Early gestational diabetes mellitus and type 2 diabetes: do they differ in perinatal outcome– a retrospective analysis

Abstract

Background

The rise in type 2 diabetes (T2D) during pregnancy is mainly due to increasing obesity and metabolic disorders. Early gestational diabetes mellitus (eGDM), diagnosed before 20 weeks, is also becoming more common and often may explain underlying metabolic problems. This study compares perinatal and neonatal outcomes in patients with T2D and eGDM.

Methods

This retrospective study included 141 pregnant women (70 with T2D and 71 with eGDM) and their singleton term neonates born between 2020 and 2025. The women attended at least one follow-up visit per trimester. eGDM was diagnosed before 20 weeks of gestation based on an oral 75 g glucose tolerance test according to Polish recommendations. Each patient had their HbA1c levels measured at the time of diagnosis and then in each trimester of pregnancy. As a comparator, we used our university hospital growth charts and calculated neonatal growth data from healthy women who delivered at the same hospital between 2017 and 2022. Statistical analysis was performed using PQStat, with p-values < 0.05 considered statistically significant.

Results

Pre-pregnancy obesity was more common in the eGDM group (94.4% vs. 77.1%,p < 0.05). Women with T2D gained more weight (p < 0.005) and had higher HbA1c levels throughout pregnancy (p < 0.005) than those with eGDM. Insulin was required more often in women with T2D (98.6% vs. 63.4%, p < 0.05) and started earlier in T2D (9 vs. 15 weeks, p < 0.005). Preterm birth rates were similar in the T2D and eGDM groups 12.7% vs. 15.7%), as were cesarean section rates (62.9% vs. 60.6%), LGA (15.7% vs. 26.8% according to local growth charts) and SGA (20% vs. 26.8% according to local growth charts). Neonatal jaundice was less frequent in the T2D group (21.4% vs. 36.8%, p < 0.05). Congenital defects occurred at a similar frequency in both groups (T2D: 5.6% vs. eGDM: 8.6%).

Conclusions

The study groups differed significantly in weight gain during pregnancy, the need for and onset of insulin administration, and the incidence of jaundice in newborns. Prepregnancy obesity in the eGDM group may be the main factor predisposing to the trend to a higher percentage of LGA babies in this group. The frequency of congenital malformations in both groups reinforces the need for pre-conception counselling for their prevention.

Background

The global prevalence of diabetes in pregnancy is rising, largely driven by increasing rates of obesity and metabolic syndrome among women of reproductive age [1, 2]. This trend has significant clinical implications, as hyperglycemia during pregnancy is associated with a range of adverse maternal, perinatal, and neonatal outcomes [3, 4]. While pregestational type 2 diabetes (T2D) and gestational diabetes mellitus (GDM) traditionally are considered distinct entities, early diagnosis of GDM, particularly before 20 weeks of gestation, has blurred this distinction. Early-diagnosed gestational diabetes mellitus (eGDM) may represent an intermediate metabolic state or, in some cases, previously undiagnosed prediabetes and T2D [5, 6].

According to current guidelines, T2D in pregnancy is diagnosed either before conception or early in the first trimester, commonly based on haemoglobin A1c (HbA1c) levels ≥ 6.5% (48 mmol/mol) [3, 7]. In contrast, eGDM is identified through abnormal oral glucose tolerance testing (OGTT) based on IADPSG criteria [8], performed before 20 weeks of gestation, particularly in patients with typical risk factors [9]. Although these diagnostic thresholds aim to differentiate chronic hyperglycemia from gestational-onset hyperglycemia, there is substantial clinical and pathophysiological overlap between these two groups [10].

Both T2D and eGDM are associated with increased risks of hypertensive disorders, cesarean delivery, fetal overgrowth, neonatal hypoglycemia, and admission to neonatal intensive care units (NICUs) [5, 8, 11]. However, the degree to which these risks differ between T2D and eGDM pregnancies remains unclear. Understanding these distinctions is essential for optimising screening strategies, risk stratification, and perinatal care [12].

Aim of the study

This study aims to compare perinatal and neonatal outcomes in pregnant women with pregestational T2D to those diagnosed with eGDM. Additionally, we will compare the frequency of macrosomic and large-for-gestational-age (LGA) neonates in both groups. This analysis will further inform clinical decision-making and help refine the classification and management of hyperglycemia in early pregnancy.

