Prediction and prevention of Gestational Diabetes: an update of recent literature

Identifying Predictor Variables for a Composite Risk Prediction Tool for Gestational Diabetes and Hypertensive Disorders of Pregnancy: A Modified Delphi Study

A composite cardiometabolic risk prediction tool will support the systematic identification of women at increased cardiometabolic risk during pregnancy to enable early screening and intervention. This study aims to identify and select predictor variables for a composite risk prediction tool for cardiometabolic risk (gestational diabetes mellitus and/or hypertensive disorders of pregnancy) for use in the first trimester. A two-round modified online Delphi study was undertaken. A prior systematic literature review generated fifteen potential predictor variables for inclusion in the tool. Multidisciplinary experts (n = 31) rated the clinical importance of variables in an online survey and nominated additional variables for consideration (Round One). An online meeting (n = 14) was held to deliberate the importance, feasibility and acceptability of collecting variables in early pregnancy. Consensus was reached in a second online survey (Round Two). Overall, 24 variables were considered; 9 were eliminated, and 15 were selected for inclusion in the tool. The final 15 predictor variables related to maternal demographics (age, ethnicity/race), pre-pregnancy history (body mass index, height, history of chronic kidney disease/polycystic ovarian syndrome, family history of diabetes, pre-existing diabetes/hypertension), obstetric history (parity, history of macrosomia/pre-eclampsia/gestational diabetes mellitus), biochemical measures (blood glucose levels), hemodynamic measures (systolic blood pressure). Variables will inform the development of a cardiometabolic risk prediction tool in subsequent research. Evidence-based, clinically relevant and routinely collected variables were selected for a composite cardiometabolic risk prediction tool for early pregnancy.

A stepwise prediction and interpretation of gestational diabetes mellitus: Foster the practical application of machine learning in clinical decision

Background

Machine learning has shown to be an effective method for early prediction and intervention of Gestational diabetes mellitus (GDM), which greatly decreases GDM incidence, reduces maternal and infant complications and improves the prognosis. However, there is still much room for improvement in data quality, feature dimension, and accuracy. The contributions and mechanism explanations of clinical data at different pregnancy stages to the prediction accuracy are still lacking. More importantly, current models still face notable obstacles in practical applications due to the complex and diverse input features and difficulties in redeployment. As a result, a simple, practical but accurate enough model is urgently needed.

Design and methods

In this study, 2309 samples from two public hospitals in Shenzhen, China were collected for analysis. Different algorithms were systematically compared to build a robust and stepwise prediction system (level A to C) based on advanced machine learning, and models under different levels were interpreted.

Results

XGBoost reported the best performance with ACC of 0.922, 0.859 and 0.850, AUC of 0.974, 0.924 and 0.913 for the selected level A to C models in the test set, respectively. Tree-based feature importance and SHAP method successfully identified the commonly recognized risk factors, while indicated new inconsistent impact trends for GDM in different stages of pregnancy.

Conclusion

A stepwise prediction system was successfully established. A practical tool that enables a quick prediction of GDM was released at https://github.com/ifyoungnet/MedGDM.This study is expected to provide a more detailed profiling of GDM risk and lay the foundation for the application of the model in practice.

The role of lipid dysregulation in gestational diabetes mellitus: Early prediction and postpartum prognosis

Gestational diabetes mellitus (GDM) is a pathological condition during pregnancy characterized by impaired glucose tolerance, and the failure of pancreatic beta-cells to respond appropriately to an increased insulin demand. However, while the majority of women with GDM will return to normoglycemia after delivery, they have up to a seven times higher risk of developing type 2 diabetes during midlife, compared with those with no history of GDM. Gestational diabetes mellitus also increases the risk of multiple metabolic disorders, including non-alcoholic fatty liver disease, obesity, and cardiovascular diseases. Lipid metabolism undergoes significant changes throughout the gestational period, and lipid dysregulation is strongly associated with GDM and the progression to future type 2 diabetes. In addition to common lipid variables, discovery-based omics techniques, such as metabolomics and lipidomics, have identified lipid biomarkers that correlate with GDM. These lipid species also show considerable potential in predicting the onset of GDM and subsequent type 2 diabetes post-delivery. This review aims to update the current knowledge of the role that lipids play in the onset of GDM, with a focus on potential lipid biomarkers or metabolic pathways. These biomarkers may be useful in establishing predictive models to accurately predict the future onset of GDM and type 2 diabetes, and early intervention may help to reduce the complications associated with GDM.

Optimising Cardiometabolic Risk Factors in Pregnancy: A Review of Risk Prediction Models Targeting Gestational Diabetes and Hypertensive Disorders

Cardiovascular disease, especially coronary heart disease and cerebrovascular disease, is a leading cause of mortality and morbidity in women globally. The development of cardiometabolic conditions in pregnancy, such as gestational diabetes mellitus and hypertensive disorders of pregnancy, portend an increased risk of future cardiovascular disease in women. Pregnancy therefore represents a unique opportunity to detect and manage risk factors, prior to the development of cardiovascular sequelae. Risk prediction models for gestational diabetes mellitus and hypertensive disorders of pregnancy can help identify at-risk women in early pregnancy, allowing timely intervention to mitigate both short- and long-term adverse outcomes. In this narrative review, we outline the shared pathophysiological pathways for gestational diabetes mellitus and hypertensive disorders of pregnancy, summarise contemporary risk prediction models and candidate predictors for these conditions, and discuss the utility of these models in clinical application.

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

OBJECTIVES

To 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.

METHODS

Four 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.

RESULTS

We 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.

