Indeveloped countries, at least, this is because the condi-tion is amenable to treatment. More women’s lives canbe, and indeed are being, saved daily by the provisionof adequate maternity services worldwide. As hemor-rhage is largely treatable (and often avoidable), andbecause all parturients are at risk, it is tragic that so manywomen still die unnecessarily worldwide. The United

Nations discusses women’s and children’s health interms of fundamental human rights43. Progresstowards Millennium Development Goal 5 (MDG 5, a75% reduction in maternal mortality 1990–2015) hasbeen disappointing44 as only 23/181 (13%) countriesanalysed are on track to achieve the target45.

What are the main causes of SAMM?

Most cases of SAMM fall into three major categoriesof causation:

● Hemorrhage

● Hypertensive diseases of pregnancy (includingeclampsia and HELLP syndrome)

● Sepsis.

The incidence of these conditions in European coun-tries appears similar despite the use of different defini-tions. Regardless of geographical factors, hemorrhageis the largest contributor, accounting for between20%26 and 50%11,18,39 of cases. Hypertensive diseaseand its consequences account for 10%39 to 45%28,whereas morbidity secondary to sepsis is much lower,at 1.5%39 to 20%11. Rarer causes of SAMM includethromboembolic disease and psychiatric illness46,47.

504


NEW WHO TERMINOLOGY

WHO has recently published a document aimed atproviding a universal framework for defining andcounting severe morbidity. The near-miss definitionis the same as was used in 20097. New terms whichare outlined below have been introduced, with theaim of unifying the near-miss and severe morbidityconcepts, whilst recognizing the morbidity ortalitycontinuum as described in Figure 1.

Women with life-threatening conditions(WLTC) = maternal near-misses (MNM) + mater-nal deaths (MD)

Severe maternal outcome ratio (SMOR) =WLTC (MNM + MD) per 1000 live births; thisgives an estimate of the amount of care and facilitiesthat may be needed in an area or facility

MNM ratio (MNMR) = number of near-misscases per 1000 live births; can also be used to estimatethe amount of care or resources needed

Maternal near-miss mortality ratio (MNM : MD)is the ratio of near misses to deaths as MNMR previ-ously described. Higher ratios would indicated bettercare as more lives are being saved

Whilst the concepts of SMOR and MNMR areuseful from a resource planning perspective, compar-isons between high and low resource settings remaindifficult to make. For example, for PPH the opera-tional definition for severe morbidity is blood lossmore than 1000 ml and standard of care implies thatall women receive 10 IU Syntocinon for third stage.

In a low-resource setting, a woman with a borderlinestarting hemoglobin in a facility lacking drugs tomanage the third stage and no access to transfusionwill create a case of severe morbidity at 1 liter bloodloss. Conversely, in a developed country the standardof care would be met simply by the routine use ofSyntocinon; a woman with a normal hemoglobincan lose 1000 ml without any significant morbidity.Comparisons based on volume loss alone mayencourage complacency in such settings where theminimum intervention set by WHO is already rou-tine and the severe morbidity occurs at bigger vol-umes of blood loss, increased interventions, ITUcare, etc.

The same working party encourages the develop-ment of ongoing audit of severe morbidity cases in allhealth facilities, at local and district level. The aim ismainly for resource planning but also to enable com-parisons regarding quality of care. The appendicesand checklists provide useful practical tools forimplementing an international audit strategy forsevere maternal morbidity. They estimate the globalprevalence to be around 7.5 per 1000 deliveries, butas shown in Table 2, the worldwide prevalence ismore widely spread. Ongoing audit using this uni-versal tool at local and national level would providevaluable information about quality of care andresource planning in different settings, but does notmake comparisons across resource brackets (high andlow) any easier42.

WHAT IS THE INCIDENCE OF SEVERE ADVERSEMATERNAL MORBIDITY ATTRIBUTABLE TOHEMORRHAGE?

Hemorrhage illustrates the difficulties faced with definingnear-miss or severe morbidity. All women experiencesome blood loss at delivery. The amount is difficult tomeasure, and often mixed with amniotic fluid. Hemor-rhage is a clinical insult that strikes the general pregnantpopulation, both low and high risk. Whether due toatony, retained placenta or genital tract lacerations it hasthe potential to cause morbidity ranging from mild tosevere or even death (Figure 1). In addition, specificbleeding causes rapidly endanger women (e.g. rupturedectopic, ruptured or inverted uterus, massive abruptionor morbid placental adherence).

Table 2 summarizes some of the landmark studiesthat have attempted to quantify this problem in devel-oped countries over the past 15 years. Wide variationsare present in study settings, definitions and maincauses. Some studies use admission to ICU22,48, othersdefine the actual conditions responsible for the mor-bidity11,12, and still others list both13. The wide varia-tion in case definition might explain the extreme rangeof incidence of SAMM (4% in UK to 53% in HongKong for studies using retrospective ITU admissionto define SAMM; 1–6% incidence in prospectivemulticenter studies). Regardless of such differences,most studies concluded that up to half of the cases ofSAMM were related to hemorrhage, and this contin-ues to be the case in recent investigations (Table 2).

World Health Organization has set somematernal near-miss criteria7 which aim to incorporate

life-threatening clinical signs (e.g. cyanosis, shock,increased respiratory rate) and investigational results(e.g. oxygen saturation, pH, lactate) as well as life-saving interventions (e.g. hysterectomy, transfusion)into an algorithm that ensures severe cases are notmissed. Worldwide adoption of this definition wouldidentify all the cases of SAMM regardless of incitingcondition but would not facilitate international com-parisons between disease processes. This is because dif-ferent pathologies can lead to the same clinical sign(e.g. raised respiratory rate in shock from hemorrhageas well as pulmonary embolus). A pragmatic proformafor case identification relating to SAMM secondaryto hemorrhage would include all aspects shown inTable 342.

