|
Postgraduate
Training Course in Reproductive Health/Chronic Disease
Incidence/prevalence of severe
maternal morbidity - a literature review
Review prepared for
the 12th Postgraduate Course in Reproductive Medicine and Biology, Geneva,
Switzerland
Meile Minkauskiene, MD, PhD student
Clinic of Obstetrics and Gynaecology,
Kaunas University Hospital, Lithuania
Tutors: Lale Say, Ana Betran
World Health Organization
See also
presentation
Abstract
Objective
Methods
A systematic literature search revealed relevant studies
reporting data on the prevalence/incidence of severe complications during
pregnancy, delivery and postpartum period. For assessment of the quality of
studies and for collecting the data, a structured data collection form from
the WHO systematic review of maternal mortality and morbidity was used.
Incidence/prevalence and case-fatality ratios were extracted.
Results
We included 38 reports, most of them were cross-sectional,
hospital based (27/37) studies. Twenty two studies presented data about one
severe condition (admissions to ICU, rupture of the uterus, hysterectomy,
eclampsia, pre-eclampsia, acute abdomen, stroke, acute renal failure).
Fourteen studies reported multiple causes of severe maternal morbidity
(rupture of the uterus, haemorrhage, sepsis, eclampsia, dystocia, caesarean
section, severe liver disorders) using different inclusion criteria
depending on the severity of the disease.
Conclusions
The incidence/prevalence of severe maternal morbidity ranges
from 0.07 to 8.23%, the case-fatality ratio from 0.02 to 37%. There is a big
difference between case-fatality ratio in developing (South Africa 1:5;
India and Niger 1:11) and developed countries (UK 1:118; France 1:222).
Background
The analysis of maternal deaths has long been used for the
evaluation of women’s’ health and the quality of obstetric care. Around 10
to 20 maternal deaths per 100 000 live births are observed in countries in
the European Union, less than one hundred deaths per year are registered in
France (1) and so few cases exist now in England, Wales and Scotland, that
the results are published every triennium for the whole United Kingdom (2).
Over the last decade the identification of cases of severe maternal
morbidity has emerged as a promising complement or alternative to the
investigation of maternal deaths (1). The studies revealed that near misses
are a potentially useful starting point for audits. Scrutiny of near-misses
may be useful for several reasons: larger numbers of cases could permit more
contemporaneous reporting; lessons to be learned from the management of
cases who survived may be at least as useful as from those who died;
near-miss cases could also be seen as controls for deaths (1). If the
requirement for total confidentiality is modified it may be possible to
interview survivors and to help in determining both risk factors and
substandard care. The ratio such as that of deaths to near-misses can be
calculated and could be compared between regions or over time.
Although obstetric complications are sometimes presented as a relatively
easy alternative to maternal deaths, difficulties remain in their definition
and identification. A number of terms are in use to describe incidents of
severe maternal ill health including life-threatening complications, severe
maternal morbidity or near-misses.
Conceptually, morbidity during pregnancy represents part of a continuum
between the extremes of good health and death. On this continuum, a
pregnancy may be thought of as being uncomplicated, complicated, severely
complicated or life threatening (Figure 1) (1). From these
conditions, the woman may recover, she may be temporarily or permanently
disabled, or she may die.
Figure 1: Pregnancy continuum between
extremes of good health and death.

The main difficulty in designating where a woman is
positioned on this continuum lies in the definition of the threshold of
severity above which morbidity becomes severe or even life threatening.
Whereas this threshold is easy to define for some conditions (e.g. few will
disagree that a ruptured uterus is life threatening), it is not
straightforward for others (e.g. what is the threshold for severe vaginal
bleeding or for prolonged labour?).
An added difficulty is that the threshold above which an adverse obstetric
event becomes life threatening may be context specific. The probability of a
woman dying depends not only on the woman’s capacity to cope with a
complication, but also on the access to and the quality of the care she
receives. For example, a blood loss of 500 ml may not be life threatening in
a non-anaemic healthy woman, but might put the mother’s life at risk if she
is severely anaemic.
Finally, some diagnoses of severe obstetric complications may be
particularly dependent on physician’s judgement. For example, cephalopelvic
disproportion (CPD) in particular is difficult to ascertain. In the USA in
the 1980s, there were six times more caesarean sections for CPD than in
Ireland among women with a comparable risk status. But these differences
were believed to reflect cultural factors rather than real differences in
the epidemiology of CPD (1).
For all of these reasons, it is unlikely that standard, universally
applicable definitions of severe morbidity can be proposed. The definitions
obtained from the literature will need to be adapted according to the local
context and the purposes of the investigation.
Three types of approaches have been proposed for defining life threatening
obstetric complications and near miss events. These approaches include
definitions based on (a) management, (b) clinical signs and symptoms, and
(c) organ systems (1).
a. Management-based definitions
In developed countries, most of the definitions of life
threatening obstetric complications and near miss events are management
based. The management criterion most commonly used is admission to intensive
care, regardless of the medical reason for the admission (3, 4, 5). The
purpose of the majority of these investigations has been to describe the
utilization patterns of obstetric care facilities or the use of general
intensive care facilities for critically ill pregnant and postpartum women
rather than to determine the rate of occurrence of life-threatening events
related to pregnancy.
Other examples of management criteria used in the definition of life
threatening complications include the use of emergency hysterectomy (6, 7),
caesarean section (7), blood transfusion (7), hospitalization for more than
four days (7), and anaesthetic accidents (6).
b. Definitions based on clinical signs and
symptoms
Definitions based on clinical signs and symptoms are
generally built around obstetric diagnoses or complications and tend to
focus on the major causes of maternal mortality, such as haemorrhage,
hypertensive disorders and sepsis. This approach is straightforward to
interpret and has an immediate appeal for both clinicians and
non-clinicians, particularly because the conditions listed tend to mirror
the main causes of maternal death. In developing countries, data on broad
diagnoses of complications might also be relatively easy to get from
hospital registers.
The above points can be illustrated using the example of definitions for
severe vaginal bleeding. In a European study, Bouvier-Colle and colleagues
(8) based their definition of a life threatening postpartum haemorrhage on
the following signs and symptoms: blood loss >= 1500 ml if measured, or
haemorrhage leading to anomalies of coagulation. On the other hand, in a
study in the UK, Stones et al (4) defined severe blood loss as that
exceeding 2000 ml. In settings where the amount of blood loss is not
routinely measured, other indicators of severe blood loss need to be sought.
