Increasing Prevalence of Diagnosed Gestational Diabetes in South Carolina: 2015-2021.

Objective: To examine trends with a focus on racial and ethnic disparities in reported gestational diabetes mellitus (GDM) and related outcomes (macrosomia, large for gestational age infants) before and during the COVID-19 pandemic in South Carolina (SC). Methods: A retrospective cohort study of pregnancies resulting in livebirths from 2015 through 2021 was conducted in SC. Statewide maternal hospital and emergency department discharge codes were linked to birth certificate data. GDM was defined by ICD-9-CM (i.e., 648.01-648.02, 648.81-648.82) or ICD-10-CM codes (i.e., O24.4, O24.1, O24.9), or indication of GDM on the birth certificate without evidence of diabetes outside pregnancy (ICD-9-CM: 250.xx; ICD-10-CM: E10, E11, O24.0, O24.1, O24.3). Results: Our study included 194,777 non-Hispanic White (White), 108,165 non-Hispanic Black (Black), 25,556 Hispanic, and 16,344 other race-ethnic group pregnancies. The relative risk for GDM associated with a 1-year increase was 1.01 (95% confidence interval [CI]: 1.01-1.02) before the pandemic and 1.12 (1.09-1.14) during the pandemic. While there were race-ethnic differences in the prevalence of GDM, increasing trends were similar across all race-ethnic groups before and during the pandemic. From quarter 1, 2020, to quarter 4, 2021, the prevalence of reported GDM increased from 8.92% to 10.85% in White, from 8.04% to 9.78% in Black, from 11.2% to 13.65% in Hispanic, and from 13.3% to 16.16% in other race-ethnic women. Conclusion: An increasing prevalence of diagnosed GDM was reported during the COVID-19 pandemic. Future studies are needed to understand the mechanisms underlying increasing trends, to develop interventions, and to determine whether the increasing trend continues in subsequent years.

Association of Beverage Consumption during Pregnancy with Adverse Maternal and Offspring Outcomes.

BACKGROUND: As the global consumption of sugary and non-sugar sweetened beverages continues to rise, there is growing concern about their health impacts, particularly among pregnant women and their offspring. OBJECTIVE: This study aimed to investigate the consumption patterns of various beverages among pregnant women in Shanghai and their potential health impacts on both mothers and offspring. METHOD: We applied a multi-stage random sampling method to select participants from 16 districts in Shanghai. Each district was categorised into five zones. Two towns were randomly selected from each zone, and from each town, 30 pregnant women were randomly selected. Data were collected through face-to-face questionnaires. Follow-up data on births within a year after the survey were also obtained. RESULT: The consumption rates of total beverages (TB), sugar-sweetened beverages (SSB), and non-sugar sweetened beverages (NSS) were 73.2%, 72.8%, and 13.5%, respectively. Logistic regression analysis showed that compared to non-consumers, pregnant women consuming TB three times or less per week had a 38.4% increased risk of gestational diabetes mellitus (GDM) (OR = 1.384; 95% CI: 1.129-1.696) and a 64.2% increased risk of gestational hypertension (GH) (OR = 1.642; 95% CI: 1.129-2.389). Those consuming TB four or more times per week faced a 154.3% higher risk of GDM (OR = 2.543; 95% CI: 2.064-3.314) and a 169.3% increased risk of GH (OR = 2.693; 95% CI: 1.773-4.091). Similar results were observed in the analysis of SSB. Regarding offspring health, compared to non-consumers, TB consumption four or more times per week was associated with a substantial increase in the risk of macrosomia (OR = 2.143; 95% CI: 1.304-3.522) and large for gestational age (LGA) (OR = 1.695; 95% CI: 1.219-2.356). In the analysis of NSS, with a significantly increased risk of macrosomia (OR = 6.581; 95% CI:2.796-13.824) and LGA (OR = 7.554; 95% CI: 3.372-16.921). CONCLUSION: The high level of beverage consumption among pregnant women in Shanghai needs attention. Excessive consumption of beverages increases the risk of GDM and GH, while excessive consumption of NSS possibly has a greater impact on offspring macrosomia and LGA.

Third-Trimester Ultrasound Diagnosis of Large for Gestational Age and Risk of Cesarean Delivery.

