Gestational Diabetes Mellitus In Early Pregnancy Research Articles

Exploring the influence of microbiota on gestational diabetes and its potential as a biomarker

Gestational diabetes mellitus (GDM) represents a significant health concern during pregnancy, impacting both maternal and fetal well-being. While conventional diagnostic protocols typically rely on blood glucose levels in the latter stages of pregnancy, there is a pressing need for early detection methods to mitigate potential risks. A plethora of glucose-based or non-glucose-based biomarkers have been investigated for their potential to predict GDM in early pregnancy. Though specific biomarkers showed promise in predicting GDM, their clinical usage has been constrained by the lack of validation and limitation in translating them into routine clinical use. This review aims to highlight and discuss the potential and practical utility of existing biomarkers and emergent biomarkers, such as microbiomes, in diagnosing GDM. A comprehensive analysis of recent studies reveals significant alterations in the composition and diversity of microbiota among women with GDM, suggesting their potential utility as predictive markers for this condition. For instance, distinct microbial profiles characterized by an increased abundance of Eisenbergiella, Tyzzerella 4, and Lachnospiraceae NK4A136, alongside decreased levels of Parabacteroides, Parasutterella, and Ruminococcaceae UCG 002, correlated with fasting blood glucose levels, hinting at their relevance in early GDM detection. Furthermore, proposed microbiota-targeted panels demonstrated promising predictive accuracy. Beyond gut microbiota, recent investigations have also explored the potential of oral microbiota as predictive biomarkers for GDM. Studies have highlighted the discriminatory capacity of specific oral microbes, such as Streptococcus in saliva and Leptotrichia in dental plaque, in distinguishing GDM from healthy pregnancies. Moreover, the examination of gut microbiota-derived metabolites has shown promising results in serum-based GDM prediction. These findings collectively underscore the potential of microbiota and its metabolites as valuable biomarkers for the early detection of GDM. However, further research is warranted to elucidate the mechanistic links between microbial dysbiosis and GDM pathogenesis, ultimately facilitating the development of targeted therapeutic interventions and personalized management strategies.

Advances in free fatty acid profiles in gestational diabetes mellitus.

The morbidity of gestational diabetes mellitus (GDM) is increasing and is associated with adverse perinatal outcomes and long-term maternal and infant health. The exact mechanism underlying changes in plasma free fatty acid (FFA) profiles in patients with GDM is unknown. However, it is believed that changes in diet and lipid metabolism may play a role. Fatty acids contain many specific FFAs, and the type of FFA has different impacts on physiological processes; hence, determining changes in FFAs in individual plasma is essential. Alterations in FFA concentration or profile may facilitate insulin resistance. Additionally, some FFAs show potential to predict GDM in early pregnancy and are strongly associated with the growth and development of the fetus and occurrence of macrosomia. Here, we aimed to review changes in FFAs in women with GDM and discuss the relationship of FFAs with GDM incidence and adverse outcomes.

Assisted reproductive technology and physical activity among Chinese pregnant women at high risk for gestational diabetes mellitus in early pregnancy: A cross-sectional study.

Currently, the number of pregnant women at high risk for gestational diabetes mellitus (GDM) and using assisted reproductive technology (ART) is increasing. The present study aims to explore the relationship between ART and physical activity in Chinese pregnant women at high risk for GDM in early pregnancy. A cross-sectional study was conducted in a regional teaching hospital in Guangzhou, China, between July 2022 and March 2023. Three hundred fifty-five pregnant women at high risk for GDM in early pregnancy completed the Chinese version of the Pregnant Physical Activity Questionnaire (PPAQ), the Pregnancy Physical Activity Knowledge Scale, the Pregnancy Physical Activity Self-Efficacy Scale, the Pregnancy Physical Activity Social Support Scale, and a sociodemographic and obstetric characteristics data sheet. Compared to women who conceived naturally, women who used ART were more likely to be 35 years or older, unemployed, primigravidae, and to have intentionally planned their pregnancies. Women who used ART had significantly lower levels of physical activity and self-efficacy compared to their counterparts who conceived naturally. Over half (55.6%) of women who used ART reported being physically inactive, and those with lower self-efficacy, as well as the unemployed, were significantly more likely to be inactive. Physical inactivity is a critical clinical issue among women who use ART, especially in the context of GDM risk. Future research should develop and test physical activity programs, including enhancing physical activity self-efficacy for women who use ART. Patient or public contribution: In this study, survey questionnaires were completed by participants among Chinese pregnant women at high risk for GDM in early pregnancy.

