Trends and predictors of gestational diabetes mellitus in Chile

Enhancing gestational diabetes mellitus risk assessment and treatment through GDMPredictor: a machine learning approach

BACKGROUND

Gestational diabetes mellitus (GDM) is a serious health concern that affects pregnant women worldwide and can lead to adverse pregnancy outcomes. Early detection of high-risk individuals and the implementation of appropriate treatment can enhance these outcomes.

METHODS

We conducted a study on a cohort of 3467 pregnant women during their pregnancy, with a total of 5649 clinical and biochemical records collected. We utilized this dataset as our training dataset to develop a web server called GDMPredictor. The GDMPredictor utilizes advanced machine learning techniques to predict the risk of GDM in pregnant women. We also personalize treatment recommendations based on essential biochemical indicators, such as A1MG, BMG, CysC, CO2, TBA, FPG, and CREA. Our assessment of GDMPredictor's effectiveness involved training it on the dataset of 3467 pregnant women and measuring its ability to predict GDM risk using an AUC and auPRC.

RESULTS

GDMPredictor demonstrated an impressive level of precision by achieving an AUC score of 0.967. To tailor our treatment recommendations, we use the GDM risk level to identify higher risk candidates who require more intensive care. The GDMPredictor can accept biochemical indicators for predicting the risk of GDM at any period from 1 to 24 weeks, providing healthcare professionals with an intuitive interface to identify high-risk patients and give optimal treatment recommendations.

CONCLUSIONS

The GDMPredictor presents a valuable asset for clinical practice, with the potential to change the management of GDM in pregnant women. Its high accuracy and efficiency make it a reliable tool for doctors to improve patient outcomes. Early identification of high-risk individuals and tailored treatment can improve maternal and fetal health outcomes http://www.bioinfogenetics.info/GDM/ .

Hyperglycaemia in Pregnancy Is Less Frequent in Smokers: A French Observational Study of 15,801 Women

Background: We aimed to explore the still-debated association between smoking and hyperglycaemia in pregnancy (HIP). Methods: A multiethnic prospective study of 15,801 women who delivered at Jean Verdier University Hospital between 2012 and 2018. Of these, 13,943 (88.2%) were non-smokers, 624 (4.5%) former smokers, and 1234 (7.8%) current smokers. Universal HIP screening was proposed to the entire sample (IADPSG/WHO criteria). Results: A total of 13,958 women were screened for HIP. Uptake differed between non-smokers, former smokers, and current smokers (89.5%, 88.3%, and 75.7%, respectively, p < 0.0001). HIP prevalence in these groups was 19.9%, 15.4%, and 12.3%, respectively (p < 0.0001). After adjusting for age, body mass index, family history of diabetes, history of HIP, history of macrosomic baby, and ethnicity, current (odds ratio 0.790 [95% confidence interval 0.636-0.981], p < 0.05) but not former (1.017 [0.792-1.306]) smokers were less likely to have HIP than non-smokers. Furthermore, 1 h and 2 h oral plasma glucose test values were lower in current smokers than in non-smokers (p < 0.01). To exclude potential selection bias, we compared risk factors for HIP and HIP-related adverse pregnancy outcomes in current smokers according to HIP screening status. Compared with screened current smokers (n = 934), their unscreened counterparts (n = 300) were younger, less frequently employed, and more likely to be of non-European origin. Moreover, infant birthweight was lower in this group, and preterm deliveries and perinatal deaths were more likely (all p < 0.01). Conclusions: Smoking during pregnancy was independently associated with lower HIP prevalence. The low HIP screening rate in current smokers did not explain this finding.

Effects of multidimensional exercise management on self-efficacy, blood glucose control, and delivery outcomes in pregnant women with gestational diabetes mellitus

Objective

This study aimed to evaluate the effects of multidimensional quantitative exercise management on self-efficacy, blood glucose control, and delivery outcomes in pregnant women with gestational diabetes mellitus (GDM).

Methods

A randomized controlled trial was conducted with 150 pregnant women diagnosed with gestational diabetes mellitus (GDM). Participants were randomly assigned to either the experimental group (Exp), which received a multidimensional quantitative exercise management intervention, or the control group (Con), which received standard GDM management. Results were compared between the groups included self-efficacy scores, blood glucose levels, and delivery outcomes.

Results

Exp group of pregnant women exhibited drastically superior self-efficacy scores as well as more stable blood glucose levels during pregnancy relative to Con group (P < 0.05). Moreover, visual analogue scale (VAS) of pregnant women and Apgar scores of infants in Exp group were considerably better than those in Con group (P < 0.05). In contrast to Con group, pregnant women in Exp group had considerably better labor outcomes along neonatal complication rates (P < 0.05).

Conclusion

Multidimensional quantitative exercise management had a positive impact on pregnant women with GDM. This intervention method can improve self-efficacy levels along better blood glucose control, and enhance delivery outcomes. These findings suggested that multidimensional quantitative exercise management has potential clinical value in the management of GDM, providing an effective management strategy to improve the health conditions of both pregnant women and infants.

