Perinatal and neonatal outcomes of pregestational diabetes mellitus: a retrospective study

Background The aim of the study was to evaluate maternal-foetal and clinical outcomes in a group of patients with pregestational diabetes mellitus (PGDM) such as mellitus and of Methods


Background
The prevalence of diabetes mellitus in pregnancy is increasing worldwide in parallel with that of obesity.
The Italian region Sardinia has an incidence rate of DM1 equal to 33.4 per 100,000, which is the second highest globally [2]. Pre-gestational diabetes is associated with adverse neonatal outcomes [3].
The incidence of adverse maternal outcomes is high in case of PGDM [4][5][6][7][8]: abortions and low birth weight (< 2,500 grams) were more common, as well as congenital anomalies. Notably, the types and patterns of congenital malformations associated with maternal PGDM are non-random [9], with an increased risk of heart, central nervous system, and skeleton malformations.
The aim of the present study was to evaluate maternal-fetal and neonatal clinical outcomes of a cohort of patients with PGDM (DM1, DM2, and maturity onset diabetes of the young -MODY-) in comparison with those of pregnant individuals without diabetes.

Methods
A retrospective longitudinal study was carried out: patients aged 18 and 44 years were enrolled between January 2016 and August 2020. They were followed-up in a tertiary care Italian hospital.
A formal ethical approval was not needed according to the Italian law on observational studies.
Selected patients were divided into two groups: PGDM and control (negative pathological history of DM and with a negative oral glucose test tolerance -OGTT-performed at 24-28 weeks of gestation) [10][11].
The two groups were homogeneous by age (calculated at the time of delivery), with a ratio of 1: 2.
The criteria for the diagnosis of diabetes included a fasting plasma glucose (FPG) levels ≥ 126 mg/dl (7.0 mmol/l) and 2-h plasma glucose (PG) level ≥ 200 mg/dl (11.1 mmol/l) during an OGTT.
Characteristics of pregnancy and delivery were collected at the hospital admission and at delivery; Neonatal data were retrieved from the admission registries and from the medical records of newborns admitted to the neonatal intensive care unit (NICU). The following data were collected: age, parity, height, pregravidic weight, weight at delivery, last menstruation, comorbidity (cardiovascular diseases, thyroid diseases, multiple sclerosis, and other autoimmune diseases), prenatal screening surveys (e.g., combined test, noninvasive prenatal test, villocentesis, amniocentesis, and fetal echocardiography).
The variables collected for each group of women were summarized in the following categories: pregnancy outcomes, diseases of pregnancy and fetal pathologies, and neonatal outcomes. The following pregnancy outcomes were collected: gestational age at childbirth (GA); hospital stay; mode of delivery (spontaneous vaginal delivery or caesarean section). Diseases of pregnancy and foetal pathologies: Threatened abortion; Threatened preterm birth; Gestational hypertension; Preeclampsia and HELLP syndrome; Placental abruption; Pathology of amniotic uid (oligohydramnios and polydramnios); Premature rupture of membranes (PROM) and preterm rupture of membranes (P-PROM); Macrosomia; Intrauterine growth retardation (IUGR) foetus; Morphological abnormalities diagnosed on ultrasound. Neonatal outcomes: Weight at birth compared to those expected for the gestational age (in percentiles), and then classi cation within one of the classes of Appropriate for Gestational Age (AGA), Small for Gestational Age (SGA), or Large for Gestational Age (LGA). For this study we used the de nition of the Royal College of Obstetricians and Gynaecologists (RCOG) [12] which informs UK clinical practice, based on sonographic estimated fetal weight (EFW) measurement < 10th percentile to describe a fetus that has not reached its target weight. Patients were divided in three groups for comparison; fetuses with EFW below the 10th percentile for gestational age (SGA), fetuses with EFW > 10th percentile for gestation (AGA) and fetuses > 90th percentile for gestation (LGA) according to the Alexander growth standard [13]; Apgar at the rst minute; Number of hospitalization days and at which intensity of care (nursery, neonatology or NICU); Recognition of respiratory diseases at birth such as Respiratory Distress Syndrome (RDS), transient tachycardia of the newborn (TTN) or apnea crisis, and if there has been any intubation; Blood glucose at the third hour; Hypoglycemia status and glucose supplementation; Neonatal jaundice, treated or not with phototherapy; Morphological abnormalities found at birth.
An ad hoc electronic database was created to collect all study variables. Qualitative data are summarized with absolute and relative (percentage) frequencies. Medians and interquartile ranges were used for quantitative variables with a non-parametric distribution. Chi-squared or Fisher exact test was used to compare qualitative variables for individuals with and without diabetes, whereas Mann-Whitney test to compare non-normal quantitative variables. Logistic regression analysis was performed to assess the relationship between pregnancy and fetal characteristics and diabetes. A two-tailed p-value < 0.05 was considered statistically signi cant. Statistical software STATA version 16 (StataCorp, Texas, USA) was adopted for all statistical analyses.  (Table 1).
Similarly 77.6% of patients in the PGDM group had a good glycemic compensation at the time of delivery.

