Chapter 4Chapter Outline22IM – 4 1

Chapter 4
Chapter Outline
2
2
IM – 4 | 1
Copyright © 2017 McGraw-Hill Education. All rights reserved.
No reproduction or distribution without the prior written
consent of McGraw-Hill Education.
THE ROLE OF SOCIALIZATION
Social Environment: The Impact of Isolation
The Influence of Heredity
THE SELF AND SOCIALIZATION
Sociological Approaches to the Self
Psychological Approaches to the Self
AGENTS OF SOCIALIZATION
Family
School
Peer Group
Mass Media and Technology
Workplace

Religion and the State
SOCIALIZATION THROUGHOUT THE LIFE COURSE
The Life Course
Anticipatory Socialization and Resocialization
ROLE TRANSITIONS THROUGHOUT THE LIFE COURSE
The Sandwich Generation
Adjusting to Retirement
SOCIAL POLICY AND SOCIALIZATION: CHILD CARE
AROUND THE WORLD
Boxes
Sociology on Campus: Impression Management by Students
Research Today: Rum Springa: Raising Children Amish Style
Taking Sociology to Work: Rakefet Avramovitz, Program
Administrator, Child Care Law Center
Sociology on Campus: Unplugging the Media: What Happens?
Chapter Summary
Socializationis the process whereby people learn the attitudes,
values, and behaviors appropriate to individuals as members of
a particular culture. Socialization occurs through human
interaction and helps us to discover how to behave properly. It
provides for the transmission of culture from one generation to
the next, to ensure the long-term continuance of a society.
Socialization experiences help to shape personality—a person’s
typical patterns of attitudes, needs, characteristics, and
behavior.
Under normal circumstances, environmental factors interact

with hereditary factors in influencing the socialization process.
Case studies—such as those of Isabelle and the Romanian
orphans—and primate studies support the necessity of
socialization in development. Conversely, twin studies have
addressed the influence of hereditary factors on personality
development.
The self is a distinct identity that sets us apart from others. It
continues to develop and change throughout our lives.
Sociologists Charles Horton Cooley, George Herbert Mead
(pioneers of the interactionist approach), and Erving Goffman
have all furthered our understanding about development of the
self. Cooley’s looking-glass self suggests that our sense of self
results from how we present ourselves to others, how others
evaluate us, and how we internalize or assess those evaluations.
Mead outlined a process by which the self emerges in early
childhood: the preparatory stage, in which children merely
imitate those around them; the play stage, in which children
become aware of symbols and begin to act out the roles of other
people; and the game stage, in which children become involved
in complex social situations involving multiple positions or
roles. Instrumental to Mead’s view are the concepts of the
generalized other (attitudes, viewpoints, and expectations of
society) and significant others (individuals most important in
development of the self). Goffman suggested that many of our
daily activities involve attempts to convey impressions
(impression management) of who we are. His view has been
termed the dramaturgical approach. Goffman also drew attention
to face-work, the efforts people make to maintain the proper
image and avoid public embarrassment.
Psychologists, such as Sigmund Freud, have stressed the role of
inborn drives in the development of the self. Child psychologist
Jean Piaget identified four stages of personality development in
his cognitive theory of development (sensorimotor,
preoperational, concrete operational, and formal operational).

Piaget viewed social interaction as key to development.
Lifelong socialization involves many different social forces and
agents of socialization. Family is considered the most important
of the socialization agents. Schools are another agent of
socialization concerned with teaching students the values and
customs of the larger society. Peer groups often serve as a
transitional source to adulthood. The mass media have an
impact on the socialization process that sociologists have also
begun to consider. Workplaces can serve as socialization agents
by teaching appropriate behavior within an occupational
environment. Additionally, social scientists have increasingly
recognized the importance of religion and the state as agents of
socialization, because of their impact on the life course.
Sociologists use the life course approach in recognizing that
biological changes mold but do not dictate human behavior.
Over the course of our lives, we may encounter points at whi ch
certain stages are dramatized or validated outwardly; these
stages are known as rites of passage. Two types of socialization
occur: anticipatory socialization (refers to the process of
rehearsing for future roles), and resocialization (refers to
discarding former behavior patterns and accepting new ones).
Resocialization is particularly intense when it occurs within a
total institution, an institution that regulates all aspects of a
person’s life under a single authority. Goffman identified four
common traits of total institutions. He suggested people often
lose their individuality within total institutions and may
undergo what is known as a degradation ceremony.
Although how we move through the life course varies
dramatically according to our personal preferences and
circumstances, certain common transitional stages have been
identified, including entering the adult world, the midlife
transition, and retirement. The midlife crisis is a stressful
period of self-evaluation that commonly begins at about age 40.

The sandwich generation consists of adults who must
simultaneously try to meet the competing needs of their parents
and their children. Gerontologist Robert Atchley has identified
several distinct phases of the retirement experience, which
suggests retirement is not a single transition but rather a series
of adjustments. Recent improvements in health care have given
older Americans new choices in where to live, and many now
congregate in naturally occurring retirement communities
(NORCs).
Introduction
• Excerpt from an interview with Crystal Moselle, director
of The Wolf Pack
I. The Role of Socialization
• The nature vs. nurture debate has evolved to a general
acceptance of interaction between the variables of heredity,
environment, and socialization.
A. Social Environment: The Impact of Isolation
• The need for human interaction is evident in actual case
studies.
1. Extreme Isolation: Isabelle
• Isabelle lived in seclusion for six years. She could not
speak and did not display reactions or emotions typical of
humans. After a period of intense language and behavioral
therapy, Isabelle became well adjusted.
2. Extreme Neglect: Romanian Orphans
• Babies in orphanages lay in cribs for 18 to 20 hours a day,
with little care from adults. The children grew up fearful of
human contact and prone to antisocial behavior. They have
made progress with supervision from attentive caregivers and
specialists.

3. Primate Studies
• Harry Harlow tested rhesus monkeys for the effects of
isolation and concluded that isolation had a damaging effect on
the monkeys.
B. The Influence of Heredity
• Twin studies reveal that both genetic factors and
socialization experiences are influential in human development.
Example: Oskar Stohr and Jack Yufe
• The validity of twin studies has been questioned because
of the small sample sizes.
II. The Self and Socialization
• The self is a distinct identity that sets each of us apart
from others. The interactionist perspective is useful in
understanding development of the self.
A. Sociological Approaches to the Self
1.Cooley: Looking-Glass Self
• According to Cooley, the self is a product of social
interactions with others. There are three phases in the looking-
glass self: (1) We imagine how we present ourselves to others;
(2) we imagine how others evaluate us; and (3) we develop a
feeling about ourselves. Example: A student’s sense of self is
changed after receiving criticism from a teacher.
2. Mead: Stages of the Self
• The preparatory stage consists of children imitating people
around them. Gradually, children begin to understand the use of
symbols.
• The play stage consists of children pretending to be other
people, like an actor “becoming” a character. Role-taking is the
process of mentally assuming the perspective of another and
responding from that imagined viewpoint. Through role-taking,
children learn to see the world from the perspectives of other
people.

• During the game stage, children grasp their own social
positions, as well as everyone else’s position around them.
Games serve as a microcosm of society. Through this process,
children learn to assume their position (or status) relative to the
positions of others.
• The term generalized other refers to the attitudes,
viewpoints, and expectations of others in society that an
individual takes into account before acting in particular way.
3. Mead: Theory of the Self
• Children picture themselves as the focus of everything
around them. As people mature, the self changes and begins to
consider the reactions of others.
• Mead used the term significant others to refer to those
individuals who are most important in the person’s
development.
4. Goffman: Presentation of the Self
• Impression management involves an individual slanting his
or her presentation of the self to create a distinctive appearance
and to satisfy particular audiences.
• The dramaturgical approach is based on people behaving as
actors by putting forth an image believed to be pleasing to
others.
• Goffman’s face-work involves people trying to maintain or
save an image or face. Example: An individual may feign
employment to avoid embarrassment.
B. Psychological Approaches to the Self
• Freud stressed the role of inborn drives. The self has
components that work in opposition to each other. Part of us
seeks limitless pleasure, while another part seeks rational
behavior.
• Piaget found that although newborns have no sense of self
in the sense of a looking-glass image, they are self-centered,
understanding only “me.” As they mature, they are gradually
socialized into social relationships.
• In his cognitive theory of development, Piaget identified

four stages of child development: (1) sensorimotor stage (child
uses senses to make discoveries),
(2) preoperational stage (child begins to use words and
symbols), (3) concrete operational stage (child engages in more
logical thinking), and (4) formal operational stage (adolescent is
capable of sophisticated abstract thought, and
can deal with ideas and values in a logical manner).
• Social interaction is the key to development.
III. Agents of Socialization
A. Family
• Family is the most important socializing agent. Parents
minister to the baby’s needs by feeding, cleansing, carrying,
and comforting.
• In the U.S., social development includes exposure to
cultural assumptions regarding gender and race.
• Parents guide children into gender roles deemed
appropriate by society.
B. School
• Schools have an explicit mandate to socialize children to
societal norms.
• Functionalists indicate schools fulfill a function by
socializing children, whereas conflict theorists suggest schools
reinforce divisive aspects of society, especially social class.
Example: A teacher praising boys may reinforce sexist attitudes.
C. Peer Group
• As a child grows older, family becomes somewhat less
important in social development, while peer groups increasingly
assume the role of Mead’s significant others.
D. Mass Media and Technology
• Media innovations have become important agents of

socialization. Ninety-five percent of those aged 12 to 17 are on
the Internet.
• Television can be both a negative and a positive influence
on children.
• Cell phones are a particularly significant communications
technology for people in low-income nations; but most of those
same people cannot afford broadband access to the Internet.
E. Workplace
• We learn to behave appropriately within an occupation.
• The U.S. has the highest level of teenage employment of
all industrialized nations, with growing concern regarding
adverse effects of work on schooling.
• Workplace socialization changes when a person shifts to
full-time employment.
F. Religion and the State
• State-run agencies are increasingly influential in life
course.
• Government and organized religion have reinstituted some
of the rites of passage once observed in earlier societies.
IV. Socialization throughout the Life Course
A. The Life Course
• Celebrating rites of passage is a means of dramatizing and
validating changes in a person’s status.
• The life course approach looks closely at the social factors
that influence people throughout their lives, from birth to death,
including gender and income. Certain life events like marriage,
completion of schooling, and birth of one’s first child mark the
passage into adulthood.
B. Anticipatory Socialization and Resocialization
• Anticipatory socialization refers to a person rehearsing for

a role they will likely assume in the future. Example: High
school students preparing for college by looking at college
websites
• Resocialization refers to discarding the former sense of
self and behavior patterns and accepting new behavior patterns.
Examples: Prisons, indoctrination camps, and religious
conversions
• Goffman suggested resocialization is particularly effective
in a total institutional environment (prisons, mental hospitals,
and military organizations).
• Individuality is often lost in total institutions, as the
individual becomes secondary in the environment and
experiences the humiliations of degradation ceremonies.
V. Role Transitions throughout the Life Course
• Role transitions are transitional stages during the life
course, i.e. entering adulthood, midlife crisis.
A. The Sandwich Generation
• This refers to adults who are trying to meet the competing
needs of their parents and children.
B. Adjusting to Retirement
• The retirement stage today is complicated by economic
deterioration.
1. Phases of Retirement
• Robert Atchley’s phases of retirement include
preretirement, the near phase, the honeymoon phase, the
disenchantment phase, the reorientation phase, the stability
phase, and the termination phase. Retirement, then, is a series
of adjustments.
• The experience of retirement varies according to gender,
race, and ethnicity.
2. Naturally Occurring Retirement Communities

• These involve the congregation of older Americans in
areas that have gradually become informal centers for senior
citizens.
VI. (Box) Social Policy and Socialization: Child Care around
the World
A. Looking at the Issue
• Day-care centers have become the functional equivalent of
the nuclear family. Eighty-eight percent of employed mothers in
the United States depend on others to care for their children,
and 30 percent of mothers who aren’t employed have regular
care arrangements.
• Research suggests good day care benefits children.
• There are no significant differences between infants who
receive extensive non-maternal care vs. those who are cared for
solely by their mothers.
B. Applying Sociology
• Conflict theorists raise concerns about the cost of day care,
especially for lower-class families.
• Feminist theorists suggest that funded child care is
opposed because it is seen as “merely a way to let women
work.” Child care workers’ average annual salary in the U.S. is
currently right at the poverty level for a family of three.
C. Initiating Policy
• When policymakers decide that child care is desirable,
they must determine the degree to which taxpayers should
subsidize it.
• Policies regarding child care outside the home vary
throughout the world. In Sweden and Denmark, one-half to two-
thirds of preschoolers are in government-subsidized child care.
In Japan, the availability of day care has not kept pace with the
growing number of mothers remaining in the labor force.