Association between maternal lipid profiles and lipid ratios in early to middle pregnancy as well as their dynamic changes and gestational diabetes mellitus

BACKGROUND

Unfavourable lipid and glucose levels may play a crucial role in the pathogenesis of gestational diabetes mellitus (GDM). However, there is a lack of prospective studies on the relationship between lipid profiles, lipid ratios and GDM during pregnancy.

AIMS

To prospectively investigate the relationship between lipid profile and lipid ratios in early and mid-pregnancy and their pattern of change from early to mid-pregnancy and the risk of GDM.

METHODS

This nested case-control study was based on maternal and child healthcare hospitals from Fujian Province, China. We included pregnant women who delivered in the hospital from January 2021 to June 2023. Lipid profiles (TC, TG, ApoA1, ApoB, HDL-c, LDL-c) and fasting glucose were measured before 14 weeks of gestation and between 20 and 28 weeks of gestation, and lipid ratios (triglyceride glucose index, TG/HDL-c and TC/HDL-c) was constructed. Logistic regression was used to assess the relationship between lipid profile, lipid ratios and GDM.

RESULTS

Of 1586 pregnant women, 741 were diagnosed with GDM. After adjusting for potential confounders, TG, ApoA1, ApoB, LDL-c, triglyceride glucose index, TG/HDL-c, and TC/HDL-c in early pregnancy were positively associated with the risk of GDM (odds ratios [95% CI] for extreme interquartile comparisons were 2.040 (1.468-2.843), 1.506 (1.091-2.082), 1.529 (1.110-2.107), 1.504 (1.086-2.086), 1.952 (1.398-2.731), 2.127 (1.526-2.971), and 2.370 (1.700-3.312), all trend P < 0.05). HDL-c was negatively associated with the risk of GDM (0.639: 0.459-0.889, trend P all less than 0.05). Similarly, in mid-pregnancy, lower levels of HDL-c, higher levels of triglyceride glucose index, TG/HDL-c ratio, and TC/HDL-c ratio were associated with increased risk of GDM (all trends P < 0.05). Stably high levels (both ≥ median for early and mid-pregnancy) of triglyceride glucose index, TG/HDL-c and TC/HDL-c were associated with increased risk of GDM (OR [95% CI]: 2.369 (1.438-3.940), 1.588 (1.077-2.341), 1.921 (1.309-2.829), respectively). The opposite was true for HDL-c, where stable high levels were negatively associated with GDM risk (OR [95% CI]: 0.599 (0.405-0.883)).

CONCLUSION

Increases in triglyceride glucose index, TG/HDL-c ratio, and TC/HDL-c ratio in early and mid-pregnancy, as well as their stable high levels from early to mid-pregnancy, are associated with a higher risk of GDM. In contrast, increased levels of HDL-c, both in early and mid-pregnancy, and their stable high levels from early to mid-pregnancy were associated with a lower risk of GDM. That highlighted their possible clinical relevance in identifying those at high risk of GDM.

Simple and Fast Prediction of Gestational Diabetes Mellitus Based on Machine Learning and Near-Infrared Spectra of Serum: A Proof of Concept Study at Different Stages of Pregnancy

Gestational diabetes mellitus (GDM) is a hyperglycemic state that is typically diagnosed by an oral glucose tolerance test (OGTT), which is unpleasant, time-consuming, has low reproducibility, and results are tardy. The machine learning (ML) predictive models that have been proposed to improve GDM diagnosis are usually based on instrumental methods that take hours to produce a result. Near-infrared (NIR) spectroscopy is a simple, fast, and low-cost analytical technique that has never been assessed for the prediction of GDM. This study aims to develop ML predictive models for GDM based on NIR spectroscopy, and to evaluate their potential as early detection or alternative screening tools according to their predictive power and duration of analysis. Serum samples from the first trimester (before GDM diagnosis) and the second trimester (at the time of GDM diagnosis) of pregnancy were analyzed by NIR spectroscopy. Four spectral ranges were considered, and 80 mathematical pretreatments were tested for each. NIR data-based models were built with single- and multi-block ML techniques. Every model was subjected to double cross-validation. The best models for first and second trimester achieved areas under the receiver operating characteristic curve of 0.5768 ± 0.0635 and 0.8836 ± 0.0259, respectively. This is the first study reporting NIR-spectroscopy-based methods for the prediction of GDM. The developed methods allow for prediction of GDM from 10 µL of serum in only 32 min. They are simple, fast, and have a great potential for application in clinical practice, especially as alternative screening tools to the OGTT for GDM diagnosis.

Genetic and inflammatory factors underlying gestational diabetes mellitus: a review

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

Trends in the prevalence of gestational diabetes in Catalonia from 2010 to 2019

INTRODUCTION

Gestational diabetes mellitus (GDM) is globally increasing due to changes in risk factors such as gestational age, obesity, and socioeconomic status (SES). This study examined trends of GDM prevalence over ten years using a real-world Primary Health Care database from Catalonia (Spain).

METHODS

A retrospective analysis of pregnant women screened for GDM was conducted, using clinical and SES data from the SIDIAP database.