RISK FACTORS FOR SEVERE ADVERSE MATERNALMORBIDITY DUE TO HEMORRHAGE

Although it is challenging to define the size of theproblem (i.e. the incidence of SAMM as a result ofhemorrhage), Table 4 summarizes risk factors identi-fied over the past 10 years that increase the risk ofsevere hemorrhage.

Some risk factors, such as previous PPH or manualremoval of placenta, are intuitive and universal.Induction of labor appears to increase the risk of PPHregardless of the indication17. This may relate to anincreased duration of labor or risk of sepsis. Anemia islikely to be more prevalent in low income countries aswell as in recent immigrants and ‘socially excluded’women in high income countries as a reflection of

505


Category Parameters Advantage Disadvantage if used alone

Actual blood loss EBL >1500–2000 ml (or more) Measured and measurable Accurate quantification notoriously difficult

Clinical symptoms Dizziness, faintnessAgitation, thirst, collapseCardiac arrest

Easy to measureCheapApplicable in low resource settings

Tolerance depends on mother’s size, pre-existingtotal blood volume and pre-delivery hemoglobin

Antenatal anemia will cause morbidity out ofproportion to actual blood loss

May be non-specific to hemorrhage; thus aidsrecognition but difficult to audit management ifused alone

Clinical signs Pulse >100 orSystolic BP <80 mmHgRespiratory ratePeripartum fall in hemoglobin

Blood productreplacement

Packed red cells >4 or >5 unitsUse of FFP/clotting factors

Measurable Product availabilityChanging guidelines re: ratios of transfusing blood

and FFPJehovah’s Witnesses and others who refuse blood

Specific life-threateningconditions

AbruptionUterine ruptureMorbid placental adherencePlacenta previaInfection

Diagnosis is fixed once madeComparisons of rates can be made

Varying degrees of severityCan have several causesManagement and thus degree of morbidity

dependent on local resources

Interventions whichimply severehemorrhage

Balloon tamponadeCompression suturesHysterectomyInterventional radiologyUse of factor VII

MeasurableEasy to identify cases both

retrospectively and prospectively

Availability dependent on setting and expertise ofpersonnel

Timeliness of intervention decreases severity ofmorbidity so use itself does not demonstratestandard of care

ITU/HDU admission Ventilatory supportRequirement for inotropes

AuditableEasy case identification

Availability depends on clinical setting

BP, blood pressure; EBL, estimated blood loss; FFP, fresh frozen plasma; HDU, high dependency unit; ITU, intensive therapy unit

Table 3 A pragmatic proforma for case identification relating to SAMM secondary to hemorrhage would include all these aspects

poorer nutrition. Waterstone et al.47 defined socialexclusion as a composite measure of a woman’s socialdeprivation beyond the traditional use of her maritalor partner’s employment status or postcode depriva-tion score. The definition included concealed preg-nancy, age less than 16 years, poor housing, ‘onincome support’ (state welfare benefit) written in thenotes, previous minor or child in local authority orstate care (currently or in the past), in trouble with thelaw (currently or previously), living alone, unbooked,unwanted pregnancy, currently or previously in fostercare, care order being considered on potential child,social worker involved or drug or alcohol dependency.

Other studies in countries such as the USA49, Brazil3and Uganda50 have found a similar trend. Kaye et al.50

defined women of ‘low status’ by a composite of pooreducation, poverty, low antenatal care attendance, lowcontraceptive-ever use and little power to make deci-sions regarding access to health care. Souza et al.31

referred mainly to the woman’s educational achieve-ment, with women educated to high school level hav-ing a lower risk of severe morbidity.

IS THE PREVALENCE OF SEVERE ADVERSEMATERNAL MORBIDITY SECONDARY TOHEMORRHAGE RISING?

Health services need to monitor trends of various dis-eases as well as the actual morbidity suffered or deathscaused. It is plausible that disease burden can be risingor falling at the same time as outcomes are improvingwhich would have implications for service provision.There are only a few register-based studies that trackrates of SAMM; these are located in Canada51,Finland52 and USA53.

In 2009 an international group explored trendsin PPH in several high-resource countries (Australia,Belgium, Canada, France, UK and USA)54. Lookingat risk factors for SAMM secondary to hemorrhage(Table 4), it is not surprising that rates of severe PPHare increasing as childbearing women are older andmore obese, with more multiple pregnancies andcesareans in high income countries. Maternal mortal-ity rates, however, were largely static in these samesettings. However, markers of severe hemorrhage(uterine rupture, hysterectomy) were increased35.Knight et al.54 compared data in several high incomecountries (Australia, Belgium, Canada, France, UKand USA) from the early 1990s with those of early 21stcentury and found that rates of hysterectomy foratonic PPH increased from 24/100,000 deliveries in1991 to 41.7/100,000 deliveries in 2004.

Canada

The rate of SAMM appears similar between the earlyand late 1990s (4.4/1000 births in 1991–1993 vs.4.25/1000 births 1998–2000)35. However, Sheehan’ssyndrome increased 4-fold in Canada over the same10 years, suggesting that the severity of PPH hadincreased. Also, the rate of peripartum hysterectomyincreased by 73% from 24/100,000 births in 1991 to41.7/100,000 births in 200454. Another retrospectiveCanadian cohort study57 looked at all hospital deliver-ies between 1991 and 2004, identifying a 34% increasein atonic PPH from 29.4/1000 deliveries in 1991 to39.5/1000 in 2004. The authors could not find asatisfactory explanation for the increased rate.

Finland

The overall rate of severe morbidity increased from5.9/1000 births in 1997 to 7.6/1000 births in1999–200235.

