Prevalence and Trends in Gestational Diabetes Mellitus Among Women in the United States, 2006-2017: A Population-Based Study

Investigating predictive factors in treatment response with metformin in patients with gestational diabetes mellitus: a cross-sectional analytical-descriptive study

Objective

As the utilization of metformin for gestational diabetes mellitus (GDM) treatment continues to rise, a substantial segment of these patients will ultimately necessitate insulin during their therapeutic journey. Hence, assessing patients' clinical and laboratory attributes becomes invaluable in determining their likelihood of responding favorably to metformin medication. This discernment aids in selecting an optimal management approach, wherein the patients most likely to benefit significantly from metformin are identified, while alternative therapies like insulin are considered for individuals with a lower probability of treatment response.

Method

This was a cross-sectional analytical-descriptive study of individuals with GDM. Initially, the subject's laboratory results and demographic information were submitted. Following that, metformin was administered to all subjects along with counseling on maintaining a healthy diet and lifestyle. Following a 4-week interval, the patients were reassessed and divided into two groups based on their response to metformin medication and then analyzed.

Result

807 people participated in this study, of which 329 people (40.8%) responded to treatment and the failure rate of metformin treatment was 59.2%. This research revealed that the predictive factors of response to metformin medication were, respectively, the amount of 1-hour oral glucose tolerance test (OGTT) (OR = 62.66), 2-hour postprandial plasma glucose (OR = 54.04), 2-hour OGTT (OR = 17.37), followed by the history of abortion (OR = 14.88), the number of pregnancies (gravida 3 and more) (OR = 5.06) and history of infertility (OR = 2.6).

Conclusion

The current study's findings indicated that to enhance GDM care, metformin prescriptions should be prescribed to patients depending on their clinical characteristics and laboratory results.

Value-based evaluation of gestational diabetes mellitus care pathway redesign by using cost and outcome data

BACKGROUND

Gestational diabetes mellitus (GDM) is a common complication of pregnancy. Implementation of Value-Based Healthcare (VBHC) to GDM care is worthwhile as traditional GDM care is fragmented and fails to meet the needs of women with GDM. Value of care can be improved through optimization and redesign of the care pathway and implementation of an outcome-based payment model. This study was conducted to perform a value-based evaluation of GDM care pathway redesign by using cost- and outcome data.

METHODS

This study was designed as a single center, prospective, observational cohort study. In January 2022, GDM care was redesigned by substituting GDM care activities from an Internal Medicine Department (IMD) to an Integrated Maternity Care Organization (IMCO) in the Netherlands. Women diagnosed with GDM in 2021 were assigned to a pre-intervention cohort (N = 264) and those diagnosed in 2022 to a post-intervention cohort (N = 407). The impact of the intervention on value of care for women with GDM was evaluated by comparing clinical outcomes, patient-reported experience measures (GDM Responsiveness questionnaire), and costs (Time-Driven Activity-Based Costing) between the cohorts.

RESULTS

Referrals to the IMD for GDM decreased by 84.8% (pre-intervention: 100%, post-intervention: 15.2%, p <.001), patient-reported experiences significantly improved (Mean responsiveness pre-intervention: 3.46, post-intervention: 3.63, p: 0.00). Initiation of insulin treatment decreased by 46.8% (pre-intervention: 25.0%, post-intervention: 13.3%, p <.001). Maternal- and neonatal clinical outcomes were not different after redesign. Weighted average costs per GDM treatment were 9.7% lower post-intervention (pre-intervention: €168,37, post-intervention: €151,97).

CONCLUSIONS

The redesign of GDM care positively impacted value through decreased referrals and improved patient-reported experiences while clinical outcomes remained constant. By de-fragmenting GDM care, cost savings were realized. This study contributes to the improvement of care delivery, particularly in pregnancy and childbirth, by promoting the adoption of comprehensive, value-based evaluations of redesign initiatives and supports the further uptake of VBHC in maternity care.

Advanced Machine Learning did not Surpass Traditional Logistic Regression in First-Trimester Gestational Diabetes Mellitus Prediction: A Retrospective Single-Center Study From Eastern China

Background

Gestational diabetes mellitus (GDM) poses serious health risks to both mothers and fetuses. However, effective tools for identifying GDM are lacking. This study, based on a Chinese cohort, aims to construct and compare the predictive performance of traditional logistic regression (LR) and six advanced machine learning (ML) models, thereby aiding in the early identification and intervention of GDM.

Methods

This retrospective study utilized medical examination data from 956 singleton pregnant women collected between January and December 2023 from ten maternal and child health hospitals in Pinghu City. We employed receiver operating characteristic curves and precision-recall curves to assess the predictive performance of the models. Decision curve analysis (DCA) was used to evaluate clinical utility, while calibration curves and Hosmer-Lemeshow (HL) tests were applied to assess the calibration of each model.

Results

The 956 participants were randomly divided into a training set and a validation set at a 3:1 ratio. We identified 13 features through Spearman correlation analysis and the Boruta algorithm to construct the models. The LR model exhibited the best AUC at 0.787 (0.723-0.85), outperforming the seven other ML models including RF at 0.776 (0.711-0.841). Furthermore, the LR model showed good calibration and clinical utility.

Conclusion

Although ML has tremendous potential, in predicting the occurrence of GDM based on common early pregnancy data, the ML models did not completely outperform the traditional LR model. Simpler, traditional models may be more effective than complex ML approaches.

Perceived Stress and Early Postpartum Depressive Symptoms in Women with Recent GDM: Implications for Postpartum Lifestyle Programs

OBJECTIVES

To inform the development and adaptation of lifestyle programs to prevent type 2 diabetes, we sought to identify factors associated with depressive symptoms in the early postpartum period among women with recent gestational diabetes (GDM).

METHODS

Participants are from the Balance after Baby Intervention (BABI) study, a two-year randomized clinical trial of a lifestyle program for women with recent GDM conducted in Boston, MA, and Denver, CO between 2016 and 2019. The Edinburgh Postpartum Depression Scale (EPDS) and Perceived Stress Scale (PSS-10) were administered at an average of 8-weeks postpartum. We defined an EPDS score of ≥ 9 as depressive symptoms and reviewed medical records for medical history. We conducted bivariate analyses to identify predictors of postpartum depressive symptoms, then modeled the odds of postpartum depressive symptoms using multivariable logistic regression and selected the best fit model.

RESULTS

Our analysis included 181 women. Thirty-five (19%) scored ≥ 9 on the EPDS. While both perceived stress and whether this was the first pregnancy complicated by GDM were significant in the bivariate analysis, only perceived stress remained a significant predictor of postpartum depressive symptoms in the multivariate regression model (OR 4.34, 95% CI [2.58-7.31]). The effect of first GDM pregnancy was no longer significant in the multivariate model (OR 2.00, 95% CI [0.63-6.33]). Additionally, a mediation model determined that perceived stress fully mediated the effect of first GDM pregnancy on depressive symptoms (Effect ratio, 0.5507/1.5377 = 0.358, p = 0.036).

CONCLUSIONS FOR PRACTICE

Perceived stress was predictive of postpartum depressive symptoms in women with recent GDM and was found to mediate the relationship between first pregnancy complicated by GDM and postpartum depressive symptoms. Addressing perceived stress in the early postpartum period may be an important target for future lifestyle programs to maximize diabetes prevention efforts.

Unveiling Gestational Diabetes: An Overview of Pathophysiology and Management

Gestational diabetes mellitus (GDM) is characterized by an inadequate pancreatic β-cell response to pregnancy-induced insulin resistance, resulting in hyperglycemia. The pathophysiology involves reduced incretin hormone secretion and signaling, specifically decreased glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), impairing insulinotropic effects. Pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), impair insulin receptor substrate-1 (IRS-1) phosphorylation, disrupting insulin-mediated glucose uptake. β-cell dysfunction in GDM is associated with decreased pancreatic duodenal homeobox 1 (PDX1) expression, increased endoplasmic reticulum stress markers (CHOP, GRP78), and mitochondrial dysfunction leading to impaired ATP production and reduced glucose-stimulated insulin secretion. Excessive gestational weight gain exacerbates insulin resistance through hyperleptinemia, which downregulates insulin receptor expression via JAK/STAT signaling. Additionally, hypoadiponectinemia decreases AMP-activated protein kinase (AMPK) activation in skeletal muscle, impairing GLUT4 translocation. Placental hormones such as human placental lactogen (hPL) induce lipolysis, increasing circulating free fatty acids which activate protein kinase C, inhibiting insulin signaling. Placental 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) overactivity elevates cortisol levels, which activate glucocorticoid receptors to further reduce insulin sensitivity. GDM diagnostic thresholds (≥92 mg/dL fasting, ≥153 mg/dL post-load) are lower than type 2 diabetes to prevent fetal hyperinsulinemia and macrosomia. Management strategies focus on lifestyle modifications, including dietary carbohydrate restriction and exercise. Pharmacological interventions, such as insulin or metformin, aim to restore AMPK signaling and reduce hepatic glucose output. Emerging therapies, such as glucagon-like peptide-1 receptor (GLP-1R) agonists, show potential in improving glycemic control and reducing inflammation. A mechanistic understanding of GDM pathophysiology is essential for developing targeted therapeutic strategies to prevent both adverse pregnancy outcomes and the progression to overt diabetes in affected women.

Association of Early-life Trauma With Gestational Diabetes and Hypertensive Disorders of Pregnancy

BACKGROUND

Early-life trauma (before age of 18 years) is hypothesized to increase the risk for adverse pregnancy outcomes through stress pathways, yet epidemiologic findings are mixed.

METHODS

Sister Study participants (US women aged 35-74 years enrolled 2003-2009) completed an adapted Brief Betrayal Trauma Survey at the first follow-up visit. Lifetime history of gestational diabetes mellitus (GDM) or hypertensive disorders of pregnancy (HDP: pregnancy-related high blood pressure, pre-eclampsia/toxemia, or eclampsia) in pregnancies lasting ≥20 weeks was self-reported. We used log-binomial regression to estimate relative risks (RR) and 95% confidence intervals (CIs) for the association between early-life trauma (modeled using conventional measures [e.g., any experience, substantive domains, individual types] and latent classes of co-occurring traumas) and GDM or HDP among 34,879 parous women.