In Benin, for example, any postpartum haemorrhage associated with clinical
signs of shock qualified as a near miss (9). Clearly, there appears to be no
consensus as to what constitutes life threatening blood loss, and
definitions will vary according to the context of the study.
c. Organ system-based definitions
Another approach to define near miss is that based on organ
systems (6). A woman with organ failure or organ dysfunction (renal failure
or cardiac decompensation, for example) during or within six weeks after
pregnancy is very likely to die if she does not receive adequate care (6).
For example, a haemorrhage might become life threatening if the bleeding
leads to vascular (hypovolemia), renal (oliguria) or coagulation
dysfunction. Infection, on the other hand, might become life threatening if
the woman shows signs of respiratory (e.g. pulmonary oedema), immunological
or cerebral dysfunction.
The actual frequency of severe maternal morbidity is not well known since
there has been such scanty data of critical or serious illnesses during
pregnancy and the puerperium. The purpose of this review is to summarise the
prevalence/incidence of severe maternal morbidity from identified studies,
to compare study designs and used definitions, and to discuss advantages and
disadvantages of used methodologies.
Methods
Inclusion criteria
Studies which report data on prevalence/incidence of severe complications
during pregnancy, delivery and postpartum are included. Studies with
interventions for reduction of severe maternal morbidity were also included.
Case-control studies or only case review studies without denominator were
excluded.
Data collection
Medical databases, including Medline, Popline, Scielo from 1998 to 2003
were searched by key words "severe maternal morbidity" or "near-miss and
maternal", limited to "human", "female and adults". The reference lists of
identified articles were also reviewed. The following journals were hand
searched: Lancet, European Journal of Obstetrics and Gynaecology, British
Medical Journal, JAMVA. The ‘WHO systematic review of maternal morbidity and
mortality database’ was scanned for studies from 1998 (67). Experts in the
field were contacted. The title and abstract of the studies identified in
the computerised search were scanned to exclude studies that were obviously
irrelevant. The full texts of remaining studies were retrieved and scanned.
Quality of methods and data abstraction
For the assessment of the study quality structured data collection forms
from the ‘WHO systematic review of maternal morbidity and mortality’ were
used. The study quality was assessed by using the following criteria:
- description of study period
- information about population characteristics
- information about place of delivery
- description of the study settings
- information about eligible and lost subjects
- definitions of used conditions (morbidity or mortality)
- quality of forms of reporting data
- information about using special efforts to capture all maternal deaths
Data on the incidence or prevalence of severe maternal
diseases and complications were extracted. The numbers and causes of
maternal deaths were also collected. The case-fatality rate was calculated
as the proportion of fatal cases among the reported cases of the specified
diseases. The incidence rate for severe maternal morbidity is the ratio of
cases with severe maternal morbidity at the beginning of a period per
pregnant/post partum women-years at risk. The prevalence of near-miss cases
is the ratio of cases with life-threatening maternal morbidity per total
number of pregnant women (or live births) at a certain point of time.
Results
We identified 58 studies. Twenty studies were excluded: twelve of them
did not have data on severe maternal morbidity prevalence or these data
were not extractable (10-22), two were case-control design (23, 24), six
- randomised placebo controlled trials (25-29). Therefore 38 studies
were included in the review.
Baseline characteristics of the studies
Table 1 depicts the baseline characteristics of the
included studies. Twenty seven studies were cross-sectional, and the
prevalence/incidence and case-fatality ratios were calculated
retrospectively by using hospital databases. Three studies were based on
national data from the USA (39), Australia (41), Haiti (62), reporting
different morbidity conditions. Only six studies are population-based: two
of them have a cohort design (7, 49), one is a case-control study (56), four
are prevalence/incidence surveys (58, 60, 61, 62). Hospital based were 25
studies, 4 of them were multicentric, 7 reported region/national data (7
studies). The sample size varied between 3777- 281 116.
Table 1. Characteristics of studies.
|
Study |
Country |
Study design |
Setting |
Population |
Sample size |
Studied condition |
Diagnosis |
Comments |
|
Al Sakka M 1998 (30) |
Qatar |
Cross-sectional |
Hospital |
Unknown |
|
Rupture of uterus |
Full thickness uterine wall defect |
65% hysterectomy |
|
Rajab SH 1998 (31) |
Botswana |
Cross-sectional |
Hospital |
Unknown |
21296 |
Rupture of uterus |
Diagnosed by laparotomy |
67% blood transfusion, 44% hysterectomy |
|
Amata AO 1998 (32) |
Nigeria |
Cross-sectional |
Hospital |
Unknown |
4625 |
Rupture of uterus |
Diagnosed by laparotomy |
32% complicated by vesicovaginal fistula. 84% due to prolonged labour |
|
Fawzi HW 1998 (33) |
Sudan |
Cross-sectional |
Hospital |
Unknown |
9111 |
Rupture of uterus |
Diagnosed by laparotomy |
50% hysterectomy |
|
Bakour SH 1998 (34) |
Syria |
Cross-sectional |
Hospital |
Unknown |
31642 |
Rupture of uterus |
Diagnosed by laparotomy |
56% hysterectomy, 85% blood transfusion |
|
Nasrat HA 1998 (35) |
Saudi Arabia |
Cross-sectional |
Hospital |
Rural |
18842 |
Peripartum hysterectomy |
|
43.5%(10) due to uterine atony, 30.4%(7) - ruptured uterus, 26.1%(6) -
placenta accreta |
|
Engelsen IB (36) 2001 |
Norway |
Cross-sectional |
Hospital |
Unknown |
70546 |
Peripartum hysterectomy |
Peripartum hysterectomy within 24h after delivery after 24th week of
gestation |
7 cases due to uterine atony, 2 due to rupture of uterus |
|
Nzerue CM 1998 (37) |
USA |
Cross-sectional |
Hospital |
Unknown |
70559 |
Acute renal failure |
Serum creatinin >71μmol/l |
Acute renal failure causes: preeclampsia 8%, drug abuse 6%, HELLP – 50 % |
|
Ali ME, 1998 (38) |
Saudi Arabia |
Cross-sectional |
Hospital |
Unknown |
15562 |
Acute abdomen |
Clinical symptoms |
Causes: appendicitis (50%), cholecystitis (25%), ovarian cyste (10%) and
others |
|
Lanska DJ 1998 (39) |
USA |
Census |
National |
Mixed |
281116 |
Stroke: subarachnoid and intracerebral haemorrhage, and ischemic stroke.
