UNASSIGNED: Pregnancy-associated fulminant type 1 diabetes (PF) occurs during pregnancy or within 2 weeks of delivery. Although it occurs infrequently, it is associated with high fetal mortality rate. Few studies have examined whether PF is associated with gestational diabetes mellitus (GDM).
UNASSIGNED: A 29-year-old woman diagnosed with GDM at 24 weeks of gestation developed a fever, sore throat, nausea and vomiting at 29 weeks of gestation. Ketoacidosis was considered based on her blood ketone and glucose levels and the results of a blood gas analysis. Since the patient\'s islet function declined rapidly, fluid replacement, insulin therapy, and other treatments were administered. The patient was ultimately diagnosed with PF, and has required ongoing insulin therapy. She delivered a healthy baby girl by elective cesarean section at 37-week gestation. Her blood glucose has been satisfactorily controlled over the 12 months since her acute presentation.
UNASSIGNED: PF is characterized by poor maternal and infant outcomes and a high stillbirth rate. Blood glucose should be regularly monitored in pregnant women with GDM. A sudden increase in blood glucose may indicate the possibility of PF, which needs to be managed in a timely manner to avoid adverse pregnancy outcomes.

Hyperglycemia in pregnancy due to pre-existing Type 2 diabetes mellitus (T2DM) and gestational diabetes mellitus (GDM) is rising globally with increasing rates of risk factors for metabolic disease. This review summarizes current evidence and recommendations from national and international guidelines for diagnosis and management of T2DM and GDM to optimize maternal and neonatal outcomes.

BACKGROUND: Pregnant women with gestational diabetes mellitus (GDM) experience higher psychological stress levels than healthy pregnant women. The objectives of the current study were to examine (1) the differences in anxiety, depression, stress, and somatization levels between women diagnosed with GDM and healthy pregnant women, and (2) the differences in anxiety, depression, stress, and somatization levels among women with well-controlled blood sugar levels compared to those who are not well controlled.
METHODS: A quantitative cross-sectional study was conducted, involving 103 women who had been pregnant at least once, including 40 women diagnosed with GDM and 63 healthy pregnant women. An online questionnaire was distributed that included three parts: socio-demographic parameters, the DASS-21 questionnaire assessing anxiety, depression, and stress, and the Brief Symptom Inventory (BSI) questionnaire assessing somatization.
RESULTS: Differences in the anxiety (t = 14.470, <0.001), depression (t = 8.17, <0.001), stress (t = 16.354, <0.001), and somatization (t = 13.679, <0.001) levels between women diagnosed with GDM and healthy pregnant women were found. Women diagnosed with GDM reported higher levels of anxiety, depression, stress, and somatization compared to those without GDM. Additionally, women with better blood sugar control, as indicated by lower glycated hemoglobin (HbA1c) levels had lower anxiety (t (38) = -2.04, p < 0.05), depression (t(38) = -2.88, p < 0.01), stress (t(38) = -1.88, p < 0.05), and somatization (t(38) = -1.88, p < 0.05) levels compared to women with poorer blood sugar control.
CONCLUSIONS: Pregnant women diagnosed with GDM report higher levels of negative mental health conditions such as anxiety, depression, stress, and somatization compared to healthy pregnant women.