Methods

This retrospective study was conducted in the Department of Reproduction at the University Hospital of Obstetrics and Gynaecology in Poznan, Poland. Medical records from January 2020 to May 2025 were analysed. All women meeting the inclusion criteria during the study period were included consecutively. Cases with incomplete maternal or neonatal data were excluded from the final analysis.

A total of 141 pregnant women with singleton pregnancies were included; seventy pregnant women had T2D, and seventy-one were diagnosed with eGDM, defined as gestational diabetes diagnosed ≤ 20 weeks of pregnancy. According to Polish recommendations, an OGTT shall be performed without delay if a pregnant woman in the first trimester has a fasting blood glucose level above 92 mg/dL (5.1 mmol/L) and presents with at least one risk factor for GDM (pre-pregnancy BMI ≥ 30 kg/m², history of GDM in a previous pregnancy, positive family history of T2D, or having previously delivered a baby weighing over 4500 g) [13]. All participants with T2D and those in the eGDM group had at least one prenatal visit in each trimester.

Women with T2D were either diagnosed before pregnancy or identified in the first trimester based on an HbA1c > 6.5% (48 mmol/mol) [14]. Fifty-three patients with T2D were treated with metformin prior to pregnancy. Patients with eGDM did not receive pharmacological treatment before pregnancy. In patients requiring treatment, metformin was discontinued, and insulin therapy was initiated at the beginning of pregnancy.

In nine T2D cases, the diagnosis was made during the first trimester (mean HbA1c: 8.2 ± 1.4% [66 ± 15 mmol/mol]). Women with eGDM were diagnosed by a 75 g OGTT performed < 20 weeks of pregnancy [9].

At the first admission visit, all women received dietary education, including recommended caloric intake, appropriate weight-gain targets for pregnancy, guidelines for carbohydrate exchanges, and instructions on safe physical activity during pregnancy. The patients monitored their blood glucose levels using either a glucometer. The patient education process is described in detail elsewhere [15]. The study group was part of the MOCART Study, registered on clinicaltrials.gov under the number NCT04924738, 14/06/2021, conducted with funding from the Doctoral School grant at the Poznan University of Medical Sciences.

Clinical data were extracted from medical records and included maternal characteristics (age, pre-pregnancy BMI, weight gain during pregnancy and HbA1c levels in each trimester), treatment details (use of metformin before pregnancy and timing of insulin initiation), and neonatal outcomes (birth weight, gestational age at delivery, hyperbilirubinemia, duration of hospital stay, mode of delivery, complications, and congenital anomalies). Triglyceride concentrations were measured in the fasting state and at comparable gestational ages within each trimester.

Newborns were classified as LGA or small for gestational age (SGA) when their birth weight was > 90th percentile or < 10th percentile, based on calculators provided by the Fetal Medicine Foundation (FMF) [16]. Additionally, we used our university hospital’s customised growth charts, developed from 31,353 electronic records of singleton births from healthy women between 2017 and 2022 at a tertiary university hospital in Poznan [17]. Preterm deliveries (< 37 weeks) and high-risk pregnancies were excluded based on well-established factors affecting fetal growth (maternal smoking, hypertension, preeclampsia, diabetes in pregnancy, congenital abnormalities), resulting in a final dataset of 21,379 records. The data were stratified by sex: female (n = 10,312 [48.2%]) and male (n = 11,067 [51.8%]). Sex specific weight percentiles were calculated for each week of gestational age, and approximately 99% of patients in the database were Caucasian [17].

We diagnosed neonatal hypoglycaemia according to the Polish Guidelines [18] when a single neonatal blood glucose concentration was < 40 mg/dl (2.2 mmol/l) in a hospital laboratory at least 3 h after birth, on the first day of life (within 3–24 h after birth). Hyperbilirubinaemia was defined as jaundice requiring phototherapy. Respiratory disorders were defined as the presence of transient tachypnoea of the newborn and/or the need for respiratory support, including supplemental oxygen, non-invasive ventilation, continuous positive airway pressure (CPAP), or endotracheal intubation [18].

