Establishment of pregnancy-specific lipid reference intervals in pregnant women in a single-centre and assessment of the predictive value of early lipids for gestational diabetes mellitus: a prospective cohort study.

INTRODUCTION: This study was aimed at establishing a pregnancy-specific lipid reference interval (RI) in pregnant women in a single-centre in the Beijing area of China, simultaneously exploring the predictive value of lipid levels in early pregnancy for gestational diabetes mellitus (GDM). MATERIAL AND METHODS: From October 2017 to August 2019, Peking University International Hospital established records for 1588 pregnant women, whose lipid profiles were determined during the first and third trimesters. The Hoffmann technique was used to calculate gestation-specific lipid RI. The 95% reference range for gestational lipids was also estimated for 509 healthy pregnant women screened according to the Clinical and Laboratory Standards Institute guideline. Multivariate logistic regression analysis was used to calculate odds ratios (OR) and their 95% confidence interval (CI), and the receiver operating characteristic (ROC) curve was applied to assess the predictive value of lipids in the first trimester for the diagnosis of GDM. RESULTS: Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels were significantly higher in the third trimester (p < 0.05). Hoffmann technique RI of the lipid profiles and the 95% reference range of the lipid profiles in healthy pregnant women did not differ statistically (p > 0.05). TC, TG, and LDL-C levels were higher in the GDM group in the first trimester (p < 0.05), and the risk of GDM was 2.1 times higher in women with higher TG (95% CI: 1.13-3.77, p < 0.05). The optimal ROC cut-off for TG to predict GDM was 2.375 mmol / L, and the area under the ROC curve was 0.622 (95% CI: 0.592-0.751), with a sensitivity of 73.7% and a specificity of 59.3%. CONCLUSIONS: This study established pregnancy-specific lipid RI for pregnant women in a single centre in the Beijing area of China. Pregnant women with TG ≥ 2.375 mmol/L in the first trimester were at significantly increased risk for GDM.

Impact of Medicaid expansion on pregnancy outcomes among women with gestational diabetes.

INTRODUCTION: The Affordable Care Act (ACA) aims to broaden health care access and significantly impacts obstetric practices. Yet, its effect on maternal and neonatal outcomes among women with gestational diabetes across diverse demographics is underexplored. OBJECTIVE: This study examines the impact of the implementation of the ACA on maternal and neonatal health in Maryland with ACA implementation and Georgia without ACA implementation. METHODOLOGY: We used data from the Maryland State Inpatient Database and US Vital Statistics System to assess the ACA's influence on maternal and neonatal outcomes in Maryland, with Georgia serving as a nonexpansion control state. Outcomes compared include cesarean section (CS) rates, low Apgar scores, neonatal intensive care unit (NICU) admissions, and assisted ventilation 7 h postdelivery. We adjusted for factors including women's age, race, insurance type, preexisting conditions, prior CS, prepregnancy obesity, weight gain during pregnancy, birth weight, labor events, and antenatal practices. RESULTS: The study included 52 479 women: 55.8% from Georgia and 44.2% from Maryland. Post-ACA, CS rates were 45.1% in Maryland versus 48.2% in Georgia (P = 0.000). Maryland demonstrated better outcomes, including lower rates of low Agar scores (odds ratio [OR], 0.74 [95% confidence interval (CI), 0.63-0.86]), assisted ventilation (OR, 0.79 [95% CI, 0.71-0.82]), and NICU admissions (OR, 0.76 [95% CI, 0.71-0.82]), but no significant change in CS rates (OR, 0.96 [95% CI, 0.92-1.01]). CONCLUSION: After ACA implementation, Maryland showed improved maternal and neonatal outcomes compared with Georgia, a nonexpansion state.

Oral glucose tolerance test and continuous glucose monitoring for gestational diabetes diagnosis: a survey study of women and health care professionals.