A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Pregnant Chinese Women.

This study aimed to develop a simplified screening model to identify pregnant Chinese women at risk of gestational diabetes mellitus (GDM) in the first trimester. This prospective study included 1289 pregnant women in their first trimester (6-12weeks of gestation) with clinical parameters and laboratory data. Logistic regression was performed to extract coefficients and select predictors. The performance of the prediction model was assessed in terms of discrimination and calibration. Internal validation was performed through bootstrapping (1000 random samples). The prevalence of GDM in our study cohort was 21.1%. Maternal age, prepregnancy body mass index (BMI), a family history of diabetes, fasting blood glucose levels, the alanine transaminase to aspartate aminotransferase ratio (ALT/AST), and the triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) were selected for inclusion in the prediction model. The Hosmer-Lemeshow goodness-of-fit test showed good consistency between prediction and actual observation, and bootstrapping indicated good internal performance. The area under the receiver operating characteristic curve (ROC-AUC) of the multivariate logistic regression model and the simplified clinical screening model was 0.825 (95% confidence interval [CI] 0.797-0.853, P < 0.001) and 0.784 (95% CI 0.750-0.818, P < 0.001), respectively. The performance of our prediction model was superior to that of three other published models. We developed a simplified clinical screening model for predicting the risk of GDM in pregnant Chinese women. The model provides a feasible and convenient protocol to identify women at high risk of GDM in early pregnancy. Further validations are needed to evaluate the performance of the model in other populations. ClinicalTrials.gov identifier: NCT03246295.

Integration of clinical demographics and routine laboratory analysis parameters for early prediction of gestational diabetes mellitus in the Chinese population.

Gestational diabetes mellitus (GDM) is one of the most common complications in pregnancy, impairing both maternal and fetal health in short and long term. As early interventions are considered desirable to prevent GDM, this study aims to develop a simple-to-use nomogram based on multiple common risk factors from electronic medical health records (EMHRs). A total of 924 pregnant women whose EMHRs were available at Peking University International Hospital from January 2022 to October 2022 were included. Clinical demographics and routine laboratory analysis parameters at 8-12 weeks of gestation were collected. A novel nomogram was established based on the outcomes of multivariate logistic regression. The nomogram demonstrated powerful discrimination (the area under the receiver operating characteristic curve = 0.7542), acceptable agreement (Hosmer-Lemeshow test, P = 0.3214) and favorable clinical utility. The C-statistics of 10-Fold cross validation, Leave one out cross validation and Bootstrap were 0.7411, 0.7357 and 0.7318, respectively, indicating the stability of the nomogram. A novel nomogram based on easily-accessible parameters was developed to predict GDM in early pregnancy, which may provide a paradigm for repurposing clinical data and benefit the clinical management of GDM. There is a need for prospective multi-center studies to validate the nomogram before employing the nomogram in real-world clinical practice.