OBJECTIVE: Determine if knowledge of a third-trimester ultrasound diagnosis of large for gestational age (LGA) independently increases the risk of cesarean delivery (CD). STUDY DESIGN: Historical cohort comparing CD rate among patients diagnosed with an LGA fetus on a clinically indicated ultrasound from January 2017 to July 2021 with those without an LGA diagnosis at 34 weeks or later. LGA was defined as an ultrasound-estimated fetal weight greater than or equal to the 90th percentile for the gestational age. Univariate analysis was performed to identify significant confounding variables and was utilized as covariates for binary regression with CD rate as the primary outcome, and adjusted odds ratios (AOR) with 95% confidence intervals (CI) were calculated. Nulliparous term singleton vertex (NTSV) and multiparous CD rates were also compared. RESULTS: There were 447 patients diagnosed with an LGA fetus and 1971 patients without an LGA diagnosis on third-trimester ultrasound. The positive predictive value of LGA diagnosis was 50.1% and the false positive rate was 10.6%. Patients with a diagnosis of LGA had higher AOR of CD (OR 2.11, 95% CI 1.56-2.83), and higher AOR of NTSV CD (OR 1.88, 95% CI 1.14-3.13) compared with those without an LGA diagnosis. There was no difference in the rates of non-medically indicated CD, multiparous primary CD, and attempted and successful TOLAC. CONCLUSION: Our results suggest third-trimester ultrasound diagnosis of LGA independently increases odds of CD, specifically among nulliparous patients, and the potential bias may be one factor contributing to excessive CDs and NTSV CDs.

Decreased complexity of glucose time series index associated with adverse pregnancy outcomes in gestational diabetes mellitus.

AIM: We investigated the relationship between the complexity of the glucose time series index (CGI) during pregnancy and adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM). MATERIALS AND METHODS: In this retrospective cohort study, 388 singleton pregnant women with GDM underwent continuous glucose monitoring (CGM) at a median of 26.86 gestational weeks. CGI was calculated using refined composite multiscale entropy based on CGM data. The participants were categorized into tertiles according to their baseline CGI (CGI <2.32, 2.32-3.10, ≥3.10). Logistic regression was used to assess the association between CGI and composite adverse outcomes or large for gestational age (LGA). The discrimination performance of CGI was estimated using receiver operating characteristic analysis. RESULTS: Of the 388 participants, 71 (18.3%) had LGA infants and 63 (16.2%) had composite adverse outcomes. After adjustments were made for confounders, compared with those with a high CGI (CGI ≥3.10), participants with a low CGI (CGI <2.32) had a higher risk of composite adverse outcomes (odds ratio: 12.10, 95% confidence interval: 4.41-33.18) and LGA (odds ratio: 12.68, 95% confidence interval: 4.04-39.75). According to the receiver operating characteristic analysis, CGI was significantly better than glycated haemoglobin and conventional CGM indicators for the prediction of adverse pregnancy outcomes (all p < .05). CONCLUSION: A lower CGI during pregnancy was associated with composite adverse outcomes and LGA. CGI, a novel glucose homeostasis predictor, seems to be superior to conventional glucose indicators for the prediction of adverse pregnancy outcomes in women with GDM.

Investigation of newborn blood metabolomics in varying intrauterine growth conditions.

OBJECTIVES: This study aimed to investigate changes in the blood metabolic profiles of newborns with varying intrauterine growth conditions. Specifically, we analyzed the levels of amino acids, carnitine, and succinylacetone among full-term newborns, including small for gestational age (SGA), appropriate for gestational age (AGA), and large for gestational age (LGA). We aim to identify differential metabolites and metabolic pathways that may offer insights into clinical interventions. METHODS: A total of 5106 full-term newborns were included in the study. Blood samples were obtained from all newborns between 3 and 5 days after birth and analyzed using tandem mass spectrometry to detect blood metabolites. Subsequently, we screened for different metabolites and metabolic pathways among the groups using the MetaboAnalystR package (Version 1.0.1) in R software (R-3.6.0). RESULTS: The levels of blood amino acids and carnitine metabolism differed significantly among newborns with varying intrauterine growth conditions. Full-term SGA newborns exhibited a decrease in multiple amino acids and an increase in multiple carnitines, while full-term LGA newborns showed an increase in multiple amino acids and acylcarnitines. CONCLUSION: Continuous monitoring of the short-term and long-term growth and metabolic status of full-term SGA and LGA newborns is warranted with individualized dietary and nutritional adjustments to promote healthy growth in a timely manner. The findings of this research contribute to the broader understanding of SGA/LGA and shall inform future research on metabolomics, interventions, and long-term outcomes.