Cerebral venous thrombosis and thrombosis of intracranial venous sinuses |
According ICD-9-CM. |
Sampling with stratification of hospitals by number of beds and
geographic location |
|
Tajammul A 1998 (40) |
Pakistan |
Cross-sectional |
Hospital |
Mixed, but most rural |
Unclear |
Eclampsia |
Women presenting with convulsions in pregnancy or pregnant women who
developed convulsions while admitted with a sBP>140mmHg or dBP>90mmHg or
both |
PM – 31.6%
Death due to pulmonary oedema |
|
Riley M, 1998 (41) |
Australia |
Census |
Region |
Unknown |
Unclear |
Eclampsia |
According ICD-9-CM |
The aim of study – compare the quality of two databases |
|
Chinayon P 1998 (42) |
Thailand |
Cross-sectional |
Tertiary Hospital |
Unknown |
167200 |
Eclampsia |
Unclear |
PM – 11.7 %( for weight>1kg). Maternal deaths due to
intracerebral haemorrhage.
The study try to evaluate the magnesium sulfate regimen too. |
|
Makhseed M 1998 (43) |
Saudi Arabia |
Cross-sectional |
Hospital |
Unknown |
10407 |
Pre-eclampsia |
Used ACOG definitions |
|
|
Wacker J 1998 (44) |
Zimbabwe |
Cross-sectional |
2 Hospital |
Mixed |
10750 |
Pre-eclampsia |
dBP>90mmHg and at least 1+ proteinuria dipstick |
Try to examine the annual change in the incidence of preeclampsia |
|
Tank PD 2002 (45) |
India |
Cross-sectional |
Tertiary Hospital |
Mixed |
6138 |
Severe liver disease: HELLP,acute acute hepatitis, fatty live |
Based on clinical symptoms and laboratory findings |
All women with acute fatty liver and fulminant
hepatitis died. 90,1% cases of all severe liver diseases – HELLP
syndrome.
PM – 62% |
|
Mc Cord 2001(46) |
India |
Cohort |
Region |
rural |
2905 |
Emergency obstetric care: obstructed labour, haemorrhage, eclampsia,
infection. |
Unclear |
PM – 3,6%. |
|
Gielchinsky Y 2002 (47) |
Israel |
Cross-sectional |
Hospital |
Unknown |
34450 |
Placenta accreta |
Based on clinical or histological criteria |
The definition very wide: included sonographic diagnosed retained
placental fragments or difficult manual removed placenta too. Rate
of hysterectomies- 3.5% |
|
1999
(48) |
Scotland |
Cross-sectional |
Hospital |
Unknown |
No data |
Primary postpartum haemorrhage |
More than 1500ml |
The audit for prevention and management emergencies in labour. |
|
Prual A 2000 (49) |
6 countries of West Africa |
Cohort
population-
based
prospective |
Total population |
Mixed |
20326 |
Haemorrhage, dystocia, sepsis, rupture of uterus, severe liver
disorders, eclampsia, sepsis, cesarean section, thrombo-embolism,
vesicovaginal fistula |
Different clinical diagnoses (haemorrhage with blood transfusion, sepsis
– septicaemia, peritonitis or odorous vaginal discharge with
hospitalisation and others) |
|
|
Baskett TF 1998 (5) |
Canada |
Cross-sectional |
Hospital |
Mixed |
76119 |
All admissions to ICU |
All admissions to ICU due to hypertensive disorders (25%), haemorrhage
(22%), sepsis (15%), pulmonary embolism, acute fatty liver |
|
|
Loverro G 2001(50) |
Italy |
Cross-sectional |
Hospital |
Unknown |
23694 |
Admissions to ICU |
All admissions to ICU: worsening of pre-eclampsia (76%), severe bleeding
(15%) and others |
PM – 10.6% |
|
Souza JPD, 2002 (51) |
Brazil |
Cross-sectional |
Tertiary Hospital |
Unknown |
28660 |
Admissions to ICU |
All admissions to ICU: hypertensive disorders (41%),
haemorrhage (15%) and sepsis(13%) |
Stillbirth – 19% |
|
Murphy DJ 2002 (52) |
UK |
Cross-sectional |
Hospital |
Unknown |
51756 |
Admissions to ICU |
All admissions to ICU: haemorrhage (24%), thrombosis, hypertensive
disorders (32%), sepsis, amniotic embolism, cardiac problems (24%) and
others. |
PM – 14%
Near-miss maternal mortality: all women admitted for ICU in pregnancy or
up 42 days post partum. |
|
Bhuinneain MN 2001 (53) |
Ireland |
Cross-sectional |
2 medical facilities |
Unknown |
67650 |
Admissions to ICU |
All admissions to ICU: haemorrhage (11%), thrombosis, hypertensive
disorders (15%), sepsis (11%), cardiac problems (31%), acute fatty liver
and others. |
Marker of serious morbidity – the transfer of an obstetric patient to
ICU. |
|
Duffy S 2001 (54) |
Ireland |
Cross-sectional |
Hospital |
Unknown |
20800 |
Admissions to ICU |
All admissions to ICU: haemorrhage (26%), thrombosis, hypertensive
disorders (48%), sepsis , cardiac problems. |
|
|
Prual A 1998 (55) |
Niger |
Cross-sectional |
6 medical facilities |
Unknown |
4081 |
Severe obstetric morbidity :dystocia, uterine rupture, preeclampsia,
eclampsia, haemorrhage, puerperal sepsis, infectious diseases and others |
Diagnosis based on usual clinical examination.
Haemorrhage – hypovolemic shock requiring urgent blood transfusion |
Severe complications from 28th week of gestation
to42nd day post partum that would have resulted in death of the mother
or definite disabling sequelae without medical intervention. |
|
Mantel GD 1998 (6) |
South Africa |
Cross-sectional prospective
multicentre
2 year audit |
Hospital |
Unknown |
13429 |
Near-misses: vascular, cardiac, immunological, coagulation, renal,
respiratory dysfunctions, all ICU admissions, emergency hysterectomies,
anaesthetic accidents |
Clear definitions of haemorrhage (hypovolemia requiring >5U blood),
abortion complications, sepsis(septic abortion, chorioamnionitis,
puerperal sepsis), pulmonary oedema and others |
Classification based on organ dysfunction and
management
A near-miss describes a patient with an acute organ system dysfunction,
which if not treated appropriately, could result in death. |
|
Waterstone M 2001 (56) |
UK |
Population-
based
multicentre
case-control
prospective study |
25 hospitals |
Mixed |
48865 |
Severe obstetric morbidity: severe preeclampsia, eclampsia, HELLP
syndrome, severe haemorrhage, severe sepsis, uterine rupture |
Clear very strict clinical definitions based on laboratory findings. For
severe haemorrhage - >1500ml or >4U of blood or fall in Hg>40g/l |
Focuses on morbidity associated specifically with pregnancy and for
which management usually involves maternity care professionals. |
|
Bernis L 2000 (7) |
Senegal |
Population-
based cohort |
2 regions |
Urban |
3777 |
Maternal morbidity: haemorrhage, hypertensive disorders, sepsis,
obstructed labour, others |
The definition of severe obstetric morbidity was based upon clinical
diagnosis and medical or obstetrical interventions. |
Compare outcomes and management in two different regions. |
|
Filippi V 1998 (9) |
Benin |
Cross-sectional |
Hospital |
Unknown |
4291 |
Near-misses: eclampsia, haemorrhage, dystocia, puerperal infections. |
Not specified |
|
|
Khosla AH 2000 (57) |
India |
Cross-sectional |
Hospital |
Rural |
5124 |
Near-misses: eclampsia, haemorrhage,, puerperal infections, ectopic
pregnancy, abortion with uterine trauma, anaesthetic complications. |
Not specified |
|
|
Canada 2000
(58) |
Canada |
Incidence/
prevalence
study |
National |
Mixed |
- |
Severe maternal morbidity: amniotic fluid embolism, obstetrical
pulmonary embolism, eclampsia, septic shock, cerebrovascular disorders,
haemorrhage requiring transfusion or hysterectomy, catastrophic rupture
of uterus, anaesthesia complications |
Clear clinical diagnosis. Septic shock included with association to
septic abortion, chorioamnionitis, pyelonephritis, endometritis .
