Gestational diabetes mellitus (GDM) is the most common pregnancy-associated metabolic disorder that is steadily increasing worldwide. Early diagnosis of pregnant women susceptible to GDM is the first step for deploying effective preventive treatment to reduce maternal, fetal, and neonatal complications. The diagnostic process of GDM is still controversial and interleukin-6 (IL-6) is one of the most recent markers used for the diagnosis of GDM. In this study, we aimed to systematically review the role of IL-6 in the diagnosis of GDM. In this systematic review, Google Scholar, Scopus, PubMed, ISI Web of Science, ProQuest, and MEDLINE databases were searched using the following keywords: GDM, screening, and IL-6, with the time interval 2009–2020. The quality of articles was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology checklist. Twenty-four articles with desired quality that met the inclusion criteria were selected and reviewed further. Sixteen studies showed a statistically significant association, while 8 studies did not report any relationship between IL-6 levels and GDM. Based on the results of these studies, assessing the serum IL-6 levels can be investigated a newly established diagnostic biomarker for GDM. Therefore, through early diagnosis of susceptible women, effective measures can be implemented to reduce its complications.

Gestational diabetes mellitus (GDM) can have adverse effects on pregnancy. GDM is associated with changes in the lipid profile of pregnant women. Finding out the early ways to diagnose GDM can prevent the adverse outcomes. This meta-analysis study aimed to determine the effect of GDM on lipid profile. PubMed, ProQuest, Web of Science, Scopus, Science Direct, Google Scholar, and ClinicalTrial were systematically searched for published articles relating to GDM until 2021 according to PRISMA guidelines. Newcastle Ottawa scale was used to assess the quality of the studies. Thirty-three studies with a sample size of 23,792 met the criteria for entering the meta-analysis. Pooled standardized mean difference (SMD) for total cholesterol (TC) and triglyceride (TG) was 0.23 mg/dL (95% CI: 0.11–0.34) and 1.14 mg/dL (95% CI: 0.91–1.38), respectively. The mean of TC and TG in people with GDM was higher than that in normal pregnant women. A similar pattern was observed for the very low-density lipoprotein (VLDL) and TG/high-density lipoprotein (HDL) ratio, with pooled SMD of 0.99 mg (95% CI: 0.71–1.27) and 0.65 mg (95% CI: 0.36–0.94), respectively. Pooled SMD for HDL was −0.35 mg/dL (95% CI: −0.54 to −0.16), women with GDM had a mean HDL lower than normal pregnant women. Although pooled SMD was higher for low-density lipoprotein (LDL) in the GDM group, this difference was not significant (0.14 [95% CI: −0.04 to 0.32]). Of all the lipid profiles, the largest difference between the GDM and control groups was observed in TG (SMD: 1.14). Elevated serum TG had the strongest effect on GDM. Higher levels of TC, LDL, VLDL, and TG/HDL ratio, and lower level of HDL were exhibited in GDM group. So, these markers can be considered as a reliable marker in the diagnosis of GDM.

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Background: Gestational diabetes mellitus (GDM) is associated with adverse diabetic complications for both mother and child during pregnancy. The common Gold Standard (GS) for diagnosis of GDM is 75 g oral glucose tolerance test (OGTT) during 24-28 gestational weeks which seems a little late for any proper intervention. This study aimed to employ the Bayesian latent class models (LCMs) for estimating the early diagnostic power of combination of serum multiple marker in detecting GDM during 14-17 weeks of gestation. Methods: Data from a sample of 523 pregnant women who participated in gestational diabetes screening tests at health centers affiliated to Shahid Beheshti University of Medical Sciences in Tehran, Iran from 2017 to 2018 were used. The beta-human chorionic gonadotropin (β-hCG), unconjugated estriol (uE3), and alfa-fetoprotein (AFP) values were extracted from case records for all participants. The Bayesian LCMs were applied for estimating sensitivity, specificity, and area under receiver operating characteristic curve (AUC) of combining the three biomarkers' results in the absence of GS, adjusting for maternal age and body mass index. Results: The mean (standard deviation) maternal age of the participants was 28.76 (±5.33) years. Additionally, the mean (standard deviation) BMI was 24.57 (±3.22) kg/m 2. According to the Bayesian model, the cSensitivity, cSpecificity, and cAUC for the optimal composite diagnostic test were estimated as 94% (95% credible interval (CrI) [0.91-0.99]), 86% (95% CrI [0.80-0.92]), and 0.92 (95% CrI [0.87-0.98]), respectively. Conclusions: Overall, the findings revealed that the combination of uE3, AFP, and β-hCG results might be considered as an acceptable predictor for detecting GDM with a rather high level of accuracy in the early second trimester of pregnancy without a GS.