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.