CONCLUSIONS

Based 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.

Molecular Changes in the Glucokinase Gene (GCK) Associated with the Diagnosis of Maturity Onset Diabetes of the Young (MODY) in Pregnant Women and Newborns

BACKGROUND

Diabetes mellitus is the most common metabolic alteration in gestation. Monogenic diabetes or Maturity-Onset Diabetes of the Young (MODY) is a subtype caused by a primary defect in insulin secretion determined by autosomal dominant inheritance.

OBJECTIVES

This study aimed to analyze molecular changes of the Glucokinase gene (GCK) in pregnant women with hyperglycemia during gestation and in their neonates. Case Study and Methods: We collected 201 blood samples, 128 from pregnant patients diagnosed with hyperglycemia and 73 from umbilical cord blood from neonates of the respective patients. DNA extraction and polymerase chain reaction (PCR) were performed to identify molecular changes in the GCK gene.

RESULTS

In a total of 201 samples (128 from mothers and 73 from neonates), we found changes in 21 (10.6%), among which 12 were maternal samples (6.0%) and 9 were neonatal samples (4.5%). DNA sequencing identified two polymorphisms and one deleterious MODY GCK-diagnostic mutation.

CONCLUSION

The prevalence of molecular changes in the Glucokinase gene (GCK) and the deleterious MODY GCK-diagnostic mutation were 9.3% and 0.7%, respectively, in women with hyperglycemia during gestation and 12.5% and 1.3%, respectively, in their neonates. The deleterious MODY GCK mutation identified is associated with a reduction in GCK activity and hyperglycemia. In the other molecular changes identified, it was impossible to exclude phenotypic change despite not having clinical significance. Therefore, these changes may interfere with the management and clinical outcome of the patients.

The Effects of Serum Folic Acid and Vitamin B12 on the Risk of Gestational Diabetes Mellitus

PURPOSE

In order to gain more knowledge on the risk of gestational diabetes mellitus (GDM), and to provide evidence for clinical guidance on the optimum level of serum folic acid and vitamin B12, this study aimed to clarify the relationship between serum folic acid and vitamin B12 and the risk of GDM.

PATIENTS AND METHODS

This retrospective case-control study was conducted based on the clinical information system of the Maternal and Child Health Hospital of Hubei Province. Clinical data including maternal socio-demographical characteristics, serum folic acid, and vitamin B12 were collected. Logistic regression analyses and restricted cubic splines were performed to examine the impact of serum folic acid and vitamin B12 on the risk of GDM.

RESULTS

Significantly elevated risks of GDM were observed in groups with high serum folic acid concentration (OR = 1.84, 95% CI: 1.07-3.16), and in low vitamin B12 concentration (OR = 2.14, 95% CI: 1.26-3.65). After stratified by age, the increased risk of GDM was still noticed in a low level of vitamin B12 among mothers aged <30 years (OR = 4.76, 95% CI: 1.45-15.61). In mothers with pre-pregnancy BMI <24, elevated risk of GDM was significantly associated with a high folic acid (OR = 2.09, 95% CI: 1.11-3.93) or a low vitamin B12 concentration (OR = 2.24, 95% CI: 1.22-4.14). Moreover, the risk of GDM was on the decline with the increased level of folic acid in the beginning, and it started to manifest an upward trend when the serum folic acid reached 19.02 ng/mL.

CONCLUSION

This study demonstrated that serum folic acid excess or vitamin B12 deficiency could contribute to the increased risk of GDM, and revealed the potential side effect of serum folic acid overdose. As serum folic acid and vitamin B12 tests are widely applied in clinical practice, this finding could help clinicians to evaluate maternal risk from a new perspective.

Early markers of gestational diabetes mellitus: what we know and which way forward?

Women's metabolism during pregnancy undergoes numerous changes that can lead to gestational diabetes mellitus (GDM). The cause and pathogenesis of GDM, a heterogeneous disease, are not completely clear, but GDM is increasing in prevalence and is associated with the modern lifestyle. Most diagnoses of GDM are made via the guidelines from the International Association of Diabetes and Pregnancy Study Groups (IADSPG), which involve an oral glucose tolerance test (OGTT) between 24 and 28 weeks of pregnancy. Diagnosis in this stage of pregnancy can lead to short- and long-term implications for the mother and child. Therefore, there is an urgent need for earlier GDM markers in order to enable prevention and earlier treatment. Routine GDM biomarkers (plasma glucose, insulin, C-peptide, homeostatic model assessment of insulin resistance, and sex hormone-binding globulin) can differentiate between healthy pregnant women and those with GDM but are not suitable for early GDM diagnosis. In this article, we present an overview of the potential early biomarkers for GDM that have been investigated recently. We also present our view of future developments in the laboratory diagnosis of GDM.

Relationship between ABO blood group and gestational diabetes mellitus: A protocol for systematic review and meta-analysis

BACKGROUND

Gestational diabetes mellitus (GDM) is a common metabolic disorder syndrome in women during pregnancy. If effective measures are not taken to intervene in the early stage of GDM, severe effects will damage maternal and infant health. ABO is the most important human blood group system. A large number of studies have displayed that ABO blood group is associated with many diseases. At present, the risk relationship between ABO blood group and GDM is controversial. The purpose of this study is to explore the risk relationship between ABO blood group and GDM by meta-analysis, thus providing basis for the prevention and treatment of GDM.