After testing for normality of data distribution, groups were compared using the Student’s t-test or the Mann-Whitney U test, as appropriate. The chi-square test was applied to categorical variables. A p-value of less than 0.05 was considered statistically significant. All analyses were performed by PQStat software. Multivariable logistic regression analyses were performed to assess independent associations between maternal clinical and metabolic parameters and adverse perinatal outcomes (including LGA and neonatal hyperbilirubinemia), with adjustment for relevant pre-defined confounders. No formal correction for multiple comparisons was applied, due to the exploratory nature of the analyses.

Results

Table 1 presents the baseline characteristics of the study groups. Maternal age was comparable between women with T2D and those with eGDM. Primiparity was significantly more frequent in the T2D group, whereas pre-pregnancy obesity was more prevalent among women with eGDM. Patients with eGDM have higher weight before pregnancy. Although women with type 2 diabetes had lower absolute body weight in each trimester, they experienced significantly greater gestational weight gain compared with women with early-diagnosed gestational diabetes (Table 1).

Table 1.

Characteristics of eGDM and T2D groups (mean (sd) or median (IQR range), as appropriate)

	T2D (N = 70)	eGDM (N = 71)	p
Age [years]	33.5 (30.0–37.0)	34 (29.0-36.5)	0.69*
Gestation age at the start of care [GW]	10 (7.0–13.0)	10 (7.0–15.0)	0.69*
Primipara [N;%]	52 (74.3)	32 (45.1)	< 0.001^
Multipara [N;%]	18 (25.7)	39 (54.9)	< 0.001^
Pre-pregnancy obesity [N;%]	54 (77.1)	66 (94.4)	0.008
Pre-pregnancy body weight [kg]	94.7 (81-102.8)	107.5 (89.5–122)	< 0.001 *
Body weight in the I trimester [kg]	92.5 (80.6-102.5)	108 (87.4–120.0)	< 0.001 *
Body weight in the II trimester [kg]	93.9 (86.0-110.6)	110 (90.3–122.0)	0.003 *
Body weight in the III trimester [kg]	98 (88.2–116.0)	113 (91.0-122.5)	0.025 *
Weight gain during pregnancy [kg]	8.1 (6.4–9.8)	2.9 (1.6–4.1)	< 0.001 **
BMI before pregnancy [kg/m2]	33.1(30.1–37,0)	37.2 (33.0-43.4)	< 0.001 *
HbA1c I trimester [%, mmol/mol]	6.3 (5.7–7.4) 45.4 (38.8–57.4)	5.3 (4.98–5.6) 34.3 (30.9–37.7)	< 0.001 *
HbA1c II trimester [%, mmol/mol]	5.5 (5.2–5.8) 36.6 (33.3–39.9)	5.1 (4.9–5.4) 32.2 (30.1–35.5)	< 0.001 *
HbA1c III trimester [%, mmol/mol]	5.7 (5.4–6.1) 38.8 (35.5–43.2)	5.4 (5.1–5.8) 35.5 (32.2–39.9)	< 0.001 *
TG I trimester [mg/dl]	122.8 (106.8-153.2)	157.0 (123.9-198.4)	< 0.001 *
TG II trimester [mg/dl]	173.8 (138.6-238.4)	217.4 (170.4-273.4)	< 0.001 *
TG III trimester [mg/dl]	258.5 (222.3-319.2)	298.8 (235.5-390.4)	0.042
Patients required insulin (N; %)	69.0 (98.6)	45.0 (63.4)	< 0.001 ^
Week of pregnancy in which insulin was started [week]	9 (7.0–12.0)	15 (12.0-19.3)	< 0.001 *

*Mann–Whitney test, ^ chi2–test, ^**student’s t-test

Bold values indicate statistically significant results (p < 0.05)

Biochemical measurements found significant differences between the groups across all trimesters. Women with T2D demonstrated consistently higher HbA1c levels throughout pregnancy (Fig. 1). Conversely, serum triglyceride concentrations were significantly higher in the eGDM group across all trimesters (Table 1).

Fig. 1.

Trimester-specific changes in HbA1c levels (left axis: %, right axis: mmol/mol; median, IQR) in both study groups (T2D: red bars; eGDM: blue bars). * p < 0.05

Insulin therapy was more frequently required in the T2D than in the eGDM group (98.6% vs. 63.4%), and insulin administration started significantly earlier in the T2D group than in the eGDM group (9 weeks vs. 15 weeks).