Key Terms
Anticipatory socialization Processes of socialization in which a
person rehearses for future positions, occupations, and social
relationships.
Cognitive theory of development The theory that children’s
thought progresses through four stages of development.
Degradationceremony An aspect of the socialization process
within some total institutions, in which people are subjected to
humiliating rituals.
Dramaturgicalapproach A view of social interaction in which
people are seen as theatrical performers.
Face-work The efforts people make to maintain the proper
image and avoid public embarrassment.
Genderrole Expectations regarding the proper behavior,
attitudes, and activities of males and females.
Generalizedother The attitudes, viewpoints, and expectations of
society as a whole that a child takes into account in his or her
behavior.
Impressionmanagement The altering of the presentation of the
self in order to create distinctive appearances and satisfy
particular audiences.
Lifecourseapproach A research orientation in which
sociologists and other social scientists look closely at the social
factors that influence people throughout their lives, from birth
to death.
Looking-glassself A concept that emphasizes the self as the
product of our social interactions.
Midlifecrisis A stressful period of self-evaluation that begins at
about age 40.
Naturallyoccurringretirementcommunity (NORC) An area that
has gradually become an informal center for senior citizens.
Personality A person’s typical patterns of attitudes, needs,
characteristics, and behavior.

Resocialization The process of discarding former behavior
patterns and accepting new ones as part of a transition in one’s
life.
Riteofpassage A ritual marking the symbolic transition from
one social position to another.
Roletaking The process of mentally assuming the perspective
of another and responding from that imagined viewpoint.
Sandwichgeneration The generation of adults who
simultaneously try to meet the competing needs of their parents
and their children.
Self A distinct identity that sets us apart from others.
Significantother An individual who is most important in the
development of the self, such as a parent, friend, or teacher.
Socialization The lifelong process in which people learn the
attitudes, values, and behaviors appropriate for members of a
particular culture.
Totalinstitution An institution that regulates all aspects of a
person’s life under a single authority, such as a prison, the
military, a mental hospital, or a convent.
Essay Questions
1. What does the case history of Isabelle tell us about the
importance of socialization?
2. What do the Romanian orphanage studies tell us about the
importance of social interaction in the socialization process?
3. How do the studies of animals raised in isolation support the
importance of socialization on development?
4. What do twin studies tell us about the nature versus nurture
argument?
5. How did Charles Horton Cooley approach the socialization
process?
6. How did George Herbert Mead approach the socialization
process?
7. Identify and explain George Herbert Mead’s three distinct
stages in childhood socialization.
8. Distinguish between significant and generalized others, and

note their importance to George Herbert Mead.
9. How can Erving Goffman’s conceptualization of impression
management be used to understand social behavior?
10. Define and offer an example you have observed of
impression management and face-work.
11. How do college students use impression management after
examinations?
12. What do psychological approaches tell us about the self?
13. Explain the role played by rites of passage and give
examples of such rites in different cultures.
14. What is the difference between anticipatory socialization
and resocialization?
15. What is meant by degradation ceremony, and how does it
relate to socialization?
16. What are the significant forces in childhood socialization?
17. What part do gender roles play in socialization?
18. What is the significance of television in the socialization
process of children?
19. What impact, if any, has access to new technology (the
Internet, cell phones) had on the socialization process?
20. In what way does the workplace play a role in socialization?
21. How does religion play a role in socialization?
22. In what way does the state or the government play a role in
socialization?
23. What is the “sandwich generation”?
24. What are the phases in the retirement experience identified
by Robert Atchley?
25. How does retirement vary by gender, race, and social class?
26. What affect does high-quality child care have on the
development of children?
27. How might functionalists and conflict theorists analyze the
controversy over child care/day care differently?
28. Examine child care outside the home using a micro-level
analysis.
29. What concerns do feminists have with high-quality
childcare?

30. How does out-of-home childcare differ in other countries?
Critical Thinking Questions
1. Discuss the influence of heredity in explaining the process of
one’s personality development. Give examples to support your
discussion. Have students identify similarities and differences
between themselves and their siblings and discuss possible
explanations for the differences, both from a “nature” and a
“nurture” perspective (i.e., Did their mother and/or father
interact differently with the siblings? Is one sibling more like
the mother, father, grandmother, grandfather, etc.?)
2. Define Goffman’s dramaturgical approach in the development
of the self. Give examples in which you may have used
impression management to portray your image as favorable to
others around you.
3. Discuss Jean Piaget’s cognitive theory of development and
offer any strengths or criticisms of his approach in viewing
personality development. Give examples from your own
observations that either support or fail to support Piaget’s
theory.
4. Identify Goffman’s four traits of total institutions and discuss
how a degradation ceremony is used to erode one’s sense of
self. Discuss why elimination of the former sense of self is
necessary to fully resocialize a person.
5. Discuss the various ways socializing agents may contribute to
an institutionalized system of social inequality. Give some
examples to support your answer.
6. Describe why adjustment to retirement may or may not be
easier for a person in a modern society compared to a person in
an earlier society.
IM – 4 | 10
Copyright © 2015 McGraw-Hill Education. All rights reserved.
No reproduction or distribution without the prior written
consent of McGraw-Hill Education.

Placenta Previa and Maternal Hemorrhagic Morbidity
Karen J. GIBBINS, MD, Brett D. EINERSON, MD, Michael W.
VARNER, MD, Robert M.
SILVER, MD
Department of Obstetrics and Gynecology, Division of Maternal
Fetal Medicine, University of Utah
School of Medicine, Salt Lake City, UT
Intermountain Healthcare Department of Maternal Fetal
Medicine, Salt Lake City, Utah
Abstract
Objective: Placenta previa is associated with maternal
hemorrhage, but most literature focuses
on morbidity in the setting of placenta accreta. We aim to
characterize maternal morbidity
associated with previa and to define risk factors for
hemorrhage.
Methods: This is a secondary cohort analysis of the NICHD
Maternal-Fetal Medicine Units
Network Cesarean Section Registry. This analysis included all
women undergoing primary
Cesarean delivery without placenta accreta. 496 women with
previa were compared to 24,201
women without previa. Primary outcome was composite
maternal hemorrhagic morbidity. Non-
hemorrhagic morbidities and risk factors for hemorrhage were
also evaluated.

Results: Maternal hemorrhagic morbidity was more common in
women with previa (19 vs 7%,
aRR 2.6, 95% CI 1.9-3.5). Atony requiring uterotonics (aRR
3.1, 95% CI 2.0-4.9), red blood cell
transfusion (aRR 3.8, 95% CI 2.5-5.7), and hysterectomy (aRR
5.1, 95% CI 1.5-17.3) were also
more common with previa. For women with previa, factors
associated with maternal hemorrhage
were pre-delivery anemia, thrombocytopenia, diabetes,
magnesium use, and general anesthesia.
Conclusion: Placenta previa is an independent risk factor for
maternal hemorrhagic morbidity.
Some risk factors are modifiable, but many are intrinsic to the
clinical scenario.
Keywords
placenta previa; obstetric hemorrhage; maternal morbidity
Introduction
The rate of placenta previa is increasing [1], accounting for
1.3% of pregnancies in 2007 [2].
This increase has coincided with the crescendo in Cesarean
deliveries (CD) [3, 4]. Placenta
previa necessitates delivery via CD, often at preterm gestations.
Deliveries complicated by
Corresponding Author: Karen J. GIBBINS, MD, University of

Utah Health Sciences Center, Department of OB/GYN, Division
of
Maternal-Fetal Medicine, Suite 2B200, 30 North Medical Drive,
Salt Lake City, UT 84132, 801-581-8425 (o),
[email protected]
Conflict of Interest/Disclosure Statement/Declaration of
Interest: The authors report no conflicts of interest.
Presentation: This study was presented in part at the 36th
Annual Society of Maternal Fetal Medicine Meeting (February
1-6, 2016,
Atlanta, GA) as an oral and a poster presentation.
HHS Public Access
Author manuscript
J Matern Fetal Neonatal Med. Author manuscript; available in
PMC 2019 August 08.
Published in final edited form as:
J Matern Fetal Neonatal Med. 2018 February ; 31(4): 494–499.
doi:10.1080/14767058.2017.1289163.
A
u
th
o
r M
a
n
u
scrip
t
A

u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a

n
u
scrip
t
placenta previa are at high risk for obstetric hemorrhage prior
to, during, and after delivery
[1, 5]. For example, placenta previa or abruption have adjusted
odds ratio of 7.0 (95% CI
6.6-7.3) for severe postpartum hemorrhage [6]. Hemorrhage is
associated with increased risk
of maternal morbidity, the need for additional medications and
procedures to staunch
bleeding and the sequelae of overwhelming hemorrhage such as
coagulopathy [1, 2, 5, 7].
Previous studies characterizing hemorrhage and morbidity due
to placenta previa have
focused on those that are also complicated by placenta accreta
or morbidly adherent
placenta[2, 8, 9, 10]. Thankfully, most placenta previas are not
comorbid with accreta.
However, few data are available to counsel women diagnosed
with placenta previa and no
accreta. One prior study evaluating morbidity of previa in

Australia found a 14% rate of
major morbidity in these women, however a large proportion of
women in this study
delivered at hospitals without 24 hour blood banks[11].
Improved knowledge of the true
morbidity of placenta previa will also allow us to justify, plan,
and adequately power
intervention trials to effectively decrease this morbidity.
Thus, our objectives were to characterize the maternal
morbidity associated with placenta
previa without accreta and to define maternal and obstetric risk
factors that increase the odds
of maternal morbidity.
Materials and Methods
This is a secondary analysis of the National Institute of Child
Health and Human
Development Maternal-Fetal Medicine Units (MFMU) Network
Cesarean Section Registry
(CSR). The CSR was a prospective registry from 1999 to 2002
conducted in 19 academic
medical centers participating in the MFMU Network. The
original cohort included women
undergoing CD or vaginal birth after at least one previous CD