RESULTS

Approximately, 4% of participants reported GDM and 11% reported HDP. Relative to no early-life trauma, the RRs for any were 1.1 (95% CI = 1.0, 1.3) for GDM and 1.2 (95% CI = 1.2, 1.3) for HDP. Women reporting physical trauma had the highest risk of GDM and HDP in comparison to other substantive domains. In analyses using latent classes of early-life trauma, high trauma was associated with an elevated risk of both GDM (RR = 1.9, 95% CI = 1.5, 2.6) and HDP (RR = 1.7, 95% CI = 1.4, 2.0) compared with low trauma.

CONCLUSIONS

Women experiencing high levels of trauma in early life were at higher risk of GDM and HDP, adding to a growing evidence base for this association.

The cardio-metabolic protein profile is associated with development of type 2 diabetes at long term follow-up after gestational diabetes mellitus: Results from the OGFUS study

AIMS

Women with previous gestational diabetes mellitus (GDM) have an increased risk for later development of type 2 diabetes. During pregnancy, GDM affects the cardio-metabolic protein profile; however, it is unknown how GDM affects the cardio-metabolic protein profile in the long term and if it is associated with type 2 diabetes after GDM. We hypothesise that the cardio-metabolic protein profile is affected long term and is associated with the development of type 2 diabetes after GDM.

MATERIALS AND METHODS

A case-control follow-up study based on the Odense GDM Follow-Up Study (OGFUS) cohort, which included women with previous GDM (n = 128) and matched controls without previous GDM (n = 70). Blood samples from a follow-up assessment 8-10 years after delivery were analysed using a 29-plex panel of apolipoproteins, transport and inflammation/immune proteins using multiple-reaction-monitoring mass spectrometry.

RESULTS

Apolipoprotein A-I, D and M were significantly lower in women with previous GDM compared to controls (all p < 0.001), while apolipoprotein L-I, H, vitamin D binding protein, CRP, vitronectin, transthyretin and complement factors 3 and B were significantly higher (p = 0.008, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p = 0.005, respectively). All associations remained significant after adjustment for multiple testing except CRP, whereas apolipoprotein D, vitronectin and complement factors 3 and B were associated with the development of type 2 diabetes in women with previous GDM (p = 0.02, p = 0.001, p < 0.001, p = 0.004, respectively).

CONCLUSIONS

The cardio-metabolic protein profile 8-10 years after pregnancy is altered in women with previous GDM. Apolipoprotein D, vitronectin and complement factors 3 and B are candidate risk markers of type 2 diabetes after GDM pregnancy.

Air Pollution Exposure and Gestational Diabetes Mellitus Risk: A Retrospective Case-Control Study with Multi-Pollutant Analysis in Wuhan, Hubei Province

Ambient air pollution has been associated with gestational diabetes mellitus (GDM); however, evidence regarding trimester-specific effects from China remains limited. This case-control study study analyzed data from pregnant women who delivered in Wuhan, China, between 2017 and 2022 (164 GDM cases and 731 controls), integrating geographic information, air quality measurements, and maternal characteristics. Using Inverse Distance Weighting interpolation and Generalized Linear Mixed Models (GLMM), we assessed associations between air pollutant exposure and GDM across different gestational periods. Results indicated that NO2 demonstrated the strongest association with GDM compared to other pollutants. Specifically, increased NO2 exposure was consistently associated with higher GDM risk throughout pregnancy. PM2.5 exposure showed significant associations during early and mid-pregnancy, while SO2 exposure was significantly associated with GDM risk exclusively in early pregnancy. Sensitivity analyses stratified by urban maternity status and maternal age revealed the stability of the study's findings. These findings underscore the importance of reducing air pollution exposure during pregnancy and implementing targeted interventions for high-risk populations to prevent GDM development.

Microscopic changes and gross morphology of placenta in women affected by gestational diabetes mellitus in dietary treatment: A systematic review

Introduction/objective

Gestational diabetes mellitus (GDM) influences adverse maternal and fetal outcomes. Nutritional therapy and exercise are the first steps to maintain normal glucose levels. During pregnancy, metabolic status influences placental development.

Methods

This systematic review focused only on the morphology of the placenta and its microscopic changes in GMD under dietary therapy. A systematic search was performed on the main databases from inception to September 2024 (PROSPERO ID: CRD42024581621). Only original articles on GDM in diet and exercise treatment that reported at least one outcome of interest (microscopic features and macroscopic morphology of the placenta) were included.

Results

A total of 716 studies were identified, and nine met the inclusion criteria. The analysis confirmed that despite dietary control, some morphological changes in the placenta, including villus immaturity, chorangiosis, and fibrinoid necrosis, occurred at a different rate. In addition, the included studies reported an increase in placental weight in the diet-controlled GDM group.

Conclusion

Therefore, the results of the present qualitative analysis show that pregnant women with diet-controlled GDM, despite adequate glycemic control, abnormal placental development may persist. Our findings remark on the importance of the correct diet-managed GDM pregnancy monitoring due to the placental morphology abnormalities related to GMD.

Impact of Vitamin D Deficiency on Gestational Diabetes and Pregnancy Outcomes Across Diverse Ethnic Groups: A Retrospective Cohort Study

Background: Vitamin D deficiency is linked to adverse pregnancy outcomes like gestational diabetes mellitus (GDM), but its effects across ethnic groups are unclear. This study examines the relationship among vitamin D levels, glucose tolerance, GDM prevalence, and neonatal outcomes in a multi-ethnic cohort of pregnant women. Methods: We conducted a retrospective analysis of 252 pregnant women from antenatal clinics between 2018 and 2022. Participants were divided into four groups based on serum vitamin D levels: severely deficient (<25 nmol/L), deficient (25-50 nmol/L), insufficient (51-75 nmol/L), and sufficient (>75 nmol/L). The analysis included multivariate linear regression models adjusted for age, ethnicity, BMI, gestational diabetes status, and seasonality. An area under the receiver operating characteristic (AUROC) analysis identified the vitamin D threshold linked to an increased GDM risk. Results: Women classified as severely deficient had higher fasting glucose levels (5.73 ± 1.24 mmol/L) than those in other groups (p = 0.003, adjusted). The AUROC analysis identified a vitamin D threshold of 45 nmol/L associated with an elevated GDM risk (AUROC = 0.78, CI: 0.70-0.85). South Asian women had lower vitamin D levels (41.17 ± 18.03 nmol/L vs. 45.15 ± 16.75 nmol/L) and higher glucose tolerance test (GTT) levels than Caucasian women, despite having lower BMIs. Moreover, vitamin D levels positively correlated with neonatal birth weight (p = 0.02). Conclusions: There is a strong link between vitamin D deficiency and increased GDM risk, especially among South Asian women. These findings underscore the need for targeted interventions to improve vitamin D levels in high-risk ethnic groups.

Electronic Monitoring of Mom's Schedule (eMOMS™): A Feasibility Randomized Controlled Trial Targeting Postpartum Weight Retention and Breastfeeding Duration Among Populations With Overweight/Obesity

BACKGROUND

Globally, rising trends in gestational diabetes and body mass index contribute to maternal and neonatal morbidity and mortality. Lifestyle modifications and breastfeeding may reverse this effect, although few studies combine these into one intervention.

RESEARCH AIMS

To measure postpartum weight retention, breastfeeding duration, hemoglobin A1C, and mean arterial blood pressure at 6 months postpartum among women with elevated pre-pregnancy body mass index.

METHODS

The electronic Monitoring of Mom's Schedule study (eMOMS™) was a feasibility, three-arm, randomized controlled trial modeled after a Diabetes Prevention Program and breastfeeding support. A health coach delivered a 12-month virtual intervention. Study arm results were compared using Wilcoxon signed-ranks exact test reporting from a two-sided test and bootstrapped samples with 95% confidence intervals.

RESULTS

Between September 2019 and May 2021, 100 individuals were screened, and 35 were randomized: nine to Group 1, 14 to Group 2, and 12 to Group 3. At baseline, participants averaged 13.0 (SD = 2.5) weeks gestation, with a mean pre-pregnancy body mass index of 29.7 (SD = 3.0). With 5,000 bootstrapped samples, mean weight retention from baseline to 6 months postpartum was: 4.0 kg, 95% CI [1.6, 6.2] for Group 1; 3.7 kg, CI [-1.8, 9.8] for Group 2; and 7.5 kg, CI [4.1, 11.6] for Group 3. Mean (exclusive) breastfeeding duration was 9.3 weeks, 95% CI [0.43, 26.1]; 9.6 weeks, CI [4.4, 15.7]; and 15.1 weeks, CI [6.5, 23.3] for each group, respectively.

CONCLUSION

Our intervention was positively associated with postpartum weight retention and breastfeeding duration. Future research is needed to assess intervention components.

Evaluation of Faecal Microbiota Following Probiotics in Infants of Mothers with Gestational Diabetes Mellitus Trial: Protocol for Double-Blind Placebo-Controlled Randomized Trial

(1) Background: The incidence of gestational diabetes mellitus (GDM) is rising globally. The current evidence indicates that GDM, especially in conjunction with maternal overweight, can alter the composition of infants' gut microbiota, potentially increasing the risk of inflammatory diseases, metabolic disorders, and neurodevelopmental issues later in life. Probiotic supplantation early in life might establish eubiosis and mitigate future complications. To best of our knowledge, no study has evaluated the effects of probiotics on gut dysbiosis in the infants of mothers with GDM. (2) Methods: This study will be a single-centre, double-blind, randomized, placebo-controlled trial enrolling sixty neonates born after 35 weeks of gestation to mothers with GDM. The participants will be randomly assigned to receive either a triple-strain probiotic or a placebo for four months. The primary objective is to assess the effectiveness of probiotic supplementation in correcting gut dysbiosis in the infants of mothers with GDM at four months of age. Faecal microbiome composition shall be estimated using 16SrRNA and shotgun sequencing. The secondary outcomes will include the quantification of faecal short-chain fatty acids at birth and at four months, as well as growth and developmental assessments at four, twelve, and twenty-four months. (3) Trial registration: This trial protocol is registered (ACTRN12624000930583p) in the Australian Clinical Trials registry (ANZCTR).

