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\begin{document}

\title{Predictive performance for placental dysfunction related stillbirth of
the competing risks model for small for gestational age fetuses}



\author[1]{Kypros Nicolaides}%
\author[2]{Ioannis Papastefanou}%
\author[3]{Argyro Syngelaki}%
\author[4]{Ghalia Ashoor}%
\author[5]{Ranjit Akolekar}%
\affil[1]{Fetal Medicine Institute}%
\affil[2]{Fetal Medicine Clinic, Monis Petraki 4, Kolonaki, 11521, Athens, Greece}%
\affil[3]{King's College Hospital}%
\affil[4]{Fetal Medicine Research Institute}%
\affil[5]{Medway Maritime Hospital}%


\vspace{-1em}



  
  \date{May 18, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Objectives: First, to examine the predictive performance for placental
dysfunction related stillbirths of the competing risks model for small
for gestational age (SGA) fetuses based on a combination of maternal
risk factors, estimated fetal weight (EFW) and uterine artery
pulsatility index (UtA-PI); and second, to compare the performance of
this model to that of stillbirth-specific model utilizing the same
biomarkers and to the Royal College of Obstetricians and Gynecologists
(RCOG) guideline for the investigation and management of the SGA fetus.
Design: Prospective observational study. Setting: Two UK maternity
hospitals. Population: 131,514 women with singleton pregnancies
attending for routine ultrasound examination at 19-24 weeks' gestation.
Methods: The predictive performance for stillbirth achieved by three
models was compared. Main outcome measures: Placental dysfunction
related stillbirth. Results: At 10\% false positive rate, the competing
risks model predicted 59\%, 66\% and 71\% of placental dysfunction
related stillbirths, at any gestation, at \textless{}37 weeks and at
\textless{}32 weeks, respectively, which were similar to the respective
figures of 62\%, 70\% and 73\% for the stillbirth-specific model. At a
screen positive rate of 21.8 \%, as defined by the RCOG guideline, the
new model predicted 71\%, 76\% and 79\% of placental dysfunction related
stillbirths at any gestation, at \textless{}37 weeks and at
\textless{}32 weeks, respectively, and the respective figures for the
RCOG guideline were 42\%, 44\% and 40\%. Conclusion: The predictive
performance for placental dysfunction related stillbirths by the
competing risks model for SGA was similar to the stillbirth-specific
model and superior to the RCOG guideline.%
\end{abstract}%



\sloppy


\textbf{INTRODUCTION}

Development of preventive strategies for stillbirth necessitate
recognition that first, the aetiology is heterogeneous and often
unknown, and second, the majority of stillbirths are related to
placental dysfunction, reflected in the coexistence of small for
gestational age (SGA) fetuses and / or preeclampsia. In a prospective
study on screening for adverse obstetric outcomes involving 131,514
women with singleton pregnancies attending for routine pregnancy care at
19-24 weeks' gestation, there were 477 (0.36\%) stillbirths, 92.5\% of
which were antepartum and 7.5\% intrapartum; placental dysfunction
related stillbirths accounted for 59\% of all antepartum
stillbirths\textsuperscript{1}. The dataset was used to develop and
validate a logistic regression model for prediction of placental
dysfunction related stillbirth; a combination of maternal risk factors,
sonographic estimated fetal weight (EFW) and uterine artery pulsatility
index (UtA-PI) predicted, at 10\% false positive rate (FPR), 62\% of all
cases of placental dysfunction related stillbirths, 70\% of those at
\textless{}37 weeks' gestation and 29\% of those at [?]37 weeks.

In 93\% of the placental dysfunction related stillbirths the birth
weight was below the 10\textsuperscript{th} percentile of The Fetal
Medicine Foundation population charts\textsuperscript{1,2}. It may
therefore be preferable to use one model for prediction of both SGA and
stillbirth, rather than two separate models; the management of
pregnancies at high risk for these conditions is essentially the same
and involves serial ultrasound examinations for early diagnosis of SGA
and then Doppler assessment of the fetal circulation to determine the
best time and mode of delivery. The traditional approach to identify a
high risk group for SGA is the application of a scoring system. For
example, in the UK, according to guidelines by the Royal College of
Obstetricians and Gynaecologists (RCOG), a scoring system is applied to
identify a high risk group for SGA in need of serial ultrasound scans
from 26 weeks onwards\textsuperscript{3}. An alternative method is
provided by our novel two dimensional continuous competing risks model
in which SGA is considered as a spectrum disorder whose severity is
continuously reflected in both the gestational age at delivery (GA) and
Z score in birth weight for gestational age (Z)\textsuperscript{4-8}.
The building block of this model is a patient-specific joint
distribution of Z and GA, that is obtained by combining a history model
with multivariate likelihood of biomarkers according to Bayes
theorem\textsuperscript{4-8}. Risk computation is feasible for any
chosen cut-off in GA and Z, at any stage of pregnancy by adding any
desired biomarker in the same model.

The objective of this study was to examine the predictive performance
for placental dysfunction related stillbirths by the competing risks
model for SGA based on a combination of maternal risk factors, EFW and
UtA-PI and compare the performance to that of our stillbirth-specific
logistic regression model using the same biomarkers
\textsuperscript{1}and to the RCOG guideline for the investigation and
management of the SGA fetus \textsuperscript{3}.

