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\begin{document}

\title{Predicting risk of postpartum haemorrhage: a systematic review}



\author[1]{Charlotte Neary}%
\author[2]{David McLernon}%
\author[3]{Sanobar Naheed}%
\author[3]{Mairead Black}%
\affil[1]{Royal Hospital for Children Glasgow}%
\affil[2]{Sch Med }%
\affil[3]{Aberdeen Maternity Hospital}%


\vspace{-1em}



  
  \date{May 22, 2024}


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\selectlanguage{english}
\begin{abstract}
Background: Postpartum haemorrhage (PPH) rates are increasing in
developed countries. A reliable prognostic tool for PPH has potential to
aid prevention efforts. Objective: To systematically identify and
appraise prognostic modelling studies for prediction of PPH. Search
strategy: MEDLINE, Embase, CINAHL and the Cochrane Library were searched
using a combination of terms and synonyms including `prediction tool',
`risk score' and `postpartum haemorrhage'. Selection criteria: Any
observational or experimental study developing a prognostic model for
women's risk of PPH. English language publications. Data collection and
analysis: Predesigned data extraction form to record: data source;
participant criteria; outcome; candidate predictors; actual predictors;
sample size; missing data; model development; model performance; model
evaluation; interpretation. Main Results: Of 1723 citations screened, 10
studies were eligible for inclusion. An additional paper was published
and identified following completion of the search. Studies addressed
populations of women who experienced; placenta praevia; vaginal births;
caesarean birth; and the general obstetric population. Primary study
authors deemed four models to be confirmatory. There was a high risk of
bias across all studies due to a combination of retrospective selection
of women, low sample size, no internal validation, suboptimal external
validation and no reporting of missing data. Conclusion: Of eleven
prognostic models for PPH risk, one developed for women undergoing
caesarean section is deemed suitable for external validation. Future
research requires robust internal and external validation of existing
tools and development of a model that can be used to predict PPH in the
general obstetric population. Protocol registration number: PROSPERO
95587%
\end{abstract}%



\sloppy


Title:

Charlotte Neary, NHS Greater Glasgow and Clyde, Paediatric Surgery,
Royal Hospital for Children in Glasgow, 1345 Govan Road Glasgow G51 4TF

Sanobar Naheed, NHS Grampian, Department of Obstetrics and Gynaecology,
Aberdeen Maternity hospital, Cornhill Road, Aberdeen, AB252ZD

David J McLernon, Department of Medical Statistics, Institute of Applied
Health Sciences, University of Aberdeen, Polwarth Building, Cornhill
Road, Aberdeen, AB252ZD

Mairead Black, Aberdeen Centre for Women's Health Research, University
of Aberdeen, Room 4, Second Floor, Aberdeen Maternity hospital, Cornhill
Road, Aberdeen, AB252ZD, 01224 438437, Mairead.black@abdn.ac.uk

Abstract

Background: Postpartum haemorrhage (PPH) rates are increasing in
developed countries. A reliable prognostic tool for PPH has potential to
aid prevention efforts.

Objective: To systematically identify and appraise prognostic modelling
studies for prediction of PPH.

Search strategy: MEDLINE, Embase, CINAHL and the Cochrane Library were
searched using a combination of terms and synonyms including `prediction
tool', `risk score' and `postpartum haemorrhage'.

Selection criteria: Any observational or experimental study developing a
prognostic model for women's risk of PPH. English language publications.

Data collection and analysis: Predesigned data extraction form to
record: data source; participant criteria; outcome; candidate
predictors; actual predictors; sample size; missing data; model
development; model performance; model evaluation; interpretation.

Main Results: Of 1723 citations screened, 10 studies were eligible for
inclusion. An additional paper was published and identified following
completion of the search. Studies addressed populations of women who
experienced; placenta praevia; vaginal births; caesarean birth; and the
general obstetric population. Primary study authors deemed four models
to be confirmatory. There was a high risk of bias across all studies due
to a combination of retrospective selection of women, low sample size,
no internal validation, suboptimal external validation and no reporting
of missing data.

Conclusion: Of eleven prognostic models for PPH risk, one developed for
women undergoing caesarean section is deemed suitable for external
validation. Future research requires robust internal and external
validation of existing tools and development of a model that can be used
to predict PPH in the general obstetric population.

Systematic review registration number: PROSPERO 95587

Tweetable abstract

Current PPH prediction tools need external validation: One for CS; one
for placenta praevia. Tools are needed for labouring women.

\section*{Introduction}

{\label{introduction}}

Postpartum haemorrhage (PPH) remains a leading cause of morbidity and
mortality globally, and was the second highest cause of direct maternal
death in the UK 2013-2015.