(VBAC). For 1999 and 2000,
patients were eligible if they delivered via primary or repeat CD
or VBAC. Starting in 2001,
only repeat CD and VBAC were included. The original registry
included only deliveries of
infants of at least 500 grams birthweight or 20 weeks
gestational age by best estimate using
standard obstetric dating criteria. Nurse coordinators and all
study nurses assigned to the
study underwent a certification process for data abstraction
using a sample chart to prove
adequacy of chart abstraction and coding. Data were obtained
from review of the patient’s
medical record. Chart abstraction forms were provided by the
MFMU.
This analysis is a cohort study with placenta previa as the
exposure and post-operative
maternal morbidity as the outcome. All women in the CSR who
underwent primary CD
were included. Only primary CDs were included in order to
control for the additional
morbidity associated with repeat CD. Women were excluded if
the number of previous CDs
was not recorded, even if the indication for current CD was

listed under “primary c-section
indications.” The previa cohort (cases) was defined as women
undergoing CD with the
indication for CD coded as “previa with hemorrhage” or “previa
without hemorrhage.” The
no previa cohort (controls) included all other CDs in the
dataset. Morbidly adherent
placentae (placenta accreta, placenta increta, or placenta
percreta) were excluded from both
cohorts. Accreta was coded as present if the placenta was
adherent to the uterine wall. When
GIBBINS et al. Page 2
PMC 2019 August 08.
A
u
th
o
r M
a
n
u
scrip
t
A

n
u
scrip
t
pathologic report of the uterus was available, pathologic
assessment of adherent placenta
took precedence over clinical suspicion.
The primary outcome was maternal hemorrhagic morbidity,
defined as mortality, blood
product transfusion, atony requiring uterotonics, uterine or
hypogastric artery ligation,
hysterectomy, coagulopathy, and/or exploratory laparotomy. A
separate analysis of the
primary outcome was performed excluding atony requiring
uterotonics since this outcome is
more common and less morbid than the others in the composite.
Severe maternal morbidity
was defined per the Joint Commission policy as ICU admission
or receipt of ≥4 units of
blood products. The decrease in hemoglobin prior to and after
delivery was compared. Rates
of emergent delivery and emergent delivery for antenatal
hemorrhage were compared as

well. The frequency of hemorrhagic morbidity was compared
between women with and
without any antenatal bleeding leading to delivery. Other
maternal outcomes examined
included mortality, cystotomy or ureteral injury, bowel injury,
venous thromboembolic
disease, postpartum endometritis, wound complication,
necrotizing fasciitis, maternal sepsis,
acute respiratory distress syndrome, cardiopulmonary arrest,
pulmonary edema, septic pelvic
thrombophlebitis, and readmission for any reason.
A case-control analysis also was conducted in the cohort of
women with placenta previa to
evaluate potential risk factors for hemorrhagic morbidity, as
defined above. Cases were those
who experienced hemorrhagic morbidity, and controls were
those who did not. We evaluated
the following exposures: maternal age, race, education,
modality of healthcare payment,
body mass index (BMI) (pre-delivery and at delivery), number
of fetuses, parity, anemia
(hematocrit <33%), thrombocytopenia (platelets <150,000/μL),
gestational age at delivery,

emergent delivery, neonatal birthweight, neonatal sex, maternal
health comorbidities
(diabetes, asthma, thyroid disease, seizure disorder,
hypertension, renal disease, heart
disease, and connective tissue disease), previous myomectomy,
tobacco use, alcohol use,
drug use, presence of preterm premature rupture of membranes
(PPROM), preterm labor,
bleeding as indication for delivery, meconium, hypertensive
disease of pregnancy,
magnesium administration, placental abruption,
chorioamnionitis, general anesthesia, and
vertical uterine incision.
In order to be sure that we could address the primary research
question, a sample size
estimate was calculated based on the assumption of a 25%
frequency of postpartum
hemorrhage in the previa group [2, 12]. If we assume a 10% or
lower rate of postpartum
hemorrhage in the no previa group [6], power of 90%, and a
two-sided alpha of 0.05, 146
subjects per group would be required.
The primary outcomes are reported with numbers, rates, relative
risks, 95% confidence

intervals, and p-values. Secondary outcomes are presented as
numbers, means, rates, and
standard deviations as appropriate. Comparisons were
conducted using the Wilcoxon rank-
sum test, chi-square test, and risk ratios as appropriate. Logistic
or Poisson linear regression
models were fitted for these outcome variables as well.
Regression models were built by
selecting variables using backwards-stepwise elimination
testing statistically different
variables into the model first. Analysis was conducted using
Stata version 13.1 (StataCorp
LP, College Station, TX).
J Matern Fetal Neonatal Med. Author manuscript; availabl e in
PMC 2019 August 08.
A
u
th
o
r M
a
n
u

scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th

o
r M
a
n
u
scrip
t
Results
54,458 women underwent CD and did not have a placenta
accreta in the MFMU CSR. 196
women with placenta accreta were excluded. 24,697 underwent
primary CD, of which 496
had placenta previa and 24,201 had no placenta previa.
Demographics of the study cohort
are presented in Table 1. Women with previa were 3.3 years
older, had a lower pre-
conception BMI by 2.1 points, and were more likely to use
tobacco than women without
previa. Women with previa had a higher median number of
previous births >20 weeks (1 vs
0, p<0.001). Women with previa were significantly less likely
to have undergone labor or
induction of labor than women without previa (22.8% vs 74.1%,

p<0.001). Births
complicated by previa occurred earlier in gestation (35.1 vs
37.6 weeks, p<0.001) and had
lower birth weight (2503 vs 2987 grams, p<0.001). Each of
these demographic and obstetric
factors were considered for the regression models.
After backwards-stepwise elimination, the Poisson regression
model for the primary
outcome of hemorrhagic morbidity included the following
variables: presence of any labor
or induction attempt, admission hematocrit, pre-conception
BMI, maternal age, diabetes,
number of fetuses, meconium, placental abruption,
chorioamnionitis, neonatal weight, years
of schooling, use of tocolysis, diagnosis of preeclampsia or
gestational hypertension, and
prior vaginal delivery
The primary outcome of maternal hemorrhagic morbidity was
higher in women with previa
(19% vs 7%; aRR 2.6, 95% CI 1.9-3.5) (Table 2). When we
compared hemorrhagic
morbidity without including use of uterotonics for atony in the
composite outcome, it

remained higher in women with previa (14.7% vs 4.2%; aRR
2.6, 95% CI 1.8-3.7).
Individual factors of the hemorrhagic morbidity composite that
were more common in the
previa cohort included atony requiring uterotonics (10.5% vs
6.4%; aRR 3.1, 95% CI
2.0-4.9), red blood cell transfusion (12.9% vs 3.1%; aRR 3.8,
95% CI 2.5-5.7), and
hysterectomy (2% vs 0.3%; aRR 5.1, 95% CI 1.5-17.3). Severe
maternal morbidity (as
defined by ICU admission or receipt of 4 or more units of
packed red blood cells) was not
increased with presence of previa (2.6 vs 1.5%; aRR 1.1, 95%
CI 0.4-3.0). In women with
previa, hemorrhagic morbidity was more common in women
with bleeding as the indication
for delivery than in women with other indications for delivery
(24.2 vs 11.2%, p<0.001).
Non-hemorrhagic morbidity was rare in both cohorts and not
statistically different (Table 3).
The previa cohort was more likely to receive ≥4 units of red
blood cells (2.2% vs 0.7%) but
this did not persist after adjustment (aRR 2.1, 95% CI 0.8-5.8).
Additionally, women with

previa had a hemoglobin decrease of 2.3 g/dL surrounding
delivery, which was 0.4 g/dL
more than the no previa cohort (p<0.001).
More women with previa underwent emergent delivery than
women without previa (23.8 vs
17.6%). However, after adjustment for confounders, there was
no difference in emergent
delivery for those with previa compared to those without (aRR
1.1, 95% CI 0.8-1.5). Of
women with previa, 20.4% of women with previa underwent
emergent delivery for antenatal
hemorrhage.
PMC 2019 August 08.
A
u
th
o
r M
a
n
u
scrip

t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M

a
n
u
scrip
t
Of the 496 women with primary CD for placenta previa, 92
(19%) had adverse hemorrhagic
outcomes and 404 (81%) did not (data not shown). In univariate
analysis, exposures more
common in women with maternal hemorrhagic morbidity were
anemia on admission,
thrombocytopenia, prematurity <34 weeks, low birth weight,
diabetes, drug use, preterm
labor requiring tocolysis, emergent delivery, bleeding as
indication for cesarean, and general
anesthesia. After adjustment for education, diabetes, drug use,
pre-delivery hematocrit,
magnesium administration, and general anesthesia, only anemia
on admission (aOR 2.49,
95% CI 1.36-4.56), thrombocytopenia (aOR 3.78, 95% CI 1.2-
11.86), diabetes (aOR 3.47,
95% CI 1.2-10.06), magnesium (aOR 4.72, 95% CI 1.33-16.7),
and general anesthesia (aOR

4.29, 95% CI 2.25-8.16) remained as risk factors for maternal
hemorrhagic morbidity. There
were 23 women with a diagnosis of preeclampsia or gestational
hypertension, and 22/23
received magnesium. Conversely, all women who received
magnesium also had a diagnosis
of preeclampsia or gestational hypertension.
Discussion
In this cohort 20% (or 1 out of 5) women with previa underwent
emergent delivery for
antenatal hemorrhage. The burden of this morbidity is
substantial. Placenta previa was
associated with an overall increased risk of maternal
hemorrhagic morbidity (aRR 2.6, 95%
CI 1.9-3.5), with 18.6% of women with previa suffering the
composite primary outcome.
Three percent of women suffered severe hemorrhagic morbidity,
and 2% underwent
hysterectomy, presumably due to persistent hemorrhage. In
contrast, women did not suffer
additional non-hemorrhagic morbidity, suggesting our focus
should be identifying women
with previa at risk for hemorrhage and finding ways to staunch

hemorrhage. A previous
series of 147 cases of placenta previa from 1975 to 1982 noted a
high maternal morbidity
rate, with 5.4% undergoing hysterectomy and three quarters
meeting the definition for
postpartum hemorrhage[7]. 11 of these women had a placenta
accreta, and previous cesarean
was a risk factor for hysterectomy. Although our results show a
lower rate of hysterectomy,
we excluded accretas and analyzed a more modern cohort.
Factors associated with hemorrhage in our cohort included pre-
delivery anemia,
thrombocytopenia, diabetes, magnesium, and general anesthesia.
Pre-delivery anemia
increases the chances of signs and symptoms of blood loss such
as tachycardia, thus
increasing the chances of being diagnosed with hemorrhage
using our criteria.
Thrombocytopenia may diminish the effectiveness of clotting
and thus increase blood loss.
Diabetes may be a marker for poor maternal health, abnormal
uterine neurovascular
function, and inability to tolerate hemorrhage (similar to pre-
delivery anemia). We suspect

that magnesium is a marker for preeclampsia with severe
features, as all women who
received magnesium also had preeclampsia. General anesthesia
increases uterine atony and
thus likely increases hemorrhage. However, it may also simply
be a marker of emergent
delivery and thus a clinical situation at increased risk of
bleeding. Regardless, these risk
factors warrant clinical vigilance and preparation for
hemorrhage.
Although hemorrhagic morbidity was more common in women
with previa who had
bleeding as an indication for delivery than in women with
previa with a non-bleeding
indication for delivery, it is impossible to know if a woman will
bleed or not when you are
PMC 2019 August 08.
A
u
th
o
r M

a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A

u
th
o
r M
a
n
u
scrip
t
diagnosing her with a previa and developing a plan of care.
Thus, it is important to consider
all women with placenta previa at increased risk for
hemorrhagic morbidity.
Several investigators have tried to predict which women with
placenta previa are at risk for
hemorrhage or early delivery. One group developed a risk score
for emergency delivery in
women with placenta previa and bleeding. They found presence
of previa, 3 or more
episodes of antepartum bleeding, and first bleed prior to 29
weeks associated with an
increased risk of emergent cesarean [13]. This model is useful
to practitioners and

researchers trying to elucidate the benefit of prolonged
hospitalization for a woman who has
ceased bleeding after her first or second antenatal bleeding
episode and remains pregnant.
However, the study was limited to women with antenatal
bleeding, which is not true of all
women with previa. The main limitation of our study was
variables of interest that were not
collected in the original dataset. It would be ideal to query the
relationship between
hemorrhage and variables such as placental location, previous
antenatal bleed, and whether
women were hospitalized prior to delivery, but these data were
not available. Lack of
detailed ultrasound data requires us to use clinician diagnosis of
placenta previa recorded in
the chart as opposed to ultrasound images or recorded
measurements. Additionally, the data
are now historic, as this cohort finished collection in 2002.
Also, since we are using women
undergoing primary CD (including emergent cesareans) as
controls, we selected a control
group that is also at increased risk for morbidity when
compared to women undergoing

spontaneous vaginal delivery, for example. This increases our
risk of type 2 error.
Additionally, the generalizability of this dataset is limited, as
the majority of included
centers are tertiary care centers.
Our strengths include the nature of the dataset – The MFMU
Network’s CSR was
prospectively collected in a rigorous fashion by trained research
nurses. Also, by limiting the
entire cohort to women with primary CD, we are able to focus
on the additional morbidity
associated with previa alone, as opposed to muddying the waters
with morbidity associated
with CD or repeat CD. This is the first comprehensive analysis
to report these outcomes in
women with previa but without accreta.
In case reports and small series, numerous strategies to decrease
postpartum hemorrhage
associated with previa have been reported. Interventions
described include compression
sutures [14, 15], Foley catheter placement [16], postpartum
hemorrhage specific intrauterine
balloon [17], hemostatic gel [18], local injection of vasopressin