Rupture of uterus accompanied by bleeding |
Data from different studies, prepared by Canadian
Perinatal Surveillance System special group, using Discharge Abstract
Database.
Severe maternal morbidity – the number of women who experience severe
(life-threatening) maternal morbidity per 100 000 live births in a given
time and place. |
|
Geller SE, 2002 (59) |
USA |
Cross-sectional |
Hospital |
Urban |
- |
Severe maternal morbidity and near-misses using classification by
diseases (severe pre-eclampsia, eclampsia, embolism, infection...),
morbid events (seizures, stroke, DIK, pulmonary oedema...),
interventions (transfusion, ICU admission, hysterectomy...). |
164 women classified as having severe morbidity and 22 as near-miss
morbidity using special qualitative assessment . |
The aim of study- to study process for the definition and
identification of near-miss morbidity with help of quantitative score. |
|
Schoon MG 1999 (60) |
South Africa |
Incidence/
prevalence,
population-
based study |
Region |
Mixed |
34100 |
Vascular, cardiac, immunological, coagulation, renal, respiratory
dysfunctions, all ICU admissions, emergency hysterectomies, anaesthetic
accidents |
Clear definitions of haemorrhage (hypovolemia requiring >5U blood),
abortion complications, sepsis(septic abortion, chorioamnionitis,
puerperal sepsis), pulmonary oedema and others |
Near-miss – all cases with organ dysfunction or organ
failure during pregnancy of any gestation until 42 days after
termination of pregnancy.
The study compare care in different regions and evaluate as optimal or
suboptimal |
|
Vandecruys HB 2002
(61) |
South Africa |
Incidence/
prevalence
multicentric
population-
based
prospective study |
Region |
Unknown |
40006 |
Severe acute maternal morbidity: hypertensive disorders, pregnancy
related and not related sepsis, haemorrhage, abortions complications,
embolism and others. |
Clinical. |
Compare data of different years. |
|
Haiti 1999
(62) |
Haiti |
Incidence/
prevalence
retrospective
study |
National |
Mixed |
80304 |
Uterine rupture, dystocia, haemorrhage, eclampsia, fetal distress,
hypertension, puerperal infection, ectopic pregnancy, breach
presentation and many other |
Not specified |
Included all women who underwent a major obstetric intervention absolute
maternal indication or died between 28th week of pregnancy and 42nd day
postpartum. |
|
Girard F 2001 (8) |
France |
Cross-sectional |
Region |
Unknown |
27875 |
Severe maternal morbidity: severe haemorrhage, maternal sepsis,
pregnancy induced hypertension. |
Clear clinical definitions. Severe haemorrhage :>1500 ml or requiring
blood and /or plasma expanders. Eclampsia – any fitting in pregnancy. |
|
Different definitions for the diseases were used. Five studies reported
on obstetric patients treated in the intensive care unit (ICU) of tertiary
hospitals. Other 18 studies also assessed only one specific condition or
intervention (rupture of the uterus, hysterectomy, eclampsia, acute renal
failure, acute abdomen, stroke, pre-eclampsia, severe liver disease,
placenta accreta, primary postpartum haemorrhage). Fifteen studies used
different morbidity definitions (near-miss, severe obstetric morbidity,
severe maternal morbidity, acute severe maternal morbidity); all of them
reported the prevalence of the disease. Most of the studies used conditions
based on clinical signs and symptoms (8, 49, 56, 57, 61), few included organ
systems based definitions (cardiac, immunological, renal dysfunction and
others) (6, 60). The aim of Geller`s study (59) was to identify and classify
all severe complications to near-miss morbidity or severe morbidity using
special qualitative assessment. The differences of included conditions, used
definitions, diagnostic evaluation of all studies are shown in
table 1. The studies identified reported severe maternal morbidity only
in the third trimester (from 22 or 28th week gestation) or all pregnancy
diseases including peripartum and postpartum life-threatening conditions
until the 42nd day after termination of pregnancy (table 2).
Table 2. Quality assessment of studies.