High-Density Lipoproteins-Cholesterol (HDL-C) in Women With Gestational Diabetes (GDM): A Predictor for Large Gestational Age (LGA) Babies.

Introduction The present study aimed to evaluate the associations between the clinical and biochemical characteristics of women with gestational diabetes (GDM) and the incidence of large for gestational age (LGA) babies. Methods This cohort study included data collected during prenatal follow-up of GDM women from January 2008 to August 2022. Clinical and biochemical variables were compared among small (SGA), adequate (AGA), or large for gestational age (LGA) babies. Associations of the main variables with the incidence of LGA were determined by multiple regression analysis. Results Out of 659 women, 56 had LGA, 547 had AGA, and 56 had SGA babies. We observed differences in the means of age, pregestational body mass index (BMI), high-density lipoproteins-cholesterol (HDL-C) levels, gestational weight gain (GWG), and gestational age at birth according to LGA, AGA, and SGA (p < 0.05). All other variables were not different between the groups. The frequencies (%) and relative risk (RR) of LGA babies were evaluated according to HDL-C in the first tertile and/or obesity, with 12.2% and risk ratio (RR)=2.77 (95% confidence interval (CI) 1.35-5.69, p=0.005) if the women had obesity and HDL in the first tertile, 11.3% and RR=2.27 (95% CI 1.03-5.03, p=0.042) if only HDL in the first tertile was present, 10.9% and RR=2.68 (95% CI 1.31-5.48, p=0.007) if the women had only obesity, using as a reference group those women without obesity or HDL-C in the first tertile (4.6% and RR=1) adjusted for age, age at birth and GWG. Conclusion In women with GDM, lower levels of HDL-cholesterol during pregnancy, as well as pregestational obesity, seem to be good predictors of the occurrence of LGA babies.

Association between changes in glycosylated hemoglobin during the second and third trimesters and adverse pregnancy outcomes among women without hyperglycemia in pregnancy.

OBJECTIVE: To explore the relationship between changes in glycated hemoglobin (HbA1c) during the second and third trimesters and adverse pregnancy outcomes among women without hyperglycemia in pregnancy (HIP). RESEARCH DESIGN AND METHODS: A total of 1,057 pregnant women who underwent serum HbA1c and delivered at Women's Hospital, Zhejiang University School of Medicine from May 2022 to March 2023, were included in this study. They were divided into four groups. Associations were evaluated using multivariate logistic regression analysis. RESULTS: In our study, an upward trend in HbA1c levels in the second trimester (HbA1c_S) and third trimester (HbA1c_T) among women without HIP was demonstrated. Multivariate logistics regression analysis showed significant associations: Pregnant women with HbA1c_S<5.5 %, HbA1c_T≥6.1 %, or with HbA1c_S≥5.5 %, HbA1c_T<6.1 % had a significant correlation with hypertensive disorders of pregnancy (HDP) (aOR:2.72, 95 %CI=1.24-5.97；aOR:2.59, 95 %CI=1.15-5.84). Furthermore, for each 1 % increase in the difference value of HbA1c between the second and third trimesters, the risk of HDP increased about 1.96 times, and the risk of delivering a large-for-gestational-age baby increased about 1.30 times. CONCLUSION: Among pregnant women without HIP, elevated HbA1c levels in the second or third trimester are associated with increased risks of adverse pregnancy outcomes.

Obstetric Outcomes in Women on Lithium: A Systematic Review and Meta-Analysis.