AIMS: The oral glucose tolerance test (OGTT), used for gestational diabetes mellitus (GDM) diagnosis for over 65 years, has poor acceptability and tolerability. Continuous glucose monitoring is being considered as potential alternative. The aim of our study was to formally assess women's and health care professionals' perception of both tests as diagnostic tools for GDM. METHODS: Participants in a pilot study on continuous glucose monitoring for GDM diagnosis were invited to fill two questionnaires, each of 6 Likert-scale and one optional open-ended question. A range of healthcare practitioners were also invited to fill a questionnaire of 13 Likert-scale and 7 optional open-ended questions. RESULTS: Sixty women completed the OGTT and 70 the continuous glucose monitoring questionnaire. OGTT was reported as poorly acceptable. Continuous glucose monitoring was described as significantly more tolerable (81% vs 27% 5/5 general acceptability rate, p < 0.001); ninety-three percent of the participants would recommend it for GDM diagnosis. Thirty health care professionals completed the survey. Most of them (73%) had confidence in OGTT as a diagnostic test for GDM with 66% raising some concerns. Doubts on continuous glucose monitoring were raised in terms of costs, accessibility and accuracy for GDM diagnosis due to "lack of evidence". CONCLUSIONS: Continuous glucose monitoring was substantially better tolerated for women than OGTT. Current lack of evidence for diagnostic accuracy for GDM underlines the need for studies on correlation between continuous glucose monitoring parameters and pregnancy outcomes to strengthen evidence for its use as diagnostic test for GDM.

Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes.

Innovations in digital health and machine learning are changing the path of clinical health and care. People from different geographical locations and cultural backgrounds can benefit from the mobility of wearable devices and smartphones to monitor their health ubiquitously. This paper focuses on reviewing the digital health and machine learning technologies used in gestational diabetes - a subtype of diabetes that occurs during pregnancy. This paper reviews sensor technologies used in blood glucose monitoring devices, digital health innovations and machine learning models for gestational diabetes monitoring and management, in clinical and commercial settings, and discusses future directions. Despite one in six mothers having gestational diabetes, digital health applications were underdeveloped, especially the techniques that can be deployed in clinical practice. There is an urgent need to (1) develop clinically interpretable machine learning methods for patients with gestational diabetes, assisting health professionals with treatment, monitoring, and risk stratification before, during and after their pregnancies; (2) adapt and develop clinically-proven devices for patient self-management of health and well-being at home settings ("virtual ward" and virtual consultation), thereby improving clinical outcomes by facilitating timely intervention; and (3) ensure innovations are affordable and sustainable for all women with different socioeconomic backgrounds and clinical resources.

Community-level social determinants of health and pregestational and gestational diabetes.

BACKGROUND: Individual adverse social determinants of health are associated with increased risk of diabetes in pregnancy, but the relative influence of neighborhood or community-level social determinants of health is unknown. OBJECTIVE: This study aimed to determine whether living in neighborhoods with greater socioeconomic disadvantage, food deserts, or less walkability was associated with having pregestational diabetes and developing gestational diabetes. STUDY DESIGN: We conducted a secondary analysis of the prospective Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-To-Be. Home addresses in the first trimester were geocoded at the census tract level. The exposures (modeled separately) were the following 3 neighborhood-level measures of adverse social determinants of health: (1) socioeconomic disadvantage, defined by the Area Deprivation Index and measured in tertiles from the lowest tertile (ie, least disadvantage [T1]) to the highest (ie, most disadvantage [T3]); (2) food desert, defined by the United States Department of Agriculture Food Access Research Atlas (yes/no by low income and low access criteria); and (3) less walkability, defined by the Environmental Protection Agency National Walkability Index (most walkable score [15.26-20.0] vs less walkable score [<15.26]). Multinomial logistic regression was used to model the odds of gestational diabetes or pregestational diabetes relative to no diabetes as the reference, adjusted for age at delivery, chronic hypertension, Medicaid insurance status, and low household income (<130% of the US poverty level). RESULTS: Among the 9155 assessed individuals, the mean Area Deprivation Index score was 39.0 (interquartile range, 19.0-71.0), 37.0% lived in a food desert, and 41.0% lived in a less walkable neighborhood. The frequency of pregestational and gestational diabetes diagnosis was 1.5% and 4.2%, respectively. Individuals living in a community in the highest tertile of socioeconomic disadvantage had increased odds of entering pregnancy with pregestational diabetes compared with those in the lowest tertile (T3 vs T1: 2.6% vs 0.8%; adjusted odds ratio, 2.52; 95% confidence interval, 1.41-4.48). Individuals living in a food desert (4.8% vs 4.0%; adjusted odds ratio, 1.37; 95% confidence interval, 1.06-1.77) and in a less walkable neighborhood (4.4% vs 3.8%; adjusted odds ratio, 1.33; 95% confidence interval, 1.04-1.71) had increased odds of gestational diabetes. There was no significant association between living in a food desert or a less walkable neighborhood and pregestational diabetes, or between socioeconomic disadvantage and gestational diabetes. CONCLUSION: Nulliparous individuals living in a neighborhood with higher socioeconomic disadvantage were at increased odds of entering pregnancy with pregestational diabetes, and those living in a food desert or a less walkable neighborhood were at increased odds of developing gestational diabetes, after controlling for known covariates.