The Role of Abdominal Ultrasound in the Prediction of GDM in Early Pregnancy

Background: To detect gestational diabetes mellitus (GDM) in pregnant women as soon as possible, this study aimed to investigate the role of ultrasound in predicting GDM in early pregnancy by measuring the thickness of abdominal subcutaneous adipose tissue. Methods: This paper is a longitudinal study performed on pregnant women at 11-14 weeks of pregnancy. All the women referred during this period were screened for the thickness of abdominal subcutaneous adipose tissue, which was measured using trans-abdominal ultrasound. The patients were followed up by performing the oral glucose tolerance test (OGTT) between the weeks of 24 and 28. Finally, abdominal subcutaneous adipose tissue thickness and other variables were compared between women with and without GDM. Oral consent was obtained from patients. Results: Overall, 210 pregnant women at 11-14 weeks of gestation were enrolled in the study. The mean of abdominal subcutaneous adipose tissue thickness was measured using linear probe ultrasound as 1.72±0.33 mm. The incidence of GDM was significantly associated with maternal age and weight, parity, family history of diabetes, and histories of preeclampsia, hypertension, and recurrent abortion. There was also a statistically significant relationship between GDM and ultrasound-derived subcutaneous adipose tissue thickness at weeks 11-14 of pregnancy (P&lt;0.0001). At the cut-off point of 2.01, the sensitivity, specificity, and area under the curve (AUC) values were 91%, 92%, and 0.96, respectively. Conclusion: Measuring the thickness of the abdominal subcutaneous adipose tissue during early pregnancy may be useful in predicting GDM in the second trimester of pregnancy. Maternal higher age and weight gain, increased parity, and positive family histories of diabetes, preeclampsia, hypertension, and recurrent abortion may also increase the risk of GDM.

A Prediction Model of Gestational Diabetes Mellitus Based on OGTT in Early Pregnancy: A Prospective Cohort Study.

Gestational diabetes mellitus (GDM) is a common obstetric complication. Although early intervention could prevent the development of GDM, there was no consensus on early identification for women at high risk of GDM. To develop a reliable prediction model of GDM in early pregnancy. In this prospective cohort study, between May 30, 2021, and August 13, 2022, a total of 721 women were included from Women's Hospital, Zhejiang University School of Medicine. Participants were asked to complete an oral glucose tolerance test (OGTT) during gestational weeks 7 through 14 for early prediction of GDM, and at weeks 24 through 28 for GDM diagnosis. Using OGTT results and baseline characteristics, logistic regression analysis was used to construct the prediction model. Receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test, decision clinical analysis, and a nomogram were used for model performances assessment and visualization. Internal and external validation was performed to testify the stability of this model. According to the International Association of Diabetes and Pregnancy Study Groups criteria in early OGTT, the mean (SD) age was 30.5 ± 3.7 years in low-risk participants and 31.0 ± 3.9 years in high-risk participants. The area under ROC curve (AUC) of the existing criteria at weeks 7 through 14 varied from 0.705 to 0.724. Based on maternal age, prepregnancy body mass index, and results of early OGTT, the AUC of our prediction model was 0.8720, which was validated by both internal (AUC 0.8541) and external (AUC 0.8241) confirmation. The existing diagnostic criteria were unsatisfactory for early prediction of GDM. By combining early OGTT, we provided an effective prediction model of GDM in the first trimester.

Reclassification of early gestational diabetes diagnoses to pregestational diabetes mellitus

Differences in perinatal outcomes are well known between patients with gestational diabetes mellitus (GDM) and pregestational diabetes (DM). It has been difficult to determine a new diagnosis of DM during pregnancy to provide adequate counseling. Our aim was to reclassify patients diagnosed with GDM in early pregnancy to DM using American College of Obstetricians and Gynecologists suggested criteria to determine if outcomes in this reclassified group were like those for patients with White’s class B DM.

Epidemiology of birth defects based on a birth defects surveillance system in southwestern China and the associated risk factors.