[12], temporary internal iliac
artery balloon occlusion [19], and even suturing the cervix to
the placental bed [20].
However, no randomized-controlled trials have been conducted.
In conclusion, in this large cohort of women, placenta previa is
an independent risk factor
for maternal hemorrhagic morbidity. Nineteen percent of women
with previa experienced
hemorrhagic morbidity, 20% were delivered emergently for
antenatal bleeding, and 2%
required hysterectomy (even in the absence of accreta). These
data will be useful in
counseling, management, and planning future intervention trials
and cost-effectiveness
analysis. In the meantime, clinicians managing these
pregnancies should remain vigilant for
antenatal and postpartum hemorrhage.
PMC 2019 August 08.
A
u
th

o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip

t
A
u
th
o
r M
a
n
u
scrip
t
Acknowledgments
Funding: This study was supported by the Center for Clinical
and Translational Sciences grant 8UL1TR000105
NCATS/NIH and by the Utah WRHR Grant Number
1K12HD085816.
References
1. Frederiksen MC, Glassenberg R, Stika CS. Placenta previa: a
22-year analysis. Am J Obstet
Gynecol 1999;180:1432–7. [PubMed: 10368483]
2. Grobman WA, Gersnoviez R, Landon MB, Spong CY, Leveno
KJ, Rouse DJ, Varner MW, Moawad
AH, Caritis SN, Harper M, Wapner RJ, Sorokin Y, Miodovnik
M, Carpenter M, O'Sullivan MJ,
Sibai BM, Langer O, Thorp JM, Ramin SM, Mercer BM,

National Institute of Child H, Human
Development Maternal-Fetal Medicine Units N. Pregnancy
outcomes for women with placenta
previa in relation to the number of prior cesarean deliveries.
Obstet Gynecol 2007;110:1249–55.
[PubMed: 18055717]
3. Solheim KN, Esakoff TF, Little SE, Cheng YW, Sparks TN,
Caughey AB. The effect of cesarean
delivery rates on the future incidence of placenta previa,
placenta accreta, and maternal mortality. J
Matern Fetal Neonatal Med 2011;24:1341–6. [PubMed:
21381881]
4. Downes KL, Hinkle SN, Sjaarda LA, Albert PS, Grantz KL.
Previous prelabor or intrapartum
cesarean delivery and risk of placenta previa. Am J Obstet
Gynecol 2015;212:669 e1–6. [PubMed:
25576818]
5. Oyelese Y, Smulian JC. Placenta previa, placenta accreta,
and vasa previa. Obstet Gynecol
2006;107:927–41. [PubMed: 16582134]
6. Kramer MS, Berg C, Abenhaim H, Dahhou M, Rouleau J,
Mehrabadi A, Joseph KS. Incidence, risk
factors, and temporal trends in severe postpartum hemorrhage.
Am J Obstet Gynecol 2013;209:449
e1–7. [PubMed: 23871950]
7. McShane PM, Heyl PS, Epstein MF. Maternal and perinatal
morbidity resulting from placenta
previa. Obstet Gynecol 1985;65:176–82. [PubMed: 4038547]
8. Yoon SY, You JY, Choi SJ, Oh SY, Kim JH, Roh CR. A
combined ultrasound and clinical scoring

model for the prediction of peripartum complications in
pregnancies complicated by placenta
previa. Eur J Obstet Gynecol Reprod Biol 2014;180:111–5.
[PubMed: 25079491]
9. Silver RM, Landon MB, Rouse DJ, Leveno KJ, Spong CY,
Thom EA, Moawad AH, Caritis SN,
Harper M, Wapner RJ, Sorokin Y, Miodovnik M, Carpenter M,
Peaceman AM, O'Sullivan MJ, Sibai
B, Langer O, Thorp JM, Ramin SM, Mercer BM, National
Institute of Child H, Human
Development Maternal-Fetal Medicine Units N. Maternal
morbidity associated with multiple repeat
cesarean deliveries. Obstet Gynecol 2006;107:1226–32.
[PubMed: 16738145]
10. Ahmed SR, Aitallah A, Abdelghafar HM, Alsammani MA.
Major Placenta Previa: Rate, Maternal
and Neonatal Outcomes Experience at a Tertiary Maternity
Hospital, Sohag, Egypt: A Prospective
Study. J Clin Diagn Res 2015;9:QC17–9. [PubMed: 26674539]
11. Olive EC, Roberts CL, Algert CS, Morris JM. Placenta
praevia: maternal morbidity and place of
birth. Aust N Z J Obstet Gynaecol 2005;45:499–504. [PubMed:
16401216]
12. Kato S, Tanabe A, Kanki K, Suzuki Y, Sano T, Tanaka K,
Fujita D, Terai Y, Kamegai H, Ohmichi
M. Local injection of vasopressin reduces the blood loss during
cesarean section in placenta
previa. J Obstet Gynaecol Res 2014;40:1249–56. [PubMed:
24750470]
13. Pivano A, Alessandrini M, Desbriere R, Agostini A, Opinel
P, d'Ercole C, Haumonte JB. A score to

predict the risk of emergency caesarean delivery in women with
antepartum bleeding and placenta
praevia. Eur J Obstet Gynecol Reprod Biol 2015;195:173–6.
[PubMed: 26550944]
14. Hwu YM, Chen CP, Chen HS, Su TH. Parallel vertical
compression sutures: a technique to control
bleeding from placenta praevia or accreta during caesarean
section. BJOG. 2005;112:1420–3.
[PubMed: 16167948]
15. Li GT, Li GR, Li XF, Wu BP. Funnel compression suture: a
conservative procedure to control
postpartum bleeding from the lower uterine segment. BJOG.
2015.
PMC 2019 August 08.
A
u
th
o
r M
a
n
u
scrip
t
A

u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n

u
scrip
t
16. Zhu L, Zhang Z, Wang H, Zhao J, He X, Lu J. A modified
suture technique for hemorrhage during
cesarean delivery complicated by complete placenta previa. Int
J Gynaecol Obstet 2015;129:26–9.
[PubMed: 25595321]
17. Uygur D, Altun Ensari T, Ozgu-Erdinc AS, Dede H, Erkaya
S, Danisman AN. Successful use of
BT-Cath((R)) balloon tamponade in the management of
postpartum haemorrhage due to placenta
previa. Eur J Obstet Gynecol Reprod Biol 2014;181:223–8.
[PubMed: 25171267]
18. Law LW, Chor CM, Leung TY. Use of hemostatic gel in
postpartum hemorrhage due to placenta
previa. Obstet Gynecol 2010;116 Suppl 2:528–30. [PubMed:
20664443]
19. Broekman EA, Versteeg H, Vos LD, Dijksterhuis MG,
Papatsonis DN. Temporary balloon
occlusion of the internal iliac arteries to prevent massive
hemorrhage during cesarean delivery
among patients with placenta previa. Int J Gynaecol Obstet
2015;128:118–21. [PubMed:
25476153]
20. El Gelany SA, Abdelraheim AR, Mohammed MM, Gad El-
Rab MT, Yousef AM, Ibrahim EM,
Khalifa EM. The cervix as a natural tamponade in postpartum

hemorrhage caused by placenta
previa and placenta previa accreta: a prospective study. BMC
Pregnancy Childbirth. 2015;15:295.
[PubMed: 26559634]
PMC 2019 August 08.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip

t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th

t
A
u
th
o
r M
a
n
u
scrip
t
Table 1.
Demographics of women undergoing cesarean delivery with and
without placenta previa.
Characteristic Previa
N=496
No Previa
N=24,201
p-value
Maternal Age (years) 30.1 (6.4) 26.8 (6.5) <0.001
Race
African-American
Caucasian

Hispanic
Asian
Native American
Other/Unknown
148 (29.8)
221 (44.6)
92 (18.6)
18 (3.6)
1 (0.2)
16 (3.2)
7404 (30.6)
10466 (43.3)
5060 (20.9)
395 (1.6)
41 (0.2)
835 (3.5)
0.021
Schooling (years) 12.5 (2.6) 12.4 (2.7) 0.360
Payment
Government funded
Private Insurance
Self-pay/None
187 (39.5)
225 (48.1)
56 (12.0)
9242 (40.4)
10609 (46.4) >
3013 (13.2

0.37
Tobacco Use 90 (18.2) 3373 (14.0) 0.008
Alcohol Use 18 (3.6) 821 (3.4) 0.778
Drug Use 16 (3.2) 820 (3.4) 0.840
Prenatal Care 482 (97.2) 23628 (97.7) 0.462
# of previous pregnancies
>20 weeks
Median (range)
1 (0-8) 0 (0-14)_ <0.001
BMI pre-conception 24.5 (4.8) 26.6 (6.8) <0.001
BMI at delivery 29.1 (5.2) 32.5 (7.1) <0.001
Any labor or attempted
induction
113 (22.8) 17922 (74.1) <0.001
Gestational age of delivery
(weeks)
35.1 (3.5) 37.6 (3.9) <0.001
Birthweight (grams) 2503.4
(805.8)
2987.9 (964.2) <0.001

Sex of neonate
Male
Female
269 (54.3)
226 (45.7)
13053 (53.9)
11144 (46.1)
0.860
Data represented as mean(SD) or n(%) as appropriate
PMC 2019 August 08.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th

t
Table 2.
Maternal hemorrhagic morbidity in women undergoing cesarean
delivery with and without placenta previa.
Variable Previa
N=496
No Previa
N=24,201
RR
(95% CI)
aRR*
(95% CI)
Emergent delivery 118 (23.8) 4270 (17.6)
1.35
(1.15-1.58)
1.12
(0.83-1.50)
Maternal
hemorrhagic
morbidity 92 (18.6) 1585 (6.6)
2.67
(2.21-3.22)

2.57
(1.87-3.53)
ICU admission
and/or ≥4 units
packed red blood
cells 13 (2.6) 354 (1.5)
1.79
(1.04-3.10)
1.14
(0.44-2.96)
Atony requiring
uterotonics 52 (10.5) 1557 (6.4)
1.63
(1.25-2.11)
3.11
(1.97-4.91)
Uterine Artery
Ligation 14 (2.8) 218 (0.9)
3.13
(1.84-5.34)
1.62
(0.63-4.21)
Hypogastric Artery
Ligation 0 (0) 6 (0.02) --- ---