Pregnancy disorders
No statistically signi cant difference were found for the following outcomes: threat of miscarriage, abnormal placental insertion and detachment, amniotic uid disorders.
However, an association between the threat of abortion and DM2 was found.
The frequency of threatened preterm birth in the PGDM group (24.1%) was higher than that in the control group (9.5%; p-value: 0.009). This difference was more striking when the incidence of preterm delivery was evaluated in DM1 patients (26.2%, p-value: 0.02).
Pregnancy-induced hypertension and preeclampsia were reported only in the PGDM group.
Amniotic uid disorders were only detected in patients with DM1 (12.1%).

Foetal disorders
Foetal growth disorders were more prevalent in the PGDM group (19%; p-value <0.0001). Foetal macrosomia (foetal growth ≥95° percentile) was found in foetuses of diabetic mothers (p-value < 0.0001), the majority of whom in the DM1 group. An intrauterine growth restriction (foetal growth < 5°p ercentile) was found more frequently in in the DM2 group (21.4%; p-value: 0.02).
Foetal echocardiography was used to investigate cardiac abnormalities more frequently in the PGDM Frequency of preterm deliveries was higher in the PGDM group (55.2% VS. 6.0%; p-value <0.0001).

Neonatal outcomes
The median length of hospital stay was 3 days for the births of the control group VS. 11 days for those of the DM1 group (p-value <0.0001) and 6 for those of the DM 2 group (p-value: 0.0001) ( There was a statistically signi cant difference in birth weight. Morphological anomalies were detected in 12.1% and 32.8% in the control and PGDM group (p-value: 0.001), respectively.

Discussion
Diabetic patients had a pregravidic body weight higher than that of the patients in the control group and the median pregravidic BMI differed by 1.7 points between cases and controls. In agreement with other studies [3][4][5][6][7][8], the increase in pre-pregnancy BMI corresponded to a lower weight gain during pregnancy, probably linked to a greater dietary and behavioral control [14]. However, BMI at delivery was signi cantly higher in diabetic patients; dietary behavioral control was apparently not su cient to reverse the differences with the control group. No statistically signi cant differences were found for: threat of miscarriage, abnormal placental insertion and detachment, amniotic uid disorders. Higher frequency of threatened preterm births was reported in the PGDM group, con rming the ndings of Kong L. et al. [15]. This difference was more evident when preterm delivery was considered in patients with PGDM, explained by spontaneous onset, induction occurred to early schedule childbirth, prevention of maternal and/or fetal complications, reduction of perinatal mortality. The most important causes of preterm childbirth in DM1 could be the uterine overdistension due to fetal macrosomia and/or polyhydramnios. Dollberg et al [16] did not associate the high incidence of preterm childbirth with polyhydramnios, but recognized the role played by genitourinary infections and a history of previous preterm deliveries.
Regarding fetal outcomes, fetal macrosomia was found in the group of cases (12.1%).
No statistically signi cant differences were found between cases and controls in the use of medical induction of labor with prostaglandins or oxytocin. This is consistent with the fact that diabetic patients are often subjected to elective CS.
LGA infants were more frequently described in DM1 patients [18,19]. Another large population-based study in Catalonia [20] found a more prevalent LGA in infants of DM1 mothers. However, no relationship was found with the number of macrosomic fetuses, in line with the literature [21]: the error in the estimation of the fetal weight (10%-15%) increases as the gestational age advances, as the fetal weight increases [21].
Morphological abnormalities at birth with diabetes have been documented; in particular congenital heart disease is the outcome most associated with diabetes mellitus [23].
The epidemiology of respiratory disorders at birth seems to partially differ from that of the scienti c literature [24][25][26]. TTN rate was 3.4% in our cohort VS. 10% of other studies. The relationship between RDS and PGDM was con rmed in a recent meta-analysis by Yan Li et al. [27]. The incidence of neonatal hypoglycemia was higher in neonates of DM1 mothers (66.7%) [27,28,29]. The percentage of neonatal jaundice in children of diabetic mothers ranged from 8.7-29% [26, 27,29]. Our study showed a higher incidence (74.1%), even if those requiring phototherapy were less frequent (44.8%).

Strengths And Limitations
Although the retrospective nature of the study and the selection associated to the enrollment in a reference center may hinder the statistical inference of the ndings, the present study shows the epidemiological perspective of an Italian region characterized by a highest incidence of diabetes mellitus in the general population. For this reason, it is of paramount importance to early detect patients at risk to immediately implement preventive measures.

Conclusion
Patients with PGDM are at increased risk of perinatal and neonatal complications in comparison with pregnant women without PGDM.