Birth defects (BDs) are associated with many potential risk factors, and its causes are complex. This study aimed to explore the epidemiological characteristics of BDs in Guangxi of China and the associated risk factors of BDs. BDs data of perinatal infants (PIs) were obtained from the Guangxi birth defects monitoring network between 2016 and 2020. Univariate Poisson regression was used to calculate the prevalence-rate ratios (PRR) to explore the changing trends of BDs prevalence by year and the correlation between the regarding of characteristics of BDs (including infant gender, maternal age, and quarter) and BDs. Clinical characteristics of PIs with BDs and general characteristics of their mothers were documented, and Spearman correlation analysis was used to explore the potential associated risk factors of BDs. Between 2016 and 2020, 44,146 PIs with BDs were monitored, with an overall BDs prevalence of 121.71 (95% CI: 120.58-122.84) per 10,000 PIs, showing a significant increase trend (PRR = 1.116, 95% CI: 1.108-1.123), especially the prevalence of congenital heart defects (CHDs) that most significantly increased (PRR = 1.300, 95% CI: 1.283-1.318). The 10 most common BDs were CHDs, polydactyly, congenital talipes equinovarus, other malformation of external ear, syndactyly, hypospadias, cleft lip with cleft palate, cleft lip, hemoglobin Bart's hydrops fetalis syndrome (BHFS), and congenital atresia of the rectum and anus. BDs were positively correlated with pregnant women's age (R = 0.732, P < 0.01) and education level (R = 0.586, P < 0.05) and having pre-gestational diabetes mellitus (PGDM)/gestational diabetes mellitus (GDM) (R = 0.711, P < 0.01), while when the pregnant women had a family history of a dead fetus (R = -0.536, P < 0.05) and a birth of a fetus with BDs (R = -0.528, P < 0.05) were negatively correlated with BDs. A significant increase in the prevalence of BDs was detected between 2016 and 2020 in Guangxi, especially the prevalence of CHDs that most significantly increased. Older maternal age, higher maternal education level, and having PGDM before pregnancy or GDM in early pregnancy were the risk factors for BDs.

Do pregnancy outcomes of women with false-positive early gestational diabetes mellitus differ from those of women with normal glucose tolerance?

BackgroundTo investigate whether false-positive early gestational diabetes mellitus (GDM) women can be managed similarly as normal glucose tolerance (NGT) women.MethodsThis retrospective study was conducted at a tertiary care center in Japan. Pregnancy and neonatal outcomes of 67 singleton pregnancies with false-positive early GDM and 1774 singleton pregnancies with NGT who delivered after 22 weeks of gestation were compared. GDM was diagnosed according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria (patients having one or more of the following: fasting plasma glucose ≥ 92 mg/dL and a 75 g oral glucose tolerance test (OGTT) value ≥ 180 mg/dL at 1 h, or ≥ 153 mg/dL at 2 h). Pregnant women diagnosed with GDM in early pregnancy who did not meet the diagnostic criteria on the second OGTT were defined as having false-positive early GDM. Women with false-positive early GDM did not receive any therapeutic intervention during gestation.ResultsMaternal age, pre-pregnancy body mass index, and gestational weight gain were significantly higher in the false-positive GDM group than in the NGT group. No significant differences were found in pregnancy outcomes, including gestational age, birth weight, large for gestational age rate, and cesarean delivery rate. Except for a higher neonatal hypoglycemia rate in the false-positive early GDM group, no significant differences were found in neonatal outcomes.ConclusionsThere were no clinically significant differences between early GDM false-positive women exhibiting GDM patterns only during early pregnancy and NGT women. False-positive early GDM women can be managed similarly as NGT women, suggesting that World Health Organization diagnostic guidelines, applying the IADPSG criteria during early pregnancy, need revision.

Clinical Value of Early-Pregnancy Glycated Hemoglobin, Fasting Plasma Glucose, and Body Mass Index in Screening Gestational Diabetes Mellitus.