506


Risk factorOdds ratios for SAMM

(95% CI) Study/Country/Year

Age >35 years 1.41 (1.03–1.95)1.2 (1.1–1.3)/(1.4 if >40)

1.02 (0.96–1.09)1.14 (1.03–1.21)

Waterstone et al./UK/200117

Zwart et al./Netherlands/200820

Ford et al./Australia/200755

Al-Zirqi et al./Norway/200856

Hypertension atbooking

1.18 (1.06–1.31)1.33 (1.07–1.66)



Ethnic minority 1.82 (1.09–3.03)1.3 (1.2–1.5) non-

Western immigrants1.16 (1.1–1.22)1.77 (1.48–2.12)




Al-Zirqi et al./Norway/2008(SE Asian ethnicity)56

Social exclusion 2.91 (1.76–4.82)2.18 (1.15–4.10)


Souza et al./Brazil/20073

BMI >30 1.5 (1.3–1.7) Zwart et al./Netherlands/200820

Previous PPH 2.74 (1.69–4.44) Waterstone et al./UK/200117

Multiplepregnancy

2.29 (1.2–4.37)4.9 (4.3–5.7)

2.34 (2.02–2.7)




Anemia 5.98 (2.28–15.65)2.2 (1.63–3.15)



Oxytocinaugmentation

1.61 (1.2–2.15) Waterstone et al./UK/200117

IOL 2.45 (1.68–3.57)3.1 (2.8–3.4)

1.5–2.42 (spontaneousvs. instrumental)1.6 (1.46–1.75)





Manual removalof placenta

13.12 (7.72–22.30) Waterstone et al./UK/200117

Emergency CS 3.09 (2.29–4.17)5.2 (4.8–5.6) all CSs0.81 (0.7–0.92) CS

in spontaneous labor3.61 (3.28–3.95)





Instrumentaldelivery

1.6 (1.4–1.71)1.87 (1.4–2.42)1.25 (1.1–1.42)




Birth weight>4.5kg

1.93 (1.71–2.17)2.55 (2.15–3.03)



BMI, body mass index; CS, cesarean section; IOL, induction of labor

Table 4 Risk factors for major obstetric hemorrhage

Scotland

An ongoing prospective audit since 2003 uses theorgan-system definitions generated by Mantel et al.11.The Scottish survey uses a cut-off of 2500 ml or morefor defining MOH, which is higher than most otherstudies, probably for pragmatic reasons and ease ofdata collection. The mortality : morbidity ratio hasimproved from 1 : 56 in 2003 to 1 : 79 in 2008; thischange reflects an increase in the rate of MOH but norise in deaths. Over half of the cases of MOH wereassociated with cesarean section (55.2% for all cesareansections, 44.3% emergency cesarean sections), ofwhich 20% were deemed of an emergency nature andperformed in the second stage. In the same nationalaudits, the rate of peripartum hysterectomy showed asteady decline between 2003 and 2008, as other con-servative surgical techniques such as brace sutures andballoon tamponade were increasingly used10.

Australia

A population-based survey of 752,374 womendelivering between 1994 and 2002 in New SouthWales, the most populous region in Australia, notedan increased rate of total PPH (defined as 500 ml atvaginal delivery and 750 ml at cesarean section) from4.7 to 6.0/1000 births. This rate appeared to increasemore after vaginal delivery. The authors postulatedthis may be due to use of Syntocinon rather thanSyntometrine for third stage management. It is, how-ever, concerning that PPH increased despite a slightreduction in the delivery rate55.

USA

Overall morbidity increased from 4.5/1000 deliveriesduring 1991–1994 to 5.9/1000 in 1999–200335.Another study58 showed an increase in severe obstetriccomplications from 0.64% in 1998–1999 to 0.81%in 2004–2005. Amongst causes of severe morbiditythere was a 24% increase in cases of shock and 92%increase in transfusion rates. These increases are partlyexplained by a rising cesarean delivery rate, althoughadjustment for mode of delivery rendered differencesstatistically insignificant.

Ireland

A population study based on 649,000 deliveries hasfound a three-fold increase in PPH rate within adecade in the Republic of Ireland from 1.5% in 1999to 4.1% in 200959. This trend was observed for bothvaginal and cesarean deliveries and was not whollyexplicable by demographic changes (i.e. advancingmaternal age or multiple birth), or by increased cesar-ean section rates59. The increase was largely related toincreased atonic PPH rates, unlike the Australiandata55 where the highest rate was among cesareansection deliveries.

SPECIFIC CAUSES OF SEVERE ADVERSE MATERNALMORBIDITY RELATED TO HEMORRHAGE

Uterine rupture

Although this diagnosis can be one surrogate measurefor SAMM due to hemorrhage, studies report it differ-ently. For example, it has been combined with data forobstructed labor in South Africa39, and analysed as acause of hemorrhage in a French study26. Waterstoneet al.17 in the UK considered uterine rupture as a sepa-rate entity, which is a more accurate means of usingthese data unless there is clear evidence of the bloodloss associated with each case. These authors found arate of 1 : 4000 deliveries (0.025%). Studies in highincome countries suggest low rates of uterine rupturecausing SAMM which range from 0.002%60 through0.017%21 to 0.06%20.

A systematic review of the literature published in2005 examined 83 studies concerning uterine rupturebetween 1990 and 200561. Prevalence was higher indeveloping than developed countries. In all countries,rupture affected 1% of women with previous cesareansection. This same trend was found by the UK Obstet-ric Surveillance Survey (UKOSS) study undertaken in2010, where 86% of ruptures occurred in women witha previous cesarean section. The 2005 review foundvariable rates of rupture across the world, especiallywhen studies were conducted in developing countries;in these settings women may die unattended out ofhospital, and studies were less likely to distinguishwomen with scarred and unscarred uteri. Rates ofrupture were lowest in developed countries and inwomen without a uterine scar (0.006%, rising to 1% inwomen with scarred uteri). In contrast, in the leastdeveloped countries rates of rupture could be as highas 25% (one study of 945 women in Ethiopia in the1990s) and mostly associated with obstructed labor;75% of cases of uterine rupture in Africa and Asia werefound to occur in unscarred uteri. In low-resourcesettings rupture is associated with a high maternalmortality which ranges from 1 to 13% and a very highperinatal mortality (74–92%)61. The WHO reviewsuggests that reducing rupture rates in these popula-tions would require a focus on reducing unwantedpregnancies, especially in women of high parity,accessibility of services and cesarean sections forobstructed labor and adequate guidelines for safe use ofmisoprostol as an induction agent61.