Background/Objectives: Lithium taken during pregnancy was linked in the past with increased risk for foetal/newborn malformations, but clinicians believe that it is worse for newborn children not to treat the mothers' underlying psychiatric illness. We set to review the available evidence of adverse foetal outcomes in women who received lithium treatment for some time during their pregnancy. Methods: We searched four databases and a register to seek papers reporting neonatal outcomes of women who took lithium during their pregnancy by using the appropriate terms. We adopted the PRISMA statement and used Delphi rounds among all the authors to assess eligibility and the Cochrane Risk-of-Bias tool to evaluate the RoB of the included studies. Results: We found 28 eligible studies, 10 of which met the criteria for inclusion in the meta-analysis. The studies regarded 1402 newborn babies and 2595 women exposed to lithium. Overall, the systematic review found slightly increased adverse pregnancy outcomes for women taking lithium for both the first trimester only and any time during pregnancy, while the meta-analysis found increased odds for cardiac or other malformations, preterm birth, and a large size for gestational age with lithium at any time during pregnancy. Conclusions: Women with BD planning a pregnancy should consider discontinuing lithium when euthymic; lithium use during the first trimester and at any time during pregnancy increases the odds for some adverse pregnancy outcomes. Once the pregnancy has started, there is no reason for discontinuing lithium; close foetal monitoring and regular blood lithium levels may obviate some disadvantages of lithium administration during pregnancy.

Association between risk of infant death and birth-weight z scores according to gestational age: A nationwide study using the Finnish Medical Birth Register.

OBJECTIVE: To investigate the association between infant mortality and birth weight using estimated fetal weight (EFW) versus birth-weight charts, by gestational age (GA). METHODS: This nationwide population-based study used data from the Finnish Medical Birth Register from 2006 to 2016 on non-malformed singleton live births at 24-41+6 weeks of gestation (N = 563 630). The outcome was death in the first year of life. Mortality risks by birth-weight z score, defined as a continuous variable using Marsál's EFW and Sankilampi's birth-weight charts, were assessed using generalized additive models by GA (24-27+6, 28-31+6, 32-36+6, 37-38+6, 39-41+6 weeks). We calculated z score thresholds associated with a two- and three-fold increased risk of infant death compared with newborns with a birth weight between 0 and 0.675 standard deviations. RESULTS: The z score thresholds (with corresponding centiles in parentheses) associated with a two-fold increase in infant mortality were: -3.43 (<0.1) at 24-27+6 weeks, -3.46 (<0.1) at 28-31+6 weeks, -1.29 (9.9) at 32-36+6 weeks, -1.18 (11.9) at 37-38+6 weeks, and - 1.34 (9.0) at 39-41+6 weeks according to the EFW chart. These values were - 2.43 (0.8), -2.62 (0.4), -1.34 (9.0), -1.37 (8.5), and - 1.43 (7.6) according to the birth-weight chart. CONCLUSION: The association between birth weight and infant mortality varies by GA whichever chart is used, suggesting that different thresholds for the screening of growth anomalies could be used across GA to identify high-risk newborns.

Fetal size monitoring in women with gestational diabetes and normal glucose tolerance.

AIMS: To monitor fetal size and identify predictors for birthweight in women with gestational diabetes (GDM) and normal glucose tolerance (NGT). METHODS: Cohort study of 1843 women universally screened for GDM, with routine ultrasounds each trimester. Women with GDM and NGT were categorized in subgroups by birthweight centile. RESULTS: Of the total cohort, 231 (12.5%) women were diagnosed with GDM. Fetal size, incidence of large-for-gestational age (LGA: 12.3% of GDM vs. 12.9% of NGT, p = 0.822) and small-for-gestational age (SGA) neonates (4.8% of GDM vs. 5.1% of NGT, p = 0.886) were similar between GDM and NGT. GDM women with LGA neonates were more insulin resistant at baseline and had more often estimated fetal weight (EFW) ≥ P90 on the 28-33 weeks ultrasound (p = 0.033) than those with AGA (appropriate-for-gestational age) neonates. Compared to NGT women with AGA neonates, those with LGA neonates were more often obese and multiparous, had higher fasting glycemia, a worse lipid profile, and higher insulin resistance between 24 -28 weeks, with more often excessive gestational weight gain. On the 28-33 weeks ultrasound, abdominal circumference ≥ P95 had a high positive predictive value for LGA neonates in GDM (100%), whereas, in both GDM and NGT, EFW ≥ P90 and ≤ P10 had a high negative predictive value for LGA and SGA neonates (> 88%), respectively. CONCLUSIONS: There were no differences in fetal size throughout pregnancy nor in LGA incidence between GDM and NGT women. EFW centile at 28-33 weeks correlated well with birthweight. This indicates that GDM treatment is effective and targeted ultrasound follow-up is useful. TRIAL REGISTRATION CLINICALTRIALS.GOV: NCT02036619. Registration date: January 15, 2014. https://clinicaltrials.gov/ct2/show/NCT02036619 .