To investigate clinical values of early-pregnancy (8-13 weeks) glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), and body mass index (BMI) in screening gestational diabetes mellitus (GDM). A total of 1120 cases underwent a 75 g oral glucose tolerance test (OGTT), of which 216 cases with GDM were selected as the study group, and 278 cases without GDM were selected as the control group. FPG, HbA1c, and BMI in early pregnancy were measured. The correlation between FPG, HbA1c and BMI in early pregnancy and the incidence of GDM was analyzed by binary logistic regression, and the value of each index in predicting GDM alone or in combination was evaluated. FPG, HbA1c, and BMI in early pregnancy in the GDM group were higher than those in the control group, and the differences were statistically significant (P < .05). Binary logistic regression analysis showed that FPG, HbA1c, and BMI were risk factors for GDM in early pregnancy (odds ratio [OR] values were 3.374 [P < .05], 4.644 [P < .001], and 1.077 [P < .001], respectively). The area under the receiver operating characteristic (ROC) curve of FPG, glycated hemoglobin, and BMI in screening GDM for early pregnancy were 0.647, 0.661, and 0.608, respectively, while the area under the ROC curve of the combination of these 3 indicators was 0.736. We found that FPG, HbA1c, and BMI in early pregnancy might be the potential risk factors for the occurrence of GDM, and the combination of them had certain clinical predictive value for GDM. However, it is still necessary for more studies, especially prospective studies, to validate our findings in the future.

Use of oral glucose tolerance testing and HbA1c at 6-14 gestational weeks to predict gestational diabetes mellitus in high-risk women.

To study the prediction of gestational diabetes mellitus (GDM) in high-risk pregnant women by testing fasting blood glucose, 1-h(1hPG) and 2-h plasma glucose (2hPG) after an oral glucose tolerance test, and glycated hemoglobin (HbA1c) in early pregnancy (6-14weeks). We recruited 1311 pregnant women at high risk for diabetes from the Obstetrics Clinic of Daxing District People's Hospital between June 2017 and December 2019. The tests performed during the first trimester included fasting blood glucose (FPG), HbA1c, and 75-g oral glucose tolerance test (OGTT) with 1hPG and 2hPG. Seventy-three pregnant women diagnosed with pregestational diabetes mellitus (PGDM) early in pregnancy and 36 who were missed in the second trimester were excluded. A total of 1202 women were followed up until 24-28weeks for GDM. The receiver operating characteristic (ROC) and area under the ROC curve (AUC) were calculated to determine the predictive values of FPG, 1hPG, 2hPG, and HbA1c for GDM in early pregnancy in high-risk pregnant women. The AUC for 1hPG for the prediction of GDM in high-risk pregnant women was greater than those for FPG, 2hPG, and HbA1c. All differences were significant. The AUCs for the predictive values of FPG, 1hPG, 2hPG, and HbA1c in high-risk pregnant women were 0.63, 0.76, 0.71, and 0.67, respectively. The prevalence of PGDM among pregnant women at high risk of diabetes was 5.6%. First-trimester levels of FPG, 1hPG, 2hPG, and HbA1c in high-risk women are significant predictors of GDM, with 1hPG having the most significant predictive value.

1059-P: Metabolic Trajectories from Preconception to Midpregnancy Using a Nontargeted Approach in Mothers with Gestational Diabetes Mellitus

The trajectories of plasma lipids and fatty acids from preconception to antenatal phases are understudied. Within a Singapore preconception and pregnancy cohort of 373 live singletons, we ascertained 35 Chinese pregnant women with gestational diabetes mellitus (GDM) according to IADPSG criteria between 24-28 weeks of gestation, and matched with 35 non-GDM Chinese controls by age and pre-pregnancy body mass index. We collected bloo samples at preconception, early (11-13 weeks) , and mid-pregnancy (18-21 weeks) . We employed OPLS-DA and logistic regression to discriminate women with and without GDM using a non-targeted approach. We applied a generalized linear mixed model in cubic spline with interaction with gestation weeks to look at metabolite trajectories across three timepoints between GDM and non-GDM matches. A total of metabolites exhibited distinctive signals from pregnant women with GDM from women without GDM in early pregnancy, such as LPE 22:6 and DHA: 22:6n3. All trajectories but one (palmitic acid) showed significant increments in preconception and mid-pregnancy phases, whereas a significant reduction in early pregnancy among GDM cases. Our data identified distinctive metabolites changes across preconception and mid-pregnancy phase among GDM subjects, and such novel findings might imply potential predictive values for incident GDM. Disclosure L.Li: None. X.Wang: None. L.Cui: None. C.Zhang: None. Spresto study group: n/a. Funding Singapore-NMRC/TCR/004-NUS/2008; NMRC/TCR/012-NUHS/2014; NMRC TA/0027/2014) .