RESULTS

Among 221,806 women studied from 2010 to 2019,17,587 had GDM, equating to a 7.9% prevalence (95% CI 7.8-8.04). GDM subjects were older (33.5 ± 5.1 vs. 31.2 ± 5.6 years; p < 0.001) and had higher BMI (29.2 ± 5.1 vs .27.8 ± 4.8 kg/m²; p < 0.001) than non-GDM individuals. Overall GDM prevalence remained unchanged throughout the study, although an increase was observed in younger women (below 20 years: 1.28% [95% CI 0.59-2.42] in 2010 to 2.22% [95% CI 0.96-4.33] in 2019, p = 0.02; ages 20-25.9 years: 3.62% [95% CI 3.12-4.17] in 2010 to 4.63% [95% CI 3.88-5.48)] in 2019, p = 0.02). Age, BMI ≥ 25 kg/m2, deprived SES, and previous hypertension and dyslipidaemia were positively associated with GDM.

CONCLUSIONS

This study offers insights into GDM prevalence in Catalonia (Spain),showing overall stability except for a rising trend among younger women.

Establishment and validation of a prediction model for gestational diabetes

AIM

To develop a visual prediction model for gestational diabetes (GD) in pregnant women and to establish an effective and practical tool for clinical application.

METHODS

To establish a prediction model, the modelling set included 1756 women enrolled in the Zunyi birth cohort, the internal validation set included 1234 enrolled women, and pregnant women in the Wuhan cohort were included in the external validation set. We established a demographic-lifestyle factor model (DLFM) and a demographic-lifestyle-environmental pollution factor model (DLEFM) based on whether the women were exposed to environmental pollutants. The least absolute shrinkage and selection lasso-logistic regression analyses were used to identify the independent predictors of GD and construct a nomogram for predicting its occurrence.

RESULTS

The DLEFM regression analysis showed that a family history of diabetes (odd ratio [OR] 2.28; 95% confidence interval [CI] 1.05-4.71), a history of GD in pregnant women (OR 4.22; 95% CI 1.89-9.41), being overweight or obese before pregnancy (OR 1.71; 95% CI 1.27-2.29), a history of hypertension (OR 2.61; 95% CI 1.41-4.72), sedentary time (h/day) (OR 1.16; 95% CI 1.08-1.24), monobenzyl phthalate (OR 1.95; 95% CI 1.45-2.67) and Q4 mono-ethyl phthalate concentration (OR 1.85; 95% CI 1.26-2.73) were independent predictors. The area under the receiver operating curves for the internal validation of the DLEFM and the DLFM constructed using these seven factors was 0.827 and 0.783, respectively. The calibration curve of the DLEFM was close to the diagonal line. The DLEFM was thus the more optimal model, and the one which we chose.

CONCLUSIONS

A nomogram based on preconception factors was constructed to predict the occurrence of GD in the second and third trimesters. It provided an effective tool for the early prediction and timely management of GD.

Iron, folic acid, and vitamin D supplementation during pregnancy: Did pregnant Chilean women meet the recommendations during the COVID pandemic?

BACKGROUND

Antenatal micronutrient supplementation has been defined as a priority for Low-and Middle-income Countries (LMICs). However, it is also relevant to assess its performance in middle-high income countries, such as Chile, particularly given the post-pandemic food insecurity context.

AIM

To assess the use (frequency and doses) of daily recommended supplementation (iron (15-30 mg), folic acid (FA) (400-800 μg/day), and vitamin (VD) (400 IU)) in a sample of Chilean pregnant women.

METHODS

In 1, 507 pregnant women selected from public health care registries of the Southeast area of Santiago-Chile, we collected maternal, supplement use, sociodemographic, and nutritional information at the first (<15 weeks), second (24-28 weeks), and third trimesters (32-36 weeks) of gestation by using a researcher administer online questionnaire.

RESULTS

The median (IQR) age of women was 29 (25-33) years. Pre-conceptional supplementation was rare (24%), but it reached >93% in the first trimester; thereafter supplement use decreased to 79% in the second and 84% in the third trimesters, particularly in women with lower income (p<0.05), lower education (p<0.05), and with excess weight (p<0.05). Use of iron supplements in the first trimester was rare (<21%) as well as the use of VD supplements across pregnancy (<31%). Most FA (70%) and iron (80%) supplement users, exceeded the recommended daily dose while ~40% of VD users took less than the recommended dose.

CONCLUSIONS

In this sample of Chilean women, timely initiation of FA, iron, and VD supplementation was low and doses were not aligned with the recommendations. Strengthening adherence and quality of micronutrient supplementation programs delivered through public primary care could benefit particularly the most vulnerable women.

Smoking during pregnancy and gestational diabetes mellitus: a systematic review and meta-analysis

PURPOSE

To investigate whether maternal cigarette smoking during pregnancy is a risk factor for developing GDM.