Association Between Red Blood Cell Distribution Width in Late Pregnancy and the Incidence of Adverse Perinatal Outcomes: A Retrospective Cohort Study.

BACKGROUND AND AIMS: This study aimed to quantify adverse perinatal outcomes (APO), including small/large for gestational age (SGA/LGA) and preterm birth (PTB), in pregnant women with abnormal red cell distribution width (RDW) and explore the related mechanisms. METHODS: This study included 11,659 pregnant women who delivered in a specialized hospital. At the time of admission, the lipid profiles and whole blood cell counts were assessed, and APO was analyzed. RESULTS: Women with high RDW (>18.5% [the 97.5th percentile]) in late pregnancy had a higher risk of LGA compared with those with low RDW (<12.3% [the 2.5th percentile]), whereas women with low RDW had a higher risk of SGA and PTB, compared with those with high RDW. A 1% increase in RDW was associated with an increased risk of LGA and a decreased risk of SGA and PTB. Consistent associations were observed in sensitivity analysis among pregnant women of non-advanced age, non-obesity, non-pregnancy complications, and non-PTB (for SGA/LGA only). Increased RDW was significantly associated with increased triglycerides and decreased high-density lipoprotein cholesterol (HDL-C). Triglycerides and HDL-C significantly mediated 10.63 and 15.8% of RDW-associated LGA, 9.51% and 9.40 of RDW-associated SGA, and 8.44 and -8.25% of RDW-associated PTB, respectively. CONCLUSION: Abnormal RDW was associated with an increased risk of APO, and the RDW-associated APO risk could be partially mediated by triglycerides and HDL-C, suggesting that RDW may be a promising APO predictor.

The impact of reference growth standards on small- and large-for-gestational age outcomes among pregnancies conceived by fresh and frozen embryo transfers.

Objective: To describe differences in the frequency of small-for-gestational age (SGA) and large-for-gestational age (LGA) driven by different birth weight curves in assisted reproductive technology (ART)-conceived pregnancies. Design: Retrospective cohort study. Setting: Single academic medical center. Patients: Singleton live births between the gestational ages of 36 weeks and 0 days and 42 weeks and 6 days from fresh or frozen embryo transfer (ET). Interventions: None. Main Outcome Measures: SGA (<10th percentile) and LGA (>90th percentile) classified by Fenton, INTERGROWTH-21, World Health Organization, Duryea, and Oken curves. Results: The median birth weight and gestational age at birth among fresh ET pregnancies were 3,289g (interquartile range [IQR], 2,977-3,600g) and 39.4 (IQR, 38.6-40.3) weeks, respectively, and those among frozen ET pregnancies were 3,399g (IQR, 3,065-3,685g) and 39.4 (IQR, 38.7-40.1) weeks, respectively. The frequencies of SGA neonates using each birth weight standard ranged from 5.8% to 13.4% for fresh ET and from 3.5% to 8.7% for frozen ET. Those of LGA neonates ranged from 5.3% to 14.3% for fresh ET and from 6.6% to 21.2% for frozen ET. Conclusion: The frequency of SGA and LGA neonates among ART-conceived gestations is partially driven by the birth weight standard. Selecting an appropriate standard that best reflects the patient population is critical to quantifying the risk of ART-conceived pregnancies.

Developing and validating a predictive model of delivering large-for-gestational-age infants among women with gestational diabetes mellitus.

BACKGROUND: The birth of large-for-gestational-age (LGA) infants is associated with many short-term adverse pregnancy outcomes. It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus (GDM) is significantly higher than that born to healthy pregnant women. However, traditional methods for the diagnosis of LGA have limitations. Therefore, this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants. AIM: To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM, and provide strategies for the effective prevention and timely intervention of LGA. METHODS: The multivariable prediction model was developed by carrying out the following steps. First, the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses, for which the P value was < 0.10. Subsequently, Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations, and the optimal combination factors were selected by choosing lambda 1se as the criterion. The final predictors were determined by multiple backward stepwise logistic regression analysis, in which only the independent variables were associated with LGA risk, with a P value < 0.05. Finally, a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve, calibration curve and decision curve analyses. RESULTS: After using a multistep screening method, we establish a predictive model. Several risk factors for delivering an LGA infant were identified (P < 0.01), including weight gain during pregnancy, parity, triglyceride-glucose index, free tetraiodothyronine level, abdominal circumference, alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks. The nomogram's prediction ability was supported by the area under the curve (0.703, 0.709, and 0.699 for the training cohort, validation cohort, and test cohort, respectively). The calibration curves of the three cohorts displayed good agreement. The decision curve showed that the use of the 10%-60% threshold for identifying pregnant women with GDM who are at risk of delivering an LGA infant would result in a positive net benefit. CONCLUSION: Our nomogram incorporated easily accessible risk factors, facilitating individualized prediction of pregnant women with GDM who are likely to deliver an LGA infant.