Obstetric outcomes did not differ significantly between groups. Gestational age at delivery, rates of preterm birth, and mode of delivery were comparable (Table 2). Similarly, neonatal outcomes showed no statistically significant differences between the groups (Table 3). However, the incidence of neonatal hyperbilirubinemia requiring treatment was significantly higher in the eGDM group.

Table 2.

Perinatal outcomes in the study groups (mean (SD) or median (IQR range), as appropriate)

	T2D (N = 70)	eGDM (N = 71)	p
Week of delivery [week]	38 (37–38)	38 (37–38)	0.99*
Term births [N; %]	59 (84.3)	62 (87.3)	0.61^
Preterm births [N; %]	11 (15.7)	9 (12.7)	0.61^
Cesarean section [N; %]	44 (62.9)	43 (60.6)	0.92^

*Mann–Whitney test, ^ chi2–test, ^** student’s t-test

Table 3.

Neonatal outcomes in the study groups (number (%) or median (IQR range), as appropriate)

	T2D (N = 70)	eGMD (N = 71)	p
Neonatal birthweight [g]	3217.5 (2963.8–3595)	3354 (3045–3695)	0.31*
LGA [N; %] according to FMF [16]	19 (27.1)	28 (38.1)	0.12^
LGA [N; %] according to Walkowiak [17]	11 (15.7)	19 (26.8)	0.12^
SGA [N; %] according to Walkowiak [17]	14 (20)	19 (26.8)	0.34^
SGA [N;%] according to FMF [16]	9 (12.9)	4 (5.6)	0.14^
Neonates > 4000 g [N; %]	8 (11.4)	4 (5.6)	0.22^
Hyperbilirubinemia [N; %]	15 (21.4)	26 (36.8)	0.047 ^
Hypoglycemia [N; %]	6 (8.6)	8 (11.3)	0.6^
Respiratory disorders [N; %]	14 (20.0)	13 (18.3)	0.8^
Congenital anomalies [N;%]	6 (8.6)	4 (5.6)	0.46^
Duration of hospitalisation of the newborn after birth [days]	4 (3–6)	4 (4–6)	0.77*

*Mann–Whitney test, ^ chi2–test, ^**student’s t-test

Bold values indicate statistically significant results (p < 0.05)

To determine birth weight percentiles, we used the Fetal Medicine Foundation (FMF) calculator and also compared these values with percentiles derived from reference charts validated in our population [16]. Figure 3 provides sex-specific birth weight percentiles. Notable discrepancies were observed between percentiles calculated using the FMF tool and those based on the local reference standard, underscoring the importance of using appropriate normative data from the local population (Figs. 2 and 3).

Fig. 3.

Birth weight distribution (%) grouped by FMF percentiles [16] separated by sex. Percentile categories were defined as < 10th percentile (SGA), 10th–90th percentile (AGA), and > 90th percentile (LGA)

Fig. 2.

Birth weight distribution (%) grouped by percentiles according to [17], separated by sex. Percentile categories were defined as < 10th percentile (SGA), 10th–90th percentile (AGA), and > 90th percentile (LGA)

The median duration of neonatal hospitalisation following delivery was similar in both groups. All newborns who experienced respiratory disorders presented transient respiratory adaptation issues or required non-invasive respiratory support. One newborn from the T2D group and two newborns from the eGDM group required admission to the Neonatal Intensive Care Unit.

In the eGDM group, two neonates were diagnosed with congenital heart defects, one neonate was diagnosed with a cleft lip and one with hydronephrosis. All mothers of infants with congenital anomalies in the eGDM group were obese, including two with morbid obesity despite having recommended first-trimester HbA1c levels. In contrast, among patients with T2D, two had HbA1c levels above the recommended range. (> 6.5%).

In the eGDM group, pre-pregnancy body weight and BMI were independently associated with an increased risk of LGA in multivariable regression after adjustment for relevant confounders. Specifically, higher pre-pregnancy body weight was associated with increased odds of LGA (aOR 1.06, 95% CI 1.01–1.10), and higher pre-pregnancy BMI was also independent predictor of LGA (aOR 1.22, 95% CI 1.06–1.41). No significant associations were observed between glycemic parameters, triglyceride levels, or gestational weight gain and the risk of LGA in this group (Table 4).

Table 4.