METHODS

An electronic database, including Embase, Cochrane Library, Pubmed, Chinese databases SinoMed, Chinese National Knowledge Infrastructure, Chinese Scientific Journals Database and Wanfang Data, will be used to search for studies of ABO blood group and GDM. The language will be limited to Chinese and English. The two reviewers will be responsible for the selection of the study, the extraction of data and the evaluation of the quality of the research. All statistical analyses will be carried out using Review Manager 5.3.

RESULTS

The results of this meta-analysis will be published in peer-reviewed journals.

CONCLUSION

This study will provide evidence to support the relationship between ABO blood group and the risk of GDM.

ETHICS AND DISSEMINATION

The private information from individuals will not be published. This systematic review also will not involve endangering participant rights. Ethical approval is not required. The results may be published in a peer-reviewed journal or disseminated in relevant conferences.

OSF REGISTRATION NUMBER

DOI 10.17605/OSF.IO/W6QSX.

Association of pre- and early-pregnancy factors with the risk for gestational diabetes mellitus in a large Chinese population

Gestational diabetes mellitus (GDM) has aroused wide public concern, as it affects approximately 1.8-25.1% of pregnancies worldwide. This study aimed to examine the association of pre-pregnancy demographic parameters and early-pregnancy laboratory biomarkers with later GDM risk, and further to establish a nomogram prediction model. This study is based on the big obstetric data from 10 "AAA" hospitals in Xiamen. GDM was diagnosed according to the International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria. Data are analyzed using Stata (v14.1) and R (v3.5.2). Total 187,432 gestational women free of pre-pregnancy diabetes mellitus were eligible for analysis, including 49,611 women with GDM and 137,821 women without GDM. Irrespective of confounding adjustment, eight independent factors were consistently and significantly associated with GDM, including pre-pregnancy body mass index (BMI), pre-pregnancy intake of folic acid, white cell count, platelet count, alanine transaminase, albumin, direct bilirubin, and creatinine (p < 0.001). Notably, per 3 kg/m² increment in pre-pregnancy BMI was associated with 22% increased risk [adjusted odds ratio (OR) 1.22, 95% confidence interval (CI) 1.21-1.24, p < 0.001], and pre-pregnancy intake of folic acid can reduce GDM risk by 27% (adjusted OR 0.73, 95% CI 0.69-0.79, p < 0.001). The eight significant factors exhibited decent prediction performance as reflected by calibration and discrimination statistics and decision curve analysis. To enhance clinical application, a nomogram model was established by incorporating age and above eight factors, and importantly this model had a prediction accuracy of 87%. Taken together, eight independent pre-/early-pregnancy predictors were identified in significant association with later GDM risk, and importantly a nomogram modeling these predictors has over 85% accuracy in early detecting pregnant women who will progress to GDM later.

Prevention of Gestational Diabetes: The Role of Dietary Intake, Physical Activity, and Weight before, during, and between Pregnancies

Gestational diabetes mellitus (GDM) is the most common complication of pregnancy and a significant clinical and public health problem with lifelong and intergenerational adverse health consequences for mothers and their offspring. The preconception, early pregnancy, and interconception periods represent opportune windows to engage women in preventive and health promotion interventions. This review provides an overview of findings from observational and intervention studies on the role of diet, physical activity, and weight (change) during these periods in the primary prevention of GDM. Current evidence suggests that supporting women to increase physical activity and achieve appropriate weight gain during early pregnancy and enabling women to optimize their weight and health behaviors prior to and between pregnancies have the potential to reduce rates of GDM. Translation of current evidence into practice requires further development and evaluation of co-designed interventions across community, health service, and policy levels to determine how women can be reached and supported to optimize their health behaviors before, during, and between pregnancies to reduce GDM risk.

Searching for Utopia, the Challenge of Standardized Medical Nutrition Therapy Prescription in Gestational Diabetes Mellitus Management: A Critical Review

Gestational diabetes mellitus (GDM) is a common pregnancy disorder and the incidence is increasing worldwide. GDM is associated with adverse maternal outcomes which may be reduced with proper management. Lifestyle modification in the form of medical nutrition therapy and physical activity, as well as self-monitoring of blood glucose levels, is the cornerstone of GDM management. Inevitably, the search for the "ultimate" diet prescription has been ongoing. Identifying the amount and type of carbohydrate to maintain blood glucose levels below targets while balancing the nutritional requirements of pregnancy and achieving gestational weight gain within recommendations is challenging. Recent developments in the area of the gut microbiota and its impact on glycemic response add another layer of complexity to the success of medical nutrition therapy. This review critically explores the challenges to dietary prescription for GDM and why utopia may never be found.

Identification of histone malonylation in the human fetal brain and implications for diabetes-induced neural tube defects

BACKGROUND

Neural tube defects (NTDs) are severe congenital malformations. Diabetes during pregnancy is a risk factor for NTDs, but its mechanism remains elusive. Emerging evidence suggests that protein malonylation is involved in diabetes. Here, we report the correlation between histone lysine malonylation in diabetes-induced NTDs.

METHODS

Nano-HPLC/MS/MS was used to screen the histone malonylation profile in human embryonic brain tissue. Then, the histone malonylation level was compared between the brains of normal control mice and mice with diabetes-induced NTDs. Finally, the histone malonylation level was compared under high glucose exposure in an E9 neuroepithelial cell line (NE4C).

RESULTS

A total of 30 histone malonylation sites were identified in human embryonic brain tissue, including 18 novel sites. Furthermore, we found an increased histone malonylation level in brain tissues from mice with diabetes-induced NTDs. Finally, both the histone malonylation modified sites and the modified levels were proved to be increased in the NE4C treated with high glucose.

