Prediction of gestational diabetes mellitus at first trimester in low-risk pregnancies

Kumru, Pınar; Arısoy, Resul; Erdoğdu, Emre; Demirci, Oya; Kavrut, Mustecep; Ardıç, Cem; Aslaner, Nihan; Ozkoral, Aysen; Ertekin, A. Aktuğ

doi:10.1016/j.tjog.2016.04.032

Cited by 37 publications

(51 citation statements)

References 17 publications

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“…Previous studies by our team in the same population have demonstrated that: a) WC ≥ 88 cm and pre BMI ≥25 Kg/m 2 have optimal Sens/Sp for predicting GDM at GA <24 weeks 25 ; b) overweight (pre BMI ≥ 25 Kg/m 2 ) and obesity (pre BMI ≥ 30 Kg/m 2 ) are risk factors for hyperglycemia in pregnancy (GDM-MGH) 22 ; and c) the proportion of metabolic syndrome markers is associated with hyperglycemia level in women with GDM-MGH 26 . The results of other studies in diverse populations do not differ from ours 11,13,14,16,42,43 . Also in agreement with other reports, we observed that the higher Sp shown by FG, HbA1c and HOMA-IR indicate them as the best predictors for ruling out GDM risk and the need for a diagnostic test 10,13,42,44,45 .…”

Section: Resultscontrasting

confidence: 63%

“…The results of other studies in diverse populations do not differ from ours 11,13,14,16,42,43 . Also in agreement with other reports, we observed that the higher Sp shown by FG, HbA1c and HOMA-IR indicate them as the best predictors for ruling out GDM risk and the need for a diagnostic test 10,13,42,44,45 . universal screening are not available 16,17,46 .…”

Section: Resultscontrasting

confidence: 63%

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Risk Factors for the Prediction of Hyperglycemia during Pregnancy – A Cohort Study from a Brazilian Public Primary Care Center

Vernini¹,

Cassetari²,

Arantes³

et al. 2020

Preprint

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BACKGROUND – In Brazil, the prevalence of maternal hyperglycemia is among the highest, costs are elevated and there is no evidence to recommend universal screening. OBJECTIVE – To evaluate the performance of risk factors (RF) for predicting hyperglycemia in pregnancy – Mild Gestational Hyperglycemia (MGH) or gestational Diabetes Mellitus (GDM) in public primary-care centers in Brazil. METHODS – A cohort study, including 514 women with a single pregnancy and no hyperglycemia. Study participants were evaluated at GA (gestational age) < or ≥ 20 weeks, and underwent a 75g-OGTT along with glycemic profile (GP) testing between 24 and 28 weeks. Clinical, anthropometric and laboratory data – fasting glucose (FG), glycated hemoglobin (HbA1c), basal insulin and lipid profile were obtained. The most common RF associations (OR and 95% CI and p <0.05) and different cut-off points were tested for the prediction of MGH-GDM. Predictive performance was assessed by Sensitivity/Specificity, negative predictive value NPV (negative predictive value) and false positive rates (FP; 1-Esp). RESULTS – At GA <20 weeks, age ≥25 years, WC (Waist circumference) ≥ 88 cm, BMI pre ≥25 kg/m 2 (pre gestational body mass index) and BMI gest ≥25 kg/m 2 (gestational body mass index ); at GA (gestational age) ≥20 weeks, age ≥25 years, BMI pre ≥25 kg/m 2 and TG (triglicerides) ≥150 mg/dL showed better performace for predicting MGH-GDM. Irrespective of gestational age, FG (Fasting glucose) ≥ 85 mg/dL, HbA1c ≥5.7% and HOMA-IR ≥2.71 were good predictors to rule out the risk of these complications. CONCLUSION – The results of this study should contribute to define the best diagnostic approach to MGH-GDM in our center and in others with similar characteristics.

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Section: Resultscontrasting

confidence: 63%

Section: Resultscontrasting

confidence: 63%

Risk Factors for the Prediction of Hyperglycemia during Pregnancy – A Cohort Study from a Brazilian Public Primary Care Center

Vernini¹,

Cassetari²,

Arantes³

et al. 2020

Preprint

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“…To date, although many risk factors for GDM have been identified (e.g., maternal age, obesity, and lipid Clinicians usually use BMI, VAT, and subcutaneous adipose tissue (SAT), to assess obesity when trying to predict GDM. However, SAT is not a good predictor for GDM during the first trimester [17,18]; neither is BMI [4,5,19]. Over recent years, several studies have revealed that VAT could be a good predictor for GDM in the first and second trimesters [18,19].…”

Section: Discussionmentioning

confidence: 99%

“…Clinicians usually use body mass index (BMI) to assess maternal obesity during pregnancy. However, previous studies found that BMI may not be a good predictor for GDM around the first trimester [4,5], due to its inability to reflect the accumulation and mass of the visceral adipose tissue (VAT) [6]. Recently, a promising echocardiographic parameter, epicardial adipose tissue (EAT), has emerged that could complement the use of BMI to assess risk for GDM.…”