\textbf{METHODS}

\textbf{Study population and design}

The data for this study were derived from prospective screening for
adverse obstetric outcomes in women attending for routine pregnancy care
at 19\textsuperscript{+0}-24\textsuperscript{+6} weeks' gestation at
King's College Hospital and Medway Maritime Hospital, UK, between 2011
and 2020. In this visit we first, recorded maternal demographic
characteristics and medical history as self-reported by the patients,
second, carried out an ultrasound examination for fetal anatomy and
measurement of fetal head circumference, abdominal circumference and
femur length to calculate the EFW by the Hadlock
formula\textsuperscript{9}, because a systematic review identified this
as being the most accurate model \textsuperscript{10}, and third,
measured the left and right UtA-PI either by transvaginal or
transabdominal color Doppler ultrasound and calculated the mean value of
the two arteries\textsuperscript{11,12}. The majority of UtA-PI
measurements were carried out transvaginally because at the same time we
were measuring cervical length; the transabdominal approach was used
when women declined transvaginal sonography. Gestational age was
determined from measurement of fetal crown-rump length at 11-13 weeks or
the fetal head circumference at 19-24 weeks\textsuperscript{13,14}. The
same study population was used for development and validation of the
model based on multivariable logistic regression analysis for prediction
of placental dysfunction related stillbirth\textsuperscript{1}.

The inclusion criteria for this study were singleton pregnancies that
delivered a phenotypically normal live birth or stillbirth
at\emph{\textgreater{}} 24 weeks' gestation. We excluded pregnancies
with known aneuploidies, major fetal abnormalities, those ending in a
miscarriage or termination of pregnancy. There was no patient
involvement in the design of the study.

\textbf{Study funding}

This study was supported by grants from the Fetal Medicine Foundation
(UK Charity No: 1037116). This body had no involvement in the study
design; in the collection, analysis and interpretation of data; in the
writing of the report; and in the decision to submit the article for
publication.

\textbf{Outcome measures}

Data on pregnancy outcome were obtained from the maternity hospital
records or the general practitioners of women. Stillbirths were divided
into those that occurred prenatally and those that occurred during
labour (intrapartum stillbirths). Antepartum stillbirths were divided
into those that were associated with placental dysfunction (preeclampsia
or birthweight \textless{}10\textsuperscript{th} percentile) and those
due to other causes. Antepartum stillbirths were further divided based
on gestational age at stillbirth into those that occurred at any
gestational age, at \textless{}37 weeks and at \textless{}32 weeks.

\textbf{Statistical analyses}

Data from continuous variables were expressed as medians and
interquartile ranges and from categorical data as n (\%). Comparison of
the maternal characteristics between the outcome groups was by the
\selectlanguage{greek}χ\selectlanguage{english}2-square test or Fisher's exact test for categorical variables or
Mann-Whitney U-test for continuous variables, respectively. The observed
measurements of UtA-PI were expressed as a multiple of the normal median
(MoM) after adjustment for maternal and pregnancy characteristics as
previously described\textsuperscript{15}. The values of EFW were
expressed as Z-scores using The Fetal Medicine Foundation population
charts\textsuperscript{2}. We used Bayes' theorem to combine
the\emph{prior} joint distribution of Z and GA according to the history
model with the likelihoods of EFW Z score and UtA-PI MoM to obtain a
pregnancy specific \emph{posterior} distribution; this was used to
produce patient specific risks according to the competing risks model
for SGA. The distributions of patient-specific risks were used to
estimate detection rates (DR) and FPR from analysis of receiver
operating characteristic (ROC) curves. Similarly, patient-specific risks
were estimated using our previously reported logistic regression model
for placental dysfunction related stillbirth \textsuperscript{1}. The
predictive performance for stillbirth of the competing risks model for
SGA\textsuperscript{7} and the stillbirth-specific logistic regression
model for placental dysfunction \textsuperscript{1} was compared.
McNemar's test was used to compare detection rates of stillbirth
achieved from the application of the RCOG guideline and those resulting
from the competing risks model for SGA, at the same screen positive rate
as that determined from the use of the RCOG guideline.

The statistical software package R was used for data
analyses.\textsuperscript{16}

\textbf{RESULTS}

\textbf{Study population}

The entry criteria were fulfilled by 131,514 singleton pregnancies;
there were 131,037 livebirths and 477 (0.36\%) stillbirths, including
441 (0.34\%) antepartum and 36 (0.03\%) intrapartum stillbirths. The
maternal and pregnancy characteristics in stillbirths and livebirths in
the study population are summarised in Table 1.

The gestational age distribution of antepartum stillbirths was
\textless{}32 weeks in 45.6\% (201/441) of cases, \textless{}37 weeks in
67.3\% (297/441) of cases and at [?]37 weeks in 32.7\% (144/441) of cases.
The gestational age and birthweight distribution of the antepartum
stillbirths is shown in Figure 1. The birthweight was \textless{}10th
percentile in 55.1\% (243/441) of all antepartum stillbirths, including
78.6\% (158/201) of those at \textless{}32 weeks' gestation, 69.4\%
(206/297) at \textless{}37 weeks, and 25.7\% (37/144) at [?]37 weeks. The
birthweight was \textless{}10th percentile in 93.1\% (243/261) of all
placental dysfunction related stillbirths, including 98.1\% (158/161) of
those at \textless{}32 weeks' gestation, 96.7\% (206/213) at
\textless{}37 weeks, and 78.7\% (37/47) at [?]37 weeks.