Disparate Risk Factors Among Pregnant Veterans Using Veterans Administration Health Benefits for Community-Based Obstetrical Care.

INTRODUCTION: Veterans using the Veterans Administration Health Care System (VAHCS) for obstetrical care experience disparate pregnancy-related risks and health outcomes when compared to their pregnant counterparts. This study examined the prevalence of risk factors associated with pregnancy-related comorbidities among U.S. Veterans receiving obstetrical care using VAHCS benefits in Birmingham, Alabama. MATERIALS AND METHODS: A retrospective chart review was conducted of pregnant Veterans receiving care at a large Veterans Administration facility from 2018 to 2021. Using one-sample t-tests, the data from the study charts were compared to the Alabama overall prevalence of tobacco and alcohol use, pregnancy-related hypertension/preeclampsia, and gestational diabetes and, when the Alabama data were unavailable, the U.S. national average prevalence of overweight, obesity, pre-pregnancy hypertension, posttraumatic stress disorder, depression, and anxiety among patients receiving obstetrical care. The institutional review board at the Birmingham VAHCS approved the study, with an exemption for human subjects research. RESULTS: The study sample (N = 210) experienced higher levels of obesity (42.3% vs. 24.3%, P < .001), tobacco (21.9% vs. 10.8%, P < .001) and alcohol (19.5% vs. 5.4%, P < .001) use, pre-pregnancy hypertension (10.5% vs. 2.1%, P < .001), posttraumatic stress disorder (33.8% vs. 3.3%, P < .001), anxiety (66.7% vs. 15.2%, P < .001), and depression (66.7% vs. 15.0, P < .001). Fewer patients in the study sample were classified as overweight (16.7% vs. 25.5%, P < .001), developed pregnancy-related hypertension/preeclampsia (7.6% vs. 14.4%, P < .001), or were diagnosed with gestational diabetes (7.1% vs. 10.2%, P < .001). The results did not vary by race or age. CONCLUSION: The findings highlight the need for further examination of social factors that may be driving disparities among pregnant Veterans, who may benefit from supplemental services to address modifiable comorbidities. Additionally, the implementation of a centralized database to track pregnancy-related outcomes for Veterans would allow these comorbidities to be more closely monitored and addressed. Heightened awareness of a patient's Veteran status and associated increased risks can alert providers to screen for depression and anxiety more frequently and to familiarize themselves with additional services the VAHCS may offer to patients. These steps could improve referrals to counseling and/or targeted exercise interventions.

Baseline Perceptions of Women With Gestational Diabetes Mellitus and Health Care Professionals About Digital Gestational Diabetes Mellitus Self-Management Health Care Technologies: Interview Study Among Patients and Health Care Professionals.