Association between hyperglycemia during pregnancy and offspring's refractive error: A focused review

This review article explores the relationship between hyperglycemia during pregnancy and the visual development of offspring, specifically focusing on refractive error. The authors conducted a comprehensive search for relevant articles in various databases and assessed the methodological quality of the included studies. The findings consistently indicate that hyperglycemia during pregnancy can have a detrimental impact on the structural and functional aspects of visual development in offspring. The intrauterine hyperglycemic environment appears to negatively affect the retina and lens, leading to refractive errors. In conclusion, there is likely an association between hyperglycemia during pregnancy and the development of refractive errors in offspring.

Practical Considerations for Using Continuous Glucose Monitoring in Patients with Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is the most prevalent metabolic complication during pregnancy. GDM is associated with adverse perinatal, neonatal, and long-term health consequences. Studies have demonstrated that the use of continuous glucose monitoring (CGM) reduces the incidence of maternal and neonatal complications in pregnant women with type 1 diabetes. Although the use of CGM in GDM has not been well studied, a growing body of evidence is showing potential benefits in the GDM population. This article discusses the advantages and challenges of CGM and provides practical guidelines for using this technology in the GDM population.

The association between gestational diabetes and fear of childbirth: a longitudinal register study

BACKGROUND

Gestational diabetes mellitus is a common condition known to be associated with pregnancy complications, larger fetus size and depression, and may therefore lead to increased concerns linked to childbirth. We sought to determine whether gestational diabetes mellitus is linked to fear of childbirth, and whether the possible association is mediated by depressive symptoms.

METHODS

This study includes women who gave birth at the Kuopio University Hospital between 2019-2022 and had reported their level of fear of childbirth after gestational week 28 (n = 3293). Two outcome measures of fear of childbirth were used: self-rated intensity on a visual analogue scale, and obstetrician-confirmed diagnosis. Gestational diabetes mellitus was diagnosed based on plasma glucose concentrations in fasting state (≥ 5.3 mmol/l) and after a 75 g glucose load (one hour: ≥ 10.0 mmol/l, two hours: ≥ 8.6 mmol/l). The Edinburgh Postnatal Depression Scale (EPDS) was used to assess depressive symptoms in the third trimester. We performed logistic and linear regression analyses while adjusting for possible confounding factors and examined the controlled direct effect by including depressive symptoms in the model.

RESULTS

Gestational diabetes mellitus was associated with increased risk of fear of childbirth diagnosis (OR = 1.42, 95% CI 1.11─1.73) and higher levels of fear of childbirth (B = 0.31, 95% CI 0.09─0.53), but the associations were attenuated and no longer significant after further adjustments for body mass index and health behaviors (OR = 1.22, 95% CI 0.91─1.5; B = 0.11, 95% CI -0.13─0.35). Inclusion of depressive symptoms in the model attenuated the non-significant estimates further.

CONCLUSIONS

The observed association between fear of childbirth and gestational diabetes mellitus in previous studies may result from the lack of adjustments for confounding factors.

LncRNAs Involved in Antioxidant Response Regulation as Biomarkers of Gestational Diabetes: A Study on H19, MALAT1 and MEG3

Recent findings highlighted the potential of long non-coding RNAs (lncRNAs) as novel indicators of gestational diabetes mellitus (GDM), as they demonstrate altered expression in metabolic disorders, oxidative stress (OS) and inflammation (IFM). The aim of this study was to evaluate the diagnostic potential and prognostic significance of the OS/IFM-related lncRNAs H19, MALAT1 and MEG3 in GDM and their correlations with redox status-related parameters. The relative quantification of selected lncRNAs from peripheral blood mononuclear cells (PBMCs) of GDM patients and controls (n = 50 each) was performed by qPCR. The expression levels were tested for correlations with metal ion concentrations, NRF2 expression, activities of glutathione reductase (GR), superoxide dismutase (SOD), catalase (CAT), serum thiol content, protein carbonyl level and thiobarbituric acid reactive substances. MALAT1 and H19 were significantly downregulated in GDM patients (p = 0.0095 and p = 0.012, respectively). A correlation was observed between H19 expression and zinc levels in both GDM patients and controls. MALAT1 expression positively correlated with NFE2L2 levels in GDM patients (p = 0.026), while H19 exhibited a positive correlation with GR activity in controls (p = 0.018) and an inverse correlation with SOD activity (p = 0.048). Our data show the disturbance of OS/IFM-lncRNAs in GDM pathogenesis and illustrate the biomarker potential of the analyzed lncRNAs, as well as of certain redox status parameters.

Serum fibroblast growth factor 21: Lack of association with gestational diabetes and pregnancy outcomes

BACKGROUND

The prevalence of gestational diabetes mellitus (GDM) has been increasing worldwide and is associated with multiple adverse pregnancy outcomes. Despite standard screening, some cases remain undiagnosed. Fibroblast growth factor 21 (FGF21) plays a role in modulating glucose metabolism. There is an ongoing controversy regarding the relevance of FGF21 to GDM.

AIM

To evaluate the association between early second trimester serum FGF21 levels and gestational diabetes, and its predictive potential for outcomes.

METHODS

This cross-sectional observational study was conducted at a tertiary medical center, Chiang Mai University, Thailand. It included 28 pregnant women diagnosed with GDM and 81 pregnant women with normal glucose status. Blood samples were collected according to the study schedule, and pregnancy outcomes were recorded meticulously. Descriptive analysis was employed to evaluate the data.

RESULTS

Most participants in our study had no risk factors for GDM (body mass index < 24 kg/m², no first-degree relatives with diabetes, no history of GDM), normal baseline glucose status (fasting glucose < 110 mg/dL), and no insulin resistance (homeostatic model assessment of insulin resistance < 2). There was a trend of increased FGF21 levels in the insulin-treated GDM group compared with dietary-treated GDM and non-GDM (73.58 pg/mL vs 62.94 pg/mL vs 63.59 pg/mL, respectively, P = 0.73). However, no significant association was found between FGF21 concentrations and pregnancy outcomes based on quintiles of FGF21 levels.

CONCLUSION

FGF21 was not associated with GDM or pregnancy outcomes; however, due to the small sample size, larger clinical trials with a diverse population are suggested to confirm these results.

Relationship between life's essential 8 and the risk of gestational diabetes among us adults

OBJECTIVE

The purpose of this study is to explore the relationship between Life's Essential 8 (LE8) and the risk of gestational diabetes among US adults.

METHOD

We used National Health and Nutrition Examination Surveys 2007-2018 data to perform this study. LE8 scores comprised 4 health behaviors (diet, physical activity, nicotine exposure, and sleep duration) and 4 health factors (BMI, non-high-density lipoprotein [HDL] cholesterol, blood glucose, and blood pressure). Then, LE8 were categorized into low CVH (0 to 49 scores), moderated CVH (50 to 79 scores), and high CVH (80 to 100 scores). Weighted multivariate Logistic regression analysis model were used to estimate the relationship between LE8 and gestational diabetes.

RESULT

A total of 3,189 participants were included, and the portion of gestational diabetes was 15.33%, 11.46%, 7.71% in low CVH, moderate CVH, and high CVH, respectively. Adjustment for covariates, we found that high CVH (OR: 0.49, 95%CI: 0.29-0.83, p = 0.01) was associated with decreased of gestational diabetes, not moderate CVH (OR: 0.78, 95%CI: 0.50-1.20, p = 0.25). This inverse associations were dose-response dependent (p-nonlinear = 0.982). This inverse associations were significant in subgroup. Significant interaction between CVH and family diabetes with the risk of gestational diabetes was found (P for interaction = 0.04). High CVH (OR: 0.357, 95%CI: 0.176-0.724, p = 0.005) could significantly decrease the risk of gestational diabetes in the population with family diabetes. The results were generally robust in sensitivity analyses after excluding of ASCVD participants.

CONCLUSION

The high CVH could decrease the risk of gestational diabetes, especially in the population of family diabetes.

Interaction between time-of-day and oxytocin efficacy in mice and humans with and without gestational diabetes

Management of labor in women with diabetes is challenging due to the high risk of peri- and postpartum complications. To avoid cesarean section and assist with labor progression, Pitocin, a synthetic oxytocin, is frequently used to induce and augment labor. However, the efficacy of Pitocin is often compromised in diabetic pregnancies, leading to increased cesarian delivery. As diabetes deregulates the body's circadian timekeeping system and the time-of-day of the first Pitocin administration contributes to labor duration, our objective was to determine how the time of day and the circadian clock gene, Bmal1, gates oxytocin efficacy. Our studies in mice show that, compared to the rest phase of the day (lights on), the uterotonic efficacy of oxytocin is significantly increased during the active phase (lights off). Using in vitro studies, a myometrium-specific Bmal1 conditional knockout mouse model, and a mouse model of food-induced gestational diabetes, we find that Bmal1 is crucial for maintaining oxytocin receptor expression and response in the myometrium in mice. These findings also translate to humans, where oxytocin-induced human myometrial cell contraction is time-of-day dependent, and retrospective clinical data suggest that administration of Pitocin in the morning should be considered for pregnant women with gestational diabetes.

Gynecologic and Obstetric Pathologies from Birth to Menopause: Unveiling the Journey and Charting the Future

Gynecologic and obstetric pathologies encompass a vast array of conditions that affect women's health throughout their lives [...].

