Methods
This study is a retrospective analysis of data collected from electronic
medical records of Saint Sophia Hospital in Warsaw. The study center is
a mono specialist municipal tertiary referral hospital. During the
study, data of all patients hospitalized from 2010-2016 were extracted
from hospital delivery admission electronic medical records and
discharge summaries. International Classification of Diseases, ninth
revision (ICD-9) codes were also abstracted. For each woman included in
the study, data from electronic medical records were available,
including demographic data, risk factors of adverse pregnancy and
delivery outcome diagnosed before and during the current pregnancy, data
on the course of the current labour and delivery, including the
occurrence of perinatal complications. Among 32332 women in singleton
pregnancies who gave birth in St Sophia’s Hospital in 2010-2016, 7269
met the exclusion criteria. These were: in vitro fertilization,
diagnosis of hypertension or diabetes before pregnancy, and diseases
complicating the current pregnancy such as hypertension diagnosed,
gestational diabetes, HELLP syndrome, cholestasis, eclampsia or
preeclampsia, previous cesarean section, prenatal genetic defect of the
fetus. The final sample for the analyses was 25063 women in low-risk
pregnancy, in which the frequency of the primary composite endpoint was
assessed.
The primary composite endpoint of the study was defined as the
occurrence of any of the complications of pregnancy or delivery:
macrosomia, intrauterine fetal growth restriction, polyhydramnios,
oligohydramnios, intrauterine fetal death, fetal distress, labour
dystocia, oxytocin augmentation, obstetric haemorrhage, third or
fourth-degree perineal lacerations, placental abruption, placenta
previa, unplanned cesarean section, premature delivery, instrumental
delivery.
The univariate statistical analysis of the results was carried out using
the Statistica 12 program. The distribution of qualitative variables is
presented by the absolute number of the subjects and the percentage
share in the studied population or group. Quantitative variables are
presented as mean values, standard deviation (SD) and median and the
smallest and largest values. The Chi-square Pearson test was used to
compare groups for qualitative variables (with the Yates continuity
correction if the number of subgroups required it). For discrete
variables, the Mann-Whitney U test was used (a non-parametric test for
the transparency of the analysis was consistently applied). Each time, a
p-value of <0.05 was considered a statistically significant
result of comparisons between defined groups.
Multivariate statistical analysis was performed using the Medcalc 14
program to determine the influence of age on the occurrence of study
endpoints. In multivariate analysis, logistic regression models were
built using the ascending method - the following inclusion parameters
were used for the model: for inclusion of the variable p
<0.05, for switching off the variable p> 0.1. The
significance of the models was determined by the value of p
<0.05 for the model.