CONCLUSION

Our results present a comprehensive map of histone malonylation in the human fetal brain. Furthermore, we provide experimental evidence supporting a relationship between histone malonylation and NTDs caused by high glucose-induced diabetes. These findings offer new insights into the pathological role of histone modifications in human NTDs.

Maternal visceral adipose tissue during the first half of pregnancy predicts gestational diabetes at the time of delivery - a cohort study

BACKGROUND

Gestational diabetes mellitus (GDM) is a common condition, often associated with high maternal and fetal morbidity. The use of new tools for early GDM screening can contribute to metabolic control to reduce maternal and fetal risk. This study aimed to ascertain whether maternal visceral adipose tissue (VAT) measurement by ultrasound during the first half of pregnancy can predict the occurrence of GDM during the third trimester.

METHODS

A prospective cohort study of 133 pregnant women with gestational age ≤20 weeks in an outpatient setting. VAT depth was measured by ultrasound at the maternal periumbilical region. GDM status was obtained through hospital charts during hospitalization to delivery. A Receiver Operator Characteristic (ROC) curve was used to determine the optimum threshold to predict GDM.

RESULTS

According to the ROC curve, a 45mm threshold was identified as the best cut-off value, with 66% of accuracy to predict GDM. Crude and adjusted odds ratios (OR) for GDM were 13.4 (95%CI 2.9-61.1) and 8.9 (95%CI 1.9-42.2), respectively. A similar result was obtained among pre-gravid non-obese women, with crude and adjusted OR of 16.6 (95%CI 1.9-142.6) and 14.4 (95%CI 1.7-125.7), respectively. Among pre-gravid obese patients, a 45mm threshold did not reach statistical significance to predict GDM.

CONCLUSION

The high and significant OR found before and after adjustments provides additional evidence of a strong association between VAT and GDM. It appears that VAT measurement during the first half of pregnancy has great potential in identifying non-obese women at high risk for GDM. This evidence can assist obstetricians in correctly allocating resources among populations of pregnant women at risk, determined not only by pre-gravid body mass index (BMI).

Alterations in Gut Microbiota of Gestational Diabetes Patients During the First Trimester of Pregnancy

Background: Dysbiosis of human gut microbiota is associated with a wide range of metabolic disorders, including gestational diabetes mellitus (GDM). Yet whether gut microbiota dysbiosis participates in the etiology of GDM remains largely unknown.

Objectives: Our study was initiated to determine whether the alternations in gut microbial composition during early pregnancy linked to the later development of GDM, and explore the feasibility of microbial biomarkers for the early prediction of GDM.

Study design: This nested case-control study was based upon an early pregnancy follow-up cohort (ChiCTR1900020652). Gut microbiota profiles of 98 subjects with GDM and 98 matched healthy controls during the early pregnancy (10–15 weeks) were assessed via 16S rRNA gene amplicon sequencing of V4 region. The data set was randomly split into a discovery set and a validation set, the former was used to analyze the differences between GDM cases and controls in gut microbial composition and functional annotation, and to establish an early identification model of GDM, then the performance of the model was verified by the external validation set.

Results: Bioinformatic analyses revealed changes to gut microbial composition with significant differences in relative abundance between the groups. Specifically, Eisenbergiella, Tyzzerella 4, and Lachnospiraceae NK4A136 were enriched in the GDM group, whereas Parabacteroides, Megasphaera, Eubacterium eligens group, etc. remained dominant in the controls. Correlation analysis revealed that GDM-enriched genera Eisenbergiella and Tyzzerella 4 were positively correlated with fasting blood glucose levels, while three control-enriched genera (Parabacteroides, Parasutterella, and Ruminococcaceae UCG 002) were the opposite. Further, GDM functional annotation modules revealed enrichment of modules for sphingolipid metabolism, starch and sucrose metabolism, etc., while lysine biosynthesis and nitrogen metabolism were reduced. Finally, five genera and two clinical indices were included in the linear discriminant analysis model for the prediction of GDM; the areas under receiver operating characteristic curves of the training and validation sets were 0.736 (95% confidence interval: 0.663–0.808) and 0.696 (0.575–0.818), respectively.

Conclusions: Gut bacterial dysbiosis in early pregnancy was found to be associated with the later development of GDM, and gut microbiota-targeted biomarkers might be utilized as potential predictors of GDM.

External validation and clinical utility of prognostic prediction models for gestational diabetes mellitus: A prospective cohort study

Introduction

We performed an independent validation study of all published first trimester prediction models, containing non‐invasive predictors, for the risk of gestational diabetes mellitus. Furthermore, the clinical potential of the best performing models was evaluated.

Material and methods

Systemically selected prediction models from the literature were validated in a Dutch prospective cohort using data from Expect Study I and PRIDE Study. The predictive performance of the models was evaluated by discrimination and calibration. Clinical utility was assessed using decision curve analysis. Screening performance measures were calculated at different risk thresholds for the best model and compared with current selective screening strategies.

Results

The validation cohort included 5260 women. Gestational diabetes mellitus was diagnosed in 127 women (2.4%). The discriminative performance of the 12 included models ranged from 68% to 75%. Nearly all models overestimated the risk. After recalibration, agreement between the observed outcomes and predicted probabilities improved for most models.

Conclusions

The best performing prediction models showed acceptable performance measures and may enable more personalized medicine‐based antenatal care for women at risk of developing gestational diabetes mellitus compared with current applied strategies.

Assisted reproductive technology and the risk of gestational diabetes mellitus: a systematic review and meta-analysis

Background

The use of assisted reproductive technology (ART) is increasing worldwide, and observational studies have indicated that women who conceived by ART have an increased risk of pregnancy complications including gestational diabetes mellitus (GDM). We aimed to determine the risk of GDM among women who conceived with ART by systematic review and meta-analysis.