The incidence of PPH is problematic in developing countries but is also
noted to be increasing in developed countries.\textsuperscript{,} While
early diagnosis is essential in the management of PPH, diagnosis of PPH
itself presents a challenge due to the reliance upon quantification of
the volume of blood loss. For vaginal delivery, cut-offs for haemorrhage
are typically over 500ml of blood loss whilst for caesarean section (CS)
it is over 1000ml\emph{.}

Prevention of PPH could arise through identification of women at highest
risk, allowing for measures to be taken for active management of third
stage of labour, presence of experienced clinicians and immediate access
to resources such as oxytocin infusion and tranexamic acid. There are
numerous studies identifying individual risk factors for PPH but these
don't reliably identify women at greatest risk by combining multiple
risk factors. A combination of risk factors is common in practice but
quantifying the associated risk without the aid of a clinical prediction
model is challenging. Once a reliable and high performing prediction
model is developed this could be converted into a user-friendly tool
such as an online risk calculator or embedded within electronic health
records.

A review by Kleinroueler et al., 2015 found over 200 prognostic models
available in obstetrics, three of which related to PPH. The review found
very few models in any area of obstetrics that were being applied to
routine clinical practice and the majority of studies had not presented
model formulas to allow researchers to conduct independent external
validation of the models.

In order to progress efforts to identify women at risk of PPH as early
and as accurately as possible, a systematic review of existing
prognostic models was considered essential. This would enable assessment
of existing models for their suitability for immediate use, or identify
those which perform well internally but require external validation on
an independent cohort before being considered for clinical use. This
approach has potential to be more efficient than the addition of a new
model to aid prevention of PPH.

Since publication of the aforementioned review several attempts at
developing prognostic models for PPH have been published. This review
aims to systematically identify and appraise studies which develop
prognostic models that can predict the chance of PPH in pregnant women.

\section*{Methods}

{\label{methods}}

This review adhered to principles outlined in guidance published by
PRISMA (Preferred Reporting Items for Systematic Reviews and
Meta-analysis) and CHARMS (CHecklist for critical Appraisal and data
extraction for systematic Reviews of prediction Modelling Studies). The
protocol for this review has been published by PROSPERO and is available
online.

A literature search was conducted during May 2018 of the following
databases: Medline, Embase, CINAHL and the Cochrane Library. To inform
the full search strategy a limited search of Medline was first conducted
followed by an extensive search of the literature of the aforementioned
databases. A copy of the search strategy for Medline and Embase is
available in Table \emph{S1.} The main search terms were `predict\$',
`risk score' and `postpartum haemorrhage' with the appropriate synonyms
adopted.

Inclusion criteria and exclusion criteria for this review are outlined
in \emph{Table 1} . Titles and abstracts were independently screened by
two reviewers (CN and SN) with any disagreements resolved by a third
reviewer (MB).

Data extraction and quality assessment (at study level) were conducted
independently in accordance with the CHARMS checklist \emph{(Table S2} )
to allow identification of potential bias in primary studies and
identify limitations to applicability of the results. Items extracted
were as follows: source of data; participants; outcome to be predicted;
candidate predictors (or index tests); sample size; missing data; model
development; model performance; model evaluation; results and
interpretation (including whether authors deemed their model fit for
purpose or nature of further research required before using). The
findings were tabulated and a narrative synthesis performed. The
findings address the baseline characteristics of the studies, the type
of models included, evaluation of the models and the applicability of
the models to clinical practice.

\section*{Results}

{\label{results}}

The search strategy identified 1723 citations; following removal of
duplicates and screening, 52 full text articles were assessed for
eligibility (PRISMA Flow Diagram, \emph{Figure 1} ). This review
included 11 studies with a total of 11 final prediction models
identified.

The populations of the included studies are shown in \emph{Tables 2 and
3} . Four studies included only women with placenta praevia, four
studies included only vaginal deliveries, two studies had a population
consisting of CS (planned and unplanned) and one study had a population
encompassing the general obstetric population.

The key findings of the studies are detailed in \emph{Table 2} including
whether the study is to be interpreted as exploratory (requiring more
research) or confirmatory (of use in clinical practice) as judged by the
primary study authors. All candidate predictors and the predictors
included in the final published models is listed in \emph{Table 3.} The
setting of the included studies were hospitals across the following
countries; Italy, China, France, United States, United Kingdom, South
Korea, Netherlands, Spain, Zimbabwe, Denmark and Egypt. The study
designs included were eight cohort studies of which one used whole
population registry data, and three case-control, of which one was
nested within a population cohort. The number of participants included
in each study ranged from 110 in a prospective cohort study to 56,967 in
a retrospective cohort.