\textbf{Comparison of the competing risks model for SGA with the
stillbirth-specific logistic regression model}

Prediction of stillbirth, expressed as AUROC and detection rate at 10\%
FPR, in screening by maternal risk factors and combinations with EFW and
UtA-PI for all stillbirths and the subgroups of antepartum stillbirths
and those that were related to placental dysfunction by the two models
of screening are summarised in Table 2. At 10\% FPR, the competing risks
model predicted 58.6\% (52.6 - 64.6), 66.2\% (59.9 - 72.6), 70.8\% (63.8
- 77.8) of placental dysfunction related stillbirths, at any gestation,
at \textless{}37 weeks' gestation and \textless{}32 weeks, respectively,
which were similar to the respective figures of 62.3\% (57.2-67.4),
69.8\% (65.0-74.6), and 72.5\% (67.8-77.2) achieved by the application
of the stillbirth-specific logistic regression model.

The ROC curves for prediction of all antepartum stillbirths and
placental dysfunction related stillbirths, at any gestation, at
\textless{}37 weeks' gestation and at \textless{}32 weeks, by the
competing risks model for SGA fetuses, are shown in Figure 2. The
detection rates at 1\%, 3\%, 5\% and 10\% FPR in screening by the
competing risks model utilising maternal risk factors and combinations
with EFW and UtA-PI are shown in Table S1. Reducing the FPR from 10\% to
3\% results in a relatively mild reduction in the detection rate, an
observation that might be useful in balancing effective prediction and
availability of resources.

\textbf{Comparison of the competing risks model for SGA with the RCOG
guideline for the prediction of SGA}

The variables used for the comparison are given in Table S2. The ROC
curves for the prediction of stillbirth by the competing risks model
combining maternal risk factors, EFW, and UtA-PI are presented in Figure
2. Prediction of stillbirth by the competing risks model was superior to
that of the RCOG guideline (Table 3, Figure 2). At a screen positive
rate of 21.8 \%, as defined by the RCOG guideline, the new model
predicted 79\%, 76\% and 71\% of placental dysfunction related
stillbirths at \textless{}32 weeks' gestation, \textless{}37 weeks and
any gestational age and the respective figures for the RCOG guideline
were 42\%, 44\% and 40\%\textsuperscript{3}.

\textbf{DISCUSSION}

\textbf{Main findings}

\par\null

There are three main findings of this large prospective screening study
for adverse pregnancy outcome. First, about 60\% of antepartum
stillbirths are related to placental dysfunction and in more 90\% of
such cases the fetuses are SGA. Second, in screening for placental
dysfunction related stillbirth by a combination of maternal risk
factors, EFW and UtA-PI utilising the competing risks model for
SGA\textsuperscript{7}, the predictive performance is similar to that
achieved in screening by a specific logistic regression model for
placental dysfunction related stillbirth\textsuperscript{1}. Third, the
performance of screening by the competing risks model for SGA is by far
superior to the RCOG guideline for the investigation and management of
the SGA fetus \textsuperscript{3}.

\textbf{Strengths and limitations}

The strengths of the study are: first, large sample size with
prospectively collected data, second, focus on placental dysfunction
related stillbirths, rather that treating all stillbirths as a
homogeneous condition, and third, comparison of the predictive
performance of two of our models that were previously internally
validated\textsuperscript{1,7}. We acknowledge the prerequisite for
external validation to support generalization of our results and wide
implementation of our model. Such external validation would require a
large prospective multicenter study.

It is possible that in some cases the birthweight of the stillborn
babies is lower than the weight at the time of death because there is a
relationship between intrauterine retention interval and reduction in
birthweight\textsuperscript{34}. In our cases we did not have
information on this interval and therefore the incidence of placental
dysfunction related stillbirths maybe overestimated.

A Some of the risk factors included in the RCOG guideline for the
prediction of SGA were not included in the competing risks model for SGA
because we did not have such risk factors for any or some of our
patients. For example, we did not have data on low fruit intake before
pregnancy, paternal SGA, daily vigorous exercise, heavy bleeding similar
to menses, or notching of the uterine artery Doppler waveforms, but
these factors may well suffer from subjectivity or information bias.
Similarly, we did not have available data on PAPP-A for all of our
patients and did not use the criterion of \textless{}0.4 MoM for
assessment of risk; in a previous study we reported that inclusion of
PAPP-A as a binary variable (\textless{}0.4 MoMs) increases the screen
positive rate without any significant improvement in the detection
rate.\textsuperscript{33}

\textbf{Comparison with results of previous studies}

In a series of previous first and second trimester studies for the
prediction of stillbirth we highlighted that the causes of this adverse
event are heterogeneous and that the focus of research should be
placental dysfunction related stillbirths because they are relatively
common and to a great extent potentially
preventable\textsuperscript{17-22}. However, a systematic review of 69
previous systematic reviews which aimed to identify variables that could
be relevant to the development of a clinical prediction model for
stillbirth treated this adverse event as a homogeneous
condition.\textsuperscript{23} The study reported that no marker had
useful screening performance, but maternal age, body mass index and
history of prior adverse pregnancy outcomes had a more convincing
association than the best performing tests, which were
pregnancy-associated plasma protein-A (PAPP-A), placental growth factor
(PlGF) and UtA-PI.\textsuperscript{23} Such types of publications that
do not recognize the fact that the causes of stillbirth are
heterogeneous could not possibly advance the development of strategies
for prediction and prevention of stillbirth.