Data from Australia and Northern Europe also sug-gest that rupture is a rare event in developed countries,but the rate is increased by induction of labor20,56.

Peripartum hysterectomy

Obstetric hysterectomy provides another means ofexamining SAMM associated with PPH and has theadvantage of being more clearly defined, and rareenough for data to be easily collected. The thresholdfor performing hysterectomy clearly varies with theoperator, unit and individual case, but evidencesuggests that early hysterectomy decreases both

507


morbidity62 and mortality63. The several studies thathave examined the incidence of peripartum hysterec-tomy as a marker of SAMM from hemorrhage arelisted in Table 5. Population studies between 1986 and2005 yielded rates of 0.3–1.55 hysterectomies/1000deliveries23. More recent rates of 0.33 and 0.77/1000deliveries have been reported in The Netherlands20

and the US64. The largest population study from theUK showed an incidence of 0.41/1000 deliveries30.

Table 5 also shows that the main causes of bleedingleading to hysterectomy are atony (30–50%) andadherent placenta (38–40%). Recently, more conser-vative treatment modalities for PPH have been intro-duced, but the hysterectomy studies show that eventhese can fail to arrest bleeding. Failed brace sutureswere found in 25% of cases in the UK30, whilst aDutch study showed that 9.7% and 13% of cases ofhysterectomy followed intrauterine balloon tampon-ade and uterine artery embolization, respectively20. Itis difficult to draw meaningful conclusions regardingfailed conservative measures as there are no standard-ized guidelines for use before proceeding to hyster-ectomy nor are there established guidelines for thetimely use of either the brace suture or the balloon.For example, if bleeding has proceeded for a long timeprior to institution of therapy, the likelihood that it isaccompanied by some degree of coagulopathy (dis-seminated, dilutional or both) is high (see Chapter 5).Practicing clinicians regularly counsel women regard-ing the risk of hysterectomy after cesarean section forplacenta previa. Studies suggest that the combinationof multiparity, history of previous cesarean section anddelivery by cesarean section should alert the obstetri-cian to a significant risk of hysterectomy secondary toplacenta accreta/percreta. Combining the odds ratiosgenerated individually by the UKOSS case–controlstudy for these three conditions, the risk could be over50 times that of the normal pregnant population.

OUTCOMES OF WOMEN WHO SUFFER SEVEREADVERSE MATERNAL MORBIDITY

Few studies follow up outcomes beyond survival andimmediate morbidity. Studies of postnatal morbidityin general populations (low- and high-risk womenanalysed together) found that problem prevalence ishigh and persists for a prolonged period of time afterdelivery47,65. Glazener et al.65 looked at a random sam-ple of deliveries (high and low risk) in a teaching hos-pital in Scotland and showed that 87% of womensuffered at least one health problem after delivery andin 76% problems persisted for 2 months postpartum.Problems ranged from urinary or bowel problems toperineal pain or breakdown, breast problems andpersistent vaginal discharge. A case–control study ofoutcome 6–12 months postpartum compared womenwho had and had not suffered SAMM47. Cases weretwice as likely to attend accident and emergencydepartments, possibly related to the underlying mor-bidity and its follow-up, but this circumstance clearlypoints to a continuing burden on health services with

personal, family and economic costs. Cases also suf-fered slightly more postnatal depression than controls(who were not entirely ‘normal’ as they includedwomen with operative deliveries and smaller hemor-rhages). While this difference was not statistically sig-nificant, cases also scored higher on the EdinburghPostnatal Depression Scale. Significantly more casesthan controls (50% vs. 29%, 95% CI for the difference9.7–33%, p < 0.001) were reluctant to re-establishsexual relations with their partners for fear of becom-ing pregnant, suggesting that a negative experience inone pregnancy may prevent a woman from achievingthe family she initially intended47. Women with still-births are almost always excluded from postnatal stud-ies65, although a higher proportion of them also sufferSAMM by the nature of underlying conditions (e.g.abruption). Only half of the studies of SAMM quotedgive data about perinatal loss. Thus, the figures quotedabove are likely underestimates of the true spectrum ofpostnatal morbidity.

Potential measures to decrease SAMM secondaryto PPH

Agreement on definitions and categorizations forcomparisons

Before designing studies into effective interventionsfor reducing SAMM, it is necessary to develop stan-dardized definitions for severe morbidity and its maincauses. A pragmatic definition could be based on amixture of parameters, as outlined in Table 3. Knightet al.54 also suggest that the ICD classification of PPHshould be revised to separate atonic PPH from othercauses, particularly due to morbid placental adherence,in order to enable meaningful comparisons to be madebetween different countries. These authors postulatethat the definition should not differ depending onmode of delivery, as the physiological impact of losingblood depends on the volume lost. Obviously, even ifthere were identical blood losses, the specific morbid-ity and healing from abdominal or vaginal operationsor tears will differ.

Accurate estimation of blood loss

Measuring blood loss accurately is notoriously difficult,but some studies have improved this by using a bloodcollector bag66 (see Chapters 9–11). Training programsincorporating clinical reconstructions that includealgorithms to facilitate visual estimation of blood lossimproved the accuracy of such estimation67,68. Routineuse of a modified obstetric early warning score (orMEOWS) may aid recognition of hypovolemia whereestimated blood loss is inaccurate69.

Address primary prevention risk factors for PPH

Decreasing major hemorrhage involves trying to reduceall risk factors for PPH (Table 4). In high incomecountries, increasing age and obesity are contributingto increasing use of oxytocin in labor as well as the

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rising cesarean section rate9,54. Independently of oneanother, obesity, oxytocin use and cesarean section arerisk factors for hemorrhage. The limited length ofpregnancy means society-wide public health inter-ventions might be better placed to address obesity.