Despite the attempt to predict PPH across all studies, the chosen
outcomes differed. Five studies listed PPH or massive haemorrhage as an
outcome, three studies listed blood transfusion or massive blood
transfusion as an outcome, two studies reported postpartum blood loss,
and one study had a combined outcome of peripartum complications
encompassing perioperative blood transfusion or uterine artery
embolization or caesarean hysterectomy. There is also variation in the
definition and method of measurement of each outcome as shown
in\emph{Table 2} .

The quality of studies, assessed using the CHARMS checklist to assess
risk of bias, is summarised in \emph{Table 4} . Overall there was a high
risk of bias across the studies. The source of data was deemed of
low/moderate risk of bias in eight studies due to the use of a
retrospective design for measurement of predictor and outcome. Two
studies

were at high risk of bias due to a lack of definition or method of
measurement of the outcome to be predicted. There was a high risk of
bias for the candidate predictors in three studies due to a lack of
definition or predictors requiring subjective interpretation. Regarding
sample size, six studies were of high risk of bias for sample size as a
result of a low number of events per variable (EPV). Risk of bias for
missing data was uncertain for all papers because none reported any
missing data.

From the 11 studies there was a total of 97 unique variables selected as
candidate predictors (range 5-23 per study) and 56 variables selected as
predictors (range 5-15 per study) in the final models. The following
predictors were found to be predictive in two or more studies: (parity
n=4 studies), low antenatal haemoglobin (n=3), antepartum
haemorrhage/bleed (n=3), maternal age [?]35 years old (n=4), high neonatal
weight (n=2), multiple pregnancy (n=2), BMI [?]25 (n=2), previous CS
(n=3), anterior placenta (n=2) and retained placenta (n=2).

The predictive ability of the statistical models evaluated using
measures of calibration (concerned with agreement between the predicted
probabilities of the outcome and the observed proportions of the
outcome) and discrimination (how well the model can differentiate
between patients with high and low risk) was evident in four and six

out of 11 studies respectively. Of the four studies to report
calibration, two used the Hosmer-Lemeshow (H-L) test with Kim et al.,
reporting good calibration with a result of p=0.44 and Rubio-Alvarez et
al., failing to report a result. However, Hosmer-Lemeshow test is not
recommended for calibration assessment due to poor interpretation as it
does not provide a direction or magnitude of the miscalibration and has
limited power in small samples. Biguzzi presented a calibration plot
demonstrating overall good performance, however, there was inadequate
information relating to curve development. Ahmadzia et al., report
calibration plots and association between predicted probability of
transfusion and observed incidence in deciles of the risk score
distribution. However, the authors have not reported, at the very least,
a Hosmer-Lemeshow test nor demonstrated a suitable calibration
plot.\textsuperscript{14} The calibration plots are described as curves
but only display a point for each decile with no 95\% confidence
intervals. Ideally the calibration slope should be reported along with a
calibration curve demonstrating the non-parametric relationship between
observed outcome and predicted risk.\textsuperscript{28} Discrimination
was reported as the area under the receiver operator curve (AUC) where 1
is perfect discrimination and 0.5 is no better than a coin toss. The AUC
ranged from 0.70 to 0.9 across all studies as shown in \emph{Table 2.}

Of 11 studies, four presented validated models deemed by their primary
study authors as ready for use in clinical
practice.\textsuperscript{14,18,19,22} Ahmadzia et al., present an
online risk calculator developed in patients who underwent CS and
Dunkerton et al., presented a decision tree based on Hothorn et al's
non-parametric recursive partitioning algorithm also developed in women
who underwent a CS. Kim et al., presented a scoring system developed in
women with placenta praevia and Rubio-Alvarez et al., present an Excel
risk tool developed in women vaginally delivering singletons. However,
Ahmadzia et al and Dunkerton et al did not externally validate their
models -- an important requirement before use in clinical
practice.\textsuperscript{29} The discriminatory performance on external
validation for Kim et al and for Rubio-Alvarez et al models were good
with AUCs of 0.88 and 0.83 respectively.

\par\null

\section*{Discussion}

{\label{discussion}}

\subsection*{Main Findings}

{\label{main-findings}}

This review is, to our knowledge, the first to systematically identify
published studies attempting to provide risk scoring or prognostic
models for the prediction of PPH. Of eleven eligible studies, two have
presented externally validated risk tools but neither were developed
using recommended methods. Kim et al. (predicting blood transfusion
([?]8u) following CS for placenta praevia) and Rubio-Alvarez et al.
(predicting excessive postpartum blood loss in women with singleton
pregnancies who underwent vaginal delivery) did not define candidate
predictors and both demonstrated very low events per variable. Chi et
al., was the only study to have a tool applicable to the general
obstetric population but is of high risk of bias; until it has been
validated, it cannot be recommended for clinical use. The other eight
studies identified are not deemed suitable for use in clinical practice
due to a lack of clinical relevance of some study populations, high risk
of bias and lack of external validation. Six out of eleven studies
featured substantially less than 10 events per potential predictor being
tested such that sample size presents a major threat to reliability of
findings.

