Current and Future Trends in Gestational Diabetes Diagnosis, Care and Neonatal Outcomes

Editorial

30 November 2023

Editorial: Current and future trends in gestational diabetes diagnosis, care and neonatal outcomes

Giulio Frontino

Elena Succurro

Rosa Corcoy

Francesco Scialabba

, 1 more and

Marina Scavini

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0 citations

Editors

Giulio Frontino

Department of Pediatrics, IRCCS San Raffaele Hospital

Elena Succurro

Department of Medical and Surgical Science, University of Magna Graecia

ROSA CORCOY

Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona

Marina Scavini

San Raffaele Scientific Institute (IRCCS)

Impact

Figure 1 showed the inclusion of participants. 623 participants were assessed for eligibility in the original study. We excluded patients with missing values of HDL-C (n=20), TG (n=20), and lack of information on GDM (n=13). The final analysis included 590 subjects in the present study.

Original Research

27 July 2023

Association between the triglyceride to high-density lipoprotein cholesterol ratio and the risk of gestational diabetes mellitus: a second analysis based on data from a prospective cohort study

Yun You

, 4 more and

Weihua Zhao

Background: Although there is strong evidence linking triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio to insulin resistance and diabetes mellitus, its clinical importance in pregnant women has not been well determined. This study sought to determine the connection between the TG/HDL-C ratio in the first trimester and the eventual onset of gestational diabetes mellitus (GDM).

Methods: We performed a secondary analysis of open-access data from a prospective cohort study. This present study included 590 singleton pregnant women at 10-14 weeks who visited the outpatient clinics for prenatal checks and were recorded at Incheon Seoul Women’s Hospital and Seoul Metropolitan Government Seoul National University Boramae Medical Center in Korea. A binary logistic regression model, a series of sensitivity analyses, and subgroup analysis were used to examine the relationship between TG/HDL-C ratio and incident GDM. A receiver operating characteristic (ROC) analysis was also conducted to assess the ability of the TG/HDL-C ratio to predict GDM.

Results: The mean age of the included individuals was 32.06 ± 3.80 years old. The mean TG/HDL-C ratio was 1.96 ± 1.09. The incidence rate of GDM was 6.27%. After adjustment for potentially confounding variables, TG/HDL-C ratio was positively associated with incident GDM (OR=1.77, 95%CI: 1.32-2.38, P=0.0001). Sensitivity analyses and subgroup analysis demonstrated the validity of the relationship between the TG/HDL-C ratio and GDM. The TG/HDL-C ratio was a good predictor of GDM, with an area under the ROC curve of 0.7863 (95% CI: 0.7090-0.8637). The optimal TG/HDL-C ratio cut-off value for detecting GDM was 2.2684, with a sensitivity of 72.97% and specificity of 75.05%.

Conclusion: Our results demonstrate that the elevated TG/HDL-C ratio is related to incident GDM. The TG/HDL-C ratio at 10-14 weeks could help identify pregnant women at risk for GDM and may make it possible for them to receive early and effective treatment to improve their prognosis.

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7 citations

Red represents GDM samples in T2, green represents GDM samples in T3, dark blue represents samples of the control group in T2, and light blue represents samples of the control group in T3. SGDM, GDM group in the second trimester; TGDM, GDM group in the third trimester; SHC, control group in the second trimester; THC, control group in the third trimester; PCoA, Principal Coordinate Analysis. *P value < 0.05.

Original Research

14 July 2023

Composition of the intestinal microbiota and its variations between the second and third trimesters in women with gestational diabetes mellitus and without gestational diabetes mellitus

Nana Liu

, 4 more and

Hang Lin

2,409 views

4 citations

RRs (95% CIs) were adjusted for parity, obesity, and number of prenatal visits. GDM, gestational diabetes mellitus; AMA, advanced maternal age; SGA, small for gestational age; LGA, large for gestational age; Ref, reference group; RR, relative risk; CI, confidence interval; RERI, relative excess risk due to interaction; AP, attributable proportion due to interaction; SI, synergy index.

Original Research

10 May 2023

Effect of gestational diabetes mellitus on pregnancy outcomes among younger and older women and its additive interaction with advanced maternal age

Jiangheng Li

, 4 more and

Wu Jiang

Background: The prevalence of gestational diabetes mellitus (GDM) and advanced maternal age (AMA, ≥ 35 years) has shown an increasing trend worldwide. This study aimed to evaluate the risk of pregnancy outcomes among younger (20-34 years) and older (≥ 35 years) women with GDM and further analyze the epidemiologic interaction of GDM and AMA on these outcomes.

Methods: This historical cohort study included 105 683 singleton pregnant women aged 20 years or older between January 2012 and December 2015 in China. Stratified by maternal age, the associations between GDM and pregnancy outcomes were analyzed by performing logistic regression. Epidemiologic interactions were assessed by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (SI) with their 95% confidence intervals (95%CIs).