Gestational Diabetes Mellitus (GDM) is a medical complication during the gestational period in which woman who had never been diagnosed with diabetes develops hyperglycemia. Prior studies have demonstrated that the advancement of GDM and its consequences arises from a disparity between oxidants and antioxidants in the cells. The observed outcomes can be attributed to an excessive formation of reactive oxygen species (ROS) within the cells, coupled with a reduced activity of anti-oxidative enzymes. Glutathione S-transferase (GSTs) is recognized as an antioxidant enzyme that is belong to as a phase II family member of detoxifying enzymes. These metabolic multigene catalysts are found into the cytoplasm of the cell. GSTs play a vital part in the elimination of cellular ROS or free radicals. The study involves total 300 pregnant women, (150 GDM cases and 150 healthy controls). The polymorphism study of GSTs genes (GSTM1 and GSTT1) was determined by conventional Polymerase Chain Reaction (PCR). The mRNA expression study of GSTM1 and GSTT1 genes analysed by qPCR/ RT-PCR (quantitative PCR/Real-Time PCR) followed by statistical analysis done using Prism8 software (version 8.01). The study revealed statistically significant variations in biochemical parameters between GDM cases and controls. It was found GSTM1-null (GSTM1-/-) polymorphism significantly (P < 0.0001) most prevalent in GDM cases (56.7%) when compared to healthy control (28%). However, no significant difference was observed for GSTT1 null and present polymorphism (P = 0.906). The gene expression levels of both GSTM1 and GSTT1 were found considerably downregulated in individuals with GDM as compared to the control group (P < 0.0001). The downregulation of gene expression has a significant (P<0.0001) association with the null/deletion polymorphism of both GSTM1/ GSTT1 genes respectively. Null/deletion genotype of GSTM1 gene and its expression showed significant association with GDM. Therefore, this gene variant has the potential to be used as a prognostic biomarker for GDM. However, there is need to study this gene variant in larger sample size and different ethnicity.

Gestational Diabetes Mellitus (GDM) poses significant health risks to mothers and infants. Early prediction and effective management are crucial to improving outcomes. Machine learning techniques have emerged as powerful tools for GDM prediction. This review compiles and analyses the available studies to highlight key findings and trends in the application of machine learning for GDM prediction. A comprehensive search of relevant studies published between 2000 and September 2023 was conducted. Fourteen studies were selected based on their focus on machine learning for GDM prediction. These studies were subjected to rigorous analysis to identify common themes and trends. The review revealed several key themes. Models capable of predicting GDM risk during the early stages of pregnancy were identified from the studies reviewed. Several studies underscored the necessity of tailoring predictive models to specific populations and demographic groups. These findings highlighted the limitations of uniform guidelines for diverse populations. Moreover, studies emphasised the value of integrating clinical data into GDM prediction models. This integration improved the treatment and care delivery for individuals diagnosed with GDM. While different machine learning models showed promise, selecting and weighing variables remains complex. The reviewed studies offer valuable insights into the complexities and potential solutions in GDM prediction using machine learning. The pursuit of accurate, early prediction models, the consideration of diverse populations, clinical data, and emerging data sources underscore the commitment of researchers to improve healthcare outcomes for pregnant individuals at risk of GDM.

UNASSIGNED: This study aimed to assess the impact of gestational diabetes mellitus (GDM) on fetal heart structure and function using a technique called fetal heart quantification (Fetal HQ), with a focus on mitochondrial dynamics, which employs advanced imaging technology for comprehensive analysis.
UNASSIGNED: A total of 180 fetuses with normal heart structures, aged 24-40 weeks of gestation, were examined. A 2-3 s cine loop in the standard four-chamber oblique view was captured and analyzed using the speckle-tracking technique with Fetal HQ. Various echocardiographic parameters were evaluated, including four-chamber view (4CV), global spherical index (GSI), global longitudinal strain (GLS), 24-segment spherical index (SI), ventricular fractional area change (FAC), cardiac output (CO), and stroke volume (SV). These parameters were compared between the GDM group and the control group during two gestational periods: 24+0 to 28+0 weeks and 28+1 to 40+1 weeks. Statistical analysis was performed using independent samples t-tests and Mann-Whitney U tests to identify significant differences.
UNASSIGNED: Twenty fetuses from mothers with GDM and 40 from the control group were recruited at 24+0 to 28+0 weeks. At 28+1 to 40+1 weeks, 40 fetuses from mothers with GDM and 80 from the control group were recruited. The fetal left ventricular global longitudinal function was similar between the GDM and control groups. However, compared to the controls, right ventricular function in the GDM group was lower only at 28+1 to 40+1 weeks. In the GDM group, the global spherical index (GSI) was lower than in the control group at 28+1 to 40+1 weeks (1.175 vs. 1.22; p = 0.001). There were significant decreases in ventricular FAC (38.74% vs. 42.83%; p < 0.0001) and 4CV GLS for the right ventricle (-22.27% vs. -26.31%; p = 0.005) at 28+1 to 40+1 weeks.
UNASSIGNED: Our findings suggest that GDM is associated with decreased right ventricular function in the fetal heart, particularly during the later stages of pregnancy (28+1 to 40+1 weeks), compared to fetuses from healthy pregnancies. The Fetal HQ technique represents a valuable tool for evaluating the structure and function of fetal hearts affected by GDM during the advanced stages of pregnancy.