BACKGROUND: Gestational diabetes mellitus (GDM) is a significant medical complication of pregnancy that requires close monitoring by a multidisciplinary health care team. The growing sophistication of mobile health (mHealth) technology could play a significant supporting role for women with GDM and health professionals (HPs) regarding GDM management. OBJECTIVE: This study included 2 phases. The aim of phase 1 was to explore the perceptions of HPs and women with GDM regarding the use of mHealth for GDM self-management and to identify their needs from these technologies. The aim of phase 2 was to explore the perceptions of women with GDM about their experiences with a state-of-the-art app for managing GDM that was offered to them during the COVID-19 lockdown. This phase aimed to understand the impact that COVID-19 has had on women's perceptions about using technology to manage their GDM. By combining both phases, the overall aim was to establish how perceptions about GDM self-management technology have changed owing to the pandemic restrictions and experience of using such technology. METHODS: In total, 26 semistructured interviews were conducted in 2 phases. In phase 1, overall, 62% (16/26) of the participants, including 44% (7/16) of HPs, 50% (8/16) of women with GDM, and 6% (1/16) of women in the postpartum period with GDM history participated in the interviews. In phase 2, overall, 38% (10/26) of women with GDM participated in the interviews. NVivo (QSR International) was used to extract qualitative data, which were subjected to thematic analysis. RESULTS: Phase 1 identified 3 themes from the interviews with women with GDM: fitting with women's lifestyle constraints, technology's design not meeting women's needs, and optimizing the technology's design to meet women's needs. Overall, 3 themes were derived from the interviews with HPs: optimizing the technology's design to improve the quality of care, technology to support women's independence, and limitations in the care system and facilities. Analysis of phase-2 interviews identified 2 further themes: enhancing the information and functionalities and optimizing the interface design. In both phases, participants emphasized a simple and user-friendly interface design as the predominant positive influence on their use of technology for GDM management. CONCLUSIONS: The combined findings underlined similar points. Poor usability, data visualization limitations, lack of personalization, limited information, and lack of communication facilities were the prime issues of current GDM self-management mHealth technology that need to be addressed. The analysis also revealed how women with GDM should play a vital role in gathering the requirements for GDM self-management technology; some needs were identified from in-depth discussion with women with GDM that would be missed without their involvement.

Lifestyle Interventions to Prevent Type 2 Diabetes in Women with a History of Gestational Diabetes: A Systematic Review and Meta-Analysis through the Lens of Health Equity.

BACKGROUND: Type 2 diabetes mellites is one of the health problems disproportionally affecting people with low socioeconomic statuses. Gestational diabetes mellites increases the risk of type 2 diabetes by up to ten-fold for women. Lifestyle interventions prevent type 2 diabetes in women with prior gestational diabetes. However, it is unknown if similar effectiveness can be expected for all population subgroups. OBJECTIVE: This study aims to assess the prevention of type 2 diabetes in women with prior gestational diabetes using population characteristics according to the PROGRESS (place of residence, race/ethnicity/culture/language, occupation, gender/sex, religion, education, socioeconomic status, and social capital) criteria. METHODS: MEDLINE, CINAHL, EMBASE, PubMed, PsycINFO, Web of Science, and EBM Reviews databases were searched for interventional studies of diet, physical activity, or behavioural interventions published up to 21 February 2023. Random effects subgroup meta-analysis was conducted to evaluate the association of population characteristics and intervention effects. RESULTS: All studies were conducted in high-income countries or middle-income countries. Two-thirds of the studies reported on race/ethnicity and education level. Less than one-third reported on place (urban/rural), occupation, and socioeconomic status. None reported on religion or social capital. Studies from high-income countries (MD = -1.46; 95% CI: -2.27, -0.66, I2 = 70.46, p < 0.001) showed a greater reduction in bodyweight compared with the studies conducted in middle-income countries (MD = -0.11; 95% CI: -1.12, 0.89, I2 = 69.31, p < 0.001) (p for subgroup difference = 0.04). CONCLUSION: There are significant equity gaps in the evidence for the prevention of type 2 diabetes in women with prior gestational diabetes due to reports on population characteristics being poor. Interventions may be less effective in reducing bodyweight in women from middle-income countries compared to high-income countries. Collecting and analysing data related to equity is needed to understand the effect of lifestyle interventions on type 2 diabetes for different population subgroups.

The yield of early-pregnancy homeostasis of model assessment -insulin resistance (HOMA-IR) for predicting gestational diabetes mellitus in different body mass index and age groups.