Associations between clinical parameters and risk of adverse perinatal outcomes

	Parameter	LGA		Hyperbilirubinemia
		OR (95% CI)	Adjusted OR (95% CI)	OR (95% CI)	Adjusted OR (95% CI)
eGDM	Age	0.98 (0.89–1.09)	-	1.03 (0.93–1.13)	-
	Pregestational body weight	1.03 (1.004–1.06)	1.06 (1.01–1.10)*	1.00 (0.98–1.02)	-
	BMI	1.11 (1.02–1.21)	1.22 (1.06–1.41)*	1.00 (0.93–1.08)	-
	Gestational weight gain	1.06 (0.99–1.13)	-	1.05 (0.99–1.12)	-
	Parity: Primiparous Multiparous	2.74 (0.93–8.13)	-	0.96 (0.37–2.51)	-
	Hypertension	1.23 (0.39–3.89)	-	0.58 (0.19–1.75)	-
	GA at delivery	0.99 (0.74–1.31)	-	0.94 (0.73–1.22)	-
	Birth weight	-	-	1.00 (1.00–1.00)	-
	HbA1c I trimester	1.29 (0.53–3.13)	-	0.90 (0.39–2.08)	-
	HbA1c II trimester	1.77 (0.62–5.03)	-	1.09 (0.41–2.88)	-
	HbA1c III trimester	1.43 (0.66–3.10)	-	0.84 (0.39–1.83)	-
	TG I trimester	1.00 (1.00–1.01)	-	1.00 (0.99–1.01)	-
	TG II trimester	1.00 (1.00–1.00)	-	1.00 (1.00–1.00)	-
	TG III trimester	1.00 (1.00–1.01)	-	1.00 (1.00–1.00)	-
T2D	Age	1.11 (0.95–1.30)	-	1.03 (0.92–1.15)	-
	Pregestational body weight	1.01 (0.98–1.04)	-	0.99 (0.96–1.02)	-
	BMI	1.05 (0.95–1.16)	-	0.97 (0.88–1.06)	-
	Gestational weight gain	1.12 (0.99–1.26)	-	0.98 (0.91–1.06)	-
	Parity: Primiparous Multiparous	0.96 (0.18–5.24)	-	1.62 (0.47–5.59)	-
	Hypertension	1.23 (0.27–5.67)	-	0.67 (0.19–2.39)	-
	GA at delivery	0.96 (0.47–1.94)	-	0.54 (0.32–0.94)	0.40 (0.19–0.81) &
	Birth weight	-	-	1.00 (1.00–1.00)	-
	HbA1c I trimester	1.02 (0.67–1.54)	-	0.90 (0.63–1.30)	-
	HbA1c II trimester	4.76 (1.23–18.45)	4.24 (0.92–19.46)**	1.55 (0.55–4.35)	-
	HbA1c III trimester	3.83 (1.14–12.84)	9.47 (1.20–74.81)**	1.06 (0.40–2.79)	-
	TG I trimester	1.00 (0.99–1.02)	-	1.00 (0.99–1.01)	-
	TG II trimester	1.01 (1.00–1.02)	-	1.00 (0.99–1.01)	-
	TG III trimester	1.00 (0.98–1.01)	-	1.00 (0.99–1.00)	-

*Adjusted for – age, gestational weight gain, parity, hypertension, TG, HbA1c, gestational age

**Adjusted for – age, pregestational body weight, gestational weight gain, parity, hypertension, TG, gestational age

^&Adjusted for – age, pregestational body weight, gestational weight gain, parity, hypertension, TG, HbA1c

Bold values indicate statistically significant results (p < 0.05)

In women with T2D, higher HbA1c levels in the second and third trimesters were independently associated with LGA. Second trimester HbA1c showed a strong association with LGA (aOR 4.24, 95% CI 0.92–19.46), while third-trimester HbA1c was associated with a markedly increased risk of LGA (aOR 9.47, 95% CI 1.20-74.81) after adjustment for confounders. No maternal metabolic parameter was independently associated with neonatal hyperbilirubinemia in the eGDM group. In the T2D group, lower gestational age at delivery was independently associated with an increased risk of neonatal hyperbilirubinemia (aOR 0.40, 95% CI 0.19–0.81) (Table 4).

Discussion

This retrospective, exploratory study analysed perinatal and neonatal outcomes in pregnancies complicated by T2D and eGDM. By comparing similarities and differences, we aimed to focus on early pregnancy and to refine the classification and management of hyperglycemia during this critical period.