Machine Learning-Based Prediction of Large-for-Gestational Age Infants in Mothers with Gestational Diabetes Mellitus.

CONTEXT: Large-for-gestational-age (LGA), one of the most common complications of gestational diabetes mellitus (GDM), has become a global concern. The predictive performance of common continuous glucose monitoring (CGM) metrics for LGA is limited. OBJECTIVE: We aimed to develop and validate an artificial intelligence (AI) based model to determine the probability of women with GDM giving birth to LGA infants during pregnancy using CGM measurements together with demographic data and metabolic indicators. METHODS: A total of 371 women with GDM from a prospective cohort at a university hospital were included. CGM was performed during 20-34 gestational weeks, and glycemic fluctuations were evaluated and visualized in women with GDM who gave birth to LGA and non-LGA infants. A convolutional neural network (CNN)-based fusion model was developed to predict LGA. Comparisons among the novel fusion model and three conventional models were made using the area under the receiver-operating characteristic curve (AUCROC) and accuracy. RESULTS: Overall, 76 (20.5%) out of 371 GDM women developed LGA neonates. The visualized 24-h glucose profiles differed at midmorning. This difference was consistent among subgroups categorized by pregestational BMI, therapeutic protocol and CGM administration period. The AI based fusion prediction model using 24-h CGM data and 15 clinical variables for LGA prediction (AUCROC 0.852, 95% CI 0.680-0.966, accuracy 84.4%) showed superior discriminative power compared with the three classic models. CONCLUSIONS: We demonstrated better performance in predicting LGA infants among women with GDM using the AI based fusion model. The characteristics of the CGM profiles allowed us to determine the appropriate window for intervention.

Interpregnancy weight change and neonatal and infant outcomes: A systematic review and meta-analysis.

PURPOSE: To synthesize evidence regarding the association between interpregnancy weight change (IPWC) in consecutive pregnancies and neonatal or infant outcomes in the subsequent pregnancy. METHODS: Search strategy was implemented in MEDLINE, EMBASE, Web of Science, Scopus and Cochrane Library from their inception to 13 November 2023. The most adjusted odds ratio (OR) or risk ratio estimates provided by original studies were used to calculate pooled risk ratios and their corresponding 95 % confidence intervals (CI) with the DerSimonian and Laird random effects method. Publication bias was assessed by funnel plots and Egger's method, and risk of bias was assessed with The NewcastleOttawa Quality Assessment Scale. RESULTS: Thirty-seven observational studies were included. Interpregnancy weight loss or gain were associated with large for gestational age (OR: 0.89; 95 % CI: 0.84-0.94; I2 = 83.6 % and OR: 1.33; 95 % CI:1.26-1.40; I2 = 98.9 %), and stillbirth risk (OR: 1.10; 95 % CI: 1.01-1.18; I2 = 0.0 % and OR: 1.21; 95 % CI: 1.09-1.33; I2 = 60.2 %,). CONCLUSIONS: Findings highlight the importance of managing weight between interpregnancy periods, although these findings should be interpreted cautiously because of the possible influence of social determinants of health and other factors.

Continuous Glucose Monitoring Prediction of Gestational Diabetes Mellitus and Perinatal Complications.

