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: 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.

Gestational diabetes mellitus (GDM) poses a significant global health concern, impacting both maternal and fetal well-being. Early detection and treatment are imperative to mitigate adverse outcomes during pregnancy. This review delves into the pivotal role of insulin function and the influence of genetic variants, including SLC30A8, CDKAL1, TCF7L2, IRS1, and GCK, in GDM development. These genetic variations affect beta-cell function and insulin activity in crucial tissues, such as muscle, disrupting glucose regulation during pregnancy. We propose a hypothesis that this variation may disrupt zinc transport, consequently impairing insulin production and secretion, thereby contributing to GDM onset. Furthermore, we discussed the involvement of inflammatory pathways, such as TNF-alpha and IL-6, in predisposing individuals to GDM. Genetic modulation of these pathways may exacerbate glucose metabolism dysregulation observed in GDM patients. We also discussed how GDM affects cardiovascular disease (CVD) through a direct correlation between pregnancy and cardiometabolic function, increasing atherosclerosis, decreased vascular function, dyslipidemia, and hypertension in women with GDM history. However, further research is imperative to unravel the intricate interplay between inflammatory pathways, genetics, and GDM. This understanding is pivotal for devising targeted gene therapies and pharmacological interventions to rectify genetic variations in SLC30A8, CDKAL1, TCF7L2, IRS1, GCK, and other pertinent genes. Ultimately, this review offers insights into the pathophysiological mechanisms of GDM, providing a foundation for developing strategies to mitigate its impact.

Gestational diabetes mellitus (GDM) is a complex and significant health concern affecting pregnant individuals and their offspring. This review provides a comprehensive examination of GDM, focusing on diagnostic strategies and the associated maternal and offspring complications. We delve into the challenges and controversies surrounding GDM diagnosis, including the variability in diagnostic criteria, diagnostic accuracy and reproducibility issues, ethical considerations, and the influence of ethnicity and genetics. Maternal complications, such as preeclampsia, cesarean sections, long-term health implications, and neonatal complications like macrosomia, hypoglycemia, and respiratory distress syndrome, are explored in detail. Additionally, we investigate the long-term risks of childhood obesity and type 2 diabetes in offspring and potential cognitive and developmental outcomes. This review underscores the critical importance of early detection and effective management of GDM, the need for standardized diagnostic criteria, personalized care plans, and the ongoing pursuit of research to enhance our understanding of this complex condition. GDM remains a dynamic field where ongoing innovation and research promise to improve the health outcomes of pregnant individuals and their children.

Currently, there is no international unanimity regarding the timings, the optimal cut-off points, and standardized methods of screening or diagnosis of gestational diabetes mellitus (GDM). The screening guidelines and recommendations for GDM evolved over time; concise information has been presented here in the review. We searched electronic databases for various guidelines for screening of GDM in PubMed, Medical Literature Analysis and Retrieval System Online (MEDLINE), Embase, Cochrane, Google Scholar, Scopus, Guidelines International Network (GIN library), National Guidelines Clearinghouse (NGC); Web sites of relevant organizations; and trial registries. The mesh headings derived after reviewing the articles and were used to further search the articles are: (\"Screening Guidelines GDM\" or \"Screening Criteria for GDM\") and (\"Glucose Intolerance in Pregnancy\" or \"Gestational Diabetes Mellitus\"). The articles published from 1960 till December 2022 were included. Key outcomes included the prevalence of GDM is 14.6% according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria and 13.4% according to Diabetes in Pregnancy Study Group India (DIPSI) criteria, making the DIPSI criterion a cost-effective method for low-resource settings. The IADPSG) criterion diagnoses and treats GDM earlier, thus reducing the complications associated with GDM in the mother and newborn. The IADPSG criteria at a cut-off of ≥140 mg/dL have a sensitivity of 81% and specificity of 93%, whereas the World Health Organization (2013) criteria at the same cut-off has a lower sensitivity of 59% and specificity of 81%. The risk factors of having GDM are family history, history during past pregnancy, medical history, multiple current pregnancies, and raised hemoglobin A1c. The screening guidelines have been developed by different organizations and institutions over the years. The guidelines with the threshold values for screening and their standardization for detecting GDM in Indian mothers are yet to be established.