BACKGROUND: Early prediction of gestational diabetes mellitus(GDM) can be beneficial for lifestyle modifications to prevent GDM. The aim of this study was to investigate the predictive values of Homeostasis of Model Assessment -Insulin Resistance (HOMA-IR) in early pregnancy to predict GDM development in different body mass index (BMI) and age risk categories. MATERIALS AND METHODS: This study is part of the Qazvin Maternal and Neonatal Metabolic Study (QMNMS) in Iran (2018-2021). In this prospective longitudinal study, pregnant women with a gestational age ≤ 14 weeks were enrolled in the study using convenience sampling method and were followed up until delivery to investigate risk factors for maternal and neonatal complications. Data collection was done using questionnaires. Serum sampling was done at a gestational age ≤ 14 weeks and sera were frozen until the end of study. GDM was diagnosed at 24-28 weeks of pregnancy using 75gr oral glucose tolerance test. Fasting blood glucose and insulin were measured in sera taken during early pregnancy in 583 participants. The Mann-Whitney U test, independent t-test, and Chi-square test were used for comparing variables between groups. The logistic regression analysis was used to examine the independent association of HOMA-IR with GDM development and receiver operating characteristic analysis was used for finding the best cut-off of HOMA-IR for predicting GDM. RESULTS: GDM was developed in 90 (15.4%) of the participants. The third HOMA-IR tertile was independently associated with 3.2 times higher GDM occurrence (95% CI:1.6-6.2, P = 0.001). Despite the high prevalence of GDM in advanced maternal age (GDM rate = 28.4%), HOMA-IR had no association with GDM occurrence in this high-risk group. In both normal BMI and overweight/obese groups, HOMA-IR was a moderate predictor of GDM development (AUC = 0.638, P = 0.005 and AUC = 0.622, P = 0.008, respectively). However, the best cut-off for predicting GDM was 2.06 (sensitivity 67.5%, specificity 61.1%) in normal BMI and 3.13 (sensitivity 64.6%, specificity61.8%) in overweight/obese BMI. CONCLUSION: The present study revealed the necessity of considering the BMI and age risk groups when using the HOMA-IR index to predict GDM. Using lower cut-offs is more accurate for women with a normal BMI. In the advanced maternal age, there is no yield of HOMA-IR for predicting GDM.

Assessment of energy and nutrient intake of sri lankan mothers with prior gestational diabetes mellitus at 6-week postpartum: A community-based study.

Background: Gestational diabetes mellitus (GDM) is one of the leading causes for the future diabetes. Diet modification is an imperative part in attenuating this progression. Objectives: This study assessed energy and nutrient intakes of Sri Lankan mothers at 6 weeks after delivery, with the aim of developing specific dietary guidelines for postpartum mothers with GDM. Materials and Methods: A community-based, descriptive cross-sectional survey was conducted as a part of a quasi-experimental study. Nutrient and energy intakes were assessed among 100 mothers using 24-h dietary recall and a validated food frequency questionnaire. Energy and nutrient intakes were analyzed using NutriSurvey 2007 (EBISpro, Germany) which was modified for native food recipes and food composition tables for Sri Lanka. Results: The mean ± standard deviation intakes of total calories, carbohydrate, protein, and fat were 2817 ± 984 kcal, 445 ± 186 g, 95 ± 39 g, and 87 ± 58 g, respectively. The total calorie intake was significantly higher when compared to recommended levels based on the body mass index in both normal weight (3033 ± 1122 vs. 2300 kcal/d; P < 0.00) and overweight or obese (2759 ± 944 vs. 1800 kcal/d; P < 0.00) postpartum women. In the obese group, daily carbohydrate, fat, and protein intakes were significantly higher than the recommended values (P < 0.00). Folic acid intake was lower in both normal (23.7 vs. 400; P < 0.001) and obese or overweight (63 vs. 400; P < 0.001) groups. Conclusion: The study indicated that in majority of the mothers with GDM, the daily calorie and carbohydrate intakes were higher than the recommended. The findings suggest the need for developing a scientifically feasible and culturally acceptable dietary modification program. All macronutrients were taken more than the recommended amounts, especially in the overweight/obese group.

The role of Gestational Diabetes Mellitus and pelvic floor 3D-ultrasound assessment during pregnancy predicting urinary incontinence: a prospective cohort study.

