Recent advances in gestational diabetes mellitus

BackgroundIn pregnancy, women experience physiological changes which could increase the risk of insulin resistance, and metabolic syndrome later in life. This study assessed the risk of future metabolic syndrome among pregnant women with either glycosuria or proteinuria at different gestational ages. MethodsEight-Six participants were recruited from health facilities in South-west, Nigeria and they were in three categories: those with glycosuria (n = 32), proteinuria (n = 27), and control (n = 27), based on urinalysis result. Data were analyzed using IBM SPSS Statistics for Windows version 25.0 (IBM Corp, Armonk, NY, USA). Groups were compared using one way ANOVA. Association between the variables was determined using Pearson correlation. Linear regression analysis was performed to predict the risk of future metabolic syndrome.ResultsParticipants with glycosuria, proteinuria and control were 29.19 (SD 6.04), 27.15 (SD 4.37) and 25.74 (SD 4.67) years respectively. Glycosuria group had higher (P = 0.01) triglycerides, HOMA-IR, and a-positive association (P = 0.001) between, FBG and HBA1C. Linear regression analysis predicted future risk of metabolic syndrome (P< 0.05) for those with glycosuria and proteinuria respectively with their plasma insulin values. ConclusionHealthy volunteers with glycosuria and proteinuria are at greater risk of developing metabolic syndrome.Rwanda J Med Health Sci. 2023;6(3): 315-325

Assessment of the Risk of Future Metabolic Syndrome among Non-Hypertensive and Non-Diabetic Nigerian Pregnant Women Presenting with either Glycosuria or Proteinuria at Different Trimesters

To elucidate the clinical and pathological characteristics of gestational diabetes mellitus (GDM) with high and low insulin resistance. In total, 1393 GDM and 1001 non-GDM singleton deliveries were included in this study. Insulin resistance subtypes were classified according to the HOMA2-IR value. Clinical data were analyzed using SPSS 26.0. Placenta samples were collected for pathological analysis. Maternal age and fasting glucose were identified as independent risk factors for GDM with high insulin resistance (p < 0.01), while fasting glucose was the sole risk factor for GDM with low insulin resistance (p < 0.001). Fetal distress was associated with both of GDM subtypes (both p < 0.01), while anemia, fetal growth restriction, large for gestational age and intrahepatic cholestasis in pregnancy were related to specific GDM insulin resistance subtype. In addition, GDM with high insulin resistance showed an increase of syncytial knots with down-regulation of PI3K/AKT signaling, while GDM with low insulin resistance showed normal syncytial knot counts and up-regulation of PI3K/AKT signaling. Our findings provide novel perspectives to the clinical and pathological comprehensions of GDM with high and low insulin resistance, which might facilitate the mechanism study of GDM and its precision pregnancy management. 

Clinical and pathological characteristics of gestational diabetes mellitus with different insulin resistance

The incidence of gestational diabetes mellitus (GDM) and overt diabetes in pregnancy is rising globally [...].

Recent Advances in Gestational Diabetes Mellitus

The worldwide prevalence of overweight and obesity in women of reproductive age is rapidly increasing and a risk factor for the development of gestational diabetes (GDM). Excess adipose tissue reduces insulin sensitivity and may underlie adverse outcomes in both mother and child. The present paper describes the rationale and design of the PRegnancy Outcomes and Maternal Insulin Sensitivity (PROMIS) study, an exploratory cohort study to obtain detailed insights in insulin sensitivity and glucose metabolism during pregnancy and its relation to pregnancy outcomes including early infancy growth. We aim to recruit healthy pregnant women with a body mass index (BMI) ≥ 25 kg/m2 before 12 weeks of gestation in Northern Netherlands. A total of 130 woman will be checked on fasted (≤7.0 mmol/L) or random (≤11.0 mmol/L) blood glucose to exclude pregestational diabetes at inclusion. Subjects will be followed up to six months after giving birth, with a total of nine contact moments for data collection. Maternal data include postprandial measures following an oral meal tolerance test (MTT), conducted before 16 weeks and repeated around 24 weeks of gestation, followed by a standard oral glucose tolerance test before 28 weeks of gestation. The MTT is again performed around three months postpartum. Blood analysis is done for baseline and postprandial glucose and insulin, baseline lipid profile and several biomarkers of placental function. In addition, specific body circumferences, skinfold measures, and questionnaires about food intake, eating behavior, physical activity, meal test preference, mental health, and pregnancy complications will be obtained. Fetal data include assessment of growth, examined by sonography at week 28 and 32 of gestation. Neonatal and infant data consist of specific body circumferences, skinfolds, and body composition measurements, as well as questionnaires about eating behavior and complications up to 6 months after birth. The design of the PROMIS study will allow for detailed insights in the metabolic changes in the mother and their possible association with fetal and postnatal infant growth and body composition. We anticipate that the data from this cohort women with an elevated risk for the development of GDM may provide new insights to detect metabolic deviations already in early pregnancy. These data could inspire the development of new interventions that may improve the management of maternal, as well as offsrping complications from already early on in pregnancy with the aim to prevent adverse outcomes for mother and child.

https://www.mdpi.com/2077-0383/10/5/976/pdf

Pregnancy Outcomes and Maternal Insulin Sensitivity: Design and Rationale of a Multi-Center Longitudinal Study in Mother and Offspring (PROMIS).

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Sicco A Scherjon

Author Tools

Chat about Author

Papers

Pregnancy Outcomes and Maternal Insulin Sensitivity: Design and Rationale of a Multi-Center Longitudinal Study in Mother and Offspring (PROMIS).