Gestational diabetes (GDM) affects approximately 14% of pregnancies globally and is associated with short- and long-term complications for both the mother and child. In addition, GDM has been linked to chronic low-grade inflammation with recent research indicating a potential immune dysregulation in pathophysiology and a disparity in regulatory T cells.
This systematic review and meta-analysis aimed to determine whether there is an association between GDM and the level of Tregs in the peripheral blood.
Literature searches were conducted in PubMed, Embase, and Ovid between the 7th and 14th of February 2022. The inclusion criteria were any original studies published in the English language, measuring differentiated Tregs in women with GDM compared with glucose-tolerant pregnant women. Meta-analysis was performed between comparable Treg markers. Statistical tests were used to quantify heterogeneity: τ 2, χ 2, and I 2. Study quality was assessed using a modified version of the Newcastle-Ottawa scale.
The search yielded 223 results: eight studies were included in the review and seven in the meta-analysis (GDM = 228, control = 286). Analysis of Tregs across all trimesters showed significantly lower Treg numbers in women with GDM (SMD, -0.76; 95% CI, -1.37, -0.15; I 2 = 90%). This was reflected in the analysis by specific Treg markers (SMD -0.55; 95% CI, -1.04, -0.07; I 2 = 83%; third trimester, five studies). Non-significant differences were found within subgroups (differentiated by CD4+FoxP3+, CD4+CD127-, and CD4+CD127-FoxP3) of both analyses.
GDM is associated with lower Treg numbers in the peripheral maternal blood. In early pregnancy, there is clinical potential to use Treg levels as a predictive tool for the subsequent development of GDM. There is also a potential therapeutic intervention to prevent the development of GDM by increasing Treg populations. However, the precise mechanism by which Tregs mediate GDM remains unclear.
https://www.crd.york.ac.uk/prospero, identifier CRD42022309796.

BACKGROUND: Induction at 38-40 weeks of gestation has been broadly suggested for women with gestational diabetes mellitus (GDM), yet its benefits and risks remain unclear. This study aimed to systematically review and meta-analyze existing evidence on the effect of induction at term gestation among women with GDM.
METHODS: We searched MEDLINE, EMBASE, Cochrane Libraries, and Web of Science from inception to June 2021. We included randomized controlled trials (RCTs) and observational studies comparing induction with expectant management among GDM term pregnancies. Primary outcomes included caesarean section (CS) and macrosomia. All screening and extraction were conducted independently and in duplicates. Meta-analyses with random-effects models were conducted to generate the pooled odds ratios (ORs) and 95% confidence intervals (CIs) using the Mantel-Haenszel method. Methodological quality was assessed independently by two reviewers using the Cochrane Risk of Bias Tool for RCTs and the Newcastle-Ottawa Scale for observational studies.
RESULTS: Of the 4,791 citations, 11 studies were included (3 RCTs and 8 observational studies). Compared to expectant management, GDM women with induction had a significantly lower odds for macrosomia (RCTs 0.49 [0.30-0.81]); observational studies 0.64 [0.54-0.77]), but not for CS (RCTs 0.95 [0.64-1.43]); observational studies 1.03 [0.79-1.34]). Induction was associated with a lower odds of severe perineal lacerations in observational studies (0.59 [0.39-0.88]). No significant difference was observed for other maternal or neonatal morbidities, or perinatal mortality between groups.
CONCLUSIONS: For GDM women, induction may reduce the risk of macrosomia and severe perineal lacerations compared to expectant management. Further rigorous studies with large sample sizes are warranted to better inform clinical implications.