\subsection*{Strengths and Limitations}

{\label{strengths-and-limitations}}

A strength of this review is the prospective publication of the protocol
in PROSPERO with strict adherence to this. The aim was to find a
clinically meaningful formula or tool which could be of use to a
clinician in daily practice. Numerous related studies have not published
a useable tool or logistic regression model with a formula which a
clinician could use in clinical practice -- this may reflect poor (or
poorer than anticipated) performance of the model. This review benefits
from use of broad and general search criteria to maximise identification
of relevant studies. Additionally, the results yielded by the search
strategy were double-screened by two reviewers (CN and SN). The use of
the CHARMS checklist allowed for systematic data extraction and
assessment of risk of bias.

A limitation of this review is that three studies were unable to be
obtained which may have been appropriate for inclusion. One of these was
part of an unpublished PhD thesis and the other two were behind a
paywall.

This review highlights shortcomings regarding the risk of bias and
reporting of the included studies.

The review included only studies in English language such that this may
limit the value of the findings.

\subsection*{Interpretation}

{\label{interpretation}}

This review suggests that there are no published prediction tools for
PPH that are ready for clinical use. Future research to generate
prognostic models for use specifically in elective CS or in women aiming
for vaginal birth would facilitate advanced planning of personnel to
optimise care provided.

The clinical usefulness of models generated by some of the identified
studies is limited by the target population. Four studies focus on
vaginal births which is not clinically meaningful as this cannot be
guaranteed in advance. The circumstances during labour are subject to
change with a risk of CS present until the fetal head is delivered.
Therefore, despite one of these studies, Rubio-Alvarez et al., providing
an externally validated user-friendly risk prediction tool in Excel,
its validity in practice is extremely limited as it is not possible to
know which women will give birth vaginally and thus for whom the model
is valid. Only one study produced a scoring tool aimed at use in the
general obstetric population but the study design was unclear and
attempts to contact the author were not successful. The study included
923 women in Beijing, China, of whom almost half had a PPH, and it did
not assess predictive performance via internal or external validation.
Therefore, despite the presentation of an equation to predict PPH with
AUC of 0.86, it's lack of performance assessment means it cannot be
recommended for use in clinical practice.

Most studies were retrospective, meaning that some predictors may not
have been measured, but the vast majority of relevant risk factors for
PPH can be assessed retrospectively such that this is not considered to
be a major problem.

Some studies' prediction models or tools are clinically unhelpful in
regard to the final predictors included due to some not being known at
time of birth. Both Biguzzi et al., and Rubio-Alvarez et al., included
neonatal birthweight as a predictor, which suggests that the intended
time for the nomogram and risk tool use is after weighing of the baby,
most likely once the highest risk of PPH has passed. These models are
therefore of limited value for preparation of resources prior to birth.
Estimated birthweight may be a more appropriate measure but this has not
been included as a predictor in any model.

Use of intrapartum factors can aid risk assessment in a dynamic
scenario. Two studies have included these: duration of the first and
second stage of delivery; non-use of uterotonics and cord traction.
Intrapartum risk scoring may be facilitated by use of electronic health
records, where the tool could be embedded within the system, but
otherwise may present logistical difficulties if it requires ongoing
computer access as per Rubio-Alvarez et al's proposed risk tool.

Robust external validation was absent from all prediction models
identified, suggesting that this is poorly understood and undervalued.
Of the two models externally validated both utilised Hosmer-Lemesow
testing which is not recommended, and only one provided validation
results. Internal validation is a reasonable alternative as this
assesses how well the model performs in the underlying population from
which the model was developed, but only five studies did this and only
one is considered appropriate for prospective use (in placenta praevia
population) and thus this would benefit from future external validation.

The prediction models identified were at high risk of bias overall, with
lack of detail of candidate predictors, small sample size and suboptimal
statistical analysis being common, and missing data not reported in any
study. Without missing data information it is not possibly to fully
assess the related risk of bias.\textsuperscript{39}

The need for adequately powered studies is clear. Half the included
studies have shown a low EPV (\textless{}10) with only one conducting
any shrinkage methods to overcome problems arising from overfitting of
the model (and risk of optimistic predictions) when there is a low
number of events. Despite this, several authors recommended use of
affected models without external validation.\textsuperscript{19,20,22}As
a result of heterogeneity and low EPV, it was not possible to conduct a
meta-analysis of the results. However, there is potential for synthesis
of findings for predicting PPH in a population of women with placenta
praevia, where individual participant data (IPD) meta-analysis could be
used.