The same group of authors attempted to externally validate previously
published prediction models for stillbirth using individual participant
data (IPD) meta-analysis from a heterogeneous group of 19
datasets\textsuperscript{24}. A literature search identified 40
stillbirth models, but they could only validate three of these models
due to lack of availability of the necessary predictors in their dataset
or the model equations in the previous publications; surprisingly for
such a study there was no attempt to contact the authors of the models
to request details on the equations. The authors reported that the three
models showed poor and uncertain predictive performance in their data,
they had limited clinical utility and that further research is needed to
identify stronger prognostic factors and develop more robust prediction
models \textsuperscript{33}. However, these conclusions are misleading
and can have a potential adverse impact on clinical practice and future
research, because first, two of the three models they evaluated were
based on maternal risk factors only and they overlooked many prediction
models based on a combination of maternal risk factors and first or
second trimester biomarkers, second, the heterogeneous datasets used for
their IPD meta-analysis were not derived from prospective screening for
stillbirth and were therefore inadequate for assessing models derived
from prospective examination of patients, and third, the authors
examined the value of the reported models for prediction of all
stillbirths and overlooked the fact that the original publications
highlighted that the models provided good prediction of placental
dysfunction related stillbirth, particularly those occurring preterm,
rather than prediction of all stillbirths.

In our study we have focussed on placental dysfunction related
stillbirth, prospectively recorded data from the maternal history and
biomarkers shown over the last few decades to be associated with the
birth of SGA neonates, developed and validated a model for prediction of
SGA and demonstrated that such model can effectively predict a high
proportion of stillbirths, especially those that occur preterm. We have
previously reported the increased risk for SGA fetuses / neonates is
provided by lower maternal weight and height, black, South and East
Asian racial origin, medical history of chronic hypertension, diabetes
mellitus and systemic lupus erythematosus or antiphospholipid syndrome,
conception by \emph{in vitro} fertilization or ovulation induction and
smoking.\textsuperscript{4} For parous women variables from the last
pregnancy that increased the risk for SGA were history of preeclampsia
or stillbirth, decreasing birth weight z-score and decreasing
gestational age at delivery of the last pregnancy and inter-pregnancy
interval \textless{}0.5 years.\textsuperscript{4}

\textbf{Clinical implications of the study}

A high proportion of placental dysfunction related stillbirths can
potentially be prevented by a three stage strategy. First, screening for
preeclampsia at 11-13 weeks' gestation and treatment of the high-risk
group by aspirin; this is effective in the prevention of preterm
preeclampsia but also in the prevention of early SGA in the absence of
preeclampsia \textsuperscript{25-30}. Second, screening during the
routine mid-trimester scan by a combination of maternal risk factors,
EFW and UtA-PI, which identifies a high-risk group that contains a high
proportion of placental dysfunction related stillbirths that occur at
24-37 weeks' gestation; close monitoring of these pregnancies for early
diagnosis of SGA fetuses could prevent at least some of such stillbirths
by defining the best approach to monitoring and best timing of delivery.
The detection rate of stillbirths is higher when UtA-PI is included in
the model in addition to maternal risk factors and EFW, highlighting the
necessity of including this measurement in the routine mid-trimester
scan; it is easy for competent sonographers to learn this technique and
it only adds about 2 minutes to the examination. Third, routine
ultrasound examination at 36 weeks' gestation, because screening at
mid-gestation provides poor prediction of stillbirth at term; more
effective screening for late SGA can be achieved by screening at
36\textsuperscript{31,32}.

\textbf{Conclusion}

Placental dysfunction related stillbirth is to a great extent
predictable and potentially preventable. In more than 90\% of such
stillbirths the fetuses are SGA and many of these can be predicted at a
routine mid-pregnancy assessment utilising a combination of maternal
risk factors ultrasonographic EFW and UtA-PI.

\textbf{Disclosure of interests}

The authors report no conflict of interest.

\textbf{Contribution to authorship}

KHN and IP conceptualized and designed the study. AS searched the
databases and provided the necessary files for analysis. KHN and RA
oversaw the study. IP conducted the statistical analysis. KHN, IP and GA
wrote the paper. All authors revised and contributed to the intellectual
content of the manuscript.

\textbf{Details of ethical approval}

Women gave written informed consent to take part in the study which was
carried out in compliance with the 1975 Declaration of Helsinki
Guidelines. The study was approved by the NHS Research Ethics Committee
(REC reference 02-03-033, date of approval 11/03/2003).