Main text

A systematic literature search was conducted in ISI Web of Knowledge, MEDLINE, Scopus, and Embase through May 2017 for English-language articles using a list of keywords. All studies comparing GDM in women conceived by ART and those who conceived spontaneously were included. Data extraction was performed by two authors independently and discrepancies were resolved by discussion. In total, 48 studies with 91,487 pregnancies conceived through ART and 2,525,234 spontaneously conceived met the inclusion criteria. There was evidence of substantial heterogeneity among these studies (P < 0.001, I2 = 98.6%). Random effects meta-analysis showed a significant increase in GDM among those who conceived by ART compared with those who conceived spontaneously (pooled relative risk = 1.51, 95% confidence interval = 1.18–1.93). Visual inspection of the funnel plot did not reveal any publication bias, which was supported by Egger’s test and Begg’s test.

Conclusion

The findings of this systematic review indicate that the use of ART treatment is associated with a 1.51-fold increase in GDM. Women need to be counselled carefully before undergoing ART treatment about the possibility and risk of GDM.

Prevention of gestational diabetes mellitus in overweight or obese pregnant women: A network meta-analysis

AIMS

Several interventions have been implemented to prevent the development of gestational diabetes mellitus (GDM) in obese pregnant women, including physical exercise programs, and administration of metformin, vitamin D and probiotics. The aim of this network meta-analysis was to compare the efficiency of these interventions and identify the optimal.

MATERIALS

A network meta-analysis of randomized trials was performed comparing the different interventions for the development of GDM in overweight or obese women, either to each other or placebo/no intervention. A search was conducted in four electronic databases and grey literature sources. The primary outcome was the development of GDM; secondary outcomes were other complications of pregnancy.

RESULTS

The meta-analysis included 23 studies (4237 participants). None of the interventions was superior compared with placebo/no intervention for the prevention of GDM. Metformin and physical exercise were superior to placebo/no intervention for gestational weight gain (MD -1.21, 95% CI -2.14 to -0.28 and MD -0.96, 95% CI -1.69 to -0.22, respectively). Metformin was superior to placebo/no intervention for caesarean sections and admission to NICU.

CONCLUSIONS

Interventions aiming to prevent the development of GDM in overweight/obese women are not effective, when applied during pregnancy.

The predictive value of weight gain and waist circumference for gestational diabetes mellitus

Objective:

The first objective of this study was to investigate the relationship between gestational diabetes mellitus (GDM) and gestational weight gain (WG), waist circumference (WC), prepregnancy, and gestational body mass index (BMI). The second aim of our study was to assess the ability of WG, WC, prepregnancy, and gestational BMI with special reference to their cut-off points on predicting the risk of GDM in pregnant women in Turkey.

Materials and Methods:

A total of 261 women who underwent screening for GDM with the 75-g glucose tolerance test (GTT) between 24^th and 28^th gestational weeks were included. According to the 75-g oral GTT results, women were classified into two groups: the GDM group and non-GDM group. The data collected included age, parity, plasma glucose level for fasting, 1- and 2-h tests, WC, prepregnancy and gestational BMI, prepregnancy weight, WG during pregnancy, gestational age at birth, and birth weight.

Results:

WC at 20-24 weeks of gestation, prepregnancy BMI, and gestational BMI had a predictive capacity for GDM. According to our results, optimal cut-off points for the best predictive value of GDM were WC of 100 cm with a sensitivity of 84% and specificity of 70%, prepregnancy BMI of 25 kg/m² with a sensitivity of 81.8% and specificity of 76%, and gestational BMI of 28.3 kg/m² with a sensitivity of 75% and specificity of 77.4%.

Conclusion:

The measurement of prepregnancy BMI, gestational BMI, and WC may be useful in predicting the risk of GDM. Pregnant women with increased prepregnancy BMI, gestational BMI, and WC measurements may be susceptible to the development of GDM.

Sex hormone binding globulin for prediction of gestational diabetes mellitus in pre-conception and pregnancy: A systematic review

AIM

The purpose of the present study was to assess the relationship of sex hormone binding globulin (SHBG) and gestational diabetes mellitus (GDM).

METHODS

The Cochrane Library, Medline, ScienceDirect, and Web of Science were searched for studies published from the inception of the databases up to February 2019. Our inclusion criteria were published observational full-text articles. All data were analyzed using Review Manager 5.3. Of 208 papers reviewed, 26 studies (n = 6668) were considered for meta-analysis.

RESULTS

The SHBG level was significantly lower in women with GDM compared to healthy women (MD = -11.86; 95% CI: [-13.02, -10.71]). Also, SHBG in women with PCOS and GDM and obesity was significantly lower than women with PCOS without GDM (MD = -38.14; 95% CI: [-56.79, -19.48]) and normal weight women (MD: -58.96; 95% CI: [-79.32, -38.59]). SHBG in the second trimester was lower than that in the first trimester and pre-conception.

CONCLUSIONS

This systematic review showed that the level of SHBG is significantly lower in GDM pregnant women than that in healthy women. The results of this systematic review about the relationship of GDM and SHBG and suggestion to assess this marker in early pregnancy should be considered with caution.

Comprehensive evaluation of irisin levels in fetomaternal circulation of pregnant women with obesity or gestational diabetes mellitus

AIM

To evaluate maternal and cord blood irisin levels in pregnant women with gestational diabetes mellitus (GDM) and in obese pregnant women without GDM.