Multiple pregnancy is another risk factor which,in low income countries, has been more likely tobe spontaneous and therefore not preventable. Inthe UK, however, recent Human Fertilisation andEmbryology Authority (HFEA) targets are encourag-ing greater use of single embryo transfers to reduce therisks associated with IVF multiple pregnancy, includ-ing PPH70,71. However, there are many countrieswhere larger numbers of embryos are still being trans-ferred (US, Eastern Europe, India), thus contributingto PPH and other obstetric morbidities.

Availability of cheap, effective drugs to use in lowresource and out of hospital settings is important.Misoprostol is one such drug which is heat stable andeasy to administer in a home birth setting. Studies inAfrica have shown reduced rates of PPH when it isused, and its administration does not require trainedbirth attendants72,73. Sublingual administration may bemost effective74,75, and the women can self-administereasily73, further reducing the cost of an already cheapintervention (see Chapters 32–35).

Basic antenatal care

This cannot be overemphasized, as ample evidenceshows that antenatal follow-up decreases a woman’srisk at labor and delivery41,76. Antenatal screening forcomplications, treatment and prevention of anemia,cleanliness during delivery, the presence of a skilledbirth attendant and active management of the thirdstage of labor are all basic requirements advocated byWHO77. Staff attending deliveries in the primary caresector need to be trained to recognize PPH early andhave access to simple drugs to treat it (e.g. misoprostol,ergometrine)72, as well as to recognize when to referto a more specialized center54. In rural South Africa,health-worker problems were identified as the cause ofsubstandard care in 35–49% of cases54 out of a total of65% where substandard care was an issue. Factorsidentified were delay in diagnosis, treatment, referraland monitoring.

Training, teamwork and skills

Effective teamwork is paramount for timely inter-ventions. Algorithms or diagrams of expectedco-ordinated actions may help identify what needs tobe done and by whom, especially when several actionsneed to be undertaken simultaneously as in briskPPH78.

Clear management protocols and regular skills-drillstraining may both contribute to the maintenance ofhigh standards in units8,27. Non-adherence to guide-lines has been identified as a risk factor for increasedmaternal morbidity8,79, whereas dissemination of guide-lines and skills-drills are associated with improvedadherence to the agreed protocols and reduction in

PPH79. However, recent research in France hasgenerated conflicting results regarding the efficacy ofadherence to guidelines on actual incidence of majorPPH. One of the studies involved 19 maternity unitswithin a regional French perinatal network80 and theother involved 106 units in six regions81. Both showedthat prompt recognition and aggressive managementof PPH improved care, and increased the use of sur-gery in management, whereas the prevalence of majorPPH did not alter. This may be explained by differentrisk factors dominating the progression from small tolarge PPH (e.g. previa), and suggests that interventionsadditional to improved recognition and secondaryprevention are necessary to make an impact on PPHrates81. Important factors involve multiprofessionaltraining within the local unit and integrating team-work training within the clinical teaching itself 82.

Access, transport and organizational change

Twenty per cent of avoidable SAMM in rural SouthAfrica is due to organizational or administrative causessuch as the shortage of essential drugs, ambulances andrecruitment and retention of experienced staff 41.These factors are less prominent in high income coun-tries. However, implementation of guidelines andissues such as staff training and effective audit usuallyoccur at organizational levels. Geller et al.49 analysedthe ‘preventability’ of events along the continuum ofsevere morbidity to near-miss to death and concludedthat the same factors contributed to the outcome in allcategories (Figure 1). These were patient factors(13–20%), system factors (33–47%) and provider-related factors (90%), mainly incomplete or inappro-priate management49. Patient factors are potentiallythe hardest to rectify, especially in low income coun-tries where access to education is limited. System fac-tors figure higher in the US (33–47%)49 than in SouthAfrica (20%)41, possibly because failures of well-established systems (as in the US) are likely to have agreater impact than in settings where transport oradministrative systems are not established in the firstplace, e.g. in rural Africa41. Provider-related factorshave been more prominent as a cause of substandardcare in the US (90%)49 than in primary care settings inSouth Africa (35–49%)41. This is more likely due tothe non-availability of specialist staff in the latter, withstaff performing to the best of their ability in light ofskills they possess. Expected standards change withtime, place and facilities, so it is not unsurprising thatprovider-related factors continue to feature even inlow mortality settings.

Health systems

Wider factors relating to health systems can move awoman both up and down the risk pyramid for sever-ity of morbidity. Social exclusion, education andinequality can be tackled at governmental level in bothlow and high income countries2,76. Access to contra-ception, safe legal abortion and antenatal care can allbe addressed. Health service planners may have to

510


provide outreach antenatal services for travelers, teen-agers and the mentally ill2. The lack of universalcoverage for health insurance in the US may play arole, as women most at risk are often not insured49,83.The population in major cities is changing, due toincreased migration especially from deprived areas oras a result of war and conflict. Access to 24-hourinterpreters should become standard and might lead tosignificant reductions in severe morbidity2.

CONCLUSION

The UK triennial Confidential Enquiries into Mater-nal Deaths started in 1952, and the latter part of the20th century witnessed a gradual decline in maternalmortality. Maternal death is now rare in high incomecountries, although still prevalent in low incomecountries. Severe adverse maternal morbidity(SAMM) is prevalent throughout the world, mostlydue to treatable conditions. Poor, socially excludedwomen suffer most, but hemorrhage can strike anywoman. For meaningful comparisons to be made,standardized, simple definitions need to be designedand agreed upon as the benchmark for future research.