|
Study |
Location |
Loss to
follow-up (%) |
Description of population characteri-stics |
Data
source |
Description of study setting characteri-stics |
Place of
delivery |
Forms of
reporting data |
Case
definition |
Maternal
deaths definition |
Comments |
|
Al Sakka
M, 1998 (30) |
Qatar |
8.31% |
yes |
Medical
records |
no |
Unknown |
crude |
clear |
No deaths |
|
|
Rajab SH
1998 (31) |
Botswana |
- |
no |
unknown |
1 referral
hospital |
Mixed |
crude |
unclear |
no |
|
|
Amata AO
1998 (32) |
Nigeria
|
- |
yes |
Medical
records |
yes |
Mixed |
crude |
unclear |
no |
|
|
Fawzi HW
1998 (33) |
Sudan |
- |
yes |
Medical
records |
yes |
Mixed |
crude |
unclear |
no |
|
|
Bakour
SH 1998 (34) |
Syria |
- |
yes |
Medical
records |
yes |
Mixed |
crude |
unclear |
no |
|
|
Nasrat
HA 1998 (35) |
Saudi
Arabia |
- |
yes |
Medical
records |
More high
risk women |
Unknown |
crude |
yes |
no |
|
|
Engelsen
IB 2001(36) |
Norway |
- |
no |
4
different source: register of <Norway, delivery and operations register
in hospitals, medical records |
no |
Unknown |
crude |
clear |
no |
|
|
Nzerue
CM 1998 (37) |
USA |
- |
no |
Medical
records |
Tertiary
care hospital |
Unknown |
crude |
clear |
no |
Included
all cases of renal insufficiency (acute and chronic) |
|
Ali ME
1998 (38) |
Saudi
Arabia |
- |
yes |
Medical
records of pregnant women, admitted to surgical ward |
Tertiary
care hospital |
Unknown |
crude |
unclear |
no |
Not all
women operated, could be wrong diagnosis |
|
Lanska
DJ 1998 (39) |
USA |
+ |
yes |
Vital
statistics |
No
settings |
Hospital |
Adjusted
and standardized; used logistic regression |
clear |
no |
Special
efforts to capture for the multiple hospitalizations. Different
identification of deliveries and hospitalizations due to the specific
disease |
|
Tajammul
A 1998 (40) |
Pakistan |
- |
yes |
Unknown |
yes |
Mixed |
crude |
clear |
no |
Not clear
method of collection data: prospective or retrospective, from medical
records or from women |
|
Riley M
1998 (41) |
Australia |
- |
no |
2
different vital statistics databases |
Clear
description of both databases |
Unknown |
crude |
clear |
no |
|
|
Chinayon
P 1998 42) |
Thailand |
- |
no |
Medical
records |
yes |
Unknown |
crude |
No
definition |
no |
|
|
Makhseed
M 1998 (43) |
Saudi
Arabia |
0.47% |
no |
Medical
records |
no |
Unknown |
crude |
unclear |
no |
|
|
Wacker J
1998 (44) |
Zimbabwe |
- |
yes |
Medical
records |
yes |
Unknown |
crude |
clear |
no data |
|
|
Tank PD
2002 (45) |
India
|
- |
no |
Medical
records |
yes |
Unknown |
crude |
clear |
no |
|
|
Gielchinsky Y, 2002 (47) |
Israel |
- |
no |
Medical
records |
no |
Unknown |
Adjusted
and standardised; used multivariate logistic regression |
clear |
no |
|
|
Scotland
1999
(48) |
Scotland |
- |
no |
Audit
(case review and others) |
yes |
+ |
Adjusted
and standardised |
yes |
no deaths |
|
|
Prual A
2000 (49) |
6
countries in West Africa |
5.70% |
yes |
Multiple
source: interview, clinical examinations, records |
yes |
mixed |
Adjusted
and standardized, used multivariate logistic regression |
clear |
yes |
special
effort to capture all deaths |
|
Baskett
TF 1998 (5) |
Canada
|
- |
no |
Medical
records |
yes |
Unknown |
crude |
no |
no |
|
|
Loverro
G 2001 (50) |
Italy |
- |
no |
Medical
records |
no |
Unknown |
crude |
no |
no |
|
|
Souza
JPD 2002 (51) |
Brazil |
- |
no |
Medical
records |
yes |
Unknown |
crude |
yes |
no |
|
|
Murphy
DJ 2002 (52) |
UK |
- |
no |
Multiple
source: maternity database, ICU admissions database |
yes |
Hospital |
crude |
yes |
no |
|
|
Bhuinneain MN 2001
(53) |
Ireland |
- |
no |
Medical
records |
no |
Unknown |
crude |
no |
no |
|
|
Duffy S
2001
(54) |
Ireland |
- |
no |
Medical
records |
yes |
Unknown |
crude |
yes |
yes |
|
|
Prual A
1998 (55) |
Niger |
- |
yes |
Multiple
source: medical records and interview |
no |
Unknown |
adjusted |
no |
no |
Only
definition of haemor-rhage |
|
Mantel
GD 1998 (6) |
South
Africa |
- |
no |
Medical
records and every morning audit meetings |
yes |
Unknown |
crude |
yes |
yes |
|
|
Waterstone M 2001 (56) |
UK |
- |
yes |
Multiple
source: medical records, staff reports, maternity computer database,
labour ward diaries |
yes |
Unknown |
adjusted
and standardized, used multivariate logistic regression |
yes |
no |
|
|
Bernis L
2000 (7) |
Senegal |
2.30% |
yes |
Multiple
source: case records and interview |
yes |
Mixed |
adjusted
and standardized, used multivariate logistic regression |
clear |
yes
|
special
effort to capture all deaths |
|
Filippi
V 1998
(9) |
Benin |
- |
no |
Medical
records |
no |
Unknown |
crude |
no |
no |
|
|
Khosla
AH 2000 (57) |
India |
- |
rural |
Multiple
source: medical records and interview |
no |
Unknown |
crude |
no |
no |
|
|
McCord C
2001
(46) |
India |
5.00% |
rural |
Multiple
source: medical records and interview |
yes |
Mixed |
adjusted
and standardized, |
yes |
yes |
|
|
Canada
2000
(58) |
Canada |
- |
no |
Vital |
no |
Unknown |
- |
yes |
no |
Data from
different studies, prepared by Canadian Perinatal Surveillance System
special group, using Discharge Abstract Database |
|
Geller
SE 2002 (59) |
USA |
5.90% |
urban |
Multiple (hospital discharge financial database, hospital quality
assurance reports, transport review logs, provider referral. Depart.
Quality assurance reports). |
yes |
Unknown |
crude |
Special
score for definition of severe morbidity or near-miss |
no |
|
|
Schoon
MG 1999 (60) |
South
Africa |
2.20% |
mixed |
Multiple:
interview and case records |
no |
unknown |
Standardised |
yes |
yes |
|
|
Vandecruys HB (62) |
South
Africa |
- |
yes |
Multiple:
daily audit meetings, case records |
yes |
unknown |
Adjusted
and standardised |
yes |
yes |
|
|
Haiti
1999
(62) |
Haiti |
+ |
yes |
Multiple
interview and case records |
yes |
Mixed |
Adjusted
and standardised |
unclear |
yes |
|
|
Girard F
2001 (8) |
France |
- |
yes |
Medical
records |
yes |
Unknown |
adjusted
and standardised, used multivariate logistic regression |
yes |
yes |
|
The more recent studies not only calculate incidence/prevalence data and
try to reveal risk factors but also evaluate the quality of perinatal care.
Several studies present morbidity data collected during audits in the
hospital producing very clear conclusions about suboptimal or optimal care.
A study in South Africa (61) compared incidence/prevalence ratio changes
during several years when special measures to improve perinatal care and to
reduce maternal mortality and morbidity were taken.