Breastfeeding frequency and incidence of type 2 diabetes among women with previous gestational diabetes compared to those without: a historical cohort study in the UK

BACKGROUND

There is a growing body of research to suggest that women with gestational diabetes are less likely to initiate and continue breastfeeding than those who have not had however findings are mixed. There is limited research in the UK assessing the frequency of breastfeeding in women with gestational diabetes, none reporting the association of breastfeeding with incidence of type 2 diabetes and existing research has not adequately adjusted for potential confounders. This study aims to assess frequency of breastfeeding among women with gestational diabetes compared to those without, and to explore how breastfeeding influences risk of future type 2 diabetes in women with gestational diabetes while adjusting for known confounders.

METHODS

Historical cohort study using routinely collected health care data from Fife and Tayside Health Boards, Scotland, UK including all women diagnosed with gestational diabetes between 1993 and 2015 and a matched comparator cohort (n = 4,968). Women with gestational diabetes were followed up until a diagnosis of type 2 diabetes, the end of the study, or date of death. Multinomial logistic regression was used to estimate odds ratios for breastfeeding for the whole sample and the association between breastfeeding and development of type 2 diabetes in women with gestational diabetes was assessed by Cox regression.

RESULTS

Women with a diagnosis of gestational diabetes, who were younger, overweight/obese or living in the most deprived areas were significantly less likely to exclusively breastfeed for a duration of longer than eight weeks. Risk of developing type 2 diabetes among women with gestational diabetes was significantly higher for those who exclusively breastfed less than 8 weeks, lived in the most deprived areas or had a family history of diabetes.

CONCLUSIONS

This study confirms the important role of a short duration of exclusive breastfeeding in protecting women with gestational diabetes against type 2 diabetes but highlights the challenges to breastfeeding in this group. Interventions are needed to support breastfeeding among women with gestational diabetes that are acceptable to younger, overweight/obese women living in deprived areas.

Utilizing the glucose challenge test during pregnancy as a predictor of future diabetes risk

BACKGROUND

Gestational Diabetes Mellitus (GDM) presents a significant health concern during pregnancy, predisposing individuals to future diabetes. Despite established postpartum diabetes screening guidelines, adherence to follow-up remains inadequate.

AIMS

This study aimed to assess the predictive value of the 50-gram glucose challenge test (GCT) for post-pregnancy diabetes development.

MATERIALS AND METHODS

A population-based retrospective cohort study was conducted on pregnant women aged 18-45 who underwent GCT screening between November 2007 and July 2017 in a large Israeli community medical organization. Baseline characteristics, GCT results, and diabetes development during follow-up were analyzed using univariate and multivariate Cox regression analyses.

RESULTS

Among 8,675 women included, 2.4% developed diabetes over a median follow-up of 73.23 months. Elevated GCT results correlated with a higher risk of future diabetes, with a 4% rise in risk per 1 mg/dL increase in glucose above 140 mg/dL. Multivariate analysis revealed a 60-fold rise in the risk of future diabetes in women with GCT results ≥ 200 mg/dL compared to those with GCT < 140 mg/dL, adjusting for age, body mass index, pre-pregnancy glucose, cholesterol, and triglycerides. A GCT result between 140 and 199 mg/dL was a predictor of future diabetes, even when adjusted for GDM based on a subsequent GTT if performed.

CONCLUSIONS

GCT results during pregnancy strongly predict future diabetes development, with higher GCT values significantly increasing risk. Recognizing abnormal GCT results as indicative of a prediabetic state offers a practical approach for risk stratification, facilitating early diagnosis, and intervention in post-pregnancy care.

Characteristics of Glucose-Lipid Metabolism in Early Pregnancy Among Overweight and Obese Women and Their Predictive Value for Gestational Diabetes Mellitus

Purpose

This study explores the link between women's pre-pregnancy overweight and obesity and glucose and lipid metabolism in their early pregnancy. It assesses how early pregnancy glucose and lipid levels predict gestational diabetes mellitus (GDM) risk, aiming to offer foundational weight management strategies for overweight and obese women to prevent GDM.

Patients and Methods

This study analyzed 2172 pregnant women from 2017 to 2021 at Waitan Street Community Health Service Center, Shanghai, monitoring early pregnancy (7-10 weeks) glucose and lipid levels (TG, TC, HDL-C, LDL-C, FBG, HbA1c) and 24-week OGTT values. Pre-pregnancy BMI categorized participants into overweight and obese, normal, and underweight groups. We compared early pregnancy glycemic and lipid metrics and GDM incidence across groups, examining the relationship between pre-pregnancy BMI and early pregnancy blood metrics. The overweight and obese cohort was further split into GDM and non-GDM groups, comparing early pregnancy glycolipid indicators and assessing their predictive value for GDM development.

Results

In the overweight and obese group, maternal FBG, HbA1c, TG, and LDL-C were higher, while HDL-C was lower than in normal and underweight groups (P<0.05), with a higher GDM incidence (P<0.05). Pre-pregnancy BMI positively correlated with FBG, HbA1c, TG, and LDL-C levels (r=0.556, 0.567, 0.686, 0.214; P<0.05) but not HDL-C. Each 1-unit BMI increase raised GDM risk by 0.204 times (P<0.05). FBG, TG, and LDL-C had high predictive accuracy for GDM in overweight and obese women, with AUCs of 0.991, 0.994, and 0.935, respectively.

Conclusion

Pre-pregnancy overweight and obesity can cause early pregnancy glucose and lipid abnormalities, raising GDM risk. Early testing in such women is a strong predictor for GDM.

Inflammatory indices-Systemic Immune-Inflammation Index (SII) and Systemic Inflammatory Response Index (SIRI)-during Pregnancy and Associations with Gestational Diabetes Mellitus

Purpose

Gestational diabetes mellitus (GDM) is a prevalent complication during pregnancy. This study aimed to explore the associations between inflammatory indices during pregnancy and the development of GDM.

Methods

Data from the Fujian Birth Cohort Study between March 2019 and December 2022 were used. Participants who delivered a live-born singleton were included and categorized into GDM and non-GDM groups. Two inflammatory indices, the systemic immune-inflammation index (SII) and systemic inflammatory response index (SIRI), were calculated for each trimester of pregnancy via hematological parameters from complete blood count tests. The distributions of inflammatory indicators across trimesters were compared between the GDM and non-GDM groups. Additionally, multivariable logistic regression models were employed to investigate the associations between inflammatory indices and the incidence of GDM.

Results

A total of 17297 participants were included, 21.2% of whom were diagnosed with GDM. In the first trimester, the median SIIs for the GDM and non-GDM groups were 817.7×109/L and 756.9×109/L, respectively, whereas the median SIRIs were 1.6×109/L and 1.5×109/L, respectively. In both groups, the SII increased to its peak in the second trimester before declining, whereas the SIRI progressively increased throughout pregnancy. The SII and SIRI were greater in the GDM group than in the non-GDM group during the first two trimesters but lower in the third trimester. Nonlinear positive associations between first-trimester SII and SIRI levels and GDM were observed, with extreme quartile odds ratios of 1.32 (95% CI: 1.19, 1.48) and 1.39 (95% CI: 1.24, 1.55), respectively.

Conclusion

The SII and SIRI increased and reached their peak values in the second and third trimesters of pregnancy, respectively. Elevated levels of the SII and SIRI in early pregnancy were linked to an increased risk of GDM, suggesting their potential utility as screening tools for GDM.

Gestational diabetes mellitus prevalence in Brazil: a systematic review and meta-analysis

This study estimates gestational diabetes mellitus prevalence in Brazil. A systematic review was conducted with articles published between 2010 and 2021 on the PubMed, Scopus, Google Scholar, SciELO, LILACS and Virtual Health Library databases, as well as gray literature. Data were extracted using a standardized instrument together with the risk of bias assessment tool proposed by Hoy et al. A meta-analysis with robust variance and random effects was developed. Heterogeneity was verified using I2 and publication bias was assessed using funnel plot and Egger's test. Prevalence according to risk of bias, diagnostic criteria and country's regions was determined by subgroup analyses. A total of 32 studies were included, representing 21,942 women. gestational diabetes mellitus pooled prevalence was 14% (95%CI: 11.0; 16.0), considerably higher than estimates from previous studies. Regarding risk of bias, studies with low, medium, and high risk showed a pooled prevalence of 12%, 14% and 14%, respectively. Overall GRADE certainty of evidence rating was low. Most studies used the International Association of Diabetes in Pregnancy Study Group (IADPSG) criteria or the adapted IADPSG, showing a pooled prevalence of 15% and 14%, respectively. As for region, the pooled prevalence was higher in the Southeast (14%) and lower in the Central-West (9%). This is the first systematic review to provide evidence on gestational diabetes mellitus prevalence at a national level and to demonstrate considerable heterogeneity among articles and the influence of region, diagnostic criteria and study quality on the referred indicator.

All Children Deserve to Be Safe, Mothers Too: Evidence and Rationale Supporting Continuous Glucose Monitoring Use in Gestational Diabetes Within the Medicaid Population

Gestational diabetes mellitus (GDM) is a common metabolic disease of pregnancy that threatens the health of several million women and their offspring. The highest prevalence of GDM is seen in women of low socioeconomic status. Women with GDM are at increased risk of adverse maternal outcomes, including increased rates of Cesarean section delivery, preeclampsia, perineal tears, and postpartum hemorrhage. However, of even greater concern is the increased risk to the fetus and long-term health of the child due to elevated glycemia during pregnancy. Although the use of continuous glucose monitoring (CGM) has been shown to reduce the incidence of maternal and fetal complications in pregnant women with type 1 diabetes and type 2 diabetes, most state Medicaid programs do not cover CGM for women with GDM. This article reviews current statistics relevant to the incidence and costs of GDM among Medicaid beneficiaries, summarizes key findings from pregnancy studies using CGM, and presents a rationale for expanding and standardizing CGM coverage for GDM within state Medicaid populations.