METHODS

The study included 109 patients, with 34 patients in the GDM group, 40 in the obese non-GDM group, and 35 in the control group. Maternal serum irisin levels at the time of delivery were measured by an enzyme-linked immunosorbent assay kit. The correlation of serum irisin levels with metabolic parameters and anthropometric measurements was analyzed.

RESULTS

There were significant differences between the study groups in terms of cord arterial, cord venous, and maternal serum irisin levels (P < 0.001, P < 0.01, P < 0.001, respectively). Cord arterial, cord venous, and maternal serum irisin levels were higher in the obese group compared to the control (P < 0.01, P < 0.01, P < 0.01, respectively) and the GDM group (P < 0.001, P < 0.001, P < 0.001, respectively).

CONCLUSION

Elevation in irisin levels of women who have pregnancies complicated with obesity may be explained as part of the compensation mechanism against disturbed metabolic functions. Pregnant individuals with GDM have lower serum irisin levels in comparison to healthy pregnant women. In this regard, it is possible that the measurement of serum irisin levels may be utilized in the future for prediction, prevention, and treatment of GDM.

Critical role of mTOR, PPARγ and PPARδ signaling in regulating early pregnancy decidual function, embryo viability and feto-placental growth

STUDY QUESTION

What are the consequences of inhibiting mTOR, the mechanistic target of rapamycin (mTOR), and the peroxisome proliferator activated receptor gamma (PPARγ) and PPARδ pathways in the early post-implantation period on decidual function, embryo viability and feto-placental growth in the rat?

SUMMARY ANSWER

mTOR inhibition from Days 7 to 9 of pregnancy in rats caused decidual PPARγ and PPARδ upregulation on Day 9 of pregnancy and resulted in embryo resorption by Day 14 of pregnancy. PPARγ and PPARδ inhibition differentially affected decidual mTOR signaling and levels of target proteins relevant to lipid histotrophic nutrition and led to reduced feto-placental weights on Day 14 of pregnancy.

WHAT IS KNOWN ALREADY

Although mTOR, PPARγ and PPARδ are nutrient sensors important during implantation, the role of these signaling pathways in decidual function and how they interact in the early post-implantation period are unknown. Perilipin 2 (PLIN2) and fatty acid binding protein 4 (FABP4), two adipogenic proteins involved in lipid histotrophic nutrition, are targets of mTOR and PPAR signaling pathways in a variety of tissues.

STUDY DESIGN, SIZE, DURATION

Rapamycin (mTOR inhibitor, 0.75 mg/kg, sc), T0070907 (PPARγ inhibitor, 0.001 mg/kg, sc), GSK0660 (PPARδ inhibitor, 0.1 mg/kg, sc) or vehicle was injected daily to pregnant rats from Days 7 to 9 of pregnancy and the studies were performed on Day 9 of pregnancy (n = 7 per group) or Day 14 of pregnancy (n = 7 per group).

PARTICIPANTS/MATERIALS, SETTING, METHODS

On Day 9 of pregnancy, rat decidua were collected and prepared for western blot and immunohistochemical studies. On Day 14 of pregnancy, the resorption rate, number of viable fetuses, crown-rump length and placental and decidual weights were determined.

MAIN RESULTS AND THE ROLE OF CHANCE

Inhibition of mTOR in the early post-implantation period led to a reduction in FABP4 protein levels, an increase in PLIN2 levels and an upregulation of PPARγ and PPARδ in 9-day-pregnant rat decidua. Most embryos were viable on Day 9 of pregnancy but had resorbed by Day 14 of pregnancy. This denotes a key function of mTOR in the post-implantation period and suggests that activation of PPAR signaling was insufficient to compensate for impaired nutritional/survival signaling induced by mTOR inhibition. Inhibition of PPARγ signaling resulted in decreased decidual PLIN2 and FABP4 protein expression as well as in inhibition of decidual mTOR signaling in Day 9 of pregnancy. This treatment also reduced feto-placental growth on Day 14 of pregnancy, revealing the relevance of PPARγ signaling in sustaining post-implantation growth. Moreover, following inhibition of PPARδ, PLIN2 levels were decreased and mTOR complex 1 and 2 signaling was altered in decidua on Day 9 of pregnancy. On Day 14 of pregnancy, PPARδ inhibition caused reduced feto-placental weight, increased decidual weight and increased resorption rate, suggesting a key role of PPARδ in sustaining post-implantation development.

LARGE SCALE DATA

Not applicable.

LIMITATIONS, REASONS FOR CAUTION

This is an in vivo animal study and the relevance of the results for humans remains to be established.

WIDER IMPLICATIONS OF THE FINDINGS

The early post-implantation period is a critical window of development and changes in the intrauterine environment may cause embryo resorption and lead to placental and fetal growth restriction. mTOR, PPARγ and PPARδ signaling are decidual nutrient sensors with extensive cross-talk that regulates adipogenic proteins involved in histotrophic nutrition and important for embryo viability and early placental and fetal development and growth.

STUDY FUNDING/COMPETING INTEREST(S)

Funding was provided by the Agencia Nacional de Promoción Científica y Tecnológica de Argentina (PICT 2014-411 and PICT 2015-0130), and by the International Cooperation (Grants CONICET-NIH-2014 and CONICET-NIH-2017) to A.J. and T.J. The authors have no conflicts of interest.