Objective: To assess the performance of continuous glucose monitoring (CGM)-measured glycemic metrics in predicting development of gestational diabetes mellitus (GDM) and select perinatal complications. Research Methods: In a prospective observational study, CGM data were collected from 760 pregnant females throughout gestation after study enrollment. GDM was diagnosed using the oral glucose tolerance test (OGTT) at 24-34 weeks of gestation. Predictive models were built using logistic and elastic net regression. Predictive performance was assessed by the area under the receiver-operating characteristic (AUROC) curve. Results: The AUROCs of using second trimester percent time >140 mg/dL (TA140) and week 13-14 TA140 in predicting GDM were 0.81 and 0.74, respectively. The AUROCs for predicting large-for-gestational-age (LGA) births and hypertensive disorders of pregnancy (HDP) using second trimester TA140 were both 0.58. When matching the specificity of OGTT, a model using TA140 in weeks 13-14 achieved similar sensitivity to OGTT in predicting HDP (13% vs. 10%, respectively) and LGA (6% for both methods). Elastic net also demonstrated similar AUROC and diagnostic performance with no meaningful improvement by using multiple predictors. Conclusion: CGM-measured hyperglycemic metrics such as TA140 predicted GDM with high AUROCs as early as 13-14 weeks of gestation. These metrics were also similar statistically to the OGTT at 24-34 weeks in predicting perinatal complications, although sensitivity was low for both. CGM could potentially be used as an early screening tool for elevated hyperglycemia during gestation, which could be used in addition to or instead of the OGTT.

Impact of previous gestational diabetes management on perinatal outcomes in subsequent pregnancies affected by gestational diabetes mellitus.

OBJECTIVE: To determine the impact of prior gestational diabetes mellitus (GDM) on perinatal outcomes in a subsequent GDM pregnancy. METHODS: This retrospective cohort study included 544 multiparous patients with two consecutive pregnancies between 2012-2019, where the second (index) pregnancy was affected by GDM. The primary exposure was prior GDM diagnosis, categorized into medical and dietary management. The primary outcome was a composite including need for pharmacotherapy, large-for-gestational age, or neonatal hypoglycemia. Adjusted odds ratios (aOR) were calculated using multivariable logistic regression controlling for maternal age, pre-pregnancy body mass index, and gestational age at GDM diagnosis in the index pregnancy. RESULTS: Of the 544 patients, 164 (30.1%) had prior GDM. Prior GDM significantly increased the likelihood of composite outcome compared to no prior GDM (74.4% vs. 57.4%; P < 0.001). After adjusting for confounders, prior GDM remained significantly associated with the composite outcome (aOR 2.03, 95% confidence interval [CI] 1.31-3.15). Stratifying by prior GDM treatment modality, a significant association was found for prior pharmacotherapy-controlled GDM (aOR 3.29, 95% CI 1.64-6.59), but not for prior diet-controlled GDM (aOR = 1.54, 95% CI 0.92-2.60). CONCLUSION: A history of pharmacotherapy-controlled GDM in a previous pregnancy increases odds of adverse perinatal outcomes in a subsequent GDM pregnancy.

Optimal gestational weight change associated with improved perinatal outcomes in women with gestational diabetes mellitus: a population-based study in the United States.

BACKGROUND: Optimal gestational weight change (GWC) is little known among pregnant women with gestational diabetes mellitus (GDM). OBJECTIVES: This study aimed to explore the optimal GWC ranges for women with GDM and validate these ranges compared with the Institute of Medicine (IOM) guidelines. METHODS: A population-based cohort study using natality data from the National Center for Health Statistics in the United States included 1,338,460 mother-infant pairs with GDM from 2014 to 2020. Poisson regression models were performed to identify GWC ranges (GDM targets) associated with acceptable risks (<10% increase) for a severity-weighted composite outcome including preterm birth (PTB) <37 wk, large for gestational age (LGA, birthweight >90th percentile) and small for gestational age (SGA, birthweight <10th percentile). These targets were validated in individual outcomes including PTB, LGA, SGA, hypertensive disorders of pregnancy, neonatal intensive care unit admission, and neonatal respiratory morbidity, and compared with the IOM guidelines using logistic regression models with population-attributable fractions (PAFs) calculated. RESULTS: The severity-weighted composite outcome had a U-shaped or a J-shaped relationship with GWC across body mass index categories. The GDM targets were 14.1 to 20.3 kg, 9.0 to 17.0 kg, 4.8 to 13.8 kg, -0.8 to 10.8 kg, -2.4 to 8.2 kg, and -8.3 to 6.0 kg for underweight, normal weight, overweight, class 1 obesity, class 2 obesity, and class 3 obesity, respectively. GWC outside the GDM or the IOM targets was associated with increased adverse perinatal outcomes in validation analyses. PAFs indicated that the IOM guidelines reduced a similar or higher proportion of adverse perinatal outcomes compared with the GDM targets for women with GDM, except for those with class 2 and 3 obesity. CONCLUSIONS: The IOM guidelines are generally applicable for women with GDM, except for women with moderate and severe obesity. The optimal GWC ranges for women with GDM and moderate to severe obesity may be lower than the IOM guidelines.