Quality assessment of studies
The quality assessment of the studies is presented in table
2. It shows that most of the studies are of poor methodological quality.
Only 24% of studies present information about lost to follow-up cases, 45%
of studies included a description of the studied population. Data sources
varied: most of the studies used case records, 42% used multiple sources,
but in two studies there was no information about it. Two studies used 4 or
5 sources to collect data: medical records, staff reports, maternity
computer database, labour ward diaries, hospital discharge financial
database, hospital quality assurance reports, transport review logs,
provider referrals and others. Description about study settings was found
not in all studies too (12 show as "-", there was not one word about setting
characteristics). Some studies described the setting with only minimal
characteristics, for example tertiary care or referral hospital. Information
about the place of delivery is relatively rare and more often reported in
studies from developing countries. Most studies had data about risk factors
(66%) and more or less clear case definition (82%). Two studies used special
efforts to capture all maternal deaths. Data reporting forms are usually
crude, some recent studies report adjusted and standardised results.
Severe maternal morbidity ratios in studies
Table 3 shows the incidence/prevalence ratio and case –
fatality. Large discrepancies exist between the surveys. Most of the
variation in the rates and ratios described is due to different inclusion
criteria. Many studies used deliveries as the denominator, making it easier
to compare data. Canada presents the lowest morbidity ratio (less than 1).
The other studies present similar incidence/prevalence ratios, varying
between 1.1 – 8.23%. All four studies from South Africa report the highest
case- fatality ratios: about 1 of 5 women with severe maternal morbidity
died in this country. In India and Niger 1 out of 11 women with
life-threatening complications died as compared to the United Kingdom with 1
of 118 or France with 1:222 maternal deaths are reported.. The very high
case- fatality rate in South Africa may be due to different definitions or
differences in perinatal care quality. The measured markers for severe
maternal morbidity were different, and haemorrhage, sepsis, eclampsia are
all included in all studies. Dystocia and cesarean section as a cause of
severe morbidity reported only form studies conducted in developing
countries, as they are less threatening conditions in developed countries.
Haemorrhage as a marker was frequently used in studies from South Africa
(49). Studies that used more strict severe haemorrhage criteria showed a
prevalence ratio of less than 1%. For example, a population-based study from
the United Kingdom (56) defining severe haemorrhage with a blood loss more
than 1500 ml, reported a prevalence of 0.03%. The same criteria used in
France by Girard (8) reported a ten times higher prevalence of haemorrhage -
0.39% and 3 times higher case-fatality ratio.
In Benin, Niger and India many deliveries are complicated by severe
haemorrhage and 1 out of 11 women dies if she has this condition. The
variations in sepsis prevalence are not so big and it may be due to a more
clear definition and can be explained only by the differences in perinatal
care level. Case-fatality ratios in all countries are extremely different:
few women die due to sepsis in Canada, Senegal, France, but in Niger and
South Africa these numbers are between 50-72%. Half of the women with
eclampsia died in India, but the average of case-fatality ratio in other
studies due to eclampsia is 5%. The incidence of ruptured uterus is between
0.01-1%, and is associated with a higher mortality rate in some countries
(South Africa). The prevalence of thrombo-embolism was reported only from
Canada and South Africa, with high lethality in both countries: in Canada
(depending on the treatment) 3-30%, in South Africa 83% -100%.
Table 3. The incidence/prevalence (1) (% ) and
case-fatality ratio (2) (% ) of severe maternal morbidity studies.
|
Study |
Denominator |
Severe maternal morbidity |
Rupture of the uterus |
Haemorrhage |
Sepsis |
Eclampsia |
Dystocia |
Cesarean section |
Thrombo- embolism |
Severe liver
disorders |
|
1 |
2 |
1 |
2 |
1 |
2 |
1 |
2 |
1 |
2 |
1 |
2 |
1 |
2 |
1 |
2 |
1 |
2 |
|
Prual A
2000 (49), West Africa |
Live births |
6.64 |
3.1 |
0.11 |
30 |
3.05 |
2.8 |
0.09 |
18 |
0.19 |
18 |
2.05 |
0 |
0.55 |
0 |
0.02 |
50 |
0.63 |
0 |
|
Baskett TF
1998 (5), Canada |
Deliveries |
0.07 |
3.6 |
- |
- |
0.02 |
8.3 |
0.01 |
0 |
- |
- |
- |
- |
- |
- |
0.01 |
25 |
0 |
0 |
|
Prual A
1998 (55), Niger |
Live births |
6.4 |
13.7 |
0.1 |
0 |
0.86 |
14,5 |
0.22 |
50 |
0.22 |
5.9 |
3.4 |
3.2 |
- |
- |
- |
- |
- |
- |
|
Mantel GD
1998 (6), South Africa |
Deliveries |
1.1 |
20.4 |
- |
- |
0.25 |
5.26 |
0.22 |
27.6 |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
|
Vandecruys
HB 2002 South Africa (61) |
|
1.1 |
20 |
- |
- |
0.83 |
- |
0.66 |
- |
- |
- |
- |
- |
- |
- |
- |
100 |
- |
- |
|
Waterstone
M 2001 UK,(56) |
Deliveries |
1.2 |
0.85 |
0.03 |
0 |
0.67 |
0.31 |
0.04 |
17.6 |
0.02 |
0 |
- |
- |
- |
- |
- |
- |
0.05 |
4 |
|
Bernis L
2000, Senegal (7) |
Deliveries |
7.1 |
5.4 |
- |
- |
2.25 |
6.02 |
0.22 |
0 |
1.68 |
4.8 |
2.2 |
0 |
- |
- |
- |
- |
- |
- |
|
Filippi V
1998, Benin (9) |
Deliveries |
8.23 |
8.5 |
- |
-- |
2.3 |
9.2 |
0.44 |
21 |
1 |
4.7 |
4.5 |
3.6 |
- |
- |
- |
- |
- |
- |
|
Khosla AH
2000, India (57) |
Deliveries |
4.37 |
13.84 |
- |
- |
1.31 |
9 |
0.74 |
26.3 |
1 |
52.4 |
. |
- |
- |
- |
- |
- |
- |
- |
|
Mc Cord
2001, India (46) |
Deliveries |
14.18 |
0.49 |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
|
Canada
2000, (58) |
Births |
- |
- |
1 |
low |
>1, if vaginal delivery,
2-12 – if cesarean |
low |
low |
3
-50 |
0.05-
0.2 |
5.8
-14 |
- |
- |
- |
- |
0.3-
0.001 |
3treated,
30 untrea-ted |
- |
- |
|
SChoon MG
1999, South Africa (60) |
Deliveries |
5.3 |
37.4 |
- |
- |
0.06 |
27.3 |
0.03 |
72.7 |
- |
- |
- |
- |
- |
- |
0.02 |
83.3 |
- |
- |
|
Haiti 2001
(62) |
Deliveries |
2.9 |
0.02 |
0.01 |
- |
0.52 |
- |
- |
- |
0.2 |
- |
0.01 |
- |
1.12 |
- |
- |
- |
- |
- |
|
Girard F
France, 2001 (8) |
Births |
0.8 |
0.45 |
- |
- |
0.39 |
0.9 |
0.03 |
0 |
0..38 |
0 |
- |
- |
- |
- |
- |
- |
- |
- |
The results from studies about severe morbidity condition
Table 4 shows the definitions used for severe maternal
morbidity. For many years ICU admissions used as indicators for a subset of
parturient women at risk of severe morbidity. If we look at the structure of
ICU according to disease it is seen that main causes are similar:
haemorrhage, severe pre-eclampsia, sepsis, pulmonary embolism. But in
intensive care we can see women with non-gynaecological diseases: injuries
and accidents, surgical problems and others. The case-fatality ratio of
women admitted to ICU is similar in all countries that show the importance
of this serious morbidity marker: the indications to admit women to ICU or
treat her in a hospital ward are not so different in different countries and
hospitals showing that ICU admission ratios can be useful for comparisons
between studies.