Postpartum urinary incontinence may have a severe impact on women's health. Despite pregnancy and parturition being the most recognized risk factors, methods to identify new pregnant predictor risk factors are needed. Our study investigated the Gestational Diabetes Mellitus, clinical and pelvic floor 3D-ultrasound markers in pregnant women as predictors for 6-18 months of urinary incontinence. This prospective cohort study included nulliparous pregnant women submitted to Gestational Diabetes Mellitus screening in the second trimester. Pelvic floor 3D Ultrasound was performed at the second and third trimesters of gestation to evaluate the pelvic floor muscles and functions. Clinical data, the ICIQ-SF, and ISI questionnaires for urinary incontinence were applied in the third trimester and 6-18 months postpartum. Univariate analysis (P < .20) to extract risk factors variables and multivariate logistic regression analysis (P < .05) to obtain the adjusted relative ratio for urinary incontinence were performed. A total of 93 participants concluded the follow-up. Using the variables obtained by univariate analysis and after adjustments for potential confounders, multivariate analysis revealed that Gestational Diabetes Mellitus exposure was a solid and independent risk factor for 6-18 months of urinary incontinence (Adjusted RR 8.08; 95%CI 1.17-55.87; P:0.034). In addition, a higher Hiatal area observed in distension maneuver from the second to third trimester was negatively associated (Adjusted RR 0.96; 95%CI 0.93-0.99; P:0.023). In conclusion, Gestational Diabetes Mellitus was positively associated with 6-18 months of urinary incontinence, and higher Hiatal area distension was negatively associated.

Development and validation of a facile rapid assessment scale for perinatal venous thromboembolism in puerperium in Chinese women.

BACKGROUND: It is still urgent and challenge to develop a simple risk assessment scale for venous thromboembolism (VTE) in puerperium in Chinese women. METHODS: The study, a retrospective case-control study, was conducted in 12 hospitals in different cities in China. A total of 1152 pregnant women were selected, including 384 cases with VTE and 768 cases without VTE. A logistic regression method was conducted to determine the risk factors of VTE. RESULTS: Age, BMI before delivery, gestational diabetes mellitus, family history (thrombosis, diabetes, cardiovascular disease), and assisted reproductive technology were independent risk factors (P<0.05). The difference between the high-risk group and the low-risk group was statistically significant(P<0.001) with a sensitivity of 0.578, specificity of 0.756, Yuden index o.334, and area under the ROC curve of 0.878. CONCLUSIONS: The age (≥ 35 years), BMI before delivery (≥ 30 kg/m2), gestational diabetes mellitus, family history of related diseases and assisted reproductive technology are more likely to cause VTE after full-time delivery. The simple and rapid assessment scale of VTE in women after full-term delivery has perfect discrimination (P < 0.001), which can be applied to predict the risk of VTE in Chinese full-term postpartum women.

Racial/Ethnic and Nativity Inequalities in Gestational Diabetes Mellitus: The Role of Psychosocial Stressors.

INTRODUCTION: Racial/ethnic and nativity disparities in gestational diabetes mellitus (GDM) persist in the United States. Identified factors associated with these differences do not fully explain them. Research has recognized psychosocial stress as a potentially modifiable risk factor for GDM. METHODS: We used New York City Pregnancy Risk and Assessment Monitoring System data (2009-2014) linked with birth certificate items (n = 7,632) in bivariate and multivariate analyses to examine associations between 12 psychosocial stressors (modeled three ways: individual stressors, grouped stressors, stress constructs) and GDM across race/ethnicity and nativity, and if stressors explain racial/ethnic/nativity differences in GDM. RESULTS: U.S. and foreign-born Black and Hispanic women reported higher stressors relative to U.S.-born White women. In fully adjusted models, the financial stress construct was associated with a 51% increased adjusted risk of GDM, and adding all stressors doubled the risk. Psychosocial stressors did not explain the elevated risk of GDM among foreign-born Black (adjusted risk ratio, 2.18; 95% confidence interval, 1.53-3.11), Hispanic (adjusted risk ratio, 1.57; 95% confidence interval, 1.10-2.25), or Asian/Pacific Islander (adjusted risk ratio, 4.10; 95% confidence interval, 3.04-5.52) women compared with U.S.-born White women. CONCLUSIONS: Historically minoritized racial/ethnic and immigrant women have an increased risk of psychosocial stressors and GDM relative to U.S.-born White women. Although financial and all stressors predicted higher risk of GDM, they did not explain the increased risk of GDM among immigrant women and women from minoritized racial/ethnic groups. Further examination into racial/ethnic and nativity inequalities in stress exposure and rates of GDM is warranted to promote healthier pregnancies and birth outcomes.