Hemorrhage accounts for the largest proportion ofsevere morbidity but is not a major cause of maternalmortality, at least in developed countries12. This sug-gests that registering SAMM would be a valuable wayto monitor and improve the quality of maternity ser-vices. Several population-based studies in countriessuch as Scotland, The Netherlands and Australia dem-onstrate that national morbidity surveys are feasible.Studies are needed at national level as numbers ofSAMM cases are relatively small, and trends are easierto analyse. As the causes of maternal deaths can be dif-ferent from those of SAMM12, it is most useful to havethe two systems running in parallel to aid understand-ing of the relationship. This has been achieved inScotland for the past 8 years. The UKOSS rare obstet-ric register system has been working nationwide in theUK since 2005. The recent study on peripartum hys-terectomy showed that there was one death for every150 hysterectomies performed for hemorrhage, thusreinforcing the value of morbidity and mortalitysurveys running in parallel.

It is important to continue to monitor trends. Inhigh income countries recognized risk factors forhemorrhage such as age, obesity and cesarean sectionrates are rising. The current cesarean section rate in theUK is 23%, and it is as high as 50% in Latin Amer-ica84,85. Globally, interventions aimed to reduce aspecific morbidity (e.g. cesarean section in obstructedlabor to prevent a ruptured uterus) may increase therisk of a different subsequent morbidity (e.g. placentaaccreta in previous cesarean section scar or uterinerupture in attempted vaginal birth after cesareansection). Overall, obstetric morbidity may thus rise,fall or remain unchanged, but information to guidehigh quality practice relies on robust, continuous,population-based SAMM audits.

References

1. Stones W, Lim W, Al-Azzawi F. An investigation of maternalmorbidity with identification of life-threatenting “near-miss”episodes. Health Trends 1991;23:13–5

2. Bewley S, Wolfe C, Waterstone M. Severe maternal morbid-ity in the UK. In: Maclean AB, Neilson J, eds. Maternal Mor-bidity and Mortality. London: RCOG Press, 2002:132–46

3. Souza JP, Cecatti JG, Patrpinelli MA, et al. Appropriate crite-ria for identification of near-miss maternal morbidity in inten-sive care facilities: a cross-sectional study. BMC PregnancyChildbirth 2007;7:20

4. Ronsmans C, Scott S, Adisasmita A, et al. Estimation of pop-ulation-based incidence of pregnancy-related illness and mor-tality (PRIAM) in two districts in Java, Indonesia. BJOG2009;116:82–90

5. Oladapo OT, Sule-Odu AO, Olatunji AO, et al. Near-missobstetric events and maternal deaths in Sagamu, Nigeria aretrospective study. Reprod Health 2005;2:96

6. Fillipi V, Ganaba R, Baggaley RF, et al. Health of womenafter severe obstetric complications in Burkina Faso: alongitudinal study. Lancet 2007;370:1329–37

7. Say L, Souza JP, Pattinson RC. Maternal near-miss – towardsa standard tool for monitoring quality of maternal health care.Best Pract Res Clin Obstet Gynaecol 2009;23:287–96

8. Hall M. Haemorrhage. In: Department of Health, WelshOffice, Scottish Office Department of Health, Department ofHealth and Social Services, Northern Ireland, Why Mothersdie. Report on Confidential Enquiries into Maternal Deathsin the United Kingdom 2000–2002. London: Her Majesty’sStationery Office, 2004

9. Norman J. Haemorrhage (chapter 4) in CMACE. BJOG2011;118(Suppl 1):1–203

10. Lennox C. Appendix 2B: summary of Scottish ConfidentialAudit of Severe Maternal Morbidity Report 2008. CMACE.BJOG 2011;118(Suppl 1):196–8

11. Mantel GD, Buchmann E, Rees H, et al. Severe acute mater-nal morbidity: a pilot study of a definition for a near-miss.BJOG 1998;105:985–90

12. Pattinson RC, Buchmann E, Mantel G, et al. Can enquiriesinto severe acute maternal morbidity act as a surrogate formaternal death enquiries? BJOG 2003;110:889–93

13. Bewley S, Creighton S. “Near-miss” obstetric enquiry.J Obstet Gynaecol 1997;17:26–9

14. Fillipi V, Alihonou E, Mukantaganda S, et al. Near-misses:maternal morbidity and mortality. Lancet 1998;351:145–6

15. Prual A, Huguet D, Gabin O, et al. Severe obstetric morbid-ity of the third trimester, delivery and early puerperium inNiamey (Niger). Afr J Reprod Health 1998;2:10–9

16. Geller SE, Rosenberg D, Cox S, et al. Defining a conceptualframework for near-miss maternal morbidity. J Am MedWomen’s Assoc 2002;57:135–9

17. Waterstone M, Bewley S, Wolfe C. Incidence and predictorsof severe obstetric morbidity: case-control study. Br Med J2001;322:109–93

18. Brace V, Penney G, Hall M. Quantifying severe maternalmorbidity: a Scottish population study. BJOG 2004;111:481–4

19. Penney G, Admason L, Kernaghan D. Scottish confidentialaudit of severe maternal morbidity second annual report2004. Scottish Programme for clinical effectiveness in repro-ductive health. 1–32 www.abdn.ac.uk/specrh

20. Zwart JJ, Richters JM, Ory F, et al. Severe maternal morbid-ity during pregnancy, delivery and puerperium in the Neth-erlands: a nationwide population-based study of 371 000pregnancies. BJOG 2008;115:842–50

21. Knight M, Spark P, Fitzpatrick K, et al. United KingdomObstetric Surveillance System (UKOSS) Annual Report2011. National Perinatal Epidemiology Unit, Oxford 2011.https://www.npeu.ox.ac.uk/files/downloads/ukoss/UKOSS-Annual-Report-2010.pdf

22. Killpatrick SJ, Matthay MA. Obstetric patients requiringcritical care. A five-year review. Chest 2002:101:1407–12

511


23. Eniola OA, Bewley S, Waterstone M, et al. Obstetric hyster-ectomy in a population of South East England. J ObstetGynaecol 2006;26:104–9

24. Rossi AC, Richard HL, Chmait RH. Emergency postpartumhysterectomy for uncontrolled postpartum bleeding. ObstetGynecol 2010;115:637–44