\section*{Conclusion}

{\label{conclusion}}

This review has identified two PPH risk prediction tools with potential
for clinical use pending robust external validation, one for use in
cases of CS (Leicester PPH predict score) and the other for predicting
massive transfusion (\textgreater{}=8u packed red cells) in cases of CS
with known placenta praevia. There is a need for the development of a
model applicable to the wider obstetric population which can be used
when planning birth.

Contribution to authorship

CN drafted the manuscript and performed the first literature search,
data extraction and analysis.

SN performed the second screening of the titles, abstracts and full
papers and approved the final draft of the manuscript.

DM commented on all versions of the manuscript and provided
methodological advice throughout the study.

MB designed the study, supervised all steps and commented on all drafts
of the manuscript. MB is corresponding author.

Conflicts of interest

The authors have no conflicts of interest to declare.

Funding

This study received no external or specific source of funding.

\par\null

\section*{References}

{\label{references}}\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
Table 1: Inclusion and Exclusion Criteria &\tabularnewline
\midrule
\endhead
Inclusion Criteria & Exclusion Criteria\tabularnewline
Observational studies & Studies which aim only to identify the risk
factors for PPH\tabularnewline
Experimental studies & Studies only describing~tools for diagnosis of
PPH\tabularnewline
Pregnant women over the age of 16 & Studies~investigating a single
predictor test or marker\tabularnewline
Development \&/or validation of a prognostic multivariable tool or model
to predict risk of PPH & Case-reports\tabularnewline
Published since 1946 & Non-English language publication\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{longtable}[]{@{}lllllllllllllll@{}}
\toprule
\begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage} & \begin{minipage}[b]{0.04\columnwidth}\raggedright\strut
Table 2: Key components of each study\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Study Author\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Study Design\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
\textbf{Study Population}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Exclusion Criteria\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Outcome with Definition and Method of Measurement\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Candidate Predictors, n\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Participants, n (events)\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Events per Variable\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Modelling Method\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Predictors in Final Model\emph{, n}\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Calibration\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Discrimination\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Validation\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Presentation of final prediction model or tool\strut
\end{minipage} & \begin{minipage}[t]{0.04\columnwidth}\raggedright\strut
Primary author nterpretation of presented model\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Ahmadzia et al., 2018\textsuperscript{14}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Retrospective Cohort\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Patients who underwent caesarean section delivery\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Vaginal delivery and incomplete data for intrapartum and postpartum
blood transfusion\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Intraoperative and postoperative blood transfusion\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Model 1: 16 Model 2: 23\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
56, 967 (1488)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Model 1: 93 Model 2: 64.7\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
14\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Association between predicted probability of transfusion and observed
incidence in deciles of the risk score distribution' Calibration graph
provided.\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Model 1: AUC 0.77 (95\% CI 0.75-0.78) Model 2: AUC 0.83 (95\% CI
0.81-0.84)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Internal validation by random split of data\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Online Risk Calculator\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Confirmatory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Baba et al., 2014 \textsuperscript{15}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Retrospective Cohort\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
All women with placenta praevia who underwent a caesarean section\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Blood Transfusion: haemoglobin \textless{}6.0g/dL or systolic BP
\textless{}70mmHg or estimated blood loss reached
\textgreater{}2500ml\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
9\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
205 (20)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
2.22\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
5\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
AUC 0.844 (95\% CI 0.731-0.958)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Equation\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Exploratory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Biguzzi et al., 2011 \textsuperscript{16}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Unclear\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
All women who underwent vaginal delivery\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Age \textless{}18 years, Caesarean section, Delivery before the 37th
week of gestation, Twin pregnancy, No comprehension of the Italian
language, Refusal to sign a written informed consent. Deliveries that
occurred on Friday afternoon\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Postpartum haemorrhage (blood loss of [?]500ml) measured by visual
estimation using graduated basin\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
16\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
6011 (1435)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
89.69\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
5\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Graph plotting predicted probabilities against observed outcomes --
inadequate information on how curve was developed\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