Red Blood Cell
Transfusion 64 (12.9) 754 (3.1)
4.14
(3.26-5.26)
3.80
(2.51-5.74)
Transfusion of
FFP/Cryo/Platelets 1 (0.2) 21 (0.1)
2.32
(0.31-17.24) ---
Coagulopathy 4 (0.8) 171 (0.7)
1.14
(0.43-3.06)
0.74
(0.10-5.71)
Unplanned
Exploratory
Laparotomy 2 (10) 67 (6.2)
1.63
(0.43-6.18)
1.04
(0.26-4.10)
Hysterectomy 10 (2) 60 (0.25)
8.13

(4.19-15.79)
5.14
(1.53-17.28)
Maternal Mortality 1 (5) 20 (1.8)
2.72
(0.38-19.33) ---
*
Adjusted for presence of any labor or induction attempt,
admission hematocrit, pre-conception BMI, maternal age,
diabetes, number of fetuses,
meconium, placental abruption, chorioamnionitis, neonatal
weight, years of schooling, use of tocolysis, diagnosis of
preeclampsia or gestational
hypertension, and prior vaginal delivery.
PMC 2019 August 08.
A
u
th
o
r M
a
n
u
scrip

t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o

r M
a
n
u
scrip
t
Table 3.
Maternal non-hemorrhagic morbidity in women undergoing
cesarean delivery with and without placenta
previa.
Variable Previa
N=496
No Previa
N=24,201
RR
(95% CI)
aRR*
(95% CI)
Genitourinary
Injury 0 (0) 45 (0.2) --- ---
Bowel Injury 0 (0) 14 (0.1) --- ---
Venous

Thromboembolic
Disease 3 (0.6) 143 (0.6)
1.02
(0.33-3.20) ---
Endometritis 24 (4.8) 2229 (9.2)
0.53
(0.35-0.78)
0.41
(0.17-0.98)
Sepsis 0 (0) 54 (0.2) --- ---
Pulmonary
Edema 1 (0.2) 180 (0.7)
0.27
(0.04-1.93) ---
ICU Admission 2 (0.4) 238 (1.0)
0.41
(0.10-1.64) ---
Acute
Respiratory
Distress
Syndrome 0 (0) 24 (0.1) --- ---
Necrotizing
Fasciitis 0 (0) 5 (0.02 --- ---
Cardiopulmonary

Arrest 0 (0) 7 (0.03) --- ---
Readmission 7 (1.4) 378 (1.6)
0.90
(0.43-1.90)
0.23
(0.03-1.69)
Wound
Complication 4 (0.8) 335 (1.4)
0.58
(0.22-1.55)
0.40
(0.05-3.11)
*
Adjusted for presence of any labor or induction attempt,
admission hematocrit, pre-conception BMI, maternal age,
diabetes, number of fetuses,
meconium, placental abruption, chorioamnionitis, neonatal
weight, years of schooling, use of tocolysis, diagnosis of
preeclampsia or gestational
hypertension, and prior vaginal delivery.
PMC 2019 August 08.
© Annals of Palliative Medicine. All rights reserved. Ann

Palliat Med 2019;8(5):611-621 |
http://dx.doi.org/10.21037/apm.2019.09.04
Original Article
A risk model to predict severe postpartum hemorrhage in
patients
with placenta previa: a single-center retrospective study
Cheng Chen, Xiaoyan Liu, Dan Chen, Song Huang, Xiaoli Yan,
Heying Liu, Qing Chang,
Zhiqing Liang
Department of Gynecology and Obstetrics, the First Affiliated
Hospital, Army, Military Medical University, Chongqing
400038, China
Contributions: (I) Conception and design: C Chen, Q Chang, Z
Liang; (II) Administrative support: Q Chang; (III) Provision of
study materials: C
Chen, X Liu, D Chen; (IV) Collection and assembly of data: C
Chen, S Huang, X Yan, H Liu; (V) Data analysis and
interpretation: C Chen; (VI)
Manuscript writing: All authors; (VII) Final approval of
manuscript: All authors.
Correspondence to: Qing Chang; Zhiqing Liang. Department of
Gynecology and Obstetrics, the First Affiliated Hospital, Ar my,
Military Medical
University, Chongqing 400038, China. Email: [email protected];
[email protected]
Background: The study aimed to establish a predictive risk
model for severe postpartum hemorrhage in

placenta previa using clinical and placental ultrasound imaging
performed prior to delivery.
Methods: Postpartum hemorrhage patients were retrospectively
enrolled. Severe postpartum hemorrhage
was defined as exceeding 1,500 mL. Data collected included
clinical and placental ultrasound images.
Results: Age of pregnancy, time of delivery, time of
miscarriage, history of vaginal delivery, gestational
weeks at pregnancy termination, depth of placenta invading the
uterine muscle wall were independent
risk factors for severe postpartum hemorrhage in placenta
previa. A model to predict severe postpartum
hemorrhage in placenta previa was established: P=Log(Y/1−Y),
where Y =−6.942 + 0.075 X1 (age) +1.531 X2
(times of delivery) + 0.223 X3 (time of miscarriage) − 3.557X4
(vaginal delivery: 1 for yes, 0 for no) + 1.753 X5
(0 for <37 weeks, 1 for ≥37 weeks) + 1.574 X6 (Depth of
placenta invading uterine muscle wall: 0 for normal,
1 for placenta adhesion, 2 for placenta implantation, 3 for
placenta penetration); discriminant boundary value
of the prediction model (probability: P) was 0.268. Predicting
sensitivity ( eS
) =0.765 (negative predicting
accuracy rate), specificity ( pS
) =0.900 (positive predicting accuracy rate), total accuracy rate
=0.795, and AUC
of ROC curve =0.8419.
Conclusions: The risk prediction model which had clinical and
ultrasound imaging information prior to
delivery had a high decision accuracy. However, before it can

be used in the clinic, multicenter large-sample
clinical studies should be performed to verify its accuracy and
reliability.
Keywords: placenta previa; severe postpartum hemorrhage;
prediction model; clinical information; placental
ultrasound image characteristics
Submitted May 08, 2019. Accepted for publication Aug 12,
2019.
doi: 10.21037/apm.2019.09.04
View this article at: http://dx.doi.org/10.21037/apm.2019.09.04
Introduction
P o s t p a r t u m h e m o r r h a g e i s t h e p r i m a r y r e
a s o n f o r
death in pregnant women. The Society of Obstetrics
and Gynecology published the Guideline for Postpartum
Hemorrhage to standardize diagnosis and treatment (1-3).
Compared to normal postpartum hemorrhage (greater
than 500 mL blood loss within 24 h after vaginal delivery,
or greater than 1,000 mL blood loss within 24 h after
caesarean section), severe postpartum hemorrhage induces
hemodynamic instability in pregnant women threatening
their lives (4,5). Treatment may include pelvic vascular
embolism or hysterectomy. Hence, severe postpartum
hemorrhage has attracted the attention of obstetricians. The
definition of severe postpartum hemorrhage as stated in the
Society of Obstetrics and Gynecology differs for each country
(1-3). The Chinese Society of Obstetrics and Gynecology

621
612 Chen et al. Severe postpartum hemorrhage in placenta
previa patients
Palliat Med 2019;8(5):611-621 |
defines severe postpartum hemorrhage as postpartum
bleeding volume reaching or over 1,500 mL and sets as grade
predicting line to demarcate the highest danger level. It
states that when postpartum blood loss is over this threshold,
obstetricians should actively initiate multi-disciplinary
treatment, timely transfer treatment and intensive care.
Placenta previa is the main reason for postpartum
hemorrhage, although placenta previa does not always
lead to severe postpartum hemorrhage (6). However, when
combined with abnormal placenta implantation in the
uterine wall, placenta previa may lead to severe postpartum
hemorrhage, which requires emergent hysterectomy. This
results in injury to the bladder or ureter and a significant
increased risk of maternal and fetal death (7,8). Hence,
accurate evaluation of the risks of severe postpartum
hemorrhage in placenta previa is critically important to
reduce the mortality in pregnant women.
Imaging methods, such as ultrasound and MRI, are often
used to evaluate the risk of severe postpartum hemorrhage
i n p l a c e n t a p r e v i a ( 9 ) . T h e s e n s i t i v i t y o f
p l a c e n t a
implantation evaluated using ultrasound is between 33–
100%, while its specificity is around 37.5–96% (10). MRI is

often used in tertiary hospitals for further evaluation (11).
Physicians can use these imaging methods to predict the
risk of severe postpartum hemorrhage and prepare during
the perioperative period to deal with possible complications.
However, not all physicians in China have the expertise
to evaluate severe postpartum hemorrhage from placenta
previa-related images, and not all hospitals have the
resources to perform MRI. Evaluating imaging data
requires a high degree of expertise. In addition, overlooking
quantitative data can influence the accuracy of the
evaluation. Hence it is clinically significant to establish a
model to predict the risk of severe postpartum hemorrhage
in patients with placenta previa. This will require patients’
clinical and imaging data. In this study, risk factors that
were correlated with severe postpartum hemorrhage in
placenta previa were analyzed, then a model to predict
severe postpartum hemorrhage derived from clinical and
imaging information was established. This model could
guide obstetricians to accurately evaluate severe bleeding
and prepare treatment strategies for patients with severe
postpartum hemorrhage.
Methods
Study subjects
Study subjects were women with placenta previa that gave
birth from Jan. 2014 to Dec. 2017 in The First Affiliated
Hospital of Army Medical University. During this period,
there were a total of 22,732 premature or mature puerperas
(28–42 weeks), among which there were 819 patients with
placenta previa. Excluding patients with surgical diseases,
fetal hypoplasia and incomplete clinical and ultrasound
information, 435 patients met the inclusion criteria for this

study.
Diagnosis of placenta previa and severe postpartum
hemorrhage
Diagnosis of placenta previa resulting in pregnancy
termination before 28 weeks is defined as miscarriage
in China. Complete electronic patient information was
extracted which included clinical and placental ultrasound
images after 28 weeks of pregnancy.
Based on the Guideline for the Management and Prevention
of Postpartum Hemorrhage issued by the Obstetrics and
Gynecology of Chinese Medical Association, blood loss
was evaluated using a combination of gauze weigh method
and blood disc collection. In this study, postpartum blood
loss was measured at the beginning of skin incision for
caesarean section or at the beginning of perioperative
vaginal bleeding for emergent caesarean section, or at the
beginning of parturition for vaginal delivery. Measurements
were obtained for 24 h after surgery or vaginal delivery.
Blood loss over 1,500 mL was defined as severe postpartum
hemorrhage, and was the only clinical observation in this
study.
Diagnosis for placenta previa was performed after
28 weeks of pregnancy using vaginal ultrasonography.
Placenta previa was defined as when the placenta reached or
covered the intracervical mouth. Ultrasound diagnosis was
verified by experienced ultrasound obstetricians 1–2 weeks
prior to pregnancy termination.
Collection of clinical information
Based on published guidelines and reviews (12-17), we
collected clinical information related to postpartum

hemorrhage, including age, residence, education level,
assisted reproduction, history of pregnancy (number of
pregnancies, times of delivery, times of miscarriage, history
of vaginal delivery, history of caesarean section, history of
uterine surgery, history of surgical complications, history
of premature births, history of placenta previa), current
pregnancy information (body mass index before pregnancy,
613Annals of Palliative Medicine, Vol 8, No 5 November 2019
Palliat Med 2019;8(5):611-621 |
number of pregnancy test, presence of uterine fibroids,
anemia, thrombocytopenia, hypertension, or ICP; amniotic
fluid index at last ultrasound; vaginal bleeding history
during gestation period, volume of bleeding, treatment with
magnesium sulfate, fetal cephalic presentation, gestational
weeks at pregnancy termination, surgical anesthesia, vaginal
blood loss, blood transfusion, etc.). Intravertebral anesthesia
was used at our hospital, and switched to general anesthesia
when needed.
Collection of placenta information
Based on guidelines and reviews (12-17), we collected
placenta information related with postpartum hemorrhage,
including placenta type (low-lying placenta, lowest site of
placenta within 2 cm from the intracervical mouth; marginal
placenta: placenta reaching the intracervical mouth; partial
placenta: part of the placenta covering the intracervical
mouth; complete placenta: placenta completely covering the
intracervical mouth); placenta site (main body of placenta