25. The Eclampsia Trial Collaborative Group. Which anti-convulsant for women with eclampsia? Evidence from thecollaborative Eclampsia Trial. Lancet 1995;337:1455–63

26. Bouvier-Colle MH, Salanave B, Ancel PY, et al. Obstetricpatients treated in intensive care units and maternal mortality.Regional teams for the survey. Eur J Obstet GynaecolReprod Biol 1996;65:121–5

27. Baskett TF, Sternadel J. Maternal intensive care and near-missmortality in obstetrics. BJOG 1998;105:981–4

28. Zhang WH, Alexander S, Bouvier-Colle MH, et al. Inci-dence of severe pre-eclampsia, post-partum haemorrhage andsepsis as a surrogate marker for severe maternal morbidity in aEuropean population-based study: the MOMS-B survey.BJOG 2005;112:89–96

29. Minkauskiene M, Nadisauskiene RJ, Padaiga Z. Severe andacute maternal morbidity: Lithuanian experience and review.Int J Fertil Womens Med 2006;51:39–46

30. Knight M. Peripartum hysterectomy in the UK: managementand outcomes of the associated haemorrhage. BJOG 2007;114:1380–7

31. Souza JP, Cecatti JG, Parpinelli MA, et al. Maternal morbid-ity and near-miss in the community: findings from the 2006Brazilian demographic health survey. BJOG 2010;117:1586–92

32. Lawton BA, Wilson LF, Dinsdale RA, et al. Audit of severematernal morbidity describing reasons for transfer and poten-tial preventability of admissions to ICU. Aust N Z J ObstetGynaecol 2010:50:346–51

33. Almerie Y, Almerie MQ, Matar HE, et al. Obstetric near-miss and maternal mortality in maternity university hospital,Damascus,Syria: a retrospective study. BMC PregnancyChildbirth 2010;10:65

34. Mutihir JT, Utoo BT. Postpartum maternal morbidity in Jos,north-central Nigeria. Nigerian J Clin Pract 2011;14:38–42

35. Van Roosmalen J, Zwart J. Severe acute maternal morbidityin high income countries. Best Pract Res Clin ObstetGynaecol 2009;23:297–304

36. Ronsmans C . Severe acute maternal morbidity in low-income countries. Best Pract Res Clin Obstet Gynaecol 2009;23:305–16

37. Vandecruys H, Pattinson RC, Macdonald A, et al. Severeacute maternal morbidity and mortality in the Pretoria Aca-demic Complex: changing patterns over 4 years. Eur J ObstetGynaecol Reprod Biol 2002;102:6–10

38. D’Ambruoso L, Achadi E, Adisasmita A, et al. Assessingquality of care provided by Indonesia village midwives: aconfidential enquiry. Midwifery 2009;25:528–39

39. Prual A, Bouvier-Colle MH, de Bernis L, et al . Severematernal morbidity from direct obstetric causes in WestAfrica: incidence and case-fatality rates. Bull WHO 2000;78:593–603

40. Fillipi V, Ronsmans C, Gohou V, et al. Maternity wards orobstetric emergency rooms? Incidence of near-miss morbidityin African hospitals. Acta Obstet Gynaecol Scand 2005;84:11–6

41. Ghandi MN, Welz T, Ronsmans C. Severe acute maternalmorbidity in rural South Africa. Int J Gynaecol Obstet 2004;87:180–7

42. World Health Organization, Department of ReproductiveHealth and Research. Evaluating the quality of care for severepregnancy complications: the WHO near-miss approachfor maternal health. WHO, 2011 http://www.who.int/r e p r o d u c t i v e h e a l t h / p u b l i c a t i o n s / m o n i t o r i n g /9789241502221/en/index.html

43. Ki-Moon B. Global Strategy for Women’s and Children’sHealth 2009 http://www.un.org/sg/hf/GlobalStategyEN.pdf

44. World Health Organisation Maternal mortality Fact sheetN°348. November 2010 http://www.who.int/mediacentre/factsheets/fs348/en/index.html

45. Hogan M, Foreman KJ, Naghavi M, et al. Maternal mortalityfor 181 countries, 1980–2008: a systematic analysis of progresstowards Millennium Development Goal 5. Lancet 2010;375:1609–23

46. CMACH 2000–2002. Department of Health, Welsh Office,Scottish Office, Department of Health and Social ServicesNorthern Ireland. Why Mothers Die. Report on Con-fidential Enquiries into Maternal Deaths in the UnitedKingdom 2000–2002. London: Her Majesty’s StationeryOffice, 2004

47. Waterstone M, Wolfe C, Hooper R, et al. Postnatal morbid-ity after childbirth and severe obstetric morbidity. BJOG2003;110:128–33

48. Monaco TJ, Spielman FJ, Katz VL. Pregnant patients in theintensive care unit: a descriptive analysis. South Med J 1993;86:414–7

49. Geller SE, Rosenberg D, Cox SM, et al. The continuum ofmaternal morbidity and mortality: factors associated withseverity. Am J Obstet Gynaecol 2004;191:939–44

50. Kaye D, Mirembe F, Aziga F, et al. Maternal mortality andassociated near-misses among emergency intrapartum referralsin Mulago Hospiatl, Kampala, Uganda. East Afr Med J 2003;80:144–9

51. Wen SW, Huang L, Liston R, et al. Severe maternal morbid-ity in Canada, 1991–2001. CMAJ 2005;173:759–64

52. Pallasmaa N, Ekblad U, Gissler M. Severe maternal morbidityand the mode of delivery. Acta Obstet Gynaecol Scand 2008;87:662–8

53. Callaghan WM, Mackay AP, Berg CJ. Identification of severematernal morbidity during delivery hospitalizations, UnitedStates, 1991–2003. Am J Obstet Gynaecol 2008;199:133.e1–133.e8

54. Knight M, Callaghan WM, Berg C, et al. Trends in post-par-tum haemorrhage in high resource countries: a review andrecommendations from the International Postpartum Haem-orrhage Collaborative Group. BMC Pregnancy Childbirth2009;9:55