Table 4. The incidence/prevalence ( %) and case-fatality
ratio (%) according to severe maternal morbidity conditions.
|
Study |
Studied condition
|
Denominator |
Prevalence/
incidence |
Case-fatality
ratio |
|
Al Sakka
M 1998 (30), Quatar |
Rupture
of uterus |
Delivery |
0.02 |
0 |
|
Rajab SH
1998 (31), Botswana |
Rupture
of uterus |
Delivery |
0.08 |
0 |
|
Amata AO
1998 (32), Nigeria |
Rupture
of uterus |
Delivery |
1.08 |
22 |
|
Fawzi HW
1998 (33), Sudan |
Rupture
of uterus |
Delivery |
0.15 |
7.14 |
|
Bakour
SH 1998 (34), Syria |
Rupture
of uterus |
Delivery |
0.18 |
5.4 |
|
Nasrat
HA1998 (35), Saudi Arabia |
Hysterectomy |
Delivery |
0.12 |
4.45 |
|
Engelsen
IB 2001, (36)Norway |
Hysterectomy |
Delivery |
0.02 |
0 |
|
Nzerue
CM 1998 (37), USA |
Acute
renal failure |
Women |
0.03 |
14.3 |
|
Ali ME
1998 (38), Qatar |
Acute
abdomen |
Delivery |
0.39 |
0 |
|
Lanska
DJ 1998 (139), USA |
Stroke
and cerebral venous thrombosis |
Delivery |
0.03 |
2 |
|
Tajammul
A1998 (40), Pakistan |
Eclampsia |
Delivery |
0.75 |
5.26 |
|
Riley M
1998 (41), Australia |
Eclampsia |
Delivery |
0.04 |
No data |
|
Chinayon
P 1998 (42), Thailand |
Eclampsia |
Delivery |
0.05 |
3.3 |
|
Makhseed
M 1998 (43), Saudi Arabia |
Preeclampsia |
Delivery |
1.68 |
No data |
|
Wacker J
1998 (44), Zimbabwe |
Preeclampsia |
Delivery |
0.92 |
No data |
|
Tank PD
2002 (45), India |
Severe
liver disease |
Delivery |
0.42 |
42.4 |
|
Gielchinsky Y 2002 (47), Israel |
Placenta
accreta |
Delivery |
0.9 |
0.32 |
|
Scotland
2001 (48) |
Postpartum haemorrhage |
Delivery |
0.84 |
0 |
|
Souza
JPD 2002, (51) Brasil |
Admissions to ICU |
Delivery |
0.14 |
4.9 |
|
Loverro
G 2001, (50) Italy |
Admissions to ICU |
Delivery |
0.17 |
4.9 |
|
Murphy
DJ 2002 (52), UK |
Admissions to ICU |
Delivery |
0.1 |
6 |
|
Bhuinneain MN 2001(53), Ireland |
Admissions to ICU |
Delivery |
0.04 |
No data |
|
Duffy S
2001 (54), Ireland |
Admissions to ICU |
Delivery |
0.09 |
5.26 |
The incidence of ruptured uterus in different counties large variation:
in Quatar and Nicaragua the incidence is between 2-8:10000 and no maternal
death , but in Nigeria one of 100 women has this complication during
delivery and one out of five of them died. Hysterectomies in Norway are
performed ten times less than in Saudi Arabia. For other conditions, such as
preeclampsia, the ratio in two different countries may be very similar, but
the eclampsia ratio can show a big difference (as shown in the previous
table). Because preeclampsia incidence is independent from treatment or
quality of care, the differences of eclampsia incidence could be useful for
the evaluation of preeclamptic patient care. The case-fatality ratio for
severe liver disease in India is very high when compared to that from the
United Kingdom (56) and could be due to differences in treatment and
pregnancy care in different countries.
Discussion
The results of analysis of these studies show that the
incidence/prevalence ratio of severe maternal morbidity varies due to the
different definitions, methods and classifications used. Ratios that are
calculated by using different denominators, different diseases
classifications with different degree of severity are not comparable between
regions. Nevertheless, the reported incidence of severe maternal morbidity
varies from 0.07—8.23% and lethality rates from 0.02-37%.
Maternal mortality risk is obviously dependant on the quality of care. There
is a big difference between case-fatality ratio in developing (South Africa
1:5; India and Niger 1:11) and developed countries (UK 1:118; France 1:222).
It is no secret, that appropriate care can decrease deaths due to severe
maternal morbidity.
Severe maternal morbidity is easy to underestimate because pregnant women
are usually healthy and recover quickly, and are discharged with relatively
little follow-up. Some conditions might be life threatening in certain
contexts while not in others, and different clinical criteria may need to be
applied to define the life threatening nature of the complication (1). In
all studies one or the combination of three types of definitions have been
proposed for defining life threatening obstetric complications and near-miss
events. These approaches include definitions based on (a) management, (b)
clinical signs and symptoms, and (c) organ systems.
The most frequent used definition, based on management, was admission to
ICU. The definition of a "near miss" may be identified by severity or by
disease - in this case, admission to ICU was chosen as it was easy to
measure. The main advantages of this definition are its simplicity and the
ease of data collection since the use of only one register may be required.