Development and validation of a clinical model for preconception and early pregnancy risk prediction of gestational diabetes mellitus in nulliparous women

Implementation of dietary and lifestyle interventions prior to and early in pregnancy in high risk women has been shown to reduce the risk of gestational diabetes mellitus (GDM) development later in pregnancy. Although numerous risk factors for GDM have been identified, the ability to accurately identify women before or early in pregnancy who could benefit most from these interventions remains limited. As nulliparous women are an under-screened population with risk profiles that differ from their multiparous counterparts, development of a prediction model tailored to nulliparous women may facilitate timely preventive intervention and improve maternal and infant outcomes. We aimed to develop and validate a model for preconception and early pregnancy prediction of gestational diabetes mellitus based on clinical risk factors for nulliparous women. A risk prediction model was built within a large California birth cohort including singleton live birth records from 2007-2012. Model accuracy was assessed both internally and externally, within a cohort of women who delivered at University of Iowa Hospitals and Clinics between 2009-2017, using discrimination and calibration. Differences in predictive accuracy of the model were assessed within specific racial/ethnic groups. The prediction model included five risk factors: race/ethnicity, age at delivery, pre-pregnancy body mass index, family history of diabetes, and pre-existing hypertension. The area under the curve (AUC) for the California internal validation cohort was 0.732 (95% confidence interval (CI) 0.728, 0.735), and 0.710 (95% CI 0.672, 0.749) for the Iowa external validation cohort. The model performed particularly well in Hispanic (AUC 0.739) and Black women (AUC 0.719). Our findings suggest that estimation of a woman's risk for GDM through model-based incorporation of risk factors accurately identifies those at high risk (i.e., predicted risk >6%) who could benefit from preventive intervention encouraging prompt incorporation of this tool into preconception and prenatal care.

Clinical Implications of the NICE 2015 Criteria for Gestational Diabetes Mellitus

BACKGROUND

In response to concerns that the International Association of Diabetes in Pregnancy Study Group (IADPSG) criteria labeled too many women with gestational diabetes mellitus (GDM) without evidence of clinical or economic benefit, NICE recommended a change in diagnostic criteria in 2015.

AIM

To compare diabetes associated maternal and neonatal complications in pregnancies complicated by GDM diagnosed using IADPSG criteria only, to those with GDM diagnosed using both IADPSG and NICE 2015 criteria. GDM screening was risk factor based.

METHODS

This was a secondary analysis of a trial of women with GDM diagnosed by the IADPSG criteria (fasting blood glucose (BG) ≥ 5.1 mmol/L, 1 h ≥ 10.0 mmol/L and 2 h ≥ 8.5 mmol/L). Outcomes were compared for two groups: NICE + IADPSG defined as those with GDM diagnosed by both the NICE 2015 and IADPSG criteria (fasting BG ≥ 5.6 mmol/L, 2 h ≥ 8.5 mmol/L); and IADPSG-ONLY (fasting BG 5.1 mmol/L to 5.5 mmol/L, and/or 1-hour ≥10.0 mmol/L, and 2 h ≥ 8.5 mmol/L). We were not able to obtain data for women with a 2-h value between BG 7.8⁻8.4 mmol/L (i.e., NICE-ONLY; NICE 2015 positive and IADPSG negative). All women were treated for GDM using targets of fasting BG < 5.3 mmol/L and 1-h post prandial BG < 7.8 mmol/L respectively.

RESULTS

Of 159 women, 65 (40.9%) were NICE + IADPSG and 94 (59.1%) IADPSG-ONLY. Hypoglycaemic medication use was similar in both groups: 52.3% NICE + IADPSG, 46.8% IADPSG-ONLY, OR 1.0 (0.5⁻1.9). The IADPSG-ONLY group delivered later than the NICE + IADPSG group; 39.0 weeks (sd 1.4) compared to 38.2 weeks (sd 2.5), p value 0.02. Fewer caesarean sections occurred in IADPSG-ONLY group 30.9% vs. 52.3%, OR 0.4 (0.2⁻0.9). Birthweight, large for gestational age, and other neonatal complications were not significantly different between groups.

CONCLUSIONS

Gestational diabetes-associated perinatal complications were similar in both groups. The IADPSG criteria detect women with evidence of ongoing hyperglycaemia who may benefit from treatment during pregnancy.

Prediction of Gestational Diabetes Mellitus and Pre-diabetes 5 Years Postpartum using 75 g Oral Glucose Tolerance Test at 14-16 Weeks' Gestation

Early detection and treatment of women at risk for gestational diabetes mellitus (GDM) could improve perinatal and long-term outcomes in GDM women and their offspring. We explored if a 75 g oral glucose tolerance test (OGTT) at 14–16 weeks of gestation could identify women who will (1) develop GDM or give birth to large-for-gestational-age (LGA) babies in 1031 pregnant women from the STORK study using different diagnostic criteria (WHO1999, IADPSG2010, WHO2013, NORWAY2017) and (2) develop pre-diabetes 5 years postpartum focusing on first trimester β-cell function in a separate study of 300 women from the STORK cohort. The sensitivity of the 14–16 week OGTT to identify women who would develop GDM or have LGA babies was low, and we could not identify alternative cut-offs to exclude women not at risk or identify women that could benefit from early intervention. First trimester β-cell function was a stronger determinant than third trimester β-cell function of predicting maternal pre-diabetes. In conclusion, in our normal low-risk population, the 75 g OGTT at 14–16 weeks is insufficient to identify candidates for early treatment of GDM or identify women not likely to develop GDM or have LGA babies. First trimester β-cell function may predict pre-diabetes 5 years postpartum.