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  Akolekar R, Tokunaka M, Ortega N, Syngelaki A, Nicolaides KH.
  Prediction of stillbirth from maternal factors, fetal biometry and
  uterine artery Doppler at 19-24 weeks. \emph{Ultrasound Obstet
  Gynecol} 2016;48:624-30.
\item
  Townsend R, Sileo FG, Allotey J, Dodds J, Heazell A, Jorgensen L, Kim
  VB, Magee L, Mol B, Sandall J, Smith GCS, Thilaganathan B, von
  Dadelszen P, Thangaratinam S, Khalil A. Prediction of stillbirth: an
  umbrella review of evaluation of prognostic variables. BJOG
  2021;128:238-50.
\item
  Allotey J, Whittle R, Snell KIE, Smuk M, Townsend R, von Dadelszen P,
  Heazell AEP, Magee L, Smith GCS, Sandall J, Thilaganathan B, Zamora J,
  Riley RD, Khalil A, Thangaratinam S; IPPIC Collaborative Network.
  External validation of prognostic models to predict stillbirth using
  the International Prediction of Pregnancy Complications (IPPIC)
  Network database: an individual participant data
  meta-analysis.\emph{Ultrasound Obstet Gynecol} 2021 Aug 18. doi:
  10.1002/uog.23757.
\item
  Tan MY, Syngelaki A, Poon LC, Rolnik DL, O'Gorman N, Delgado JL,
  Akolekar R, Konstantinidou L, Tsavdaridou M, Galeva S, Ajdacka U,
  Molina FS, Persico N, Jani JC, Plasencia W, Greco E, Papaioannou G,
  Wright A, Wright D, Nicolaides KH. Screening for pre-eclampsia by
  maternal factors and biomarkers at 11-13 weeks'
  gestation.\emph{Ultrasound Obstet Gynecol} 2018;52:186-95.
\item
  Wright D, Wright A, Nicolaides KH. The competing risk approach for
  prediction of preeclampsia. \emph{Am J Obstet
  Gynecol}2020;223:12-23.e7.
\item
  Wright D, Tan MY, O'Gorman N, Poon LC, Syngelaki A, Wright A,
  Nicolaides KH. Predictive performance of the competing risk model in
  screening for preeclampsia. \emph{Am J Obstet Gynecol} 2019; 220:
  199.e1-199.e13.
\item
  Rolnik DL, Wright D, Poon LC, O'Gorman N, Syngelaki A, de Paco
  Matallana C, Akolekar R, Cicero S, Janga D, Singh M, Molina FS,
  Persico N, Jani JC, Plasencia W, Papaioannou G, Tenenbaum-Gavish K,
  Meiri H, Gizurarson S, Maclagan K, Nicolaides KH. Aspirin versus
  placebo in pregnancies at high risk for preterm preeclampsia. \emph{N
  Engl J Med} 2017;377:613-22.
\item
  Roberge S, Bujold E, Nicolaides KH. Aspirin for the prevention of
  preterm and term preeclampsia: systematic review and
  metaanalysis.\emph{Am J Obstet Gynecol} 2018; 218: 287-293.e1.
\item
  Tan MY, Poon LC, Rolnik DL, Syngelaki A, de Paco Matallana C, Akolekar
  R, Cicero S, Janga D, Singh M, Molina FS, Persico N, Jani JC,
  Plasencia W, Greco E, Papaioannou G, Wright D, Nicolaides KH.
  Prediction and prevention of small-for-gestational-age neonates:
  evidence from SPREE and ASPRE. \emph{Ultrasound Obstet
  Gynecol}2018;52:52-59.
\item
  Fadigas C, Saiid Y, Gonzalez R, Poon LC, Nicolaides KH. Prediction of
  small for gestational age neonates: Screening by fetal biometry at
  35-37 weeks. \emph{Ultrasound Obstet Gynecol} 2015;45:559-65.
\item
  Ciobanu A, Rouvali A, Syngelaki A, Akolekar R, Nicolaides KH.
  Prediction of small for gestational age neonates: screening by
  maternal factors, fetal biometry, and biomarkers at 35-37 weeks'
  gestation. \emph{Am J Obstet Gynecol} 2019; 220: 486.e1-486.e11.
\item
  Papastefanou I, Wright D, Syngelaki A, Lolos M, Anampousi K,
  Nicolaides KH. Competing-risks model for prediction of
  small-for-gestational-age neonates from maternal characteristics and
  serum pregnancy-associated plasma protein-A at 11-13 weeks'
  gestation.\emph{Ultrasound Obstet Gynecol} 2020;56:541-48.
\item
  Man J, Hutchinson JC, Ashworth M, Jeffrey I, Heazell AE, Sebire NJ.
  Organ weights and ratios for postmortem identification of fetal growth
  restriction: utility and confounding factors. \emph{Ultrasound Obstet
  Gynecol} 2016;48:585-90.
\end{enumerate}

\textbf{FIGURE LEGENTS}

\textbf{Figure 1.} Gestational age distribution of antepartum
stillbirths (white histograms) and proportion with birthweight
\textless{}10\textsuperscript{th} percentile (black histograms).

\textbf{Figure 2.} Detection rates and screen positive rates by the
competing risks model for SGA combining maternal risk factors, Z score
of EFW, and UtA-PI MoM for placental dysfunction related stillbirth at
\textless{}32 weeks' gestation (red curve), \textless{}37 weeks (blue
curve), any gestation (green curve) and all antepartum stillbirths
(black curve). The circles demonstrate the respective detection rates
according to the RCOG guideline.