In addition, this definition encompasses non-obstetric medical conditions
that might become life threatening and lead to death, for example, cerebral
haemorrhage and hepatitis. The major disadvantage is that intensive care may
only identify a subset of life threatening conditions. In France, for
example, most maternal deaths had been seen in intensive care units, while
in Britain only a third of maternal deaths had received intensive care (1).
Admission criteria to intensive care vary between countries, hospitals and
clinicians, and the capacity and location of the intensive care unit also
influences the number of admissions to these units (40). The definition of
what constitutes an intensive care unit is in itself not clear and varies
across hospitals (5), and some hospitals may not have an intensive care
unit. Because of such variations, comparisons across settings have to be
interpreted with caution.
Other examples of management criteria used in the definition of life
threatening complications include the use of emergency hysterectomy (6, 7,
66), caesarean section (7,9), blood transfusion (7,9), hospitalization for
more than four days (7), and anaesthetic accidents (6). In Benin for
example, any woman with an obstetric haemorrhage necessitating a major
intervention to stop the bleeding qualified as a near miss. Major
interventions included hysterectomy, a blood transfusion of two litres or
more for acute anaemia and coagulation defects, a manual revision of the
uterus with extraction of placental fragments, a caesarean section, and a
suture of the cervix or vagina (9). The main reason for this choice was that
the interventions received were generally noted in the hospital records,
while detailed clinical signs and symptoms were not. The above management
criteria are prone to the same disadvantages as intensive care, however,
since indications for their use may not be standardized and will differ
between settings and clinicians (1). In South Africa for example, the
definition of severe hypovolemia proposed for use in the tertiary hospital
(i.e. hypovolemia requiring >= 5 units of whole blood or packed cells for
resuscitation) (6) had to be adapted for use in a rural district hospital.
In the rural area, thresholds for transfusion were much higher and the
volumes of blood given much lower. The definition for hypovolemia adopted
was: if available, one would transfuse four units of blood or packed cells
for resuscitation (these women should be included even if blood was not
available) (1). The latter illustrates that where blood is not routinely
available, relying on the need for transfusion will clearly not work, and
other - probably clinical - criteria will have to be used.
Most of studies used definitions based on clinical signs and symptoms, such
as haemorrhage, sepsis, hypertensive disorders, but this approach has
several difficulties too. These definitions require the consensus of
clinicians on criteria of severity, which can be difficult to obtain given
the diversity of clinical experience. The criteria also depend on the means
available to clinicians for making diagnoses. Finally, the criteria need to
build on information that is routinely available in medical records to
facilitate data extraction and verification (1).
The organ system-based definition, used in Mantel GD (6) and Schoon MG (60),
is maybe the most accurate definition of a life threatening complication or
a near miss in that only very severe endpoints are selected. This approach
does not entirely avoid the weaknesses outlined above, in that the criteria
used to define organ system failure or dysfunction may also rely on the
management received (e.g. admission to intensive care or emergency
hysterectomy) (1). In addition, the diagnosis of organ failure could require
technologies which may not be available in many developing country hospitals
(for example oxygen saturation).
Since the majority of cases of life threatening complications require
hospital care to save the woman’s life, hospital records are the most likely
source of information on these complications (63). Although some have argued
that cases can also be identified in the community because women can
remember an event as distressing as a near miss, there is now substantial
evidence that this is not the case. Studies assessing women’s recall of
obstetric morbidity have found disagreement between the woman’s recall of
her childbirth experience and medically diagnosed complications (63,64) or
near miss. At a task force meeting on the validation of women’s reporting of
obstetric complications, it was concluded that the estimation of the
population prevalence of obstetric complications based on interview data
collected in national surveys are not likely to be valid or reliable (65).
While this does not mean that obtaining the community perspective on severe
maternal illness is not possible, it does imply that life threatening
adverse events need to be identified in the hospital first, or a study risks
interviewing cases which are not truly life threatening (64).
The estimates of incidence probably underestimate the true incidence as case
ascertainment is unlikely to be complete, especially if events occur outside
the delivery suite and are not recognised; this may be particularly true of
less serious cases. Only few studies used prospective data collection
methods (6, 49, 56, 61). In countries with good access to health care
hospital-based reviews can measure the incidence of serious conditions,
because the untreated segment represents a smaller proportion of morbid
population, but existing registers often need modification to supply the
required data (64). Most hospital registers record the type of delivery and
obstetric interventions, but specifying the complications as indications for
the interventions appears to be inadequate. Within facilities, the data on
obstetric complications often need to be collected from a series of
registers and case notes, including admission, delivery, discharge,
referral, intensive care and surgical registers. (1). Geller (59) used five
different data sources: 38% of cases were identified from hospital discharge
financial database, 20% from hospital quality assurance reports, and another
20% from transport review logs. Obtaining information from several sources
helps to achieve more exact results but only 50% of included studies in this
review studies used this approach. Missing information seems to be more
likely for emergency admissions, which are also likely to represent more
serious complications. Women with complications are likely to be admitted in
different wards of the hospital, and tracing patients across different
registers is not easy because many registers lack a clear patient
identification. Double counting may be a problem if more than one register
needs to be consulted. Two studies conducted in the USA (39) and the UK (56)
tried to solve this problem. If daily staff meetings are held, obstetric
events can also be identified from a review of the case notes from these
meetings (6, 61).
These dramatic differences are a good illustration of the problems when the
studies are not population based. Measuring the morbidity in one or two
departments in a teaching hospital or even in one or two clinics in a town,
can lead to a biased picture of the real situation. Population based surveys
(7, 49, 56, 60, 61) are preferable because the situation has to be depicted
in a complete health area, taking into account all medical facilities
playing a role in obstetric health fields.
Current data base and hospital records do not respond accurately to all
purposes of measuring maternal morbidity. As there is no universal health
indicator, it will be necessary to carry out specific surveys with the
appropriate methodologies.
Conclusions
- Incidence of severe maternal morbidity ranges from 0.07—8.23%,
case-fatality ratio 0.02-37%.
- There is big difference between case-fatality ratio in developing
(south africa 1:5; india and niger 1:11) and developed countries (uk
1:118; france 1:222).
- Studies estimating the incidence of severe morbidity have used
different definitions.
- Identifying cases of severe maternal morbidity requires
sophisticated tools and clear definitions.
- Reviewing cases of severe maternal morbidity can provide useful
complimentary insights into quality of care.
- A good quality medical system is required.
The severe maternal morbidity-mortality ratio can possibly
be a new indicator of maternal care and could be used to compare
improvements in treatments more accurately than mortality data alone. This
major health risk to childbearing women is still relatively under
investigated. Severe maternal morbidity is measurable and may be a more
meaningful way to measure improvements in health care. Further work should
identify those elements of the definition that are associated with poorer
outcomes.
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