UNASSIGNED: Obesity and metabolic-associated fatty liver disease (MAFLD) during pregnancy constitute significant problems for routine antenatal care, with increasing prevalence globally. Similar to obesity, MAFLD is associated with a higher risk for maternal complications (e.g. pre-eclampsia and gestational diabetes) and long-term adverse health outcomes for the offspring. However, MAFLD during pregnancy is often under-recognized, with limited management/treatment options.
UNASSIGNED: PubMed/MEDLINE, EMBASE, and Scopus were searched based on a search strategy for obesity and/or MAFLD in pregnancy to identify relevant papers up to 2024. This review summarizes the pertinent evidence on the relationship between maternal obesity and MAFLD during pregnancy. Key mechanisms implicated in the underlying pathophysiology linking obesity and MAFLD during pregnancy (e.g. insulin resistance and dysregulated adipokine secretion) are highlighted. Moreover, a diagnostic approach for MAFLD diagnosis during pregnancy and its complications are presented. Finally, promising relevant areas for future research are covered.
UNASSIGNED: Research progress regarding maternal obesity, MAFLD, and their impact on maternal and fetal/offspring health is expected to improve the relevant diagnostic methods and lead to novel treatments. Thus, routine practice could apply more personalized management strategies, incorporating individualized algorithms with genetic and/or multi-biomarker profiling to guide prevention, early diagnosis, and treatment.

Background Antenatal corticosteroids prevent multiple fetal complications and improve overall neonatal survival but at the cost of adverse effects including maternal hyperglycemia. This study aimed to understand the effect of antenatal corticosteroids on maternal glycemic control. Methodology This prospective observational study included 93 pregnant women with singleton pregnancies between 32 and 37 weeks gestation admitted for potential preterm labor. We assessed their glucose tolerance and categorized 56 participants with normal glucose tolerance in group 1, while 37 who had diabetes mellitus (DM) were categorized in group 2. Of the women with DM, 30 had gestational diabetes mellitus and seven had pre-existing type 2 diabetes. Betamethasone was administered as per the standard of care, two doses of 12 mg each, 24 hours apart. To assess the effect of corticosteroids on maternal blood glucose control, we monitored capillary blood glucose levels at specific time intervals for three days following the steroid administration. Fasting and post-meal glucose levels were checked a week after the administration of the steroid therapy, and it was observed that participants from group 1 had developed steroid-related hyperglycemia. Blood glucose levels ≥140 mg/dL were considered significant hyperglycemia, while blood glucose levels ≥160 mg/dL were considered severe hyperglycemia. Following this observation, we documented any modifications in the diabetes management plan during or after the corticosteroid treatment, including medical nutrition therapy, addition of oral anti-diabetic medications, commencement of insulin, or increasing insulin dosage. Standard software programs such as Microsoft Excel and SPSS (IBM Corp., Armonk, NY, USA) were used to analyze the collected data, summarize the findings, and identify any statistically significant relationships between the variables descriptive and inferential statistics, respectively. Results Participants from both groups demonstrated worsening glycemia requiring treatment involving insulin, following corticosteroid administration. The percentages of significant hyperglycemic participants from groups 1 and 2 were 72% and 92%, respectively. Severe hyperglycemia was seen in 43% and 84% of the participants from groups 1 and 2, respectively. An intervention involving insulin administration was required by group 2 participants with pre-existing diabetes within six hours of steroid administration, followed by those with gestational diabetes requiring intervention within 12-24 hours, and by group 1 participants at 24-48 hours. One week after the administration of antenatal corticosteroids, hyperglycemia persisted in 20 (35.71%) of the 56 participants in group 1, of which six (30%) participants required insulin therapy. On the other hand, 18 (48.64%) participants from group 2 required additional insulin therapy after a week of administration of steroids when compared to pre-steroid administration status. Conclusions The findings of this study demonstrate that antenatal betamethasone therapy resulted in worsening hyperglycemia in most pregnant women, regardless of pre-existing glycemic status. These findings highlight the need for close monitoring of blood glucose levels and potential adjustments to medication regimens following antenatal betamethasone administration, irrespective of the pre-existing glycemic status.