\textbf{Table 1.} Maternal and pregnancy characteristics in pregnancies
that had a stillbirth, stratified according to sub-groups, compared with
pregnancies that had live births.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
\textbf{Maternal characteristics}\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
\textbf{Live births} \textbf{(n=131,037)}\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
\textbf{Stillbirths}\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
\textbf{Stillbirths}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{All} \textbf{(n=477)}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{Placental dysfunction} \textbf{(n=261)}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Age in years, median (IQR)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
31.1 (26.7-34.9)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
31.0 (26.4-35.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
30.7 (26.1-35.7)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Weight in Kg, median (IQR)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
67.2 (59.7-78.1)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
72.6 (63.2-85.0)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
74.6 (62.6-85.6)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Height in cm, median (IQR)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
165 (160-169)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
165 (160-168)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
164 (160-168)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Racial origin\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
White, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
95,575 (72.9)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
270 (56.6)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
131 (50.2)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Black, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
23,397 (17.9)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
170 (35.6)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
107 (41.0)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
South Asian, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
6,045 (4.6)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
18 (3.8)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
13 (5.0)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
East Asian, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2,496 (1.9)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
7 (1.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
5 (1.9)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Mixed, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
3,524 (2.7)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
12 (2.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
5 (1.9)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Method of conception\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Spontaneous, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
126,500 (96.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
457 (95.8)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
150 (96.6)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Assisted conception, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
4,537 (3.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
20 (4.2)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
9 (3.5)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Cigarette smoking, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
12,178 (9.3)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
64 (13.4)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
32 (12.3)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Chronic hypertension, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
1,650 (1.3)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
21 (4.4)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
18 (6.9)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
SLE / APS, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
281 (0.2)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2 (0.4)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2 (0.8)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Diabetes mellitus, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
1,362 (1.0)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
13 (2.7)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
7 (2.7)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Parity\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Nulliparous, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
62,084 (47.4)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
236 (49.5)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
128 (49.0)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Previous stillbirth, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
975 (0.7)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
21 (4.4)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
16 (6.1)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Previous SGA, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
9,573 (7.3)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
57 (12.0)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
37 (14.2)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Previous preeclampsia, n (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
3713 (2.8)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
41 (8.6)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
30 (11.5)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Inter-pregnancy interval in years, median (IQR)\textsuperscript{a}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2.9 (1.8 - 4.8)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
3.6 (2.1-6.6)\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
4.2 (2.4-7.3)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

IQR, interquartile range; SLE, systemic lupus erythematosus; APS,
anti-phospholipid syndrome; SGA, small for gestational
age;\textsuperscript{a} Inter-pregnancy interval reported for parous
women.

\textbf{Table 2.} Prediction of stillbirth by the two models of
screening, expressed as AUROC and detection rate at 10\% false positive
rate, in screening by maternal risk factors and combinations with EFW
and UtA-PI for all stillbirths and the subgroups of antepartum
stillbirths and those that were related to placental dysfunction.\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\textbf{Outcome measure} & \textbf{n} & \textbf{Method of screening} &
\textbf{Competing risk model for SGA} & \textbf{Competing risk model for
SGA} & \textbf{Logistic regression model\textsuperscript{1}} &
\textbf{Logistic regression model\textsuperscript{1}}\tabularnewline
\midrule
\endhead
& & & \textbf{AUROC} & \textbf{DR for FPR 10\%} & \textbf{AUROC} &
\textbf{DR for FPR 10\%}\tabularnewline
All stillbirths & 477 & MF & 0.639 (0.596 - 0.682) & 23.5 (19.7 - 27.3)
& 0.680 (0.646-0.715) & 27.7 (23.0-32.4)\tabularnewline
& & MF + EFW & 0.659 (0.617 - 0.702) & 34.2 (29.9 - 38.5) & 0.682
(0.644-0.721) & 35.7 (30.7-40.7)\tabularnewline
& & MF + UtA-PI & 0.707 (0.667 - 0.748) & 40.7 (36.3 - 45.1) & 0.706
(0.668-0.745) & 42.9 (37.7-48.1)\tabularnewline
& & MF + EFW + UtA-PI & 0.698 (0.657 - 0.739) & 39.4 (35.0 - 43.8) &
0.701 (0.662-0.740) & 41.6 (36.4-46.8)\tabularnewline
Antepartum stillbirths & 441 & MF & 0.643 (0.598 - 0.688) & 23.4 (19.5 -
27.4) & 0.683 (0.647-0.718) & 28.2 (28.5-32.9)\tabularnewline
& & MF + EFW & 0.670 (0.626 - 0.714) & 35.6 (31.1 - 40.1) & 0.691
(0.651-0.730) & 36.8 (31.8-41.8)\tabularnewline
& & MF + UtA-PI & 0.712 (0.670 -- 0.754) & 42.0 (37.4 - 46.6) & 0.713
(0.672-0.753) & 43.6 (38.4-48.8)\tabularnewline
& & MF + EFW + UtA-PI & 0.708 (0.665 - 0.750) & 41.5 (36.9 - 46.1) &
0.708 (0.668-0.749) & 43.6 (38.4-48.8)\tabularnewline
Placental dysfunction all & 261 & MF & 0.689 (0.633 - 0.745) & 28.4
(22.9 - 33.9) & 0.736 (0.692-0.780) & 34.6 (29.6-39.6)\tabularnewline
& & MF + EFW & 0.779 (0.729 - 0.829) & 51.3 (45.2 - 57.4) & 0.810
(0.769-0.852) & 52.3 (47.1-57.5)\tabularnewline
& & MF + UtA-PI & 0.804 (0.756 - 0.852 & 58.2 (52.2 - 64.2) & 0.805
(0.759-0.852) & 60.0 (54.9-65.1)\tabularnewline
& & MF + EFW + UtA-PI & 0.829 (0.783 - 0.875) & 58.6 (52.6 - 64.6) &
0.838 (0.799-0.878) & 62.3 (57.2-67.4)\tabularnewline
Placental dysfunction \textless{}37 weeks & 213 & MF & 0.715 (0.654 -
0.776) & 32.4 (26.1- 38.7) & 0.743 (0.694-0.793) & 35.8
(30.8-40.8)\tabularnewline
& & MF + EFW & 0.817 (0.765 - 0.869) & 58.2 (51.6 - 64.8) & 0.835
(0.790-0.880) & 57.5 (52.3-62.7)\tabularnewline
& & MF + UtA-PI & 0.825 (0.774 - 0.876) & 63.4 (56.9 - 69.9) & 0.815
(0.763-0.866) & 64.2 (59.1-69.2)\tabularnewline
& & MF + EFW + UtA-PI & 0.857 (0.810 - 0.904) & 66.2 (59.9 - 72.6) &
0.856 (0.813-0.900) & 69.8 (65.0-74.6)\tabularnewline
Placental dysfunction \textless{}32 weeks & 161 & MF & 0.722 (0.653 -
0.791) & 33.5 (26.2 - 40.8) & 0.759 (0.705-0.812) & 37.8
(32.7-42.9)\tabularnewline
& & MF + EFW & 0.859 (0.805 - 0.913) & 64.6 (57.2 - 72.0) & 0.808
(0.747-0.870) & 62.5 (57.4-67.6)\tabularnewline
& & MF + UtA-PI & 0.819 (0.760 - 0.879) & 68.3 (61.1 - 75.5) & 0.879
(0.834-0.924) & 67.5 (62.6-72.4)\tabularnewline
& & MF + EFW + UtA-PI & 0.871 (0.819 - 0.923) & 70.8 (63.8 - 77.8) &
0.864 (0.813-0.916) & 72.5 (67.8-77.2)\tabularnewline
\bottomrule
\end{longtable}