METHODS

MEDLINE, Scopus, CENTRAL and Google Scholar databases were searched from inception to December 2022 to identify eligible original articles. A systematic review and meta-analysis (weighted data, random-effects model) were performed. The primary outcome was the development of GDM in pregnant women. The results were expressed as odds ratios (OR) with 95% confidence interval (CI) (inverse variance method). Subgroup analysis was planned according to the maternal smoking status and GDM diagnostic criteria. Statistical heterogeneity was checked with the Chi-squared (Chi2) test and the I2 index was used to quantify it. The studies were evaluated for publication bias.

RESULTS

Thirty-five studies, including 23,849,696 pregnant women, met the inclusion criteria. The pooled OR of smoking during pregnancy compared with non-smoking (never smokers and former smokers) was 1.06 (95% CI 0.95-1.19), p = 0.30; I2 = 90%; Chi2 = 344; df=34; p < 0.001. Subgroup analysis was performed according to the two-step Carpenter-Coustan diagnostic criteria, due to the high heterogeneity among the other applied methods. The pooled OR for the Carpenter-Coustan subgroup was 1.19 (95% CI 0.95-1.49), p = 0.12; I2 = 63%; Chi2 = 27; df=10; p < 0.002. Further subgroup analysis according to maternal smoking status was not performed due to missing data.

CONCLUSION

There is no evidence to support an association between maternal cigarette smoking during pregnancy and the risk for GDM. Universally accepted diagnostic criteria for GDM must be adopted to reduce heterogeneity and clarify the association between smoking and GDM.

Temporal and Spatial Trends of Adverse Pregnancy and Birth Outcomes in a Sample of Births from a Public Hospital in Chile

Understanding temporal and spatial trends in pregnancy and birth outcomes within an urban area is important for the monitoring of health indicators of a population. We conducted a retrospective cohort study of all births in the public hospital of Temuco, a medium-sized city in Southern Chile between 2009 and 2016 (n = 17,237). Information on adverse pregnancy and birth outcomes, as well as spatial and maternal characteristics (insurance type, employment, smoking, age, and overweight/obesity), was collected from medical charts. Home addresses were geocoded and assigned to neighborhood. We tested whether births and prevalence of adverse pregnancy outcomes changed over time, whether birth events were spatially clustered (Moran's I statistic), and whether neighborhood deprivation was correlated to outcomes (Spearman's rho). We observed decreases in eclampsia, hypertensive disorders of pregnancy, and small for gestational age, while gestational diabetes, preterm birth, and low birth weight increased over the study period (all p < 0.01 for trend), with little changes after adjusting for maternal characteristics. We observed neighborhood clusters for birth rate, preterm birth, and low birth weight. Neighborhood deprivation was negatively correlated with low birth weight and preterm birth, but not correlated with eclampsia, preeclampsia, hypertensive disorders of pregnancy, small for gestational age, gestational diabetes, nor stillbirth. Several encouraging downward trends and some increases in adverse pregnancy and birth outcomes, which, overall, were not explained by changes in maternal characteristics were observed. Identified clusters of higher adverse birth outcomes may be used to evaluate preventive health coverage in this setting.

Association between second- and third-trimester maternal lipid profiles and adverse perinatal outcomes among women with GDM and non-GDM: a retrospective cohort study

BACKGROUND

Lipid metabolism disorder during pregnancy has been reported in women with gestational diabetes mellitus (GDM). However, controversy remains regarding the relationship between maternal changes in lipid profiles and perinatal outcomes. This study investigated the association between maternal lipid levels and adverse perinatal outcomes in women with GDM and non-GDM.

METHODS

In total, 1632 pregnant women with GDM and 9067 women with non-GDM who delivered between 2011-2021 were enrolled in this study. Serum samples were assayed for fasting total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) levels during the second and third trimesters of pregnancy. Adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) were calculated via multivariable logistic regression analysis to determine the association of lipid levels with perinatal outcomes.

RESULTS

The serum TC, TG, LDL, and HDL levels in the third trimester were significantly higher than those in the second trimester (p < 0.001). Women with GDM had significantly higher levels of TC and TG in the second and third trimesters than those with non-GDM in the same trimesters, while HDL levels decreased in women with GDM (all p < 0.001). After adjusting for confounding factors by multivariate logistic regression, every mmol/L elevation in TG levels of women with GDM in second and third trimesters was associated with a higher risk of caesarean section (AOR = 1.241, 95% CI: 1.103-1.396, p < 0.001; AOR = 1.716, 95% CI: 1.556-1.921, p < 0.001), large for gestational age infants (LGA) (AOR = 1.419, 95% CI: 1.173-2.453, p = 0.001; AOR = 2.011, 95% CI: 1.673-2.735, p < 0.001), macrosomia (AOR = 1.220, 95% CI: 1.133-1.643, p = 0.005; AOR = 1.891, 95% CI: 1.322-2.519, p < 0.001), and neonatal unit admission (NUD; AOR = 1.781, 95% CI: 1.267-2.143, p < 0.001; AOR = 2.052, 95% CI: 1.811-2.432, p < 0.001) cesarean delivery (AOR = 1.423, 95% CI: 1.215-1.679, p < 0.001; AOR = 1.834, 95% CI: 1.453-2.019, p < 0.001), LGA (AOR = 1.593, 95% CI: 1.235-2.518, p = 0.004; AOR = 2.326, 95% CI: 1.728-2.914, p < 0.001), macrosomia (AOR = 1.346, 95% CI: 1.209-1.735, p = 0.006; AOR = 2.032, 95% CI: 1.503-2.627, p < 0.001), and neonatal unit admission (NUD) (AOR = 1.936, 95% CI: 1.453-2.546, p < 0.001; AOR = 1.993, 95% CI: 1.724-2.517, p < 0.001), which were higher than the relative risk of these perinatal outcomes in women with non-GDM. Additionally, every mmol/L increase in second and third-trimester HDL levels of women with GDM was associated with decreased risk of LGA(AOR = 0.421, 95% CI: 0.353-0.712, p = 0.007; AOR = 0.525, 95% CI: 0.319-0.832, p = 0.017) and NUD (AOR = 0.532, 95% CI: 0.327-0.773, p = 0.011; AOR = 0.319, 95% CI: 0.193-0.508, p < 0.001), and the risk reduction was not strong than that of women with GDM.