Assessment of Myocardial Function in Infants of Mothers with Gestational Diabetes Mellitus Using Deformation Imaging over the First Year of Age.

OBJECTIVE: To assess serial myocardial performance and pulmonary vascular resistance (PVR) in infants of mothers with gestational diabetes mellitus (GDM) over the first year of life. STUDY DESIGN: This was a prospective, observational study. Echocardiography was performed at birth, 6 months, and 1 year of age. Pulmonary artery acceleration time and left ventricular (LV) eccentricity index provided surrogate measurements of PVR. Biventricular function was assessed by tissue Doppler imaging and deformation analysis. RESULTS: Fifty infants of mothers with GDM were compared with 50 controls with no difference in gestation (38.9 ± 0.8 weeks vs 39.3 ± 0.9 weeks; P = .05) or birthweight (3.55 ± 0.49 kg vs 3.56 ± 0.41 kg; P = .95). At 1 year of age, the pulmonary artery acceleration time was lower (70 ± 11 vs 79 ± 10; P = .01) in the GDM group. LV global longitudinal strain (24.7 ± 1.9 vs 28.8 ± 1.8 %; P < .01), LV systolic strain rate (1.8 ± 0.2 vs 2.1 ± 0.3 1/s; P < .01), and RV free wall strain (31.1 ± 4.8 vs 34.6 ± 3.9 %; P < .01) were lower in the GDM cohort at 1 year of age (all P values adjusted for gestation, mode of delivery, and maternal body mass index). CONCLUSIONS: Our findings demonstrate higher indices of PVR and lower biventricular function in infants of mothers with GDM compared with controls at each time point assessed in this study over the first year of life.

Ultrasonographic Assessment of Body Fat Index for Prediction of Gestational Diabetes Mellitus and Neonatal Complications.

OBJECTIVES: To assess maternal pre-peritoneal fat and subcutaneous fat at 16-20 weeks gestation by ultrasound. Thus, calculate body fat index (BFI) and determine its cut-off value for prediction of gestational diabetes mellitus (GDM) and neonatal subcutaneous adiposity. METHODS: A cohort study was conducted in 200 pregnant women with singleton fetus during anomaly scan using BFI where they were screened for GDM at 24-28 weeks gestation by oral glucose tolerance test. Labour and neonatal outcomes were recorded. The receiver operating characteristic curve was used to determine the cut-offs for BFI, pre-peritoneal fat thickness, and subcutaneous fat thickness in order to predict GDM. RESULTS: The area under receiver operating characteristic curve for BFI was 0.967 (95% CI 0.932-0.987) with a sensitivity of 97.3%, specificity of 89.57%, negative predictive value of 99.3%, and diagnostic accuracy of 91% at a BFI cut-off of 0.88. The study analysis demonstrated BFI to be statistically superior to BMI > 22.9 kg/m2 for prediction of GDM. BFI > 0.88 was a risk factor for developing neonatal subcutaneous adiposity. CONCLUSIONS: BFI is a practical and convenient non-invasive screening tool to predict GDM and neonatal subcutaneous adiposity.

Postpartum Expansion of Emergency Medicaid is Associated with Increased Receipt of Recommended Glycemic Screening and Care.

Oregon expanded Emergency Medicaid coverage to 60 days of postpartum care in 2018, facilitating ongoing care for conditions such as gestational diabetes. We linked Medicaid claims and birth certificates from 2010 to 2019 in Oregon and South Carolina, which did not expand postpartum care. We used a difference-in-difference design to measure the effects of postpartum care coverage among Emergency Medicaid recipients with gestational diabetes. Primary outcomes were receipt of recommended glucose tolerance testing and new diagnosis of Type 2 diabetes. Our sample included 2,270 live births among a predominantly multiparous, Latina population. Postpartum coverage was associated with a significant increase in receipt of a recommended glucose tolerance test (23.1 percentage points, 95% CI 16.9-29.3) and in diagnosis of Type 2 diabetes (4.6 percentage points, 95% CI 3.3-65.9). Expansion of postpartum coverage increased recommended screenings and care among Emergency Medicaid enrollees with pregnancies complicated by gestational diabetes.