55. Ford JB, Roberts CL, Simpson JM, et al. Increased post-partum haemorrhage rates in Australia. Int J Gynaecol Obstet2007;98:237–43

56. Al-Zirqi I, Vangen S, Forsen L, Stray-Pedersen B. Prevalenceand risk factors of severe obstetric haemorrhage. BJOG 2008;115:1265–72

57. Joseph KS, Rouleau J, Kramer MS, et al. Investigation of anincrease in post-partum haemorrhage in Canada. BJOG 2007;114:751–9

58. Kuklina EV, Meikle SF, Jamieson DJ, et al. Severe obstetricmorbidity in the United States: 1998–2005. Obstet Gynaecol2009;113:293–9

59. Lutomski L, Byrne B, Devane D, Greene R. Increasingtrends in atonic postpartum haemorrhage in Ireland: an 11-year population based cohort study. BJOG 2012;119:306–14

60. Manoharan M, Wuntakal R, Erskine K. Uterine rupture: arevisit. The Obstetrician Gynaecologist 2010;12:223–30

61. Hofmeyr GJ, Say L, Gulmezoglu AM. WHO systematicreview of maternal mortality and morbidity: the prevalence ofuterine rupture. BJOG 2005;112:1221–8

62. Al-Nuaim LA, Mustafa MS, Abdel Gader AG. Disseminatedintravascular coagulation and obstetric haemorrhage. Man-agement dilemma. Saudi Med J 2002;23;658–62

63. Lewis GE, ed. The Confidential Enquiry into Maternal andChild Health (CEMACH). Saving Mothers Lives: reviewingmaternal deaths to make motherhood safer 2003–05. London:CEMACH, 2007

64. Whiteman MK, Kuklina E, Hillis SD, et al. Incidence anddeterminants of peripartum hysterectomy. Obstet Gynaecol2006;108:1486–92

65. Glazener CMA, Abdalla M, Stroud P, et al. Postnatal mater-nal morbidity: extent, causes, prevention and treatment.BJOG 1995;102:282–7

512


66. Zhang WH, Deneux-Tharaux C, Brocklehurst P, et al. Effectof a collector bag for measurement of postpartum blood lossafter vaginal delivery: cluster randomised trial in 13 Europeancountries. BMJ 2010;340:c293

67. Bose P, Regan F, Paterson-Brown S. Improving the accuracyof estimated blood loss at obstetric haemorrhage using clinicalreconstructions. BJOG 2006;113:919–24

68. Maslovitz S, Barkai G, Lessing JB, et al. Improved accuracy ofpost-partum blood loss estimation as assessed by simulation.Acta Obstet Gynaecol Scand 2008; 87:929–34

69. Smith GB, Pryterch DR, Schmidt P, et al. Hospital-widephysiological surveillance – a new approach to the early iden-tification and management of the sick patient. Resuscitation2006;71:19–28

70. Kjellberg AT, Carlsoon P, Bergh C. Randomized singleversus double embryo transfer: obstetric and paediatric out-come and a cost-effectiveness analysis. Hum Reprod 2006;21:210–6

71. Braude P. One Child at a Time 4 One Child at a Time.Report of the Expert Group on Multiple Births after IVF,Oct 2006. http://www.oneatatime.org.uk/images?MBSET_reprt_Final_Dec_06.pdf

72. Prata N, Mbaruku G, Campbell M, et al. Controlling post-partum haemorrhage after home births in Tanzania. Int JGynaecol Obstet 2005;90:51–5

73. Potts M, Campbell M. Three meetings and fewer funerals –misoprostol in post-partum haemorrhage. Lancet 2004;364:1110–11

74. Vimala N, Mittal S, Kumar S, et al. Sublingual misoprostolversus methylergometrine for actice management of the thirdstage of labour. Int J Gynaecol Obstet 2004;87:1–5

75. Hofmeyr GJ, Walraven G, Gulmezoglu AM, et al. Miso-prostol to treat post-partum haemorrhage: a systematicreview. BJOG 2005;112:547–53

76. World Health Organisation 1994. The mother-baby package:WHO’s guide to saving women’s and infant’s lives. SafeMother 1994;15:4–7

77. Lazarus JV, Lalonde A. Reducing post-partum haemorrhagein Africa. Int J Gynaecol Obstet 2005;88:89–90

78. Briley A, Bewley S. Management of obstetric haemorrhage:obstetric management. In: Pavord S, Hunt B, eds. TheObstetric Haematology Manual. Cambridge: CambridgeUniversity Press, 2010:151–7

79. Rizvi F, Mackey R, Barett T, et al. Successful reduction ofmassive post-partum haemorrhage by use of guidelines andstaff education. BJOG 2004;111:495–8

80. Audureau E, Deneux-Tharaux C, Lefevre P, et al. practicesfor prevention, diagnosis and management of postpartumhaemorrhage: impact of a regional multifaceted intervention.J Obstet Gynacol 2009;116:1325–33

81. Deneux-Tharaux C, Dupont C, Colin C, et al. Multifacetedintervention to decrease the rate of severe postpartum haem-orrhage: the PITHAGORE6 cluster-randomised controlledtrial. J Obstet Gynaecol 2010;117:1278–7

82. Siassakos D, Crofts JF, Winter C, et al. The active compo-nents of effective training in obstetric emergencies. J ObstetGynaeol 2009;116:1028–32

83. Deadly Delivery. The Maternal Health Care Crisis in theUSA www.amnestyusa.orgIndex AMR 51/007/2010

84. Villar J, Valladares E, Wojdyla D, et al. Caesarean deliveryrates and pregnancy outcomes: the 2005 WHO global surveyon maternal and perinatal health in Latin America. Lancet2006;367:1819–29

85. Knight M, Kurinczuk JJ, Spark P. Caesarean delivery andperipartum hysterectomy. Obstet Gynecol 2008;111:97–105

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