Results: Among younger women, individuals with GDM had a higher risk of all maternal outcomes, preterm birth (relative risk [RR] 1.67, 95%CI 1.50–1.85), low birthweight (RR 1.24, 95%CI 1.09–1.41), large for gestational age (RR 1.51, 95%CI 1.40–1.63), macrosomia (RR 1.54, 95%CI 1.31–1.79), and fetal distress (RR 1.56, 95%CI 1.37–1.77) than those without GDM. Among older women, GDM increased the risk of gestational hypertension (RR 2.17, 95%CI 1.65–2.83), preeclampsia (RR 2.30, 95%CI 1.81–2.93), polyhydramnios (RR 3.46, 95%CI 2.01–5.96), cesarean delivery (RR 1.18, 95%CI 1.10–1.25), preterm birth (RR 1.35, 95%CI 1.14–1.60), large for gestational age (RR 1.40, 95%CI 1.23–1.60), macrosomia (RR 1.65, 95%CI 1.28–2.14) and fetal distress (RR 1.46, 95%CI 1.12–1.90). Additive interactions of GDM and AMA on polyhydramnios and preeclampsia were found, with RERI of 3.11 (95%CI 0.05-6.16) and 1.43 (95%CI 0.09-2.77), AP of 0.51 (95%CI 0.22-0.80) and 0.27 (95%CI 0.07-0.46), and SI of 2.59 (95%CI 1.17-5.77) and 1.49 (95%CI 1.07-2.07), respectively.

Conclusion: GDM is an independent risk factor for multiple adverse pregnancy outcomes, and may exert additive interactions with AMA on the risk of polyhydramnios and preeclampsia.

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7 citations

Review

20 June 2023

Lights and shadows on the use of metformin in pregnancy: from the preconception phase to breastfeeding and beyond

Giulia Tosti

, 9 more and

Dario Pitocco

4,269 views

1 citations

Original Research

04 May 2023

Birth weight and large for gestational age trends in offspring of pregnant women with gestational diabetes mellitus in southern China, 2012-2021

Li-Rong He

, 1 more and

Yong Guo

1,101 views

2 citations

Original Research

28 March 2023

Maternal and fetal predictors of anthropometry in the first year of life in offspring of women with GDM

Maria-Christina Antoniou

, 8 more and

Jardena Jacqueline Puder

3,454 views

1 citations

Serum taurine concentration in control decreased significantly (P<0.001).

Original Research

23 March 2023

Dynamic changes of serum taurine and the association with gestational diabetes mellitus: A nested case-control study

Jia Wang

, 9 more and

Guanghui Li

2,189 views

1 citations

Demonstrates the inclusion and exclusion criteria of our study population; glycated hemoglobin A1c (HbA1c); gestational diabetes mellitus (GDM); fasting plasma glucose (FPG); 2hPG (2-hour plasma glucose); Oral glucose tolerance test (OGTT); chronic diseases (hypertension, liver, kidney, heart, lung and other major organ diseases, or tumors); autoimmune diseases (Sjogren's syndrome, anticardiolipin syndrome, myasthenia gravis).

Original Research

16 March 2023

The association between maternal HbA1c and adverse outcomes in gestational diabetes

Marie Parfaite Uwimana Muhuza

, 4 more and

Zhaoxia Liang

Background: The role of HbA1c in women with gestational diabetes mellitus (GDM) is still unclear, particularly in the Asian population.

Aim: To investigate the association between HbA1c levels and adverse outcomes considering maternal age, pre-pregnancy body mass index (BMI), and gestational weight gain (GWG) in women with GDM.

Method: A retrospective study included 2048 women with GDM and singleton live births. Using logistic regression, the associations between HbA1c and adverse pregnancy outcomes were assessed.

Result: Compared to women with HbA1c ≤ 5.0%, HbA1c was significantly associated with macrosomia (aOR 2.63,95%CI1.61,4.31), pregnancy-induced hypertension (PIH, aOR 2.56,95%CI1.57,4.19), preterm birth (aOR 1.64,95%CI 1.05,2.55), and primary Cesarean section (primary C-section, aOR1.49,95%CI1.09,2.03) in GDM women with HbA1c ≥5.5% while significantly associated with PIH (aOR 1.91,95%CI1.24,2.94) in women with HbA1c 5.1-5.4%. The associations between HbA1c and adverse outcomes varied with maternal age, pre-pregnancy BMI, and GWG. In women aged ≤29 years, there’s significant association between HbA1c and primary C-section when HbA1c was 5.1-5.4% and ≥5.5%. In women aged 29-34 years and HbA1c ≥5.5%, HbA1c was significantly associated with macrosomia. In women aged ≥35 years, there’s significant association between HbA1c and preterm birth when HbA1c was 5.1-5.4% and macrosomia and PIH when HbA1c ≥5.5%. In pre-pregnant normal-weight women, HbA1c was significantly associated with macrosomia, preterm birth, primary C-section, and PIH when HbA1c ≥5.5% while HbA1c was significantly associated with PIH when HbA1c was 5.1-5.4% . In pre-pregnant underweight women with HbA1c 5.1-5.4%, HbA1c was significantly associated with primary C-section. HbA1c was significantly associated with macrosomia among women with inadequate GWG or excess GWG and HbA1c≥5.5%. In women with adequate GWG, there’s significant association between HbA1c and PIH when HbA1c was 5.1-5.4% and ≥5.5% .