Pregnancy outcomes in women with polycystic ovary syndrome in two Latin American populations

Pregnancy complications and obstetric outcomes were compared in 80 Chilean (PPCOS_Ch) and 70 Argentinian (PPCOS_Ar) pregnant women. Reference groups of Chilean and Argentinian normal pregnant women from the same antenatal care units were also compared. PPCOS_Ch showed a higher prevalence of gestational diabetes mellitus (GDM) (OR, 2.28, 95% CI: 1.08-4.77, p = .030) and a lower prevalence of pregnancy-induced hypertension (PIH) (OR, 0.20, 95% CI: 0.07-0.54, p = .001) compared to PPCOS_Ar. In the normal pregnant groups, the prevalence of PIH was lower in Chilean women compared to Argentinian women (OR, 0.24, 95% CI: 0.10-0.62, p = .001). Similar to the pattern observed in the normal populations, newborns from PPCOS_Ch had higher birth weight and length compared with the newborns of PPCOS_Ar (p = .006 and .014, respectively). In conclusion, differences in pregnancy complications and obstetric outcomes between Chilean and Argentinian pregnant women with PCOS could be determined by ethnic diversity together with environmental factors of both populations. Impact Statement What is already known on this subject: The reproductive and metabolic phenotypes of women with polycystic ovary syndrome vary between different populations, which could significantly influence the obstetric and neonatal outcomes in this syndrome. What the results of this study add: Pregnant women with PCOS from two Latin American countries (Chile and Argentina) exhibit differences in the prevalence of gestational diabetes and pregnancy-induced hypertension, and in the birth weight of their newborns. What the implications are of these findings for clinical practice and/or further research: Ethnic diversity together with environmental factors are fundamental elements that must be considered in the management of pregnant women with PCOS.

Metformin in gestational diabetes mellitus: predictors of poor response

OBJECTIVE

Metformin can be regarded as a first-line treatment in gestational diabetes mellitus (GDM) due to its safety and effectiveness. However, a proportion of women do not achieve adequate glycemic control with metformin alone. We aim to identify predictors of this poor response to metformin.

DESIGN AND METHODS

Retrospective multicentre cohort study of women with GDM who started metformin as first-line treatment. The assessed cohort was divided into a metformin group and metformin plus insulin group. Biometric and demographic characteristics, glycemic control data, obstetric, neonatal and postpartum outcomes were compared between groups and analysed in order to identify predictors of poor response to metformin. Data were analysed using STATA, version 13.1.

RESULTS

Of the 388 women enrolled in the study, 135 (34.8%) required additional insulin therapy to achieve the glycemic targets. Higher age (aOR: 1.08 (1.03-1.13), P = 0.003), higher pre-pregnancy body mass index (BMI) (1.06 (1.02-1.10), P = 0.003) and earlier introduction of metformin (0.89 (0.85-0.94), P < 0.001) were independent predictors for insulin supplementation. Regarding all the analysed outcomes, only cesarean delivery rates and postpartum glucose levels were higher in women requiring insulin supplementation.

CONCLUSIONS

Although almost 35% of women did not achieve adequate glycemic control with metformin, insulin supplementation was not associated with poor neonatal outcomes. Higher age, higher pre-pregnancy BMI and earlier introduction of metformin could be used as predictors of poor response to metformin.

Obesity and Weight Gain in Pregnancy and Postpartum: an Evidence Review of Lifestyle Interventions to Inform Maternal and Child Health Policies

Background: Maternal obesity, excessive gestational weight gain (GWG) and post-partum weight retention (PPWR) constitute new public health challenges, due to the association with negative short- and long-term maternal and neonatal outcomes. The aim of this evidence review was to identify effective lifestyle interventions to manage weight and improve maternal and infant outcomes during pregnancy and postpartum. Methods: A review of systematic reviews and meta-analyses investigating the effects of lifestyle interventions on GWG or PPWR was conducted (Jan 2009-2018) via electronic searches in the databases Medline, Pubmed, Web of Science and Cochrane Library using all keywords related to obesity/weight gain/loss, pregnancy or postpartum and lifestyle interventions;15 relevant reviews were selected. Results: In healthy women from all BMI classes, diet and physical activity interventions can decrease: GWG (mean difference -1.8 to -0.7 kg, high to moderate-quality evidence); the risks of GWG above the IOM guidelines (risk ratio [RR] 0.72 to 0.80, high to low-quality evidence); pregnancy-induced hypertension (RR 0.30 to 0.66, low to very low-quality evidence); cesarean section (RR 0.91 to 0.95; high to moderate-quality evidence) and neonatal respiratory distress syndrome (RR 0.56, high-quality evidence); without any maternal/fetal/neonatal adverse effects. In women with overweight/obesity, multi-component interventions can decrease: GWG (-0.91 to -0.63 kg, moderate to very low-quality evidence); pregnancy-induced hypertension (RR 0.30 to 0.66, low-quality evidence); macrosomia (RR 0.85, 0.73 to 1.0, moderate-quality evidence) and neonatal respiratory distress syndrome (RR 0.47, 0.26 to 0.85, moderate-quality evidence). Diet is associated with greater reduction of the risks of GDM, pregnancy-induced hypertension and preterm birth, compared with any other intervention. After delivery, combined diet and physical activity interventions reduce PPWR in women of any BMI (-2.57 to -2.3 kg, very low quality evidence) or with overweight/obesity (-3.6 to -1.22, moderate to very low-quality-evidence), but no other effects were reported. Conclusions: Multi-component approaches including a balanced diet with low glycaemic load and light to moderate intensity physical activity, 30-60 min per day 3-5 days per week, should be recommended from the first trimester of pregnancy and maintained during the postpartum period. This evidence review should help inform recommendations for health care professionals and women of child-bearing age.