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
χ2-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 described15. The values of EFW were
expressed as Z-scores using The Fetal Medicine Foundation population
charts2. We used Bayes’ theorem to combine theprior 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 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 1. The
predictive performance for stillbirth of the competing risks model for
SGA7 and the stillbirth-specific logistic regression
model for placental dysfunction 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.16