Gestational diabetes mellitus (GDM) is a state of pre-diabetic impaired glucose tolerance initially occurring during pregnancy. Although abnormalities in glucose metabolism normally resolve rapidly after delivery, women with GDM have a higher lifetime risk of developing diabetes mellitus than those without GDM; thus, postpartum healthcare is essential. Of all GDM patients, 5%-10% test positive for diabetes-related autoantibodies, which increase the risk of developing type 1 diabetes mellitus (T1DM). Autoantibody measurement in GDM screening remains debatable; however, it may be useful for the postnatal follow-up of GDM patients at high risk of developing T1DM. We treated a 29-year-old woman who was GDM positive for anti-glutamic acid decarboxylase antibody (GADA) requiring high-dose insulin therapy during pregnancy. As the patient tested positive for GADA, she received judicious postpartum management, allowing for early diagnosis of T1DM and resumption of treatment. Her insulin secretory capacity was preserved at 1 year after parturition, suggesting either slowly progressive insulin-dependent T1DM or latent autoimmune diabetes in adults. This was a rare case of slowly progressive insulin-dependent T1DM or latent autoimmune diabetes in adults in the early postpartum period, but the fact that GADA was positive during pregnancy enabled early treatment without overlooking it. Measuring diabetes-related autoantibodies in patients considered to be at a high risk for T1DM, such as those who are of slim build, young, or suffering from autoimmune thyroid disorders, may be important for appropriate individualized follow-up.

OBJECTIVE: Air pollution is an environmental stimulus that may predispose pregnant women to gestational diabetes mellitus (GDM). This systematic review and meta-analysis were conducted to investigate the relationship between air pollutants and GDM.
METHODS: PubMed, Web of Science, and Scopus were systematically searched for retrieving English articles published from January 2020 to September 2021, investigating the relationship of exposure to ambient air pollution or levels of air pollutants with GDM and related parameters, including fasting plasma glucose (FPG), insulin resistance, and impaired glucose tolerance. Heterogeneity and publication bias were evaluated using I-squared (I2), and Begg\'s statistics, respectively. We also performed the subgroup analysis for particulate matters (PM2.5, PM10), Ozone (O3), and sulfur dioxide (SO2) in the different exposure periods.
RESULTS: A total of 13 studies examining 2,826,544 patients were included in this meta-analysis. Compared to non-exposed women, exposure to PM2.5 increases the odds (likelihood of occurrence outcome) of GDM by 1.09 times (95% CI 1.06, 1.12), whereas exposure to PM10 has more effect by OR of 1.17 (95% CI 1.04, 1.32). Exposure to O3 and SO2 increases the odds of GDM by 1.10 times (95% CI 1.03, 1.18) and 1.10 times (95% CI 1.01, 1.19), respectively.
CONCLUSIONS: The results of the study show a relationship between air pollutants PM2.5, PM10, O3, and SO2 and the risk of GDM. Although evidence from various studies can provide insights into the linkage between maternal exposure to air pollution and GDM, more well-designed longitudinal studies are recommended for precise interpretation of the association between GDM and air pollution by adjusting all potential confounders.

Observational studies suggest that the potential role of magnesium remains controversial in gestational diabetes mellitus (GDM). This meta-analysis aims to consolidate the available information from observational studies that have focused on the relationship between magnesium levels and GDM. A systematic and comprehensive literature search was conducted in PubMed, Embase, Web of Science, CNKI, and Wanfang databases. Data were extracted independently by two investigators. Standardized mean differences (SMD) and 95% confidence intervals (CIs) were used to summarize the circulating magnesium levels (CI). This meta-analysis included a total of 17 studies involving 2858 participants including 1404 GDM cases and 1454 healthy controls, which showed that magnesium levels were significantly lower in GDM compared to healthy controls (SMD: - 0.35; 95% CI: - 0.62, - 0.07, P = 0.013). Likewise, the same phenomenon was observed in the third trimester (SMD =  - 1.07; 95% CI: - 1.84 to - 0.29, P = 0.007). Other subgroup analyses revealed that this trend of decreasing magnesium concentration was only observed in Europeans (SMD =  - 0.64; 95% CI: - 0.90, - 0.38, P < 0.0001). This meta-analysis revealed that serum magnesium levels were lower in patients with GDM than in healthy pregnant women, and this discrepancy was most pronounced in European populations and during the third trimester. Nevertheless, current evidence suggests that circulating magnesium deficiency is associated with gestational diabetes; the challenge for the future is to further elucidate the possible benefits of preventing gestational diabetes through magnesium supplementation.