Metabolic profiles

Women with T2D gained more weight during pregnancy and required earlier and more frequent insulin therapy, which may reflect more pronounced β-cell dysfunction or insulin resistance than in women with eGDM. As expected, HbA1c levels were consistently higher in T2D, although median values generally remained within recommended targets for pregestational diabetes [19]. In contrast, eGDM was characterised by a predominantly insulin-resistant, lipotoxic phenotype, with lower HbA1c but markedly higher triglyceride concentrations and a higher prevalence of pre-pregnancy obesity, supporting the concept that eGDM represents a metabolically distinct entity rather than simply “early-detected” GDM [19].

Fetal growth and obesity

Despite better glycemic control in the eGDM group across all trimesters, rates of LGA were similar between groups. Pre-pregnancy obesity, which was more prevalent among women with eGDM, may have contributed to this finding. This interpretation is consistent with previous studies demonstrating that maternal adiposity and dyslipidemia independently increase the risk of LGA, independent of glycemic control [5]. Similarly, in the Treatment of Booking Gestational Diabetes Mellitus (TOBOGM) trial - a prospective randomized trial evaluating early treatment of hyperglycemia before 20 weeks of gestation - maternal BMI and lipid metabolism differentiated women with T2D from those with eGDM [20]. These findings may suggest that fetal overgrowth in T2D is linked to chronic hyperglycemia, while overgrowth in eGDM is largely obesity-driven, a relationship that was also confirmed in multivariable analysis.

Pregnancy outcomes

Our data are consistent with the TOBOGM study, which showed that although both conditions share insulin resistance, their predominant pathophysiological mechanisms differ. However, when comparing its findings with those of the present cohort, it should be noted that the TOBOGM study differed from the present study in both design and population characteristics, as it enrolled a broader, multicenter cohort.

T2D women had a more profound β-cell dysfunction and or insulin resistance with higher HbA1c and greater insulin need than eGDM, which was strongly associated with maternal obesity and hypertriglyceridemia [20]. Despite these pathophysiological differences, most obstetric and neonatal outcomes were comparable: no significant differences were found in preterm birth, mode of delivery, neonatal weight, hypoglycemia, or respiratory disorders. While neonatal hyperbilirubinemia was more frequent in the eGDM group, no independent metabolic predictors were identified. In contrast, in T2D, lower gestational age at delivery emerged as an independent risk factor for neonatal hyperbilirubinemia.

Congenital anomalies and obesity

Congenital anomalies were rare and occurred at similar frequencies in both groups. Analysis of the available literature indicates that obesity reduces the sensitivity of prenatal ultrasound, particularly for cardiac and craniofacial anomalies [21–23]. A large study found anomaly detection rates of 19% in obese versus 26% in normal-weight women [24], and prenatal echocardiography was incomplete in 17% of obese versus 6% of normal-weight pregnancies [25]. Moreover, obesity itself is a teratogenic factor, independent of hyperglycemia [21–23, 26]. The presence of anomalies in eGDM pregnancies with normal HbA1c may indicate the multifactorial nature of teratogenesis.

Comparison with previous literature

Our results partially align with earlier findings, which may be accounted for by differences in eGDM definition and time of OGTT between published studies and ours. Importantly, eGDM in our cohort was diagnosed using IADPSG [8] thresholds, performed before 20 weeks of gestation, particularly in patients with typical risk factors, whereas IADPSG/WHO criteria are primarily implemented at 24–28 weeks of pregnancy. This earlier identification and management may partly explain the relatively comparable outcomes observed between T2D and eGDM and should be considered when interpreting our findings in an international context.

We did not find higher congenital anomaly rates in T2D than in eGDM, unlike another study [27], likely due to the small sample size. Stogianni et al. found that women with pregestational diabetes had higher rates of preterm birth, lower Apgar scores, and more LGA infants compared to early GDM [28]. Balsells et al. reported in a systematic review of 33 studies that T2D pregnancies had higher perinatal mortality than T1D [29]. More recently, Clement et al. (2025) confirmed that T2D is associated with increased risks of perinatal mortality, congenital anomalies, stillbirth, neonatal mortality, and LGA compared with GDM and non-diabetic pregnancies [27]. Together, these studies highlight that T2D represents a higher-risk condition than eGDM, even when both metabolic disorders are diagnosed early. Our results, therefore, complement rather than contradict the broader literature by highlighting how early identification and targeted management can narrow outcome gaps between T2D and eGDM, even though their metabolic profiles remain distinct.