Introduction Gestational diabetes mellitus (GDM) is a common disease affecting pregnant females, and it carries a major risk of short and long-term health problems for both mothers and their offspring. Multiple factors like advanced maternal age, obesity, and unhealthy lifestyle can increase the risk of GDM. The current guidelines recommend screening all pregnant females for risk factors during the first trimester with subsequent testing of the blood glucose level at 24 weeks gestation. Lack of awareness about GDM is a main contributing factor in the delay in screening and diagnosis of GDM with subsequent fetal and maternal complications. This study aims to identify the level of knowledge about GDM among the adult population in the Kingdom of Saudi Arabia (KSA). Material and methods A descriptive cross-sectional questionnaire-based study was conducted to identify the level of knowledge about risk factors, prevention, and treatment of GDM in a community sample from Saudi Arabia. A self-administered electronic questionnaire was designed, tested for validity and reliability, and distributed through social media platforms. It consisted of 18 questions asking about the socio-demographic characteristics, the type of hospital in which the participant receives their medical care, whether the participant heard about GDM or not, and if they know someone with GDM, in addition to questions to assess the level of knowledge about risk factors, complications, prevention, and treatment of GDM. The total score of knowledge was calculated. The multivariate regression analysis test was employed to analyze the relationship between various demographic variables and the level of knowledge about GDM among the study population. A p-value of 0.05 or less was considered statistically significant. Results A total of 539 (100%) participants completed the questionnaire: 263 (48.8%) of them were in the age category (18-25 years), 440 (81.6%) of them were females, 307 (57%) had a bachelor\'s degree, 275 (51%) were single, 454 (84.2%) had heard about GDM, and 258 (47.9%) of them have or know someone with GDM. The total score of knowledge revealed excellent, good, fair, and poor levels among 334 (62%), 140 (26%), 49 (9%), and 16 (3%) of participants, respectively. The multivariable linear regression model revealed that participants who received health care from governmental hospitals heard about GDM and had or knew someone with GDM were positively associated with a higher level of knowledge. Conclusions The findings revealed that among participants, 62% showed excellent knowledge about GDM, although, the other 38% had non-optimal levels of knowledge. Awareness campaigns are recommended to improve the level of knowledge about this disease, its risk factors, treatment, and complications.

Understanding how maternal micronutrient intake and dietary habits impact gestational diabetes mellitus (GDM) is crucial. Data from 797 pregnant women were prospectively analyzed to assess GDM status with the oral glucose tolerance test (OGTT). Nutritional intake was evaluated using a validated food frequency questionnaire (FFQ) across two periods: Period A, covering 6 months before pregnancy, and Period B, from pregnancy onset to mid-gestation (24 weeks). Micronutrient intakes were compared against the European Food Safety Authority (EFSA) dietary reference values (DRVs) and were used to estimate the mean adequacy ratio (MAR) to assess dietary adequacy. GDM was diagnosed in 14.7% (n = 117) of women with the characteristics of a higher mean maternal age (MA) and pre-pregnancy body mass index (BMI). Out of the 13 vitamins assessed, biotin, folate, niacin, and pantothenic acid were found significantly higher in the GDM group, as did iron, magnesium, manganese, phosphorus, and zinc from the 10 minerals. The results were influenced by the timing of the assessment. Importantly, MAR was higher during pregnancy and was found to increase the risk of GDM by 1% (95%CI: 1, 1.02). A sensitivity analysis revealed that reducing MAR significantly raised the GDM risk by 68% (95%CI: 1.02, 2.79). No association was revealed between adherence to the Mediterranean diet (MD) and GDM risk. These findings highlight areas for further investigation into whether dietary modifications involving these specific micronutrients could effectively influence GDM outcomes.