Conclusion: Conclusively, HbA1c at the time of diagnosis is significantly associated with macrosomia, preterm birth, PIH, and primary C-section in Chinese women with GDM.

4,850 views

10 citations

XG Boost ML, extreme gradient boosting (XG) machine learning (ML).

Original Research

09 March 2023

Prediction model for gestational diabetes mellitus using the XG Boost machine learning algorithm

Xiaoqi Hu

, 2 more and

Jia Wang

Objective: To develop the extreme gradient boosting (XG Boost) machine learning (ML) model for predicting gestational diabetes mellitus (GDM) compared with a model using the traditional logistic regression (LR) method.

Methods: A case–control study was carried out among pregnant women, who were assigned to either the training set (these women were recruited from August 2019 to November 2019) or the testing set (these women were recruited in August 2020). We applied the XG Boost ML model approach to identify the best set of predictors out of a set of 33 variables. The performance of the prediction model was determined by using the area under the receiver operating characteristic (ROC) curve (AUC) to assess discrimination, and the Hosmer–Lemeshow (HL) test and calibration plots to assess calibration. Decision curve analysis (DCA) was introduced to evaluate the clinical use of each of the models.

Results: A total of 735 and 190 pregnant women were included in the training and testing sets, respectively. The XG Boost ML model, which included 20 predictors, resulted in an AUC of 0.946 and yielded a predictive accuracy of 0.875, whereas the model using a traditional LR included four predictors and presented an AUC of 0.752 and yielded a predictive accuracy of 0.786. The HL test and calibration plots show that the two models have good calibration. DCA indicated that treating only those women whom the XG Boost ML model predicts are at risk of GDM confers a net benefit compared with treating all women or treating none.

Conclusions: The established model using XG Boost ML showed better predictive ability than the traditional LR model in terms of discrimination. The calibration performance of both models was good.

4,161 views

9 citations

Original Research

24 February 2023

Establishment and validation of a predictive nomogram for gestational diabetes mellitus during early pregnancy term: A retrospective study

Luman Li

, 6 more and

Yuanzhen Zhang

A total of 1,216 pregnant women enrolled in our study were selected by inclusion criteria. The training dataset (n = 824) was used to estimate a GDM predictive model, and our study applied LASSO logistic regression and multivariate ROC risk analysis to determine significant predictors and establish the nomogram. A total of 392 early pregnant women were used as a validation dataset. We evaluate the nomogram by AUC, C-index, calibration curve, and decision curve analysis (DCA).

Objective: This study aims to develop and evaluate a predictive nomogram for early assessment risk factors of gestational diabetes mellitus (GDM) during early pregnancy term, so as to help early clinical management and intervention.

Methods: A total of 824 pregnant women at Zhongnan Hospital of Wuhan University and Maternal and Child Health Hospital of Hubei Province from 1 February 2020 to 30 April 2020 were enrolled in a retrospective observational study and comprised the training dataset. Routine clinical and laboratory information was collected; we applied least absolute shrinkage and selection operator (LASSO) logistic regression and multivariate ROC risk analysis to determine significant predictors and establish the nomogram, and the early pregnancy files (gestational weeks 12–16, n = 392) at the same hospital were collected as a validation dataset. We evaluated the nomogram via the receiver operating characteristic (ROC) curve, C-index, calibration curve, and decision curve analysis (DCA).

Results: We conducted LASSO analysis and multivariate regression to establish a GDM nomogram during the early pregnancy term; the five selected risk predictors are as follows: age, blood urea nitrogen (BUN), fibrinogen-to-albumin ratio (FAR), blood urea nitrogen-to-creatinine ratio (BUN/Cr), and blood urea nitrogen-to-albumin ratio (BUN/ALB). The calibration curve and DCA present optimal predictive power. DCA demonstrates that the nomogram could be applied clinically.

Conclusion: An effective nomogram that predicts GDM should be established in order to help clinical management and intervention at the early gestational stage.

2,571 views

5 citations