AUC 0.70\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Internal Validation with bootstrap sampling\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Nomogram\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Exploratory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Chi et al., 2016 \textsuperscript{17}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Retrospective Case-control\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Parturient patients with complete prenatal examination data\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Postpartum haemorrhage\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
21\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
923 (447)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
21.29\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
15\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Score assigned\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Exploratory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Dunkerton et al., 2018 \textsuperscript{18}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Retrospective cohort\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
All caesareans at a single university hospital trust in U. K\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Postpartum haemorrhage (estimated blood loss of [?] 1000ml, annual staff
training with pictorial reference cards)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
17\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
24,230 (2997)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
176.29\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Hothorn et al's non-parametric recursive partitioning algorithm\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
9\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Internal validation by data splitting\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Decision tree\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Confirmatory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Kim et al., 2017 \textsuperscript{19}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Registry data\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Patients with placenta praevia who underwent caesarean section\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Coagulopathie-s and incomplete data\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Massive transfusion (transfusion of [?]8 units pRBC within 24h after
delivery)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
12\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
238 (31)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
2.58\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
5\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Hosmer-Lemeshow test (p=0.44)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Internal validationAUC (0.84) External validation AUC (0.88)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Internal validation by bootstrapping and External Validation of score
model\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Scoring system\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Confirmatory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Lee et al., 2018 \textsuperscript{20}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Retrospective Cohort\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Pregnant women with placenta praevia\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Multiple pregnancies, Maternal obstetrical or medical problems other
than placenta praevia and Fetal anomalies\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Massive haemorrhage defined as blood loss [?] 2000ml during surgery,
postpartum transfusion of four or more pints of packed red blood cells,
caesarean hysterectomy or uterine arterial embolization triggered by
post-partum bleeding.\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
16\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
560 (73)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
4.56\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
7\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
AUC (0.856)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Sum score\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Confirmatory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Prata et al., 2011 \textsuperscript{21}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Prospective Cohort\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Women anticipating a singleton vaginal delivery of gestational age
\textgreater{}36 weeks\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Delivery by caesarean section, missing information on delivery
type\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Postpartum haemorrhage defined as blood loss greater than 500ml during
the first 4 hours after delivery (measured by calibrated drapes)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
20\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
2510 (93)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
4.65\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
8\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Cumulative scores: number of risk factors vs risk\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Exploratory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Rubio-Alvarez et al., 2018 \textsuperscript{22}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Retrospective cohort\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Women with singleton pregnancies who had vaginal birth\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Antenatal fetal demise, Multiple pregnancies and Gestations
\textless{}35 weeks\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Excessive postpartum blood loss defined as a reduction in haemoglobin
(Hb)levels greater than 3.5g/dL and a final Hb \textless{}8g/dL between
onset of birth and 24 hours after it\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
14\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
2336 (43)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
3.07\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
6\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Hosmer-Lemeshow test (no result reported)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
AUC 0.9 (0.85-0.93)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Internal Validation by random-split of data External validation
(temporal) AUC of 0.83 (0.74-0.92)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Risk Tool for Excel\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Confirmatory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Tsu 1994 \textsuperscript{23}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Case-control\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Women with singleton vertex deliveries and spontaneous onset of
labour\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Postpartum blood loss of at least 600ml after a normal, unassisted