Trends in the Incidence of Gestational Diabetes Mellitus Among the Medicaid Population Before and During the COVID-19 Pandemic

Importance: Although there are many regional and national studies on the trends in the incidence of gestational diabetes mellitus (GDM), the trends in the incidence of GDM among the Medicaid population are lacking, especially before and during coronavirus disease of 2019 (COVID-19). Objective: To investigate the trends in the incidence of GDM before and during COVID-19 pandemic (2016-2021) among the Louisiana Medicaid population. Design, Setting, and Participants: This study included 111,936, Louisiana Medicaid pregnant women of age 18-50 between January 1, 2016, to December 31, 2021. Main Outcomes and Measures: Pregnancies, GDM, and pre-pregnancy diabetes cases were identified by using the Tenth Revisions of the International Classification of Disease code. The annual incidence of GDM and annual prevalence of pre-pregnancy diabetes were calculated for each age and race subgroup. Results: The age-standardized incidence of GDM increased from 10.2% in 2016 to 14.8 in 2020 and decreased to 14.0% in 2021. The age-standardized prevalence of pre-pregnancy diabetes increased from 2.8% in 2016 to 3.4% in 2018 and decreased to 2.3% in 2021. The age-standardized rate of GDM was the highest among Asian women (23.0%), then White women (15.5%), and African American women (13.9%) (p for difference <0.001). The COVID-19 pandemic saw an increase in the incidence of GDM, with a rise in prominent GDM risk factors, such as obesity and sedentary behaviors, suggesting an association. Conclusion and Relevance: The incidence of GDM significantly increased during the COVID-19 pandemic. Potential reasons might include increased sedentary behavior and increased prevalence of obesity. GDM is a major public health issue, and the prevention of GDM is particularly essential for the Louisiana Medicaid population owing to the high prevalence of GDM-related risk factors in this population.

Examining rurality and social determinants of health among women with GDM: a 15-year comprehensive population analysis

BACKGROUND

Gestational diabetes mellitus (GDM) is a common pregnancy complication with long-term health consequences for mothers and their children. The escalating trends of GDM coupled with the growing prevalence of maternal obesity, a significant GDM risk factor projected to approach nearly 60% by 2030 in Kansas, has emerged as a pressing public health issue.

METHODS

The aim of this study was to compare GDM and maternal obesity trends in rural and urban areas and investigate maternal demographic characteristics influencing the risk of GDM development over a 15-year period. Trend analyses and a binary logistic regression were employed utilizing 2005 to 2019 de-identified birth record vital statistics from the Kansas Department of Health and Environment (N = 589,605).

RESULTS

Over the cumulative 15-year period, a higher prevalence of GDM was observed across age, race/ethnicity, education, and insurance source. Throughout this period, there was an increasing trend in both GDM and obese pre-pregnancy BMI age-adjusted prevalence, with noticeable rural-urban disparities. From 2005 to 2019, women, including Asians (OR: 2.73, 95% CI 2.58%-2.88%), American Indian or Alaskan Natives (OR: 1.58, 95%, CI 1.44-1.73%), Hispanics (OR: 1.42, 95% CI 1.37%-1.48%), women residing in rural areas (OR: 1.09, 95%, CI 1.06-1.12%), with advanced maternal age (35-39 years, OR: 4.83 95% CI 4.47%-5.22%; ≥40 years, OR: 6.36 95%, CI 5.80-6.98%), with lower educational status (less than high school, OR: 1.15, 95% CI 1.10%-1.20%; high school graduate, OR: 1.10, 95% CI 1.06%-1.13%), Medicaid users (OR: 1.10, 95% CI 1.06%-1.13%), or with an overweight (OR: 1.78, 95% CI 1.72%-1.84%) or obese (OR: 3.61, 95% CI 3.50%-3.72%) pre-pregnancy BMI were found to be at an increased risk of developing GDM.

CONCLUSIONS

There are persistent rural-urban and racial/ethnic disparities present from 2005 to 2019 among pregnant women in Kansas with or at-risk of GDM. There are several socioeconomic factors that contribute to these health disparities affecting GDM development. These findings, alongside with prominent rising maternal obesity trends, highlight the need to expand GDM services in a predominantly rural state, and implement culturally-responsive interventions for at-risk women.

Lysophosphatidylcholine Impairs the Mitochondria Homeostasis Leading to Trophoblast Dysfunction in Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a common pregnancy disorder associated with an increased risk of pre-eclampsia and macrosomia. Recent research has shown that the buildup of excess lipids within the placental trophoblast impairs mitochondrial function. However, the exact lipids that impact the placental trophoblast and the underlying mechanism remain unclear. GDM cases and healthy controls were recruited at Kaohsiung Medical University Hospital. The placenta and cord blood were taken during birth. Confocal and electron microscopy were utilized to examine the morphology of the placenta and mitochondria. We determined the lipid composition using liquid chromatography-mass spectrometry in data-independent analysis mode (LC/MSE). In vitro studies were carried out on choriocarcinoma cells (JEG3) to investigate the mechanism of trophoblast mitochondrial dysfunction. Results showed that the GDM placenta was distinguished by increased syncytial knots, chorangiosis, lectin-like oxidized low-density lipoprotein (LDL) receptor-1 (LOX-1) overexpression, and mitochondrial dysfunction. Lysophosphatidylcholine (LPC) 16:0 was significantly elevated in the cord blood LDL of GDM patients. In vitro, we demonstrated that LPC dose-dependently disrupts mitochondrial function by increasing reactive oxygen species (ROS) levels and HIF-1α signaling. In conclusion, highly elevated LPC in cord blood plays a pivotal role in GDM, contributing to trophoblast impairment and pregnancy complications.

Gestational Diabetes and Subsequent Metabolic Dysfunction: An National Health and Nutrition Examination Survey Analysis (2011-2018)

Background: Gestational diabetes mellitus (GDM) complicates ∼10% of pregnancies, with the highest rates among Asian women. Evidence suggests that GDM is associated with an increased risk for future chronic health conditions, yet data for Asian women are sparse. We explored the association between prior GDM and metabolic dysfunction with nationally representative data to obtain Asian-specific estimates. Methods: For this cross-sectional study, data were drawn from the National Health and Nutrition Examination Survey for 7195 women with a prior pregnancy. GDM (yes/no) was defined using the question "During pregnancy, were you ever told by a doctor or other health professional that you had diabetes, sugar diabetes, or gestational diabetes?." Current metabolic dysfunction (yes/no) was based on having at least one of four indicators: systolic blood pressure (SBP, ≥130 mmHg), waist circumference (≥88 cm), high-density lipoprotein (HDL) cholesterol (<50 mg/dL), and glycosylated hemoglobin (HbA1c) (≥6.5%). Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association between prior GDM and metabolic outcomes, overall and by race. Models included sampling weights and demographic and behavioral factors. Results: Overall, women with prior GDM had 46% greater odds of high waist circumference (OR: 1.5; 95% CI: 1.1-2.0) and 200% greater odds (OR: 3.0; 95% CI: 2.1-4.2) of high HbA1c. Prior GDM was not associated with high blood pressure or low HDL cholesterol. In race-specific analyses, prior GDM was associated with increased risk of elevated HbA1c among Asian (OR: 6.6; 95% CI: 2.5-17.2), Mexican American (OR: 3.0; 95% CI: 1.5-5.8), Black (OR: 3.0; 95% CI: 1.7-5.5), and White (OR: 2.6; 95% CI: 1.5-4.6) women. Prior GDM was associated with elevated SBP among Mexican American women and low HDL among Black women. Discussion: Prior GDM is associated with elevated HbA1c among all women, yet is a stronger predictor of elevated HbA1c among Asian women than other women. Race-specific associations between prior GDM and metabolic dysfunction were observed among Mexican American and Black women. Further research is warranted to understand the observed race/ethnic-specific associations.

Associations Between Serum Vitamin A Levels in Early Pregnancy and the Risk of Gestational Diabetes Mellitus

Background

The relationship between vitamin A levels and gestational diabetes mellitus (GDM) is not well understood, and prospective studies are lacking.

Methods

This was a prospective, longitudinal study. A total of 391 women in early pregnancy were recruited between October and December 2018 at Shunyi District Maternal and Child Health Hospital (Beijing, China). Serum vitamin A concentration was measured at enrollment. GDM was diagnosed on the basis of a 75 g oral glucose-tolerance test at 24-28 weeks of follow-up. Logistic regression was used for the analysis.

Results

None of the subjects in the cohort had vitamin A deficiency or excess. At the follow-up, 76 participants had developed GDM. Participants who developed GDM were older and had higher body mass index, fasting insulin, HbA1c, fasting glucose, homeostasis model assessment for insulin resistance, triglyceride, low-density lipoprotein cholesterol, and high-sensitivity CRP levels, as well as higher serum vitamin A levels at baseline. On logistic multivariate analysis, higher vitamin A was positively associated with higher risk of GDM. The adjusted OR was 2.85 (95% CI 1.04-7.80, P=0.042) for Q4 versus Q1 and 1.59 (95% CI 1.11-2.28, P=0.011) for every 1 SD increase in serum vitamin A levels. In participants within the vitamin A reference range (0.33-0.78 mg/L), the positive association also maintained significance.

Conclusion

Higher serum vitamin A levels were associated with higher GDM risks, even within the reference range. The results and possible mechanisms need to be further verified and clarified.

Benefits of Resistance Training During Pregnancy for Maternal and Fetal Health: A Brief Overview

Research demonstrates resistance training is not only safe but also beneficial for pregnant women. However, exercise recommendations for pregnant women still minimize the importance of resistance exercise and provide minimal guidance. With a large increase in strength-focused sports among women, it is critical to re-evaluate the risk/benefit ratio of these exercises and ensure the latest recommendations reflect the latest clinical research. The purpose of this review is to highlight the safety and benefits of resistance training for both maternal and fetal health, particularly focusing on recent work. Relevant research involving resistance training during pregnancy was accessed and analyzed via a quasi-systematic search. Results demonstrate that appropriate prenatal resistance training can help alleviate some of the common symptoms of pregnancy, such as fatigue, back pain, and poor mental health. Resistance exercise can assist with glucose control in gestational diabetes mellitus, as well as decrease the risk of infant macrosomia and childhood metabolic dysfunction associated with uncontrolled gestational diabetes. Resistance training can also increase the likelihood of a vaginal delivery, which is beneficial for both mother and baby. Concerning fetal health, resistance training increases uterine blood flow, decreases the risk of neonatal macrosomia, and improves cognitive function and metabolic health in childhood. As with all forms of exercise, pregnant women should avoid resistance exercises that involve the supine position for extended bouts of time, trauma (or risk of trauma) to the abdomen, ballistic movements, movements that rely heavily on balance, and conditions that prohibit appropriate temperature control. With these considerations in mind, resistance training's benefits far surpass the lack of risk to the fetus. Resistance training is a safe and effective way to improve and maintain physical fitness during pregnancy and represents no risk to fetal health and development. Thus, healthcare providers should recommend resistance training for pregnant women.