CONCLUSIONS

Among women with GDM, high maternal TG in the second and third trimesters was independently associated with an increased risk of cesarean section, LGA, macrosomia, and NUD. High maternal HDL during the second and third trimesters was significantly associated with decreased risk of LGA and NUD. These associations were stronger than those in women with non-GDM, suggesting the importance of monitoring second and third-trimester lipid profiles in improving clinical outcomes, especially in GDM pregnancies.

Platelets and endothelial dysfunction in gestational diabetes mellitus

The prevalence of gestational diabetes mellitus (GDM) has increased in recent years, along with the higher prevalence of obesity in women of reproductive age. GDM is a pathology associated with vascular dysfunction in the fetoplacental unit. GDM-associated endothelial dysfunction alters the transfer of nutrients to the foetus affecting newborns and pregnant women. Various mechanisms for this vascular dysfunction have been proposed, of which the most studied are metabolic alterations of the vascular endothelium. However, different cell types are involved in GDM-associated endothelial dysfunction, including platelets. Platelets are small, enucleated cell fragments that actively take part in blood haemostasis and thrombus formation. Thus, they play crucial roles in pathologies coursing with endothelial dysfunction, such as atherosclerosis, cardiovascular diseases, and diabetes mellitus. Nevertheless, platelet function in GDM is understudied. Several reports show a potential relationship between platelet volume and mass with GDM; however, platelet roles and signaling mechanisms in GDM-associated endothelial dysfunction are unclear. This review summarizes the reported findings and proposes a link among altered amount, volume, mass, reactivity, and function of platelets and placenta development, resulting in fetoplacental vascular dysfunction in GDM.

Consequences of the exposome to gestational diabetes mellitus

The exposome is the cumulative measure of environmental influences and associated biological responses throughout the lifespan, including those from the environment, diet, behaviour, and endogenous processes. The exposome concept and the 2030 Agenda for the Sustainable Development Goals (SDGs) from the United Nations are the basis for understanding the aetiology and consequences of non-communicable diseases, including gestational diabetes mellitus (GDM). Pregnancy may be developed in an environment with adverse factors part of the immediate internal medium for fetus development and the external medium to which the pregnant woman is exposed. The placenta is the interface between maternal and fetal compartments and acts as a protective barrier or easing agent to transfer exposome from mother to fetus. Under and over-nutrition in utero, exposure to adverse environmental pollutants such as heavy metals, endocrine-disrupting chemicals, pesticides, drugs, pharmaceuticals, lifestyle, air pollutants, and tobacco smoke plays a determinant role in the development of GDM. This phenomenon is worsened by metabolic stress postnatally, such as obesity which increases the risk of GDM and other diseases. Clinical risk factors for GDM development include its aetiology. It is proposed that knowledge-based interventions to change the potential interdependent ecto-exposome and endo-exposome could avoid the occurrence and consequences of GDM.

Evaluation of first and second trimester maternal thyroid profile on the prediction of gestational diabetes mellitus and post load glycemia

Maternal thyroid alterations have been widely associated with the risk of gestational diabetes mellitus (GDM). This study aims to 1) test the first and the second trimester full maternal thyroid profile on the prediction of GDM, both alone and combined with non-thyroid data; and 2) make that prediction independent of the diagnostic criteria, by evaluating the effectiveness of the different maternal variables on the prediction of oral glucose tolerance test (OGTT) post load glycemia. Pregnant women were recruited in Concepción, Chile. GDM diagnosis was performed at 24-28 weeks of pregnancy by an OGTT (n = 54 for normal glucose tolerance, n = 12 for GDM). 75 maternal thyroid and non-thyroid parameters were recorded in the first and the second trimester of pregnancy. Various combinations of variables were assessed for GDM and post load glycemia prediction through different classification and regression machine learning techniques. The best predictive models were simplified by variable selection. Every model was subjected to leave-one-out cross-validation. Our results indicate that thyroid markers are useful for the prediction of GDM and post load glycemia, especially at the second trimester of pregnancy. Thus, they could be used as an alternative screening tool for GDM, independently of the diagnostic criteria used. The final classification models predict GDM with cross-validation areas under the receiver operating characteristic curve of 0.867 (p<0.001) and 0.920 (p<0.001) in the first and the second trimester of pregnancy, respectively. The final regression models predict post load glycemia with cross-validation Spearman r correlation coefficients of 0.259 (p = 0.036) and 0.457 (p<0.001) in the first and the second trimester of pregnancy, respectively. This investigation constitutes the first attempt to test the performance of the whole maternal thyroid profile on GDM and OGTT post load glycemia prediction. Future external validation studies are needed to confirm these findings in larger cohorts and different populations.