An early prediction model for gestational diabetes mellitus based on genetic variants and clinical characteristics in China

ObjectivesTo evaluate the influence of genetic variants and clinical characteristics on the risk of gestational diabetes mellitus (GDM) and to construct and verify a prediction model of GDM in early pregnancy.MethodsFour hundred seventy five women with GDM and 487 women without, as a control, were included to construct the prediction model of GDM in early pregnancy. Both groups had complete genotyping results and clinical data. They were randomly divided into a trial cohort (70%) and a test cohort (30%). Then, the model validation cohort, including 985 pregnant women, was used for the external validation of the GDM early pregnancy prediction model.ResultsWe found maternal age, gravidity, parity, BMI and family history of diabetes were significantly associated with GDM (OR > 1; P < 0.001), and assisted reproduction was a critical risk factor for GDM (OR = 1.553, P = 0.055). MTNR1B rs10830963, C2CD4A/B rs1436953 and rs7172432, CMIP rs16955379 were significantly correlated with the incidence of GDM (AOR > 1, P < 0.05). Therefore, these four genetic susceptible single nucleotide polymorphisms (SNPs) and six clinical characteristics were included in the construction of the GDM early pregnancy prediction model. In the trial cohort, a predictive model of GDM in early pregnancy was constructed, in which genetic risk score was independently associated with GDM (AOR = 2.061, P < 0.001) and was the most effective predictor with the exception of family history of diabetes. The ROC-AUC of the prediction model was 0.727 (95% CI 0.690–0.765), and the sensitivity and specificity were 69.9% and 64.0%, respectively. The predictive power was also verified in the test cohort and the validation cohort.ConclusionsBased on the genetic variants and clinical characteristics, this study developed and verified the early pregnancy prediction model of GDM. This model can help screen out the population at high-risk for GDM in early pregnancy, and lifestyle interventions can be performed for them in a timely manner in early pregnancy.

Global burden of early pregnancy gestational diabetes mellitus (eGDM): A systematic review.

Gestational diabetes mellitus (GDM) diagnosed during the first trimester of pregnancy is called 'early pregnancy Gestational Diabetes Mellitus' (eGDM). The burden of eGDM has only been studied sporadically.This review aims to understand the global burden of eGDM in terms of prevalence, risk factors, pregnancy outcomes, treatment and postpartum dysglycemia. METHODS: A review of epidemiologic studies reporting on early GDM screening as per Joanna Briggs Institute (JBI) methodology for prevalence reviews was conducted. A customized search strategy was used to search electronic databases namely, PubMed, CINAHL, EMBASE, Cochrane Library, Scopus, MEDLINE, Ovid, ScienceDirect, and Google Scholar. Three independent reviewers reviewed studies using Covidence software. Observational studies irrespective of study design and regardless of diagnostic criteria were included. Quality of evidence was appraised, and findings were synthesized. Of 58 included studies, 41 reported a prevalence of eGDM, ranging from 0.7 to 36.8%. Body mass index (BMI), previous history of GDM, family history of diabetes and multiparity were reported as eGDM risk factors. Adverse pregnancy outcomes associated with eGDM were macrosomia, caesarean delivery, induction of labour, hypertension, preterm delivery, and shoulder dystocia. The incidence of postpartum dysglycemia and the need for insulin was higher in women with eGDM. The risk of bias was moderate. Heterogeneity of studies is a limitation. Meta-analysis was not performed. There is heterogeneity in the prevalence of eGDM and intrapartum and postpartum ill effects for the mother and the offspring. There is a need to develop a universal screening protocol for eGDM.