Gestational Metabolic Risk: A Narrative Review of Pregnancy-Related Complications and of the Effectiveness of Dietary, Exercise and Lifestyle Interventions during Pregnancy on Reducing Gestational Weight Gain and Preventing Gestational Diabetes Mellitus

Objective: This study is a Narrative Review that aims at investigating the implications of obesity, excessive gestational weight gain (GWG) and gestational diabetes mellitus (GDM). Additionally, this Review seeks to explore the effectiveness of nutrition, and/or exercise interventions during pregnancy on reducing GWG and preventing GDM. Materials and Methods: The search in literature included studies that identified obesity, GWG, GDM and associated risks during pregnancy. Also, SR and MA focusing on interventions including diet, or physical activity (PA), or combined (i.e., lifestyle interventions) and their impact on metabolic risk during pregnancy, were identified through searches in PubMed, Cochrane Database of Systematic Reviews (CDSRs), and Scopus. Results: The study findings suggest that lifestyle interventions during pregnancy may be effective in reducing excessive GWG. Regarding the prevention of GDM, results from studies evaluating lifestyle interventions vary. However, significant and less controversial results were reported from studies assessing the efficacy of exercise interventions, particularly in high-risk pregnant women. Conclusions: Lifestyle interventions during pregnancy may reduce excessive GWG. Exercise during pregnancy may prevent GDM, especially in high-risk pregnant women. Future research is warranted to tailor lifestyle interventions for optimal effectiveness during pregnancy.

Neighborhood Environment and Poor Maternal Glycemic Control-Associated Complications of Gestational Diabetes Mellitus

Introduction

Risk of complications due to gestational diabetes mellitus is increasing in the U.S., particularly among individuals from racial minorities. Research has focused largely on clinical interventions to prevent complications, rarely on individuals' residential environments. This retrospective cohort study aims to examine the association between individuals' neighborhoods and complications of gestational diabetes mellitus.

Methods

Demographic and clinical data were extracted from electronic health records and linked to American Community Survey data from the U.S. Census Bureau for 2,047 individuals who had 2,164 deliveries in 2014-2018. Data were analyzed in 2021-2022 using Wilcoxon rank sum test and chi-square test for bivariate analyses and logistic regression for analysis of independent effects. All census tract-based variables used in the model were dichotomized at the median.

Results

Bivariate analysis showed that the average percentage of adults earning <$35,000 was higher in neighborhoods where individuals with complications were living than in neighborhoods where individuals without complications were living (30.40%±12.05 vs 28.94%±11.71, p=0.0145). Individuals who lived in areas with ≥8.9% of residents aged >25 years with less than high school diploma had a higher likelihood of complications than those who lived in areas with <8.9% of such residents (33.43% vs 29.02%, p=0.0272). Individuals who lived in neighborhoods that had ≥1.8% of households receiving public assistance were more likely to have complications than those who lived in areas where <1.8% of households received public assistance (33.33% vs 28.97%, p=0.0287). Logistic regression revealed that the odds of deliveries with complications were 44% higher for individuals with obesity (OR=1.44; 95% CI=1.17, 1.77), 35% greater for individuals residing in neighborhoods with higher percentages of households living below the poverty level (OR=1.35; 95% CI=1.09, 1.66), and 28% lower for individuals from neighborhoods where a higher percentage of households had no vehicles available for transportation to work (OR=0.72; 95% CI=0.59, 0.89).

Conclusions

Clinical interventions in concert with environmental changes could contribute to preventing maternal and neonatal complications of gestational diabetes mellitus.

Comprehensive data on the relationship between KCNJ11 polymorphisms and gestational diabetes mellitus predisposition: a meta-analysis

Purpose

The genetic aspect of gestational diabetes mellitus (GDM) is influenced by multiple causal genetic variants, each with different effect sizes. The KCNJ11 gene is particularly noteworthy as a potential contributor to the risk of GDM due to its role in regulating glucose-induced insulin secretion. To evaluate the association between KCNJ11 polymorphisms and GDM, a comprehensive meta-analysis was conducted to review the existing literature and quantitatively assess the correlation.

Methods

A thorough search was performed on the PubMed, EMBASE, Scopus, and CNKI databases until December 25, 2023, using precise terms and keywords related to Gestational Diabetes, KCNJ11 gene, and polymorphism. Odds ratios and 95% confidence intervals were used to evaluate the relationships. The statistical analysis was conducted using Comprehensive Meta-Analysis software, and the Cochrane risk of bias assessment tool was used to determine bias presence.

Results

The meta-analysis comprised 9 studies with 3108 GDM cases and 5374 controls for the rs5219 polymorphism, and 3 studies with 1209 GDM cases and 1438 controls for the rs5210 polymorphism. The pooled data indicated a noteworthy link between the rs5219 polymorphism and GDM globally and among various ethnic groups, notably in Caucasian and Asian populations. However, no substantial association was observed between the rs5210 polymorphism and GDM.

Conclusions

Pooled data showed a correlation between the KCNJ11 rs5219 polymorphism and GDM susceptibility, but no association was found for the rs5210 polymorphism. Future research with larger sample sizes and more diverse populations is needed to improve result generalizability.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-024-01428-0.

Protocol for cost-effectiveness analysis of a randomised trial of mHealth coaching (Bump2Baby and Me) compared with usual care for healthy gestational weight gain and postnatal outcomes in at-risk women and their offspring in the UK, Australia, Ireland and Spain

INTRODUCTION

Gestational diabetes mellitus and overweight are associated with an increased likelihood of complications during birth and for the newborn baby. These complications lead to increased immediate and long-term healthcare costs as well as reduced health and well-being in women and infants. This protocol presents the health economic evaluation to investigate the cost-effectiveness of Bump2Baby and Me (B2B&Me), which is a health coaching intervention delivered via smartphone to women at risk of gestational diabetes.

METHODS AND ANALYSIS

Using data from the B2B&Me randomised controlled trial, this economic evaluation compares costs and health effects between the intervention and control group as an incremental cost-effectiveness ratio. Direct healthcare costs, costs of pharmaceuticals and intervention costs will be included in the analysis, body weight and quality-adjusted life-years for the mother will serve as the effect outcomes. To investigate the long-term cost-effectiveness of the trial, a Markov model will be employed. Deterministic and probabilistic sensitivity analysis will be employed.

ETHICS AND DISSEMINATION

The National Maternity Hospital Human Research and Ethics Committee was the primary approval site (EC18.2020) with approvals from University College Dublin HREC-Sciences (LS-E-20-150-OReilly), Junta de Andalucia CEIM/CEI Provincial de Granada (2087-M1-22), Monash Health HREC (RES-20-0000-892A) and National Health Service Health Research Authority and Health and Care Research Wales (HCRW) (21/WA/0022). The results from the analysis will be disseminated in scientific papers, through conference presentations and through different channels for communication within the project.

TRIAL REGISTRATION NUMBER

ACTRN12620001240932.

Quantifying the Occurrence of High-Risk Pregnancy: A Comprehensive Survey

Background High-risk pregnancies are characterized by various factors that pose potential risks to maternal and newborn health outcomes. Early detection of these high-risk pregnancies serves as a crucial initial step in preventing maternal mortality and morbidity, thereby promoting the overall health of both mother and baby. This study sought to assess the occurrence of high-risk pregnancy and investigate the factors associated with it among pregnant women. Methods A descriptive survey was undertaken at the Obstetrics and Gynaecology outpatient department of a District Government Hospital in Tamil Nadu, involving 1889 pregnant women in their second and third trimesters. A structured questionnaire, constructed following the Indian standard criteria outlined by the National Health Portal of India, served as the data collection tool. The survey was conducted in February and March 2022, during which pregnant women were interviewed. Subsequently, the collected data underwent descriptive and inferential statistical analysis. Results Among the 1889 pregnant women surveyed, 29% (n=530) were classified as high-risk pregnancies. Within this group, 34.3% (n=182) were diagnosed with hypothyroidism, while 23.2% (n=123) experienced pregnancy-induced hypertension. Significant associations with high-risk pregnancy were observed for factors such as age, education status, occupation, family income, socioeconomic status, and gravida among the pregnant women. Conclusion Policymakers must urgently implement evidence-based interventions aimed at early detection and treatment of high-risk pregnancies. This proactive approach is essential in preventing maternal mortality and morbidity.

Maternal gestational diabetes and childhood adiposity risk from 6 to 8 years of age

BACKGROUND/OBJECTIVE

Previous studies found conflicting results on the association between maternal gestational diabetes mellitus (GDM) and childhood overweight/obesity. This study was to assess the association between maternal GDM and offspring's adiposity risk from 6 to 8 years of age.

METHODS

The present study longitudinally followed 1156 mother-child pairs (578 GDM and 578 non-GDM) at 5.9 ± 1.2 years postpartum and retained 912 mother-child pairs (486 GDM and 426 non-GDM) at 8.3 ± 1.6 years postpartum. Childhood body mass index (BMI), waist circumference, body fat and skinfold were measured using standardized methods.