Evolution of Gestational Diabetes Mellitus across Continents in 21st Century

Over the last few decades, several definitions of gestational diabetes mellitus (GDM) have been described. There is currently not enough research to show which way is the best to diagnose GDM. Opinions differ in terms of the optimal screening and diagnostic measures, in part due to the differences in the population risks, the cost-effectiveness considerations, and the lack of an evidence base to support large national screening programs. The basic method for identifying the disease is the measurement of glucose plasma levels which may be determined when fasting, two hours after a meal, or simply at any random time. The currently increasing incidence of diabetes in the whole population, the altering demographics and the presence of lifestyle changes still require better methods of screening for hyperglycemia, especially during pregnancy. The main aim of this review is to focus on the prevalence and modifications to the screening criteria for GDM across all continents in the 21st century. We would like to show the differences in the above issues and correlate them with the geographical situation. Looking at the history of diabetes, we are sure that more than one evolution in GDM diagnosis will occur, due to the development of medicine, appearance of modern technologies, and the dynamic continuation of research.

Gestational diabetes mellitus and hypertensive disorder of pregnancy play as spouse-pair risk factors of diabetes and hypertension: Insights from Tehran Lipid and Glucose Study

BACKGROUND

Complicated pregnancies by gestational diabetes mellitus (GDM) and hypertensive disorder of pregnancy (HDP) are relatively common worldwide. The evidence is still inconclusive regarding the role of GDM and HDP as spousal risk factor of diabetes (DM) and hypertension (HTN). This study aimed to determine the spousal risk of development of DM and/or HTN in the context of GDM and/or HDP.

METHODS

This population-based cohort study involved couples who participated in Tehran Lipid and Glucose Study. A total of 3650 pairs of spouses were identified, and among them, 2820 met the inclusion criteria. Included participants, followed up 3-year intervals visits from 1999 to 2018. All pairs underwent standard data collection. GDM and HDP were the main exposure of interest in females, and DM and HTN were the main outcomes in both females and their spouses. Cox proportional hazard regression models were used for both females and their spouses, adjusting for age, consanguinity, waist-to-height ratio, physical activity, smoking, and parity.

RESULTS

Of 2820 females, 558 (19.79 %) had histories of GDM or HDP, and 72 (2.55 %) experienced both. Among females who experienced GDM and HDP, 24 (33 %) and 31 (33 %) developed DM and HTN during the follow-up. The corresponding numbers were 89 (16 %) and 191 (34 %) for those who experienced GDM or HPD, and 274 (13 %) and 623 (28 %) for the non-risk factors group. The incidences of DM were 9 (12 %), 100 (18 %), and 373 (17 %) for males whose spouses experienced both GDM and HDP, either one or none of them, respectively. Among males in these groups, 20 (28 %), 150 (27 %), and 630 (29 %) developed HTN, respectively. Females who never had history of GDM and HDP have 34 % (95 % CI: 21, 45) less hazard of being diabetic than their spouses if they have the same age and waist to hip ratio. In cases with histories of both GDM and HDP, the risk of females increases to 3.05 (95 % CI: 1.43, 6.52) times of their spouses. Also, females who had experienced GDM (HR: 3.51, 95 % CI: 2.23, 5.53), or HDP (HR: 2.80, 95 % CI: 1.72, 4.56) were at higher risk of developing DM compared with females who never had GDM or HDP. We found that females with neither GDM nor HDP were more likely than males to be hypertensive in the future by the hazard ratio of 1.21 (95 % CI: 1.06, 1.39).

CONCLUSIONS

Complicated pregnancies by GDM and/or HDP were associated with increased risk of development DM and HTN in later life of females and their spouses. Further studies are required to confirm these results. Preventive care programs should be considered pregnancy complications as couple-based risk factors for subsequent DM and HTN.