covering the anterior wall of the uterus, defined as the
anterior wall of placenta, and that covering the posterior or
lateral wall of the uterus defined as the posterior wall of the
placenta); uterine placenta junction echo (spongy placenta;
placental cleft appearance: 4 or more low-echo regions with
a diameter greater than 5 mm in the placenta); placenta
covering the uterine-bladder junction (uterine serosal line
is clear and continuous, uterine serosal line is discontinuous
or completely not visible); abundance of blood vessels at
the uterine placenta junction viewed under Color Doppler.
Depth of placenta invading the uterine muscle wall:
based on vascular richness at echo of the uterine placenta
junction, uterine bladder junction covered by the placenta,
and uterine placenta junction. Correlation was preliminarily
evaluated based on no abnormal implantation, placenta
adhesion, placenta implantation and placenta penetration.
Placenta previa was confirmed using surgical records
that described the relationship between the placenta and
mesometrium and post-surgical pathology.
Statistical analysis
Statistical analysis was performed using Windows SPSS
22.0 software. For descriptive statistics, quantitative data
was represented as mean ± SD (or SE), and discrete data
was represented as frequencies. Distribution index was
evaluated using Kolmogorov-Smirnov with a cut-off of
α=0.05. Comparison of the quantitative index between
groups was performed using an independent sample t test or
Mann-Whitney U test, while qualitative index was analyzed
using 2×2 contingency table or Kendall correlation analysis
(non-parametric test).
R i s k f a c t o r s c o r r e l a t e d w i t h s e v e r e p o s t
p a r t u m

hemorrhage were obtained after all the variables were
analyzed using univariate analysis. The R language
programme was used to randomly sample at 8:2 (n=377 for
the control group and n=98 for the experimental group).
They were then divided into the training set (n=269 for
the control group, n=78 for the experimental group) and
the verification set (n=68 for the control group, n=20 for
the experimental group). Independent risk factors were
obtained using stepwise logistic regression analysis to
establish the severe postpartum hemorrhage prediction
model. In addition, discriminant boundary values of the
model (probability) was performed. Receiver operating
characteristic curve (ROC) was used to evaluate the
effectiveness of the model. Area under curve (AUC) was
used to determine the accuracy of the model.
Results
General data
A total of 435 patients were enrolled in our study, and
included 29 patients who underwent vaginal delivery
and 406 patients who underwent caesarean sections. The
patients in the vaginal delivery group were those with low -
lying placentas. Four of these patients had blood loss lower
than 500 mL, while 22 had blood loss that ranged between
500–1,499 mL. Of the 7 patients who had blood loss of
over 1,000 mL needed blood transfusion, while 3 patients
with blood loss greater than 1,500 mL (severe postpartum
hemorrhage) also had blood transfusions. None of the
patients underwent hysterectomy. For the 406 patients who
underwent caesarean section, 74 were diagnosed with low -
lying placenta, 29 with marginal placenta previa, 9 with
partial placenta previa, and 294 with central placenta previa.
There were 222 patients with blood loss less than 1,000 mL,
89 with blood loss ranging from 1,000–1,500 mL and 95

patients who had blood loss greater than 1,500 mL (severe
postpartum hemorrhage). There were 194 patients who had
blood transfusions while 10 patients had hysterectomies.
No deaths were recorded for both mothers and newborns.
Table 1 shows all the clinical parameters of each patients.
previa patients
Palliat Med 2019;8(5):611-621 |
Table 1 Clinical indices of patient population
Clinical parameters
Total number of
patients (N=435)
Postpartum hemorrhage
P valuePatients with non-
severe (N=337)
Patients with
severe (N=98)
Previous information
Age of mother (years), mean ± SD 31.3±5.4 30.9±5.6 32.8±4.4
0.002*
Place of residence (town), n (%) 424 (97.5) 329 (97.6) 95 (96.9)
0.717

Education level (under college), n (%) 363 (83.4) 281 (83.4) 82
(83.7) 0.946
Assisted reproduction, n (%) 424 (97.5) 326 (96.7) 98 (100.0)
0.134
Number of pregnancies, mean ± SD 3.8±2.3 3.7±2.4 4.4±2.03
0.000*
Time of delivery, mean ± SD 0.9±0.80 0.8±0.76 1.2±0.86
0.000*
Time of miscarriage, mean ± SD 2.1±2.13 2.0±2.20 2.4±1.87
0.000*
History of vaginal delivery (yes), n (%) 79 (18.2) 72 (21.4) 7
(7.1) 0.001*
History of cesarean section (yes), n (%) 235 (54.0) 159 (47.2)
76 (77.6) 0.000*
Previous history of surgical complications (yes), n (%) 6 (1.4) 0
(0) 6 (6.1) 0.000*
Previous history of preterm birth (yes), n (%) 9 (2.1) 6 (1.8) 3
(3.1) 0.428
Previous history of placenta previa (yes), n (%) 9 (2.1) 6 (1.8) 3
(3.1) 0.428
Previous history of uterine surgery (yes), n (%) 0 (0) 0 (0) 0 (0)
0.219
Current pregnancy information

Body mass index before pregnancy (kg/m2), mean ± SD
21.7±2.8 20.9±4.7 22.6±3.5 0.002*
Number of fetus (single birth), n (%) 426 (97.9) 328 (97.3) 98
(100.0) 0.000*
Number of weeks at pregnancy termination, n (%) 0.025*
Within 37 weeks 429 (98.6) 336 (99.7) 93 (94.9)
37–40 weeks 6 (1.4) 1 (0.3) 5 (5.1)
Number of pregnancy test (times) (fewer than 5 times), n (%)
412 (94.7) 306 (90.8) 76 (77.6) 0.999
Combined with uterine fibroid (yes), n (%) 13 (3.0) 10 (3.0) 3
(3.1) 0.015*
Combined with anemia (yes), n (%) 272 (62.5) 221 (65.6) 51
(52.0) 0.541
Combined with thrombocytopenia (yes), n (%) 28 (6.4) 23 (6.8)
5 (5.1) 0.187
Combined with hypertension (yes), n (%) 7 (1.6) 4 (1.2) 3 (3.1)
0.191
Combined with ICP (yes), n (%) 9 (2.1) 6 (1.8) 3 (3.1) 0.443
Amniotic fluid index (normal), n (%) 426 (97.9) 331 (98.2) 95
(96.9) 0.231
History of vaginal bleeding during trimester of pregnancy
(yes), n (%)
250 (57.5) 188 (55.8) 62 (63.6) 0.114

Vaginal bleeding during trimester of pregnancy (more than
menstrual volume), n (%)
76 (17.5) 62 (18.4) 14 (14.3) 0.343
Use of magnesium sulfate (yes), n (%) 134 (30.8) 104 (30.9) 30
(30.6) 0.963
Length of cervical canal (decreased), n (%) 39 (9.0) 30 (9.0) 9
(9.2) 0.932
Table 1 (continued)
Palliat Med 2019;8(5):611-621 |
Table 1 (continued)
Clinical parameters
Total number of
patients (N=435)
Postpartum hemorrhage
P valuePatients with non-
severe (N=337)
Patients with
severe (N=98)

Fetal presentation, n (%) 0.718
Head 372 (85.5) 288 (85.5) 84 (85.7)
Hip 21 (4.8) 10 (3.0) 11 (11.2)
Horizontal 42 (9.7) 39 (11.6) 3 (3.1)
Pregnancy termination (caesarean section), n (%) 406 (93.3) 311
(92.3) 95 (96.9) 0.376
Anesthesia method (general anesthesia), n (%) 19 (4.4) 15 (4.5)
4 (4.1) 0.999
Blood transfusion (yes), n (%) 194 (44.6) 96 (28.5) 98 (100)
0.000*
Blood loss, mean ± SD 1,063.7.2±908.9 695.2±308.0
2,330.6±1,128.9 0.000*
Ultrasound data
Placental type, n (%) 0.001*
Low-lying 103 (23.7) 100 (29.7) 3 (3.1)
Marginal 29 (6.7) 24 (7.1) 5 (5.1)
Partial 9 (2.1) 6 (1.8) 3 (3.1)
Central 294 (67.6) 207 (61.4) 87 (88.8)
Location of placenta, n (%) 0.640
Anterior wall 302 (69.4) 237 (70.3) 65 (66.3)

Posterior wall 133 (30.6) 100 (29.7) 33 (33.7)
Uterine placenta junction echo, n (%) 0.324
Fissure echo 393 (90.3) 307 (91.1) 86 (87.8)
Spongy 42 (9.7) 30 (8.9) 12 (12.2)
Uterus-bladder junction at placenta, n (%) 0.094
Continuous 415 (95.4) 325 (96.4) 90 (91.8)
Ruptured 20 (4.6) 12 (3.6) 8 (8.2)
Not-visible 0 (0) 0 (0) 0 (0)
Depth of placenta invading the uterine muscle wall, n (%)
0.000*
Normal 234 (53.8) 205 (60.8) 29 (29.6)
Adhesion 95 (21.8) 75 (22.3) 20 (20.4)
Implant 106 (24.4) 57 (16.9) 49 (50.0)
Penetration 0 (0) 0 (0) 0 (0)
Posterior vascular blood flow, n (%) 0.208
Normal 198 (45.5) 154 (45.7) 48 (49.0)
Rick 237 (54.5) 183 (54.3) 50 (51.0)
*P<0.05.

previa patients
Palliat Med 2019;8(5):611-621 |
Risk factor of severe postpartum hemorrhage
Univariate analysis was used to analyze clinical and
ultrasound imaging data. The results showed that age, time
of pregnancy, time of delivery, time of miscarriage, history
of vaginal delivery, history of caesarean section, surgical
complications, body mass index before pregnancy, number
of fetus, weeks at pregnancy termination, combined with
uterine fibroid, type of placenta previa, depth of placenta
invading into uterine muscle wall, and blood transfusions
were significantly correlated with severe postpartum
hemorrhage (P<0.05), as shown in Table 1.
A risk model to predict severe postpartum hemorrhage
Stepwise logistic regression analysis of the 13 risk factors
indicated that age, times of delivery, time of miscarriage,
history of vaginal delivery, weeks at pregnancy termination,
depth of placenta invading the uterine muscle wall, and
blood transfusion during delivery were independent risk
factors for severe postpartum hemorrhage (Table 2). We
found that blood transfusions during delivery was an
intraoperative variable and should be determined prior to
delivery when including variables for model establishment.
Therefore, it should be omitted at the time of establishing
the model. Logistic regression prediction model was used
to predict severe postpartum hemorrhage after random
sampling using R language, with the discriminant boundary

value of the model being established (probability: P, 0.268)
(0≤P≤1). That is, after each variable is introduced into the
model equation, if the probability calculated is higher than
0.268, it denotes a higher occurrence of severe postpartum
hemorrhage, while a lower than 0.268 denotes a lower
probability.
Logistic risk prediction model equation was as follows:
P=Log(Y/1−Y), where Y =−6.942 + 0.075 X1(age) + 1.531
X2 (times of delivery) + 0.223 X3 (time of miscarriage) −
3.557X4 (vaginal delivery: 1 for yes, 0 for no) + 1.753 X5
(0 for <37 weeks, 1 for ≥37 weeks) +1.574 X6 (relationship
between placenta and uterine muscle wall: 0 for normal,
1 for placenta adhesion, 2 for placenta implantatio n, 3 for
placenta penetration).
F o r e x a m p l e , a p r e g n a n t w o m a n a g e d 2 9 y
e a r s
(X1=29), delivered once (X2=1), miscarriage once (X3=1),
vaginal delivery 0 (X4=0), gestational weeks at pregnancy
termination 36+5 weeks (X5=0), normal in placenta (X6=0),
Y=−6.942 + 0.075 × 29+ 1.531×1 + 0.223×1 − 3.557×0 +
1.753×0 + 1.574×0 =−3.016, Y was inserted into logical
equation to obtain P=0.0467<0.268, indicating a lower
possibility to have severe postpartum hemorrhage.
Effectiveness of the logistic risk prediction model
To verify the effectiveness of the logistic risk prediction
model equation, 88 patients were randomly selected
from the total patient population (n=435) (0, no severe
postpartum hemorrhage n=68; 1, severe postpartum
hemorrhage, n=20) to determine the verification rate. The
results showed that sensitivity was ( eS