vaginal delivery\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
5\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
653 (151)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
30.2\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
5\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
only ROC no AUC\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Equation\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Exploratory\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Yoon et al., 2014 \textsuperscript{24}\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Prospective Cohort\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Singleton pregnancy women with placenta praevia delivered by caesarean
section\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Occurrence of peripartum complications: Perioperative blood transfusion
(determined by attending anaesthesiologist during CS when clinical
evidence of inadequate oxygen-carrying capacity or ongoing profuse blood
loss) or uterine artery embolization (to control moderate uterine
bleeding immediately after CS when vital status of the patient was
stable) or caesarean hysterectomy (vital status of patient was unstable
despite vigorous massive transfusion and haemostatic manoeuvres)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
12\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
110 (38)\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
2.89\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Logistic\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
6\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
None\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Scoring model\strut
\end{minipage} & \begin{minipage}[t]{0.06\columnwidth}\raggedright\strut
Exploratory\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
Table 3: Study population of included studies alongside predictors\strut
\end{minipage} & \begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
Table 3: Study population of included studies alongside predictors\strut
\end{minipage} & \begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
Table 3: Study population of included studies alongside predictors\strut
\end{minipage} & \begin{minipage}[b]{0.22\columnwidth}\raggedright\strut
Table 3: Study population of included studies alongside predictors\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Study Author\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Study Population\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Candidate Predictors\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{Predictors in Final Model}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Ahmadzia et al., 2018\textsuperscript{14}\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Intraoperative and postoperative blood transfusion\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Maternal age (extremes \textless{}21 or \textgreater{}36), BMI at
delivery, Number of previous term deliveries, Gestational age
\textgreater{}37 weeks, total years of schooling, African American
ethnicity, insurance status for prenatal care, white blood cell count,
platelet count, haematocrit, previous cesarean delivery, asthma, heart
disease, connective tissue disorder, hypertensive disorder (gestational
hypertension/preeclampsia/HELLP), abruption, non-elective caesarean
delivery, use of general anaesthesia, failure to progress,
preeclampsia/eclampsia or HELLP, abnormal placentation, intrapartum
antibiotic use (including treatment for chorioamnionitis or prophylaxis
for GBS/caesarean delivery)\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Model 1 \& 2: Maternal Age, Body Mass Index (BMI,
kg/m\textsuperscript{2}), Platelets x10\textsuperscript{3}, Haematocrit
(\%), Gestational hypertension or Preeclampsia, HELLP, History of
asthma, Suspected Abruption, African American, Insurance, Gestational
age \textless{}37 weeks, 3 or more previous term deliveries, Heart
disease, Number prior caesarean deliveries Model 2 also contained:
non-elective repeat caesarean delivery, use of general anaesthesia,
failure to progress, preeclampsia/eclampsia or HELLP, abnormal
placentation, intrapartum antibiotic use\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Chi et al., 2016\textsuperscript{17}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Parturient patients with complete prenatal examination data\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Age, BMI, Multiplets, Hypertension family history, Adverse maternal
history, History of abdominal operation, Hypertensive disorder
complicating pregnancy, Gestational diabetes mellitus, Giant baby,
Amniotic fluid, Myoma of uterus, Placenta praevia, Placental abruption,
Retained placenta, Adherent placenta, Threatened premature labour,
Abnormal pelvic canal, Haemoglobin, Platelet count, Caesarean delivery,
Placenta factor\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Multiplets, Hypertension family history, Adverse maternal history,
History of abdominal operation, Hypertensive disorder complicating
pregnancy, Giant baby, Amniotic fluid, Myoma of uterus, Abnormal pelvic
canal, Threatened premature labour, Haemoglobin [?] 100, Platelet Count
\textless{} 100x10\^{}9, Age [?] 35, BMI [?] 25, Pregnancy bleeding
history\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Dunkerton et al., 2018\textsuperscript{18}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
All caesareans at a single university hospital trust in U.K\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Previous Caesarean, antepartum/intrapartum haemorrhage, emergency
caesarean, age [?]40y, maternal sepsis, suspected scar dehiscence,
second-stage section, polyhydramnios, macrosomia, fibroids,
preeclampsia/pregnancy induced hypertension, multiple pregnancies,
previous three caesarean sections, Asian ethnicity, grandmultiparity,
placenta praevia, suspected abruption\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Placenta praevia, previous caesarean, antepartum haemorrhage, BMI
\textgreater{}35, Emergency caesarean section, Asian ethnicity, Multiple
Pregnancy, grandmultiparity, pregnancy induced
hypertension/Pre-eclampsia\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Kim et al., 2017\textsuperscript{19}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Patients with placenta praevia who underwent caesarean section\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Maternal age, BMI, parity, Gestational age, previous caesarean,
placental abruption, previous uterine surgery, twin pregnancy,
artificial abortion, anterior placenta, cervical vascularity, Suspicion
of placental adhesion\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Gestational age, previous caesarean, anterior placenta, cervical