Pathophysiological Role of Genetic Factors Associated With Gestational Diabetes Mellitus

Gestational Diabetes Mellitus (GDM) is a highly prevalent maternal pathology characterized by maternal glucose intolerance during pregnancy that is, associated with severe complications for both mother and offspring. Several risk factors have been related to GDM; one of the most important among them is genetic predisposition. Numerous single nucleotide polymorphisms (SNPs) in genes that act at different levels on various tissues, could cause changes in the expression levels and activity of proteins, which result in glucose and insulin metabolism dysfunction. In this review, we describe various SNPs; which according to literature, increase the risk of developing GDM. These SNPs include: (1) those associated with transcription factors that regulate insulin production and excretion, such as rs7903146 (TCF7L2) and rs5015480 (HHEX); (2) others that cause a decrease in protective hormones against insulin resistance such as rs2241766 (ADIPOQ) and rs6257 (SHBG); (3) SNPs that cause modifications in membrane proteins, generating dysfunction in insulin signaling or cell transport in the case of rs5443 (GNB3) and rs2237892 (KCNQ1); (4) those associated with enzymes such as rs225014 (DIO2) and rs9939609 (FTO) which cause an impaired metabolism, resulting in an insulin resistance state; and (5) other polymorphisms, those are associated with growth factors such as rs2146323 (VEGFA) and rs755622 (MIF) which could cause changes in the expression levels of these proteins, producing endothelial dysfunction and an increase of pro-inflammatory cytokines, characteristic on GDM. While the pathophysiological mechanism is unclear, this review describes various potential effects of these polymorphisms on the predisposition to develop GDM.

Impact of Remote Monitoring Technologies for Assisting Patients With Gestational Diabetes Mellitus: A Systematic Review

Introduction: In Chile, 1 in 8 pregnant women of middle socioeconomic level has gestational diabetes mellitus (GDM), and in general, 5–10% of women with GDM develop type 2 diabetes after giving birth. Recently, various technological tools have emerged to assist patients with GDM to meet glycemic goals and facilitate constant glucose monitoring, making these tasks more straightforward and comfortable.

Objective: To evaluate the impact of remote monitoring technologies in assisting patients with GDM to achieve glycemic goals, and know the respective advantages and disadvantages when it comes to reducing risk during pregnancy, both for the mother and her child.

Methods: A total of 188 articles were obtained with the keywords “gestational diabetes mellitus,” “GDM,” “gestational diabetes,” added to the evaluation levels associated with “glucose level,” “glycemia,” “glycemic index,” “blood sugar,” and the technological proposal to evaluate with “glucometerm” “mobile application,” “mobile applications,” “technological tools,” “telemedicine,” “technovigilance,” “wearable” published during the period 2016–2021, excluding postpartum studies, from three scientific databases: PUBMED, Scopus and Web of Science. These were managed in the Mendeley platform and classified using the PRISMA method.

Results: A total of 28 articles were selected after elimination according to inclusion and exclusion criteria. The main measurement was glycemia and 4 medical devices were found (glucometer: conventional, with an infrared port, with Bluetooth, Smart type and continuous glucose monitor), which together with digital technology allow specific functions through 2 identified digital platforms (mobile applications and online systems). In four articles, the postprandial glucose was lower in the Tele-GDM groups than in the control group. Benefits such as improved glycemic control, increased satisfaction and acceptability, maternal confidence, decreased gestational weight gain, knowledge of GDM, and other relevant aspects were observed. There were also positive comments regarding the optimization of the medical team’s time.

Conclusion: The present review offers the opportunity to know about the respective advantages and disadvantages of remote monitoring technologies when it comes to reducing risk during pregnancy. GDM centered technology may help to evaluate outcomes and tailor personalized solutions to contribute to women’s health. More studies are needed to know the impact on a healthcare system.

Gestational Diabetes Mellitus and Preeclampsia: Correlation and Influencing Factors

Gestational diabetes mellitus (GDM) and preeclampsia (PE) are common pregnancy complications with similar risk factors and pathophysiological changes. Evidence from previous studies suggests that the incidence of PE is significantly increased in women with GDM, but whether GDM is independently related to the occurrence of PE has remained controversial. GDM complicated by PE further increases perinatal adverse events with greater impact on the future maternal and offspring health. Identify factors associated with PE in women with GDM women, specifically those that are controllable, is important for improving pregnancy outcomes. This paper provides the findings of a review on the correlation between GDM and PE, factors associated with PE in women with GDM, possible mechanisms, and predictive markers. Most studies concluded that GDM is independently associated with PE in singleton pregnancy, and optimizing the treatment and management of GDM can reduce the incidence of PE, which is very helpful to improve pregnancy outcomes.

Analysis of Risk Factors for the Development of Gestational Diabetes Mellitus in a Group of Romanian Patients

INTRODUCTION

Gestational diabetes mellitus (GDM) is caused by numerous risk factors, the most common being old age, obesity, family history of diabetes mellitus, GDM, history of fetal macrosomia, history of polycystic ovary syndrome or treatment with particular drugs, multiple births, and certain races. The study proposed to analyze the risk factors causing GDM.

METHOD

In the study, we included 97 pregnant women to whom there was an OGTT performed between weeks 24th and 28th of pregnancy, divided into two groups, with GDM and without GDM. The statistical analysis was performed with SPSS 26.0, the tests being statistically significant if p value < 0.05.