Comparison of Diabetes in Pregnancy Study Group India (DIPSI) and WHO criteria for diagnosis of gestational diabetes by assessment of fetomaternal outcomes.

OBJECTIVE: To evaluate fetomaternal outcomes in women who are normoglycemic by Diabetes in Pregnancy Study Group India (DIPSI) but have gestational diabetes mellitus (GDM) by WHO criteria versus those who are normoglycemic by both DIPSI and WHO criteria. METHODS: This was a prospective, cohort study. A total of 635 women participated. They underwent a 2-h non-fasting oral glucose tolerance test (OGTT) and results were interpreted by DIPSI. Out of 635 women, 52 were lost to follow up and 33 were diagnosed as GDM by DIPSI and excluded from the study. The remaining 550 women, after 72 h from the first test, underwent a 75-g fasting-OGTT and results were interpreted using WHO 2013 criteria. Results of the second test were blinded till delivery. The 550 women were followed for fetomaternal outcomes. Participants with normal DIPSI and normal WHO 2013 OGTT were labeled group 1. Participants with normal DIPSI but abnormal WHO 2013 OGTT were labeled group 2. Fetomaternal outcomes were compared between these groups. RESULTS: Occurrence of GDM by DIPSI was 5.1%, by WHO 2013 criteria it was 10.5%. Composite fetomaternal outcomes occurred more commonly in women with a normal DIPSI but an abnormal WHO 2013 test. Out of 550 women, 492 had normal DIPSI and normal WHO 2013 test. Out of this 492, 116 (23.6%) women had adverse fetomaternal outcomes. Fifty-eight women out of 550 had a normal DIPSI but an abnormal WHO 2013 test. Thirty-seven (63.8%) women out of 58 had adverse fetomaternal outcomes. We found statistically significant association between adverse fetomaternal outcome and GDM by WHO 2013 test (with normal DIPSI test). CONCLUSION: WHO 2013 has superior diagnostic value compared with DIPSI criteria for diagnosis of GDM.

Associations of cesarean sections with comorbidities within the Pregnancy Risk Assessment Monitoring System.

OBJECTIVES: Cesarean delivery (CD) is a common obstetrical procedure aimed at reducing maternal and infant morbidity and mortality in complicated pregnancies and medical emergencies yet carries potential complications. CD rates in the USA have increased over the years - likely associated with increased comorbidities. Thus, to expand the literature, our objective was to identify the likelihood of a woman having a CD when comorbidities - diabetes, high blood pressure (HBP), or depression - are present. METHODS: We conducted a cross-sectional analysis of the 2019 Pregnancy Risk Assessment Monitoring System. Binary and multivariable logistic regression were used to calculate adjusted odds ratios (AORs) to determine associations between pre-existing and gestational comorbidities and CD among pregnant women. RESULTS: Compared to those without a diagnosis, women with pre-existing diabetes (AOR: 1.69; CI: 1.54-1.86), pre-existing HBP (AOR: 1.58; CI: 1.46-1.69), and pre-existing depression (AOR: 1.14; CI 1.08-1.20; Table 2) were more likely to have a CD. Additionally, participants with gestational diabetes (AOR 1.43; CI 1.34-1.52), HBP (AOR 1.86; CI 1.76-1.95) and depression (AOR 1.13; CI 1.07-1.19) were also more likely to have a CD than those without comorbidities. CONCLUSIONS: Higher rates of CD were found among individuals with a pre-existing or gestational diagnosis of diabetes, HBP, or depression than those without these diagnoses. With increasing rates of these conditions, it is likely that CD rates will continue their trajectory in the USA. Thus, professional organizations can have more impact by popularizing and making effective evidence-based guidelines for management.