Growth standards

An important strength of our study is the use of locally validated birthweight percentiles. Discrepancies with FMF charts were striking: nearly 40% of eGDM neonates were classified as LGA by FMF, likely overestimating overgrowth. This highlights the problems of using non-population-specific standards. These discrepancies have already been demonstrated, with differences between Polish regional data and international references such as INTERGROWTH or Fenton [17, 30]. The observed discrepancies between FMF and locally derived growth charts may have important clinical implications, potentially influencing decisions on antenatal surveillance intensity, delivery timing, or induction of labour. While the local growth charts are validated for the studied population, their relevance beyond this population may be limited, further underscoring the need for population-specific growth standards.

Strengths and limitations

The homogeneity of our cohort, recruited from a single tertiary care centre, is a key strength, ensuring consistency in diagnostics and management. Despite the applied diagnostic criteria, residual misclassification between early T2D and eGDM remains possible and represents an inherent limitation of early pregnancy hyperglycaemia classification.

As this was a single-centre study conducted in Poland with a predominantly Caucasian population, the applicability of our findings to other ethnic or regional groups may be limited, and caution is warranted when extrapolating these results to more diverse populations. Recruiting patients from a tertiary care centre carries the potential for selection bias.

The retrospective design and relatively small sample size of the study (N = 141) limit the statistical power to detect differences in rare outcomes, such as congenital anomalies, neonatal intensive care unit admission, and perinatal mortality.

Future directions

Larger prospective multicentre studies with substantially larger cohorts are needed to confirm these findings. Inclusion of biomarkers beyond glucose and HbA1c may improve early risk stratification. Long-term follow-up of offspring combined with metabolomic/lipidomic analyses hay help determine the impact of maternal and neonatal metabolic profiles on future cardiometabolic health. TOBOGM data suggest limited benefit from treating “booking GDM” before 20 weeks unless overt diabetes is present [20, 31], raising questions about the optimal timing of intervention in eGDM. Finally, national or regional growth charts should be developed to improve the validity of LGA/SGA classification in diverse populations.

Conclusions

This study demonstrates that most perinatal outcomes are comparable in women with T2D and early GDM, despite differences in metabolic characteristics and treatment requirements. The higher incidence of neonatal hyperbilirubinaemia in the eGDM group and the observed discrepancies between growth standards underline the need for population-specific references and vigilant perinatal monitoring. Accurate early diagnosis and appropriate management strategies are crucial to minimising adverse outcomes in pregnancies complicated by hyperglycaemia.

Abbreviations

ADA

American Diabetes Association

BMI

Body Mass Index

eGDM

Early Gestational Diabetes Mellitus

FMF

Fetal Medicine Foundation

GDM

Gestational Diabetes Mellitus

GW

Gestational Week

HbA1c

Glycated Hemoglobin

IADPSG

International Association of Diabetes and Pregnancy Study Groups

Kg/m²

Kilograms per square meter

LGA

Large for Gestational Age

NICU

Neonatal Intensive Care Unit

OGTT

Oral Glucose Tolerance Test

SD

Standard Deviation

SGA

Small for Gestational Age

TG

Triglycerides

T2D

Type 2 Diabetes

WHO

World Health Organization

TOBOGM

Treatment of Booking Gestational Diabetes Mellitus

CPAP

Continuous Positive Airway Pressure

Authors’ contributions

Aleksandra Gladych-Macioszek: study design, data and material collection, writing the manuscript. Urszula Mantaj: data and material collection, writing the manuscript. Kinga Tobola-Wrobel: writing the manuscript. Sandra Radzicka-Mularczyk: writing the manuscript. Rafal Sibiak: statistical analysis, graphs. Lukasz Adamczak: data and material collection. Gernot Desoye: substantive supervision. Ewa Wender-Ozegowska: study design, writing the manuscript, substantive supervision.

Funding

The authors received no specific funding for this work.

Data availability

The datasets generated during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Group of Patients took part in the study that was approved by the local bioethics committee of the Poznan University of Medical Sciences number 525/17 and the procedures have been performed in accordance with the Declaration of Helsinki. Authors confirm that all methods were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.