RESULTS

Compared with the counterparts born to mothers with normal glucose during pregnancy, children born to mothers with GDM during pregnancy had higher mean values of adiposity indicators (waist circumference, body fat, subscapular skinfold and suprailiac skinfold) at 5.9 and 8.3 years of age. There was a positive association of maternal GDM with changes of childhood adiposity indicators from the 5.9-year to 8.3-year visit, and β values were significantly larger than zero: +0.10 (95% CI: 0.02-0.18) for z score of BMI for age, +1.46 (95% CI: 0.70-2.22) cm for waist circumference, +1.78% (95% CI: 1.16%-2.40%) for body fat, +2.40 (95% CI: 1.78-3.01) mm for triceps skinfold, +1.59 (95% CI: 1.10-2.09) mm for subscapular skinfold, and +2.03 (95% CI: 1.35-2.71) mm for suprailiac skinfold, respectively. Maternal GDM was associated with higher risks of childhood overweight/obesity, central obesity, and high body fat (Odd ratios 1.41-1.57 at 5.9 years of age and 1.73-2.03 at 8.3 years of age) compared with the children of mothers without GDM.

CONCLUSIONS

Maternal GDM was a risk factor of childhood overweight/obesity at both 5.9 and 8.3 years of age, which was independent from several important confounders including maternal pre-pregnancy BMI, gestational weight gain, children's birth weight and lifestyle factors. This significant and positive association became stronger with age.

Filling a gap in OBGYN education: a pilot lecture series on perinatal mental health

Perinatal mood and anxiety disorders (PMADs) are one of the most common complications in the peripartum period. The Council for Resident Education in Obstetrics and Gynecology (CREOG) includes diagnosis and management of PMADs as educational objectives, but no formal curriculum for trainees exists. Consequently, providers often struggle to identify and treat these disorders. We aimed to assess the effects of a pilot lecture series on obstetrics and gynecology (OBGYN) residents' knowledge and comfort in the diagnosis and management of PMADs. As part of an educational cross-sectional study, a Qualtrics survey was distributed to OBGYN residents at a single center in New York City. Residents were exposed to a 10-h virtual lecture series on perinatal mental health, and a follow-up survey was distributed. Initially, few residents were familiar with screening tools (45%), and few felt comfortable providing resources (5-45%), diagnosing (0-55%), and managing (0-30%) patients with the PMADs presented. After the pilot, improvement was seen in residents' familiarity with screening tools (86%), and their comfort in providing resources (11-67%) and diagnosing (11-78%) PMADs. However, comfort in management did not improve (0-22%). The majority of trainees (75%) found the virtual setting appropriate. There is a deficit in OBGYN residents' knowledge and comfort regarding diagnosis and discussion of PMADs that can be improved with a focused lecture series, though a greater emphasis on treatment is needed. The majority of OBGYN learners found the virtual setting conducive to learning this material. Their preferences should guide the development of a formal, national curriculum.

Assessment of potential risk factors associated with gestational diabetes mellitus: evidence from a Mendelian randomization study

Background

Previous research on the association between risk factors and gestational diabetes mellitus (GDM) primarily comprises observational studies with inconclusive results. The objective of this study is to investigate the causal relationship between 108 traits and GDM by employing a two-sample Mendelian randomization (MR) analysis to identify potential risk factors of GDM.

Methods

We conducted MR analyses to explore the relationships between traits and GDM. The genome-wide association studies (GWAS) for traits were primarily based on data from the UK Biobank (UKBB), while the GWAS for GDM utilized data from FinnGen. We employed a false discovery rate (FDR) of 5% to account for multiple comparisons.

Results

The inverse-variance weighted (IVW) method indicated that the genetically predicted 24 risk factors were significantly associated with GDM, such as "Forced expiratory volume in 1-second (FEV1)" (OR=0.76; 95% CI: 0.63, 0.92), "Forced vital capacity (FVC)" (OR=0.74; 95% CI: 0.64, 0.87), "Usual walking pace" (OR=0.19; 95% CI: 0.09, 0.39), "Sex hormone-binding globulin (SHBG)" (OR=0.86; 95% CI: 0.78, 0.94). The sensitivity analyses with MR-Egger and weighted median methods indicated consistent results for most of the trats.

Conclusion

Our study has uncovered a significant causal relationship between 24 risk factors and GDM. These results offer a new theoretical foundation for preventing or mitigating the risks associated with GDM.

Association of vitamin A with gestational diabetes and thyroid disorders in pregnancy and their influence on maternal, fetal, and neonatal outcomes

Gestational diabetes mellitus (GDM) and thyroid disorders during pregnancy pose significant health concerns, impacting a substantial number of mothers globally. Globally, about 14% of pregnant women develop GDM, while thyroid disorders impact approximately 2%-3%. Both conditions contribute to adverse outcomes, including gestational hypertension, excessive fetal growth, and heightened perinatal morbidity. The central focus of this literature review is to examine the relationship between vitamin A, a crucial fat-soluble micronutrient in fetal development, and the occurrence of GDM and thyroid disorders during pregnancy. The primary research question investigates the association between vitamin A, GDM, and thyroid disorders, analyzing their combined impact on maternal, fetal, and neonatal outcomes. The review underscores the potential of vitamin A to modulate the risk and outcomes of GDM and thyroid disorders during gestation, emphasizing its role in GDM development and resolution and its influence on thyroid function in pregnancy.

Impact of adverse pregnancy outcomes on brain vascular health and cognition

A State of the Art lecture titled "Impact of Adverse Pregnancy Outcomes on Brain Vascular Health and Cognition" was presented at the International Society on Thrombosis and Haemostasis Congress in 2023. Adverse pregnancy outcomes, encompassing conditions such as gestational hypertension, eclampsia, preeclampsia, preterm birth, fetal growth restriction, stillbirth, and gestational diabetes, may form part of an underrecognized pathway from early adulthood reproductive health factors to later-life vascular cognitive impairment and dementia in women. Adverse pregnancy outcomes are caused by dysregulated vascular and metabolic adaptations during pregnancy, and these pathophysiological changes may persist after delivery. Adverse pregnancy outcomes may contribute to the increased risk of cognitive impairment and dementia directly through vascular and metabolic dysregulation and subsequent development of cardiovascular diseases, or other biological processes may be at play, such as shared maternal risk factors. Extensive epidemiologic evidence has shown that many cognitive impairment and dementia cases may be prevented or delayed by strategies targeting midlife cardiovascular health. Despite the recognized importance of adverse pregnancy outcomes for cardiovascular health, the literature on associated long-term health outcomes is limited. In this State of the Art review article, we summarize the current epidemiologic evidence on the relationship between adverse pregnancy outcomes and cognitive impairment and dementia and provide an overview of the potential pathophysiological mechanisms. Finally, we summarize relevant new data on this topic presented during the 2023 International Society on Thrombosis and Haemostasis Congress.

Time trends and projections in the prevalence of gestational diabetes mellitus in Queensland, Australia, 2009-2030: Evidence from the Queensland Perinatal Data Collection

BACKGROUND

Gestational diabetes mellitus (GDM) is the fastest-growing type of diabetes in Australia. We aimed to assess the time trends during 2009-2018 and projections of GDM in Queensland, Australia up to 2030.

MATERIALS AND METHODS

The study data were from the Queensland Perinatal Data Collection (QPDC) and included data on 606 662 birth events with the births reported from at least 20 weeks gestational age or birth weight at least 400 g. Bayesian regression model was used to assess the trends in the prevalence of GDM.

RESULTS

The prevalence of GDM increased from 5.47 to 13.62% from 2009 to 2018 (average annual rate of change, AARC = +10.71%). If the trend remains the same, the projected prevalence will increase to 42.04% (95% uncertainty interval = 34.77-48.96) by 2030. Observing AARC across different subpopulations, we found that the trend of GDM increased markedly among women living in inner regional areas (AARC = +12.49%), were non-Indigenous (AARC = +10.93%), most disadvantaged (AARC = +11.84%), aged either of two age groups (AARC = +18.45% and + 15.17% for <20 years and 20-24 years, respectively), were with obesity (AARC = +11.05%) and smoked during pregnancy (AARC = +12.26%).

CONCLUSIONS

Overall, the prevalence of GDM has sharply increased in Queensland, and if this trend continues, about 42% of pregnant women will experience GDM by 2030. The trends vary across different subpopulations. Therefore, targeting the most vulnerable subpopulations is vital to prevent the development of GDM.

Unraveling the Link: A Comprehensive Literature Review of Type 2 Diabetes and Menopause Onset

Women with diabetes mellitus (DM), a metabolic endocrine illness, may experience a variety of reproductive problems. The age at menopause onset has been extensively studied as a major predictor of women's health in the future; however, its relationship to diabetes in Indian women has received less attention. This literature review looked at the consequences of diabetes in women as well as the association between diabetes and the age at which menopause begins. The average age at menopause onset among women with type 2 diabetes mellitus (T2DM) has decreased globally. According to one Indian study, the average menopause age dropped to 45 years for 26% of women with T2DM. In the current review, 10 studies indicated that women with T2DM displayed an imbalanced hormonal profile resulting in an extended anovulatory period. Two investigations highlighted the significance of altered body composition of women with T2DM, thereby suggesting obesity as the primary risk factor of ovarian aging and early climacteric symptoms. T2DM may lower the average age at menopause onset; however, further research on Indian women is necessary. There is a need of studies on T2DM in premenopausal women are needed to demonstrate how the changes in body composition impact the age at which menopause begins. Delaying the onset of menopause in women with T2DM necessitates diet and lifestyle interventions to minimize ovarian aging and hormonal imbalance.