First Trimester Glycated Hemoglobin (HBA1C) Level as a Novel Predictor of Gestational Diabetes Mellitus: a Systematic Review and Meta-Analysis

Introduction: Gestational diabetes mellitus (GDM) is a severe yet neglected threat to maternal and child health, due to its association with multiple adverse pregnancy outcomes. glycated hemoglobin (HbA1c) level is one of the most promising predictor of GDM in early pregnancy based on several cohort studies done recently.&#x0D; Purpose of study: This systematic review and meta-analysis aims to evaluate the potency of HbA1c level in first trimester as a novel predictor of GDM.&#x0D; Methods: This review selects cohort studies found by database searching systematically using previously determined inclusion, such as pregnant woman as the subject, assess Hb1Ac level in the first trimester, and assess odds ratio towards (GDM), and exclusion criteria such as assess outcome at postpartum, not assess GDM outcomes, and studies written in languages other than English or Bahasa Indonesia. This review was arranged based on PRISMA guideline.&#x0D; Results and Discussion: This review included seven cohort studies with the pooled OR of 4.36 [95%CI: 3.66-5.20]. Quantitative analysis shows that HbA1c level in the first trimester is a significant risk factor of GDM development (p&lt;0.00001). However, heterogeneity analyses revealed substantial heterogeneity are detected in the pooled studies. Therefore, to understand the significance of HbA1c level and the development of GDM, further studies are needed.&#x0D; Conclusion: This study has proven the potency of first trimester HbA1c level as a novel predictor of gestational diabetes mellitus. Thus, it is necessary to integrate the use of HbA1c level screening as part of antenatal care in the first trimester of pregnancy.

An Update on Screening Strategies for Gestational Diabetes Mellitus: A Narrative Review.

Gestational diabetes mellitus (GDM) is a frequent medical complication during pregnancy. Screening and diagnostic practices for GDM are inconsistent across the world. This narrative review includes data from 87 observational studies and randomized controlled trials (RCTs), and aims to give an overview of the current evidence on screening strategies and diagnostic criteria for GDM. Screening in early pregnancy remains controversial and studies show conflicting results on the benefit of screening and treatment of GDM in early pregnancy. Implementing the one-step “International Association of Diabetes and Pregnancy Study Groups” (IADPSG) screening strategy at 24–28 weeks often leads to a substantial increase in the prevalence of GDM, without conclusive evidence regarding the benefits on pregnancy outcomes compared to a two-step screening strategy with a glucose challenge test (GCT). In addition, RCTs are needed to investigate the impact of treatment of GDM diagnosed with IADPSG criteria on long-term maternal and childhood outcomes. Selective screening using a risk-factor-based approach could be helpful in simplifying the screening algorithm but carries the risk of missing significant proportions of GDM cases. A two-step screening method with a 50g GCT and subsequently a 75g oral glucose tolerance test (OGTT) with IADPSG could be an alternative to reduce the need for an OGTT. However, to have an acceptable sensitivity to screen for GDM with the IADPSG criteria, the threshold of the GCT should be lowered from 7.8 to 7.2 mmol/L. A pragmatic approach to screen for GDM can be implemented during the COVID-19 pandemic, using fasting plasma glucose (FPG), HbA1c or even random plasma glucose (RPG) to reduce the number of OGTTs needed. However, usual guidelines and care should be resumed as soon as the COVID pandemic is controlled.

The role of ultrasonographic adipose tissue thickness measurement in the first trimester in predicting gestational diabetes: a prospective study.