RESULTS

The favoring risk factors for the onset of GDM were analyzed, with statistically significant differences between the GDM group and the group without GDM related to the delivery age (32.39 ± 4.66 years old vs. 28.61 ± 4.71 years old), history of fetal macrosomia (13.7% vs. 0%), presence of GDM during previous pregnancies (7.8% vs. 0%), HBP before pregnancy (9.8% vs. 0%), gestational HBP (17.6% vs. 0%), glycemia value at first medical visit (79.37 ± 9.34 mg/dl vs. 71.39 ± 9.16 mg/dl), and weight gain during pregnancy (14.61 ± 4.47 kg vs. 12.48 ± 5.87 kg).

CONCLUSIONS

Identifying the risk factors for the GDM onset has a special importance, implying an early implementation of interventional measures in order to avoid the onset of GDM and associated maternal and fetal complications.

Increased individual glucose tolerance test values in women with gestational diabetes

BACKGROUND

Individual oral glucose tolerance test (OGTT) values may be of interest to clinicians. We evaluate factors associated with these values.

METHODS

This retrospective study included 225 pregnant women diagnosed with gestational diabetes by abnormal 100-gram oral GTT. Predictor variables were maternal age, race/ethnicity, gravida, parity, pre-pregnancy body mass index (BMI), weight gain in current pregnancy, family history of diabetes, personal history of gestational diabetes, and neonate gender. Outcome variables were continuous OGTT and categorical elevated OGTT for fasting, 1-hour postprandial, 2-hour postprandial, and 3-hour postprandial.

RESULTS

Obese BMI was associated with increased odds for higher fasting level in the continuous OGTT and elevated categorical OGTT; for 1-hour postprandial this significant obese association only occurred for the continuous OGTT. Higher weight gain in pregnancy was associated with a higher fasting level continuous OGTT and elevated categorical OGTT. Higher maternal age at time of delivery was associated with higher 2-hour continuous OGTT and an elevated 1-hour categorical OGTT. Female neonate gender was associated with decreased odds for elevated 2-hour categorical OGTT. Hispanic and Black race/ethnicities were each associated with higher 3-hour continuous OGTT.

CONCLUSIONS

These findings can help clinicians identify the women potentially at risk for having abnormal GTT values diagnostic of GDM to provide preemptive early intervention. Clinicians have the goals to identify these women early so that women can be properly educated and counseled in terms of their nutrition status and as to what negative clinical outcomes may occur should their glucose levels remain poorly controlled in the pregnancy.

What is known and what remains unresolved regarding gestational diabetes mellitus (GDM)

Gestational diabetes mellitus (GDM) has become a major public health issue and one of the most discussed topics in contemporary obstetrics. Due to rising prevalence of GDM worldwide impact and importance of this medical condition in good quality antenatal care is growing. GDM is associated with serious adverse perinatal outcomes and unfavorable long-term health consequences for both, mother and her child. Despite a great amount of knowledge accumulated regarding GDM, medical community remains indecisive and still debates the most appropriate diagnostic strategy, screening policy, and treatment options for pregnancies complicated with GDM. These unresolved issues generate controversies, motivate further research and contribute to the growing interest surrounding GDM. In this review we will discuss and try to explain some of them.

Early pregnancy levels of gingival crevicular fluid matrix metalloproteinases-8 and -9 are associated with the severity of periodontitis and the development of gestational diabetes mellitus

BACKGROUND

Gestational diabetes mellitus (GDM) is increasing worldwide and women with a history of GDM are at risk of developing type 2 diabetes which is a risk factor for periodontitis. The aim of this study was to explore the association between the concentrations of matrix metalloproteinase (MMP)-8 and -9 in gingival crevicular fluid (GCF) during early pregnancy with the periodontal diagnosis and the risk of GDM development.

METHODS

A prospective cohort study, including 314 women, enrolled at 11 to 14 weeks of pregnancy was conducted. A complete maternal/obstetric and periodontal exam was performed, and GCF samples were obtained for the MMP-8 and -9 determination by Multiplex Elisa Assays. Mann-Whitney test; Spearman's correlation and log-binomial regression model estimated the association between MMPs concentration in GCF and GDM.

RESULTS

Fourteen percent of the pregnancies were diagnosed with GDM. An increase in the concentration of MMP-8 and -9 in women with periodontitis stage III and IV compared to periodontitis stage I was observed (99.31 ng/mL [IQR: 85.32] versus 71.95 ng/mL [IQR: 54.04], and 262.4 ng/mL [IQR: 312.55] versus 114.1 ng/mL [IQR: 184.94], respectively). Women who developed GDM showed increased concentrations of MMP-8 and -9 in GCF since the beginning of pregnancy (P = 0.0381; P = 0.0302, respectively). MMP-8 concentration in GCF was associated with GDM (RR: 1.19; P = 0.045; CI 95% 1.00 to 1.40; and RR: 1.20; P = 0.063; CI 95% 0.99 to 1.45 in the adjusted model).

CONCLUSION(S)

GCF concentrations of MMP-8 and -9 at early of pregnancy are increased in women with severe periodontitis and associated with the GDM development.