The CHANGED Score-A New Tool for the Prediction of Insulin Dependency in Gestational Diabetes

Gestational diabetes (GDM) is a frequent complication during pregnancy. We aimed to develop a score to predict future insulin dependency in gestational diabetes (GDM). Data from 1611 patients from Charité Berlins gestational diabetes clinic from 2015 to 2022 were utilized. A stepwise backwards regression, including patient characteristics obtained at the initial presentation, was performed. Predictors examined included age, fasting blood glucose level, blood glucose levels one and two hours after oral glucose tolerance test, pre-pregnancy BMI, number of previous pregnancies and births, and fetal sex. The ideal cutoff value between high and low risk for insulin dependency was assessed and the score was internally validated. There were 1249 (77.5%) women diagnosed with dietary GDM and 362 (22.5%) were diagnosed with insulin-dependent GDM. The CHarité AssessmeNt of GEstational Diabetes (CHANGED) Score achieved an area under the curve of 0.77 (95% confidence interval 0.75-0.80; 0.75 in internal validation). The optimal cutoff value was calculated at a score value of 9 (72% sensitivity, 69% specificity). We developed an easily applicable tool to accurately predict insulin dependency in gestational diabetes. The CHANGED Score is routinely available and can potentially improve maternal and fetal outcomes.

Temporal Patterns of Diabetes in Pregnancy: Analyzing Pregestational and Gestational Diabetes Mellitus Among Women Aged 15-44 Years Using the United States Diabetes Surveillance System (USDDS) Database

BACKGROUND

Diabetes in pregnancy, including pregestational diabetes mellitus (PGDM) and gestational diabetes mellitus (GDM), is a significant global health concern. Understanding its temporal patterns is crucial for effective healthcare planning and intervention strategies.

METHODS

This retrospective observational study utilized data from the United States Diabetes Surveillance System (USDDS) spanning 2000 to 2019. We conducted a comprehensive analysis of temporal trends in PGDM and GDM prevalence among people aged 15-44 years. Additionally, age and race-based subgroup analyses were performed to identify variations in diabetes patterns.

RESULTS

Over the two-decade study period, PGDM and GDM exhibited distinct temporal patterns. PGDM prevalence remained stable initially (1.1% per 100 deliveries) but gradually increased to 1.6% by 2019. In contrast, GDM prevalence showed a consistent rise, reaching 9.6% per 100 deliveries by 2019. Age-specific analysis revealed higher prevalence rates in older age groups, peaking at 40-44 years. Race-based analyses unveiled significant disparities, with Asians having the highest GDM rates and Black individuals having the highest PGDM rates.

CONCLUSION

The prevalence of diabetes in pregnancy in the United States has increased significantly from 2000 to 2019, emphasizing the need for continued surveillance and tailored interventions. Age and race-specific disparities highlight the importance of the growing impact of diabetes in pregnancy on maternal and fetal health.

Maternal cardiovascular disorders before and during pregnancy and offspring cardiovascular risk across the life course

Obesity, hypertension, type 2 diabetes mellitus and dyslipidaemia are highly prevalent among women of reproductive age and contribute to complications in >30% of pregnancies in Western countries. An accumulating body of evidence suggests that these cardiovascular disorders in women, occurring before and during their pregnancy, can affect the development of the structure, physiology and function of cardiovascular organ systems at different stages during embryonic and fetal development. These developmental adaptations might, in addition to genetics and sociodemographic and lifestyle factors, increase the susceptibility of the offspring to cardiovascular disease throughout the life course. In this Review, we discuss current knowledge of the influence of maternal cardiovascular disorders, occurring before and during pregnancy, on offspring cardiovascular development, dysfunction and disease from embryonic life until adulthood. We discuss findings from contemporary, large-scale, observational studies that provide insights into specific critical periods, evidence for causality and potential underlying mechanisms. Furthermore, we focus on priorities for future research, including defining optimal cardiovascular and reproductive health in women and men before their pregnancy and identifying specific embryonic, placental and fetal molecular developmental adaptations from early pregnancy onwards. Together, these approaches will help stop the intergenerational cycle of cardiovascular disease.

Group vs Individual Prenatal Care and Gestational Diabetes Outcomes: A Secondary Analysis of a Randomized Clinical Trial

Importance

The impact of group-based prenatal care (GPNC) model in the US on the risk of gestational diabetes (GD) and related adverse obstetric outcomes is unknown.

Objective

To determine the effects of the GPNC model on risk of GD, its progression, and related adverse obstetric outcomes.

Design, Setting, and Participants

This is a single-site, parallel-group, randomized clinical trial conducted between February 2016 and March 2020 at a large health care system in Greenville, South Carolina. Participants were individuals aged 14 to 45 years with pregnancies earlier than 21 weeks' gestational age; follow-up continued to 8 weeks post partum. This study used an intention-to-treat analysis, and data were analyzed from March 2021 to July 2022.

Interventions

Eligible participants were randomized to receive either CenteringPregnancy, a widely used GPNC model, with 10 group-based sessions or traditional individual prenatal care (IPNC).

Main Outcomes and Measures

The primary outcome was the incidence of GD diagnosed between 24 and 30 weeks of gestation. The secondary outcomes included progression to A2 GD (ie, GD treated with medications) and GD-related adverse obstetric outcomes (ie, preeclampsia, cesarean delivery, and large for gestational age). Log binomial models were performed to estimate risk differences (RDs), 95% CIs, and P values between GPNC and IPNC groups, adjusting for all baseline covariates.

Results

Of all 2348 participants (mean [SD] age, 25.1 [5.4] years; 952 Black participants [40.5%]; 502 Hispanic participants [21.4%]; 863 White participants [36.8%]), 1176 participants were randomized to the GPNC group and 1174 were randomized to the IPNC group. Among all participants, 2144 (91.3%) completed a GD screening (1072 participants [91.3%] in GPNC vs 1071 [91.2%] in IPNC). Overall, 157 participants (6.7%) developed GD, and there was no difference in GD incidence between the GPNC (83 participants [7.1%]) and IPNC (74 participants [6.3%]) groups, with an adjusted RD of 0.7% (95% CI, -1.2% to 2.7%). Among participants with GD, GPNC did not reduce the risk of progression to A2 GD (adjusted RD, -6.1%; 95% CI, -21.3% to 9.1%), preeclampsia (adjusted RD, -7.9%; 95% CI, -17.8% to 1.9%), cesarean delivery (adjusted RD, -8.2%; 95% CI, -12.2% to 13.9%), and large for gestational age (adjusted RD, -1.2%; 95% CI, -6.1% to 3.8%) compared with IPNC.

Conclusions and Relevance

In this secondary analysis of a randomized clinical trial among medically low-risk pregnant individuals, the risk of GD was similar between participants who received GPNC intervention and traditional IPNC, indicating that GPNC may be a feasible treatment option for some patients.

Trial Registration

ClinicalTrials.gov Identifier: NCT02640638.

Profiles and Outcomes of Women with Gestational Diabetes Mellitus in the United States

Introduction Gestational diabetes mellitus (GDM) is a major contributor to adverse pregnancy outcomes both in the United States and globally. As the prevalence of obesity continues to rise, the incidence of GDM is anticipated to increase as well. Despite the significant impact of GDM on maternal and neonatal health, research examining the independent associations between GDM and adverse outcomes remains limited in the U.S. context. Objective This study aims to address this knowledge gap and further elucidate the relationship between GDM and maternal and neonatal health outcomes. Method We performed a retrospective study using data from the United States Vital Statistics Records, encompassing deliveries that occurred between January 2015 and December 2019. Our analysis aimed to establish the independent association between GDM and various adverse maternal and neonatal outcomes. The multivariate analysis incorporated factors such as maternal socioeconomic demographics, preexisting comorbidities, and conditions during pregnancy to account for potential confounders and elucidate the relationship between GDM and the outcomes of interest. Result Between 2015 and 2019, there were 1,212,589 GDM-related deliveries, accounting for 6.3% of the 19,249,237 total deliveries during the study period. Among women with GDM, 46.4% were Non-Hispanic Whites, 11.4% were Non-Hispanic Blacks, 25.7% were Hispanics, and 16.5% belonged to other racial/ethnic groups. The median age of women with GDM was 31 years, with an interquartile range of 27-35 years. The cesarean section rate among these women was 46.5%. GDM was identified as an independent predictor of adverse maternal and neonatal outcomes, including cesarean section (OR=1.40; 95% CI: 1.39-1.40), maternal blood transfusion (OR=1.15; 95% CI: 1.12-1.18), intensive care unit admission (OR=1.16; 95% CI: 1.10-1.21), neonatal intensive care unit admission (OR=1.53; 95% CI: 1.52-1.54), assisted ventilation (OR=1.37; 95% CI: 1.35-1.39), and low 5-minute Apgar score (OR=1.01; 95% CI: 1.00-1.03). Conclusion GDM serves as an independent risk factor for adverse maternal and neonatal outcomes, emphasizing the importance of early detection and management in pregnant women.

Development of machine learning models to predict gestational diabetes risk in the first half of pregnancy

BACKGROUND

Early prediction of Gestational Diabetes Mellitus (GDM) risk is of particular importance as it may enable more efficacious interventions and reduce cumulative injury to mother and fetus. The aim of this study is to develop machine learning (ML) models, for the early prediction of GDM using widely available variables, facilitating early intervention, and making possible to apply the prediction models in places where there is no access to more complex examinations.

METHODS

The dataset used in this study includes registries from 1,611 pregnancies. Twelve different ML models and their hyperparameters were optimized to achieve early and high prediction performance of GDM. A data augmentation method was used in training to improve prediction results. Three methods were used to select the most relevant variables for GDM prediction. After training, the models ranked with the highest Area under the Receiver Operating Characteristic Curve (AUCROC), were assessed on the validation set. Models with the best results were assessed in the test set as a measure of generalization performance.

RESULTS

Our method allows identifying many possible models for various levels of sensitivity and specificity. Four models achieved a high sensitivity of 0.82, a specificity in the range 0.72-0.74, accuracy between 0.73-0.75, and AUCROC of 0.81. These models required between 7 and 12 input variables. Another possible choice could be a model with sensitivity of 0.89 that requires just 5 variables reaching an accuracy of 0.65, a specificity of 0.62, and AUCROC of 0.82.

CONCLUSIONS

The principal findings of our study are: Early prediction of GDM within early stages of pregnancy using regular examinations/exams; the development and optimization of twelve different ML models and their hyperparameters to achieve the highest prediction performance; a novel data augmentation method is proposed to allow reaching excellent GDM prediction results with various models.