Section: Introductionmentioning

confidence: 99%

Epicardial adipose tissue thickness as a potential predictor of gestational diabetes mellitus: a prospective cohort study

Liu

Song

Meng

et al. 2020

BMC Cardiovasc Disord

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Background: Gestational diabetes mellitus (GDM) is the most common metabolic disorder that can occur during pregnancy and is associated with a long-term risk of both maternal and neonatal comorbidities. This study aimed to investigate the association between echocardiographic epicardial adipose tissue (EAT) and the risk for GDM during the early second trimester of pregnancy. Method: We recruited all singleton pregnancies between January 2014 and December 2018 at 16 weeks + 0 days to 19 weeks + 6 days. We then used generalized linear models to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for EAT as a potential predictor for GDM. Receiver-operating-characteristic (ROC) analysis was then conducted to investigate the discriminative capacity of any individual maternal factor for the prediction of GDM. Results: In total, our study involved 314 pregnant women with GDM and 1832 pregnant women without GDM. Multivariate regression analysis revealed that EAT thickness (OR = 2.87; 95% CI: 2.49-3.31) was significantly associated with the presence of GDM (P < 0.001). Furthermore, EAT thickness was also significantly associated with a range of adverse outcomes in the GDM group, including large size for gestational age, neonatal hypoglycemia, admission to the neonatal intensive care unit, preterm delivery, and hyperbilirubinemia (P < 0.001). ROC analysis revealed that the area under the curve was 0.790 (95% CI: 0.768-0.812). When the cutoff value for EAT thickness was set to 5.49 mm, the sensitivity was 95.2% and the specificity was 50.5%. Conclusions: Echocardiographic EAT thickness is positively and significantly associated with both the risk of GDM and adverse outcomes related to GDM. Echocardiographic EAT has the potential to predict GDM prior to actual clinical diagnosis.

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“…However, BMI can't reflect the accumulation and mass of fat very sensitively, especially visceral adipose tissue (VAT) [5]. The previous study found BMI may not be a good predictor for GDM, particularly around the first trimester [6,7]. Recently, a promising ultrasound parameter, epicardial adipose tissue (EAT), has emerged interest to clinical doctors.…”

Section: Introductionmentioning

confidence: 99%

Epicardial adipose tissue thickness as a predictor of gestational diabetes mellitus: a prospective cohort study

Liu

Song

Meng

et al. 2019

Preprint

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BackgroundGestational diabetes mellitus (GDM), the most common metabolic disorder of pregnancy, is a long term risk of comorbidities for maternal and neonatal. The study aimed to assess the association between the echocardiographic epicardial adipose tissue (EAT) and the risk for gestational diabetes mellitus (GDM) in the early second trimester.MethodsSingleton pregnancies were enrolled in this study between September 2017 and January 2019 during their 16–20 gestational week. Odds ratio (OR) and 95% confidence intervals (CIs) of individual maternal factors as potential predictors for GDM were calculated using generalized linear models. The receiver-operating-characteristic (ROC) analysis was conducted to assess the discriminative capacity of any individual maternal factor in predicting GDM.Results69 GDM and 420 normal women were included in the main analysis. Multivariate regression analysis revealed that EAT thickness (OR = 1.96, 95%CI: 1.50–2.55) and high-density lipoprotein cholesterol (OR = 0.21, 95%CI: 0.05–0.84) were associated with the presence of GDM (P < 0.05). Meanwhile, EAT thickness was associated with adverse outcomes (including large for gestational age, neonatal hypoglycemia, admission to neonatal intensive care unit, preterm delivery, and hyperbilirubinemia) in the GDM group (P < 0.05). ROC analysis revealed that the area under curve was 0.698 and the cutoff value is 6.77mm only using EAT thickness. After added high-density lipoprotein cholesterol into the analysis, the area under curve was increase into 0.713.ConclusionsEchocardiographic EAT thickness is positively and significantly associated with GDM risk and adverse outcomes related to GDM. Echocardiographic EAT is a simple method to predict the development of GDM prior to actual clinical diagnosis. This method provides a new early window of opportunity to implement primary prevention strategies to prevent GDM and reduce the related adverse maternal and perinatal outcomes.

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Prediction of gestational diabetes mellitus at first trimester in low-risk pregnancies

Abstract: The HOMA, SHBG, TG, and LDL-C levels are independent predictors for subsequent development of GDM in low-risk pregnancies, but they exhibit low sensitivity.

Cited by 37 publications

References 17 publications

Risk Factors for the Prediction of Hyperglycemia during Pregnancy – A Cohort Study from a Brazilian Public Primary Care Center

Risk Factors for the Prediction of Hyperglycemia during Pregnancy – A Cohort Study from a Brazilian Public Primary Care Center

Epicardial adipose tissue thickness as a potential predictor of gestational diabetes mellitus: a prospective cohort study

Epicardial adipose tissue thickness as a predictor of gestational diabetes mellitus: a prospective cohort study

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