) =0.765 (negative
prediction accuracy rate), specificity ( pS
) =0.900 (positive
prediction accuracy rate), and total accuracy rate was 0.795.
Based on the validation results, AUC of ROC was 0.8419,
as shown in Figure 1 and Table 3.
Table 2 Regression coefficient estimation and test value
^
OR of the risk model predicting severe postpartum hemorrhage
in placenta previa
Clinic variable b SE (b) Wald χ2 P
^
OR
^
OR 95%CI
Lower Upper
Constant term −6.942 1.059 −6.555 0.000***
Age (X1) 0.075 0.030 2.465 0.013* 1.016 1.091 1.291
Time of delivery (X2) 1.531 0.217 7.061 0.000*** 3.087 1.889
5.197
Time of miscarriage (X3) 0.223 0.066 3.363 0.000*** 1.099

1.200 1.852
Vaginal delivery (X4) −3.557 0.593 −5.993 0.000*** 0.008
0.003 0.082
Gestational weeks at termination (X5) 1.753 0.282 6.220
0.000*** 3.373 5.584 28.148
Depth of placenta invading the uterine
muscle wall (X6)
1.574 0.165 9.552 0.000*** 3.537 2.961 7.072
*P<0.05, ***P<0.001.
Palliat Med 2019;8(5):611-621 |
Discussion
Placenta previa is a major reason for severe postpartum
hemorrhage (12-18). With the increase in caesarean sections
worldwide, as well as the incidence of placenta previa,
a significant increase in severe postpartum hemorrhage
has been documented (19,20). Predicting accurately the
occurrence of severe postpartum hemorrhage in placenta
previa patients in advance will be helpful to reduce
maternal and fetal mortality. The established model that
we generated predicted severe postpartum hemorrhage in
placenta previa patients based on independent risk factors
of severe postpartum hemorrhage, and included clinical and

ultrasound imaging data. The sensitivity and specificity of
the model was 76.5% and 90.0%, respectively. Using this
model physicians could effectively use it to determine the
risks of severe postpartum hemorrhage in placenta previa
patients.
The definition on severe postpartum hemorrhage as
stated in the Society of Obstetrics and Gynecology differs
between countries (1-3). The definition of blood loss in
severe postpartum hemorrhage varies between the different
countries’ guidelines, i.e., over 1,500 mL (17), 2,000 mL (17),
30–40% of whole blood volume (20), or over 4 units
of blood transfusion (800 mL) (6). In this study, severe
postpartum hemorrhage was defined as blood loss over
1,500 mL. The Management and Prevention of Postpartum
Hemorrhage published by the Gynecology and Obstetrics
of Chinese Medical Association (19), states that when
postpartum blood loss over 1,500 mL occurs, special
measures should be implemented to save the patients’
life. This includes timely referrals, MDT joint treatment,
uterine artery embolism, or panhysterectomy, as well
as intensive care in ICU. We did not define postpartum
hemorrhage based on blood transfusion volume, because it
is associated with basal hemoglobin of puerpera (17).
I n t h i s s t u d y, r i s k f a c t o r s f o r s e v e r e p o s t
p a r t u m
hemorrhage included age, number of pregnancies, number
of deliveries, number of miscarriages, history of vaginal
delivery, history of caesarean section, surgical complications,
body mass index before pregnancy, number of fetus, weeks
at pregnancy termination, presence of uterine fibroids,
placenta previa types, depth of placenta invading into the
uterine muscle wall, and blood transfusions. Stepwise
logistic regression analysis indicated that age, number

of deliveries, number of miscarriages, history of vaginal
delivery, weeks at pregnancy termination, correlation
between placenta and uterine muscle wall, and blood
transfusion during delivery were independent risk factors
for severe postpartum hemorrhage. However, these risk
factors differed from other previous studies (16,21).
In this study, we found that age was an independent risk
factor for severe postpartum hemorrhage of placenta previa
(OR=1.078) (18). Elderly pregnant women have reduced
reproductive function (greater than 40 years old was defined
as elderly pregnant women in our study) and may be
accompanied with miscarriages or uterine surgical history.
The possibility of complicated pregnancies is high, and the
risk of severe postpartum hemorrhage is also increased (22).
In addition, multiple deliveries are considered risk factors
for postpartum hemorrhage (23). Time of deliver has also
been proven to be an independent risk factor for severe
postpartum hemorrhage with OR of 4.635. Since multiple
Table 3 Results of validating the risk prediction model
Actual
category
Prediction category
Total
Negative prediction
accuracy rate (%)
Positive prediction
accuracy rate (%)
General prediction
accuracy rate (%)0 1

0 52 16 68 76.5 (52/68) – –
1 2 18 20 – 90.0 (18/20) –
Total 54 34 88 – – 79.5 (70/88)
Figure 1 ROC curve of the risk prediction model.
Tr
u
e
p
o
si
ti
ve
r
a
te
1.0
0.8
0.6
0.4
0.2
0.0

AUC: 0.8419
False positive rate
0.0 0.2 0.4 0.6 0.8 1.0
previa patients
Palliat Med 2019;8(5):611-621 |
deliveries could lead to changes in contraction in the
mesometrium, it is hypothesized to be a significant factor
for severe postpartum hemorrhage (23).
High incidence of induced abortions and miscarriages
are worldwide problems (24). Repeated miscarriages
significantly increased the risk of postpartum hemorrhage
(17,19). Our study demonstrated that the time of miscarriage
was an independent risk factor for severe postpartum
hemorrhage in placenta previa (OR=1.250). Repeated
miscarriage leads to injury of the endometrium, and the
probability of abnormal placenta previa implantation
is significantly increased, leading to severe postpartum
hemorrhage (11,25).
We found correlations with caesarean sections and uterine
surgical complications with severe postpartum hemorrhage
in placenta previa, which was consistent with a previous
study (26). Histories of caesarean sections and uterine
surgical complications are considered risk factors for the
occurrence of placenta previa implantation, and is frequently
associated with severe postpartum hemorrhage (26).

In addition, body mass index before pregnancy, number of
fetuses, and the presence of uterine fibroids are associated
with severe postpartum hemorrhage (27), but were not
independent risk factors for severe postpartum hemorrhage.
Interestingly, we found that vaginal delivery history was
an independent protective factor for severe postpartum
hemorrhage (OR=0.029). This could be explained by the
cervix uteri being relaxed after vaginal delivery. However,
the contraction ability of the lower uterine segment
becomes weakened with additional deliveries and the risk
of postpartum hemorrhage increases (25). There are no
published reports to explain this observation.
At the time of emergent caesarean section, risk of severe
postpartum hemorrhage is significantly higher compared to
selective cesarean section and is associated with emerge nt
hysterectomy (28). Emergent caesarean section is often
closely related with uterine tear, macrovascular injury and
unskilled surgeons, which may result in severe postpartum
hemorrhage (13). Complete perioperative preparation will
be helpful to reduce the occurrence of severe postpartum
hemorrhage and related complications (13). Hence,
selective caesarean section before and after 37 weeks of
pregnancy is often preferred for pregnancy termination
in placenta previa. In this study, we found that gestational
weeks of pregnancy termination was an independent risk
factor for severe postpartum hemorrhage (OR=5.774).
Pregnancy termination after 37 weeks increases the risk of
severe postpartum hemorrhage and may be related with the
higher possibility of urgent caesarean section (29).
Complete placenta previa is a risk factor for severe
postpartum hemorrhage (30,31). More placenta covering
the intracervical mouth the higher risk of bleeding during
the perioperative period (6). Partial placenta previa covering

the intracervical mouth is also a risk factor for severe
postpartum hemorrhage (30). Placental vessels penetrate
other blood vessels supplying the bladder wall adjacent to
the lower anterior region of the uterus which will result in
massive bleeding during the separation of the placenta from
the uterus when the placenta is located anteriorly (6). Based
on this, the placenta previa at the anterior wall is more
likely to result in severe postpartum hemorrhage. However,
comparisons between different implantation of the
placenta previa suggests that placenta previa located in the
posterior wall of the uterus is no different to that located
in the anterior for the occurrence of severe postpartum
hemorrhage (32).
An abnormal invasion of chorionic villi into the
myometrium leads to Placenta Accreta spectrum. This
includes the attachment of the placenta to the myometrium
without intervening decidua (placenta accreta), the invasion
of the myometrium (placenta increta), and the infiltrati on
of the surrounding organs into the uterine serosa (placenta
percreta) (33). The average blood loss at delivery in women
with Placenta Accreta spectrum is reported to be over
3,000 mL and will require blood transfusion in 90% of
patients (21). Our results indicate that the association
between the placenta and the uterine muscle wall is the
highest independent risk factor for severe postpartum
hemorrhage (OR=4.825). The incidence of placenta
implantation increases with the number of caesarean
sections (7). Placenta implantation is considered the
main reason for intrapartum hysterectomy (34) and has
attracted increased attention from Society of Obstetrics
and Gynecology worldwide. For placenta previa (especially
suspicious abnormal placenta implantation), the RANZOG
and SOGC guidelines recommend vigilant prenatal
evaluation and transfer to tertiary medical centers with
blood transfusion and intensive care facilities. ACOG and