MF = maternal risk factors, EFW = estimated fetal weight, UtA-PI =
uterine artery pulsatility index

\textbf{Table 3.} Comparisons of detection rates of stillbirths between
the competing risks model for SGA and the RCOG guideline.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\textbf{Outcome measure}\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\textbf{Stillbirths}\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\textbf{SPR\%}\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\textbf{Comparison of detection} \textbf{rates n (\%) vs. n (\%)}\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\textbf{p-value}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
All stillbirths\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
477\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
21.8\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
171 (35.9) vs. 240 (50.3)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textless{}0.0001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Antepartum stillbirths\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
441\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
21.8\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
157 (35.6) vs. 230 (52.2)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textless{}0.0001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Placental dysfunction all\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
Any gestation\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
261\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
21.8\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
104 (39.9) vs. 185 (70.9)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textless{}0.0001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textless{}37 weeks\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
213\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
21.8\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
93 (43.7) vs. 162 (76.1)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textless{}0.0001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textless{}32 weeks\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
161\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
21.8\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
68 (42.2) vs. 127 (78.9)\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\textless{}0.0001\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

RCOG, Royal College of Obstetricians and Gynaecologists; SGA, small for
gestational age; SPR, screen positive rate

Competing risks model uses maternal and pregnancy characteristics and
medical history, sonographic estimated fetal weight uterine artery
pulsatility index.

The SPR was the one that was derived from the RCOG guideline.

McNemar's test was used to compare detection rates of the competing
risks model and that of the RCOG guideline.\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\textbf{Outcome measure} & \textbf{n} & \textbf{Method of screening} &
\textbf{Detection rate at false positive rates of:} & \textbf{Detection
rate at false positive rates of:} & \textbf{Detection rate at false
positive rates of:} & \textbf{Detection rate at false positive rates
of:}\tabularnewline
\midrule
\endhead
& & & \textbf{1\%} & \textbf{3\%} & \textbf{5\%} &
\textbf{10\%}\tabularnewline
All stillbirths & 477 & MF & 5.9 (3.8 - 8.0) & 12.4 (9.4 - 15.4) & 16.4
(13.1 - 19.7) & 23.5 (19.7 - 27.3)\tabularnewline
& & MF + EFW & 18.5 (15.0 - 22.0) & 22.9 (19.1 - 26.7) & 26.2 (22.3 -
30.2) & 34.2 (29.9 - 38.5)\tabularnewline
& & MF + UtA-PI & 13.2 (10.2 - 16.2) & 26.6 (22.6 - 30.6) & 33.3 (29.1 -
37.5) & 40.7 (36.3 - 45.1)\tabularnewline
& & MF + EFW + UtA-PI & 23.7 (19.9 - 27.5) & 30.4 (26.3 - 34.5) & 32.5
(28.3 - 36.7) & 39.4 (35.0 - 43.8)\tabularnewline
Antepartum stillbirths & 441 & MF & 6.4 (4.1 - 8.7) & 12.9 (9.8 - 16.0)
& 16.6 (13.1 - 20.1) & 23.4 (19.5 - 27.4)\tabularnewline
& & MF + EFW & 19.7 (16.0 - 23.4) & 24.0 (20.0 - 28.0) & 27.7 (23.5 -
31.9) & 35.6 (31.1 - 40.1)\tabularnewline
& & MF + UtA-PI & 13.8 (10.6 - 17.0) & 27.7 (23.5 - 31.9) & 34.9 (30.5 -
39.4) & 42.0 (37.4 - 46.6)\tabularnewline
& & MF + EFW + UtA-PI & 24.9 (20.9 - 28.9) & 32.0 (27.7 - 36.4) & 34.2
(29.8 - 38.6) & 41.5 (36.9 - 46.1)\tabularnewline
Placental dysfunction all & 261 & MF & 8.8 (5.4 - 12.2) & 16.9 (12.4 -
21.5) & 21.1 (16.2 - 26.1) & 28.4 (22.9 - 33.9)\tabularnewline
& & MF + EFW & 32.2 (26.5 - 37.9) & 37.6 (31.7 - 43.5) & 41.8 (35.8 -
47.8) & 51.3 (45.2 - 57.4)\tabularnewline
& & MF + UtA-PI & 21.1 (16.2 - 26.1) & 40.6 (34.6 - 46.6) & 50.6 (44.5 -
56.7) & 58.2 (52.2 - 64.2)\tabularnewline
& & MF + EFW + UtA-PI & 40.6 (34.6 - 46.6) & 48.7 (42.6 - 54.8) & 51.3
(45.2 - 57.4) & 58.6 (52.6 - 64.6)\tabularnewline
Placental dysfunction \textless{}37 weeks & 213 & MF & 10.3 (6.2 - 14.4)
& 19.7 (14.5 - 25.0) & 24.4 (18.6 - 30.2) & 32.4 (26.1-
38.7)\tabularnewline
& & MF + EFW & 38.5 (32.0 - 45.0) & 44.6 (37.9 -- 51.3) & 48.8 (42.1 -
55.5) & 58.2 (51.6 - 64.8)\tabularnewline
& & MF + UtA-PI & 24.9 (19.1 - 30.7) & 47.9 (41.2 - 54.6) & 57.3 (50.7 -
63.9) & 63.4 (56.9 - 69.9)\tabularnewline
& & MF + EFW + UtA-PI & 48.8 (42.1 - 55.5) & 57.3 (50.7 - 63.9) & 60.1
(53.5 - 66.7) & 66.2 (59.9 - 72.6)\tabularnewline
Placental dysfunction \textless{}32 weeks & 161 & MF & 11.8 (6.8 - 16.8)
& 21.1 (14.8 - 27.4) & 25.5 (18.8 - 32.2) & 33.5 (26.2 -
40.8)\tabularnewline
& & MF + EFW & 47.8 (40.1 - 55.5) & 54.7 (47.0 - 62.4) & 58.4 (50.8 -
66.0) & 68.3 (61.1 - 75.5)\tabularnewline
& & MF + UtA-PI & 29.2 (22.2 - 36.2) & 50.3 (42.6 - 58.0) & 59.0 (51.4
-- 66.5) & 64.6 (57.2 - 72.0)\tabularnewline
& & MF + EFW + UtA-PI & 58.4 (50.8 - 66.0) & 65.8 (58.5 - 73.1) & 67.7
(60.5 - 74.9) & 70.8 (63.8 - 77.8)\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table S1.} Prediction of stillbirth by the competing risks model
for SGA utilizing maternal risk factors and combinations with EFW and
UtA-PI for all stillbirths and the subgroups of antepartum stillbirths
and those that were related to placental dysfunction.