This prospective observational study aimed to assess the association between maternal abdominal subcutaneous and visceral fat thickness measured with ultrasound scan during the first trimester and the risk of developing gestational diabetes mellitus (GDM). We recruited 43 non-diabetic women with singleton pregnancy between 11 and 14 week of gestation and evaluated ultrasonographic measurements of subcutaneous fat thickness (SFT) and preperitoneal fat (PF) above the umbilicus. During the 2nd trimester, GDM screening was performed by 75 g two-hour oral glucose tolerance test (OGTT) and diagnosis was made when one or more plasma glucose values meets or exceeds the values indicated by International Association of the Diabetes and Pregnancy Study Groups (IADPSG). Among the 43 woman, 8 developed GDM (18.6%). Of these 37,5% (N.=3) had been diagnosed with GDM during a previous pregnancy, with a statistically significant correlation (P=0.035). Mean SFT for all patients was significantly higher in the GDM group compared to non-GDM group (27.30±8.78 mm vs. 18.56±9.99 mm; P=0.049). Mean PF for all women showed a statistically significant correlation with GDM (13.27±9.07 mm for non GDM group vs. 23.52±10.24 mm for GDM group; P=0.038). Abdominal adiposity, both subcutaneous and visceral, seem to be a suitable predictor of GDM in early pregnancy and it can be easily assessed during a first trimester routine ultrasound, although further studies are needed to evaluate their role in the screening protocols.

Screening for Gestational Diabetes Mellitus in Early Pregnancy: What Is the Evidence?

The incidence of gestational diabetes mellitus (GDM) is increasing worldwide. This has a significant effect on the health of the mother and offspring. There is no doubt that screening for GDM between 24 and 28 weeks is important to reduce the risk of adverse pregnancy outcomes. However, there is no consensus about diagnosis and treatment of GDM in early pregnancy. In this narrative review on the current evidence on screening for GDM in early pregnancy, we included 37 cohort studies and eight randomized controlled trials (RCTs). Observational studies have shown that a high proportion (15–70%) of women with GDM can be detected early in pregnancy depending on the setting, criteria used and screening strategy. Data from observational studies on the potential benefit of screening and treatment of GDM in early pregnancy show conflicting results. In addition, there is substantial heterogeneity in age and BMI across the different study populations. Smaller RCTs could not show benefit but several large RCTs are ongoing. RCTs are also necessary to determine the appropriate cut-off for HbA1c in pregnancy as there is limited evidence showing that an HbA1c ≥6.5% has a low sensitivity to detect overt diabetes in early pregnancy.

Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population.

Objective Gestational diabetes mellitus (GDM) is a common metabolic disorder with onset during pregnancy. However, the etiology and pathogenesis of GDM have not been fully elucidated. In this study, we used a metabolomics approach to investigate the relationship between maternal serum metabolites and GDM in early pregnancy. Methods A nested case-control study was performed. To establish an early pregnancy cohort, pregnant women in early pregnancy (10‐13+6 weeks) were recruited. In total, 51 patients with GDM and 51 healthy controls were included. Serum samples were analyzed using an untargeted high-performance liquid chromatography mass spectrometry metabolomics approach. The relationships between metabolites and GDM were analyzed by an orthogonal partial least-squares discriminant analysis. Differential metabolites were evaluated using a KEGG pathway analysis. Results A total of 44 differential metabolites were identified between GDM cases and healthy controls during early pregnancy. Of these, 26 significant metabolites were obtained in early pregnancy after false discovery rate (FDR < 0.1) correction. In the GDM group, the levels of L-pyroglutamic acid, L-glutamic acid, phenylacetic acid, pantothenic acid, and xanthine were significantly higher and the levels of 1,5-anhydro-D-glucitol, calcitriol, and 4-oxoproline were significantly lower than those in the control group. These metabolites were involved in multiple metabolic pathways, including those for amino acid, carbohydrate, lipid, energy, nucleotide, cofactor, and vitamin metabolism. Conclusions We identified significant differentially expressed metabolites associated with the risk of GDM, providing insight into the mechanisms underlying GDM in early pregnancy and candidate predictive markers.