RCOG guidelines recommend pregnant women should
consider the possibility of blood transfusions, hysterectomy
or termination of their pregnancies.
None of the guidelines specify a preferred modality
for evaluating abnormal placentation. However, there are
multiple investigations trying to predict severe postpartum
hemorrhage risk by analyzing imaging data of placenta
previa. Ultrasound is the primary tool to diagnose AIP in
Palliat Med 2019;8(5):611-621 |
women at risk, such as those with placenta previa and with
prior cesarean sections (35). Ultrasound had an overall good
diagnostic accuracy in identifying the depth of placental
invasion with sensitivities of 90.6%, 93.0%, 89.5%, and
81.2% for placenta accreta, increta, accreta/increta, and
percreta respectively (10). Several ultrasound features have
been suggested for the diagnosis of placenta accrete, such
as irregularly shaped placental lacunae (vascular spaces),
thinning of the myometrium overlying the placenta, loss of
the retroplacental “clear space”, protrusion of the placenta
into the bladder, increased vascularity of the uterine serosa/
bladder interface, and turbulent blood flow through the
lacunae on Doppler ultrasonography (36). However, using
a single ultrasound image to predict the risk of severe
postpartum hemorrhage lacks an objective evaluation
standard. Diagnostic accuracy depends on the training and
experience level of the physician, irrespective of the imaging
technique (35). A growing interest towards the use of

magnetic resonance (MR) imaging for evaluating placenta
previa has been observed (10). MRI could be helpful in
adding topographical and morphological information and
represents a complementary tool for patients with equivocal
ultrasound findings or when additional information is
required (37). However, analyzing MRI images requires
professional training, which limits its promotion and
application for predicting severe postpartum hemorrhage in
placenta previa.
For predicting the risk of severe postpartum hemorrhage
in placenta previa, experienced obstetricians could make a
judgement using the relevant clinical factors and imaging
data (38), and get prepared in advance for the occurrence of
severe complications, such as severe postpartum hemorrhage,
and emergent hysterectomy (21). However, not all the
obstetricians in China are clinically experienced to determine
these risks. Hence, it is critical to establish a model to
accurately predict severe postpartum hemorrhage in placenta
previa patients. After analyzing relevant risk factors, our
prediction model was established to include clinical and
imaging data. The establishment of the prediction model for
severe postpartum hemorrhage in placenta previa is based on
subjective assessments of risk factors from clinical experience,
and through a scoring system established after risk factor OR
determination (15,16). Conversely, independent risk factors
were analyzed in R to ensure objectivity and accuracy of the
model. Risk factor variables contained in the model were
objective and hence reduced bias. Even if abnormal placenta
implantation was not determined preoperatively, it could be
corrected intraoperatively.
Limitations of the study were as follows; first, this was
a single center study and may not be representative and
the clinical strategies may not completely correspond with

established guidelines. Second, this study was a retrospective
in nature. We observed that clinical information for some
patients were missing or lacked detail, i.e. observation of
adherent placenta and placenta implantation but without
details of placental penetration. In addition, some of the
ultrasounds were of poor quality and were omitted from
our study. However, the prediction model we established
for severe postpartum hemorrhage in placenta previa had
high sensitivity and specificity and is appropriate for clinical
application.
Taken together, by analyzing data from placenta previa
in the last 4 years in our center, independent risk factors
for severe postpartum hemorrhage in placenta previa were
established and were used in our model. Based on clinical
information, the model reduced subjective dependence on
clinical experience and had predictive accuracy, and hence
could be clinically applicably. However, our predictive
model needs to be validated in other clinical institutions.
Meanwhile, we will prospectively collect additional clinical
patient data to supplement our prediction model to enhance
its accuracy. We believe our model will help surgeons
prepare and reduce severe bleeding and mortality in
pregnant women with placenta previa.
Acknowledgments
Funding: This study was supported by Social People’s
Livelihood Scientific and Technological Innovation Special
Project (No. cstc2015shmszx120065).
Footnote
Conflicts of Interest: The authors have no conflicts of interest
to declare.

Ethical Statement: The authors are accountable for all aspects
of the work in ensuring that questions related to the accuracy
or integrity of any part of the work are appropriately
investigated and resolved. The study was supported by grants
from the Chongqing Science and Technology Commission
(CSTC2015SHMSZX120065) and approved by the Ethics
Committee of The First Affiliated Hospital of the Army
Medical University (2007-11).
previa patients
Palliat Med 2019;8(5):611-621 |
References
1. ACOG Practice Bulletin: Clinical Management
Guidelines for Obstetrician-Gynecologists Number 76,
October 2006: postpartum hemorrhage. Obstet Gynecol
2006;108:1039-47.
2. Clinical Practice Obstetrics Committee. Active
management of the third stage of labour: prevention and
treatment of postpartum hemorrhage: No. 235 October
2009 (Replaces No. 88, April 2000). Int J Gynaecol Obstet
2010;108:258-67.
3. Tunçalp O, Souza JP, Gulmezoglu M. New WHO
recommendations on prevention and treatment of
postpartum hemorrhage. Int J Gynaecol Obstet
2013;123:254-6.

4. Creanga AA, Berg CJ, Syverson C, et al. Pregnancy-
related mortality in the United States, 2006-2010. Obstet
Gynecol 2015;125:5-12.
5. Grobman WA, Bailit JL, Rice MM, et al. Frequency of and
factors associated with severe maternal morbidity. Obstet
Gynecol 2014;123:804-10.
6. Lee HJ, Lee YJ, Ahn EH, et al. Risk factors for massive
postpartum bleeding in pregnancies in which incomplete
placenta previa are located on the posterior uterine wall.
Obstet Gynecol Sci 2017;60:520-6.
7. Silver RM. Abnormal Placentation: Placenta Previa,
Vasa Previa, and Placenta Accreta. Obstet Gynecol
2015;126:654-68.
8. Timor-Tritsch IE, Monteagudo A. Unforeseen
consequences of the increasing rate of cesarean deliveries:
early placenta accreta and cesarean scar pregnancy. A
review. Am J Obstet Gynecol 2012;207:14-29.
9. Riteau AS, Tassin M, Chambon G, et al. Accuracy of
ultrasonography and magnetic resonance imaging in the
diagnosis of placenta accreta. PLoS One 2014;9:e94866.
10. Pagani G, Cali G, Acharya G, et al. Diagnostic accuracy of
ultrasound in detecting the severity of abnormally invasive
placentation: a systematic review and meta-analysis. Acta
Obstet Gynecol Scand 2018;97:25-37.
11. Einerson BD, Rodriguez CE, Kennedy AM, et al.
Magnetic resonance imaging is often misleading when
used as an adjunct to ultrasound in the management of
placenta accreta spectrum disorders. Am J Obstet Gynecol
2018;218:618.e1-7.

12. Butwick AJ, Ramachandran B, Hegde P, et al. Risk
Factors for Severe Postpartum Hemorrhage After
Cesarean Delivery: Case-Control Studies. Anesth Analg
2017;125:523-32.
13. Ekin A, Gezer C, Solmaz U, et al. Predictors of severity
in primary postpartum hemorrhage. Arch Gynecol Obstet
2015;292:1247-54.
14. Green L, Knight M, Seeney FM, et al. The epidemiology
and outcomes of women with postpartum haemorrhage
requiring massive transfusion with eight or more units
of red cells: a national cross-sectional study. Bjog
2016;123:2164-70.
15. Kim JW, Lee YK, Chin JH, et al. Development of a
scoring system to predict massive postpartum transfusion
in placenta previa totalis. J Anesth 2017;31:593-600.
16. Lee JY, Ahn EH, Kang S, et al. Scoring model to predict
massive post-partum bleeding in pregnancies with placenta
previa: A retrospective cohort study. J Obstet Gynaecol
Res 2018;44:54-60.
17. Nyfløt LT, Sandven I, Stray-Pedersen B, et al. Risk factors
for severe postpartum hemorrhage: a case-control study.
BMC Pregnancy Childbirth 2017;17:17.
18. Lal AK, Hibbard JU. Placenta previa: an outcome-based
cohort study in a contemporary obstetric population. Arch
Gynecol Obstet 2015;292:299-305.
19. Obstetrics Subgroup, Chinese Society of Obstetrics and
Gynecology, Chinese Medical Association; Obstetrics
Subgroup Chinese Society of Obstetrics and Gynecology

Chinese Medical Association. Guideline of prevention
and treatment about postpartum hemorrhage (2014).
Zhonghua Fu Chan Ke Za Zhi 2014;49:641-6.
20. Sebghati M, Chandraharan E. An update on the risk
factors for and management of obstetric haemorrhage.
Womens Health (Lond) 2017;13:34-40.
21. Duzyj CM, Cooper A, Mhatre M, et al. Placenta Accreta:
A Spectrum of Predictable Risk, Diagnosis, and Morbidity.
Am J Perinatol 2019;36:1031-8.
22. Durmaz A, Komurcu N. Relationship Between Maternal
Characteristics and Postpartum Hemorrhage: A Meta-
Analysis Study. J Nurs Res 2018;26:362-72.
23. Dahlke JD, Mendez-Figueroa H, Maggio L, et al.
Prevention and management of postpartum hemorrhage: a
comparison of 4 national guidelines. Am J Obstet Gynecol
2015;213:76.e1-10.
24. Ngo TD, Keogh S, Nguyen TH, et al. Risk factors
for repeat abortion and implications for addressing
unintended pregnancy in Vietnam. Int J Gynaecol Obstet
2014;125:241-6.
25. Eshkoli T, Weintraub AY, Sergienko R, et al. Placenta
accreta: risk factors, perinatal outcomes, and consequences
for subsequent births. Am J Obstet Gynecol 2013;208:219.
e1-7.

Palliat Med 2019;8(5):611-621 |
26. Kramer MS, Berg C, Abenhaim H, et al. Incidence,
risk factors, and temporal trends in severe postpartum
hemorrhage. Am J Obstet Gynecol 2013;209:449.e1-7.
27. Briley A, Seed PT, Tydeman G, et al. Reporting errors,
incidence and risk factors for postpartum haemorrhage and
progression to severe PPH: a prospective observational
study. Bjog 2014;121:876-88.
28. Giambattista E, Ossola MW, Duiella SF, et al. Predicting
factors for emergency peripartum hysterectomy in women
with placenta previa. Arch Gynecol Obstet 2012;285:901-6.
29. Bao Y, Xu C, Qu X, et al. Risk factors for transfusion
in cesarean section deliveries at a tertiary hospital.
Transfusion 2016;56:2062-8.
30. Pivano A, Alessandrini M, Desbriere R, et al. A score to
predict the risk of emergency caesarean delivery in women
with antepartum bleeding and placenta praevia. Eur J
Obstet Gynecol Reprod Biol 2015;195:173-6.
31. Sekiguchi A, Nakai A, Kawabata I, et al. Type and location
of placenta previa affect preterm delivery risk related to
antepartum hemorrhage. Int J Med Sci 2013;10:1683-8.
32. Belachew J, Eurenius K, Mulic-Lutvica A, et al. Placental
location, postpartum hemorrhage and retained placenta
in women with a previous cesarean section delivery: a
prospective cohort study. Ups J Med Sci 2017;122:185-9.
33. Silver RM, Branch DW. Placenta Accreta Spectrum. N

Engl J Med 2018;378:1529-36.
34. D'Arpe S, Franceschetti S, Corosu R, et al. Emergency
peripartum hysterectomy in a tertiary teaching hospital: a
14-year review. Arch Gynecol Obstet 2015;291:841-7.
35. Collins SL, Ashcroft A, Braun T, et al. Proposal for
standardized ultrasound descriptors of abnormally invasive
placenta (AIP). Ultrasound Obstet Gynecol 2016;47:271-5.
36. Calì G, Giambanco L, Puccio G, et al. Morbidly adherent
placenta: evaluation of ultrasound diagnostic criteria
and differentiation of placenta accreta from percreta.
Ultrasound Obstet Gynecol 2013;41:406-12.
37. Delli Pizzi A, Tavoletta A, Narciso R, et al. Prenatal
planning of placenta previa: diagnostic accuracy of a
novel MRI-based prediction model for placenta accreta
spectrum (PAS) and clinical outcome. Abdom Radiol (NY)
2019;44:1873-82.
38. Baba Y, Ohkuchi A, Usui R, et al. Calculating probability
of requiring allogeneic blood transfusion using three
preoperative risk factors on cesarean section for placenta
previa. Arch Gynecol Obstet 2015;291:281-5.
Cite this article as: Chen C, Liu X, Chen D, Huang S, Yan
X, Liu H, Chang Q, Liang Z. A risk model to predict severe
postpartum hemorrhage in patients with placenta previa: a
single-center retrospective study. Ann Palliat Med
2019;8(5):611-
621. doi: 10.21037/apm.2019.09.04

Chapter 4Chapter Outline22IM – 4 1

Chapter 4Chapter Outline22IM – 4 1

Recomendados

Recomendados

Mais conteúdo relacionado

Semelhante a Chapter 4Chapter Outline22IM – 4 1

Semelhante a Chapter 4Chapter Outline22IM – 4 1 (20)

Mais de WilheminaRossi174

Mais de WilheminaRossi174 (20)

Último

Último (20)

Chapter 4Chapter Outline22IM – 4 1