vascularity, suspicion of placental adhesion\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Lee et al., 2018\textsuperscript{20}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Pregnant women with placenta praevia\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Maternal age at delivery, Parity, BMI, Number of previous uterine
curettages, Previous uterine surgery (caesarean or myomectomy), Presence
of uterine myoma, Cervical length within a week before delivery,
Gestational age at first episode of AP bleed (after 20 weeks), Number of
incidences of antepartum bleeding (after 20w), Need for emergency CS,
Fetal presentation, Placental type (complete or incomplete), Location
(anterior or posterior), Multiple lacunae ([?]4 defined as an irregular
area of low echogenicity larger than 1x1cm in placental parenchyma),
Lack of translucent zone (clear zone defined as the line of low
echogenicity between myometrium and placenta), Uteroplacental
hypervascularity evident on colour doppler imaging\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Maternal age [?]35 years, Antepartum bleeding, fetal non-cephalic
presentation, complete placenta praevia, anterior placenta, Multiple
lacunae [?]4, Uteroplacental hypervascularity\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Prata et al., 2011\textsuperscript{21}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Women anticipating a singleton vaginal delivery of gestational age
\textgreater{}36 weeks\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Maternal age, Education, Nulliparity, Previous antenatal care, PPH in
previous pregnancy, History of obstetric complications, Intact
membranes, Anaemia (measured by blood collected after enrolment and
defined as antepartum Hb at or below 11mg/dl), cervical dilatation,
Vaginal delivery with instruments, Episiotomy, Labour augmentation,
Retained placenta, Vaginal tears, Fetal macrosomia
(\textgreater{}3500g), Length of 1st and 2nd stage, Absence of AMTSL (a
protocol), Use of uterotonics, Cord clamping, Cord traction, Uterine
massage\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Elevated number of antenatal care visits, history of PPH, anaemia,
labour augmentation, retained placenta, length of 1st and 2nd stage,
non-use of uterotonics in the 3rd stage and cord traction\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Rubio-Alvarez et al., 2018\textsuperscript{22}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Women with singleton pregnancies who had vaginal birth\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Age, BMI, Antepartum haemoglobin, Previous caesarean, Primiparity,
Instrumental birth, Duration of first stage, duration of second stage of
labour (hours), Use of regional analgesia, Active management (5IU
intraoperative oxytocin and consequent controlled umbilical cord
traction), Manual removal of placenta, Episiotomy or vaginal tear,
Gestational age (weeks)and Neonatal birthweight(g)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Primiparity, Maternal age, Duration of first stage, Duration of second
stage, Neonatal birthweight and Antepartum haemorrhage\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Tsu 1994\textsuperscript{23}\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Women with singleton vertex deliveries and spontaneous onset of
labour\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Advanced maternal age (\textgreater{}35), Low parity (0,1), Poor
obstetric outcome in preceding pregnancy, Anaemia during current
pregnancy (antenatal haemoglobin \textless{}12g/dL) and Admission to
hospital for any pregnancy related problem before onset of labour\strut
\end{minipage} & \begin{minipage}[t]{0.24\columnwidth}\raggedright\strut
Combination 1: Poor obstetric outcome in last pregnancy or antenatal
admission to hospital for a pregnancy related problem Combination 2:
Poor obstetric outcome in last pregnancy or antenatal admission to
hospital for a pregnancy related problem or low haemoglobin Combination
3: any 2 or more risk factors (as listed under `Candidate Predictors')
Combination 4: any 1 or more risk factors (as listed under `Candidate
Predictors')\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Yoon et al., 2014\textsuperscript{24}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Singleton pregnancy women with placenta praevia delivered by caesarean
section\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Type of praevia: partialis and totalis, Location of praevia (posterior,
lateral and anterior), Lacunae (classified into 4 grades (0-3)),
Echolucent area (intact or absent) Hypervascularity (normal, moderately
increased intraplacental vascularity and severe uteroplacental
hypervascularity), Bladder-uterine interface (intact or interrupted)
Maternal age ([?] 35), Multiparity, Prior caesarean section, Prior
praevia, Prior abortion, Antepartum bleeding\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Type of placenta praevia, Lacunae, Hypervascularity, Multiparity, Prior
praevia, Prior caesarean section\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\textbf{Table 4: Summary table of risk of bias} & \textbf{Table 4:
Summary table of risk of bias} & \textbf{Table 4: Summary table of risk
of bias} & \textbf{Table 4: Summary table of risk of bias} &
\textbf{Table 4: Summary table of risk of bias} & \textbf{Table 4:
Summary table of risk of bias} & \textbf{Table 4: Summary table of risk
of bias}\tabularnewline
\midrule
\endhead
\textbf{Study Author} & \textbf{Source of Data} & \textbf{Outcomes to be
Predicted} & \textbf{Candidate Predictors} & \textbf{Sample Size} &
\textbf{Missing Data} & \textbf{Statistical Analysis}\tabularnewline
Ahmadzia et al., 2018\textsuperscript{14} & +/- & - & + & + & ? &
-\tabularnewline
Baba et al., 2014\textsuperscript{15} & +/- & + & + & - & ? &
-\tabularnewline
Biguzzi et al., 2011\textsuperscript{16} & ? & + & + & + & ? &
+\tabularnewline
Chi et al., 2016\textsuperscript{17} & +/- & - & - & + & ? &
-\tabularnewline
Dunkerton et al., 2018\textsuperscript{18} & +/- & + & + & + & ? &
+\tabularnewline
Kim et al., 2017\textsuperscript{19} & +/- & + & - & - & ? &
+\tabularnewline
Lee et al., 2018\textsuperscript{20} & +/- & + & - & - & ? &
-\tabularnewline
Prata et al., 2011\textsuperscript{21} & + & + & + & - & ? &
-\tabularnewline
Rubio-Alvarez et al.,2018\textsuperscript{22} & +/- & + & + & - & ? &
+\tabularnewline
Tsu 1994\textsuperscript{23} & +/- & - & + & + & ? & -\tabularnewline
Yoon et al., 2014\textsuperscript{24} & + & + & + & - & ? &
-\tabularnewline
\bottomrule
\end{longtable}

Green boxes (+) indicate low risk of bias, yellow boxes (+/-) indicate
low/moderate risk of bias, red boxes (-) indicate high risk of bias and
orange boxes (?) indicate unclear risk of bias.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/BJOG-Fig1/BJOG-Fig1}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