\textbf{Table S2.} Variables used in the RCOG guideline and the
competing risks model for prediction of SGA neonates.\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
\textbf{RCOG guideline} & \textbf{Competing risks model}\tabularnewline
\midrule
\endhead
Not included & Race\tabularnewline
\textbf{Minor risk factors (\emph{\textgreater{}}3)} &\tabularnewline
Maternal age [?]35 years & Examined but not included in the final
model\tabularnewline
Conception by IVF & Included\tabularnewline
Nulliparous & Parity included as a protective factor\tabularnewline
Body mass index \textless{}20 kg/m\textsuperscript{2} & Weight and
height included as continuous variables\tabularnewline
Body mass index 25-34.9 kg/m\textsuperscript{2} &\tabularnewline
Smoker 1-10 cigarettes per day & Smoking status included\tabularnewline
Low fruit intake pre-pregnancy & Not available\tabularnewline
Previous preeclampsia & Included\tabularnewline
Pregnancy interval \textless{}6 months & Included as continuous
variable\tabularnewline
Pregnancy interval [?]60 months &\tabularnewline
\textbf{Major risk factors (\emph{\textgreater{}}1)} &\tabularnewline
Maternal age \textgreater{}40 years & Examined but not included in the
final model\tabularnewline
Smoker [?] 11 cigarettes per day & Smoking status included\tabularnewline
Body mass index [?]35 kg/m\textsuperscript{2} & Weight and height included
as continuous variables\tabularnewline
Paternal SGA & Not available\tabularnewline
Maternal SGA & Not available\tabularnewline
Previous SGA baby & Included as continuous variable\tabularnewline
Serum PAPP-A \textless{}0.4 MoM & Not available\tabularnewline
Cocaine use & Not available\tabularnewline
Daily vigorous exercise & Not available\tabularnewline
Previous stillbirth & Included\tabularnewline
Chronic hypertension & Included\tabularnewline
Diabetes with vascular disease & Any type of diabetes\tabularnewline
Renal impairment & Not included in the model\tabularnewline
Antiphospholipid syndrome & Included as SLE and/or antiphospholipid
syndrome\tabularnewline
Heavy bleeding & Not available\tabularnewline
\textbf{Biophysical markers} &\tabularnewline
UtA-PI \textgreater{}95\textsuperscript{th} percentile & UtA-PI included
as continuous likelihood\tabularnewline
Not included & EFW included as continuous likelihood\tabularnewline
Not included & MAP included as continuous likelihood\tabularnewline
\bottomrule
\end{longtable}

PAPP-A, Pregnancy associated plasma protein-a; UtA-PI, Uterine artery
pulsatility index at 20 -- 24 weeks; EFW, Estimated fetal weight at 20
-- 24 weeks; MAP, Mean arterial pressure at 20 - 24 weeks.

\textbf{Hosted file}

\verb`Stillbirth three models.pptx`  available at \url{https://authorea.com/users/332817/articles/543238-predictive-performance-for-placental-dysfunction-related-stillbirth-of-the-competing-risks-model-for-small-for-gestational-age-fetuses}

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