Association between maternal lipid profiles and vitamin D status in second trimester and risk of LGA or SGA: a retrospective study.

Background: Accumulating evidence has linked dyslipidemia during pregnancy to the risk of delivering infants born either large for gestational age (LGA) or small for gestational age (SGA). However, the effects of the vitamin D status on these relationships require further investigation. This study investigated whether the relationship between lipid profiles and the risk of LGA or SGA was influenced by vitamin D levels during the second trimester. Methods: Maternal lipid profile levels, including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and vitamin D levels, were measured in a cohort of 6,499 pregnant women during the second trimester. Multivariate regression models and subgroup analyses were employed to evaluate the potential associations between maternal lipid profiles, vitamin D levels, and the risk of LGA or SGA. Results: The prevalence of SGA infants was 9.8% (n=635), whereas that of LGA infants was 6.9% (n=447). Maternal TG levels were found to be positively associated with the risk of LGA (odds ratio [OR] = 1.41, 95% confidence interval [CI]:1.17-1.70), whereas a negative association was observed between maternal TG, TC, LDL-C levels, and risk of SGA. Additionally, mothers with higher HDL-C levels were less likely to give birth to an LGA infant (OR=0.58, 95% CI:0.39-0.85). Importantly, associations between TG, TC, LDL-c, and SGA as well as between TG and LGA were primarily observed among pregnant women with insufficient vitamin D levels. As for HDL-C, the risk of LGA was lower in mothers with sufficient vitamin D (OR = 0.42, 95% CI:0.18-0.98) compared to those with insufficient vitamin D (OR = 0.65, 95% CI:0.42-0.99). Conclusion: Vitamin D status during the second trimester exerts a modifying effect on the association between lipid profiles and the risk of LGA and SGA infants.

Identifying First-Trimester Risk Factors for SGA-LGA Using Weighted Inheritance Voting Ensemble Learning.

The classification of fetuses as Small for Gestational Age (SGA) and Large for Gestational Age (LGA) is a critical aspect of neonatal health assessment. SGA and LGA, terms used to describe fetal weights that fall below or above the expected weights for Appropriate for Gestational Age (AGA) fetuses, indicate intrauterine growth restriction and excessive fetal growth, respectively. Early prediction and assessment of latent risk factors associated with these classifications can facilitate timely medical interventions, thereby optimizing the health outcomes for both the infant and the mother. This study aims to leverage first-trimester data to achieve these objectives. This study analyzed data from 7943 pregnant women, including 424 SGA, 928 LGA, and 6591 AGA cases, collected from 2015 to 2021 at the Third Affiliated Hospital of Sun Yat-sen University in Guangzhou, China. We propose a novel algorithm, named the Weighted Inheritance Voting Ensemble Learning Algorithm (WIVELA), to predict the classification of fetuses into SGA, LGA, and AGA categories based on biochemical parameters, maternal factors, and morbidity during pregnancy. Additionally, we proposed algorithms for relevance determination based on the classifier to ascertain the importance of features associated with SGA and LGA. The proposed classification solution demonstrated a notable average accuracy rate of 92.12% on 10-fold cross-validation over 100 loops, outperforming five state-of-the-art machine learning algorithms. Furthermore, we identified significant latent maternal risk factors directly associated with SGA and LGA conditions, such as weight change during the first trimester, prepregnancy weight, height, age, and obstetric factors like fetal growth restriction and birthing LGA baby. This study also underscored the importance of biomarker features at the end of the first trimester, including HDL, TG, OGTT-1h, OGTT-0h, OGTT-2h, TC, FPG, and LDL, which reflect the status of SGA or LGA fetuses. This study presents innovative solutions for classifying and identifying relevant attributes, offering valuable tools for medical teams in the clinical monitoring of fetuses predisposed to SGA and LGA conditions during the initial stage of pregnancy. These proposed solutions facilitate early intervention in nutritional care and prenatal healthcare, thereby contributing to enhanced strategies for managing the health and well-being of both the fetus and the expectant mother.