Gestationsdiabetes mellitus (GDM)

Kleinwechter, Helmut; Schäfer‐Graf, Ute; Bührer, C; Hoesli, Irène; Kainer, Franz; Kautzky‐Willer, Alexandra; Pawlowski, B.; Schunck, Karl‐Ulrich; Somville, T.; Sorger, M.

doi:10.1055/s-0031-1283757

Cited by 25 publications

(7 citation statements)

References 68 publications

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“…A second cause for the hitherto difficult determination of prevalence was the lack of a standardised and binding definition of gestational diabetes, complete with its determination and cutt-off values. The current guidelines, "GDM -Evidence-based guidelines on diagnosis, treatment and aftercare by the German Diabetes Association (DDG) and the German Society for Gynaecology and Obstetrics (DGGG)" were published recently [10]. These guidelines recommend a standardised definition of gestational diabetes and standardised cut-off values in venous plasma in accordance with the new consensus recommendations of the International Association of Diabetes and Pregnancy Study Groups (IADPSG).…”

mentioning

confidence: 99%

“…These guidelines recommend a standardised definition of gestational diabetes and standardised cut-off values in venous plasma in accordance with the new consensus recommendations of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). From an epidemiological and methodical perspective, the fact that a pre-existing and undetected diabetes mellitus which is only diagnosed during pregnancy will no longer be categorised under the diagnostic class of gestational diabetes should be welcomed [10]. As a result, diabetes mellitus of another kind diagnosed for the first time during pregnancy will in future be clearly and reliably distinguished from cases of gestational diabetes.…”

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confidence: 99%

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Prevalence, Trend and Determining Factors of Gestational Diabetes in Germany

Huy

Loerbroks

Hornemann

et al. 2012

Geburtsh Frauenheilk

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The true prevalence of gestational diabetes in Germany is unknown. Thus, the studyʼs purposes were to estimate the prevalence of gestational diabetes as well as to describe the temporal prevalence trend and to identify determinants. Material and Methods: We calculated prevalence estimates based on two datasets: the registerbased German perinatal statistic (n = 650 232) and the maternal self-reports from the German children and youth health survey (KiGGS; n = 15 429). Differences between prevalence estimates were analysed using χ 2 and trend tests, and determinants were identified using logistic regression. Results: According to the perinatal statistic, gestational diabetes was present in 3.7 % of pregnant women in Germany in 2010. The prevalence across the years 2001 to 2006 was estimated at 1.9 % which differed significantly from the prevalence estimate derived from the KiGGS dataset for the same period of time (5.3 %; 95 % confidence interval: 4.6-6.1 %). Both datasets show an increasing trend of gestational diabetes (p < 0.001). The risk for gestational diabetes was mainly associated with age, BMI and social class of pregnant women as well as with multiple pregnancies. Conclusion: The lack of significant screening studies among representative samples hampers a sound estimation of the true prevalence of gestational diabetes in Germany. The increasing trend in gestational diabetes might continue due to the projected increase of important risk factors (e.g., maternal age, obesity). Our analyses support the current consensus recommendations regarding standardised gestational diabetes screening. Zusammenfassung

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confidence: 99%

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confidence: 99%

Prevalence, Trend and Determining Factors of Gestational Diabetes in Germany

Huy

Loerbroks

Hornemann

et al. 2012

Geburtsh Frauenheilk

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“…In cases of pathological results, a 75 g oGTT is mandatory. Diabetes care was provided according to the German S3 guidelines published in 2011 [ 15 ]. The local Ethical Committee of the Friedrich-Schiller-University, Jena, Germany approved this study (5280-09/17).…”

Section: Methodsmentioning

confidence: 99%

The Relevance of Fetal Abdominal Subcutaneous Tissue Recording in Predicting Perinatal Outcome of GDM Pregnancies: A Retrospective Study

Weschenfelder

Baum

Schleußner

et al. 2020

JCM

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Guidelines on the management of gestational diabetes (GDM) instruct physicians to involve ultrasound-based monitoring of fetal growth in addition to blood glucose. So far, glucose control besides clinical parameters like maternal body mass index (BMI) and gestational weight gain have been shown to predict neonatal outcome. We aimed to evaluate the discriminative ability of fetal abdominal subcutaneous tissue (FAST) in addition to standard ultrasound parameters like abdominal circumference (AC) and estimated fetal weight (EFW) for perinatal complications like large for gestational age (LGA), hypoglycemia, hyperbilirubinemia, mode of delivery and admission to neonatal intensive care unit (NICU). Ultrasound data and neonatal outcome was collected of 805 GDM cases from 2012 to 2016: 3205 FAST, 3195 AC-measurements and 3190 EFW calculations were included. AC, EFW and FAST increased linear with gestational age. Combining ultrasound and clinical parameters improved predictive power for LGA. In the subgroup where fetuses grow with an AC > 75th additional adding of FAST to standard ultrasound parameters increased predictive power for hypoglycemia. Our results confirm inclusion of ultrasound parameters to be beneficial in monitoring GDM pregnancies. Additional FAST determination revealed to be of potential clinical relevance in the subgroup AC > 75th percentile.

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“…BMIs were categorized according to the WHO criteria (normal weight: 18.5-24.9 kg/m 2 , overweight: 25.0-29.9 kg/m 2 , obese: ≥30.0 kg/m 2 ). GDM screening was performed between gestational weeks 24 to 28 according to the national guidelines at the time of recruitment [45,46]. No oral antidiabetic drugs were administered in the GDM group, eight were treated by diet and eleven were treated with diet and additional insulin therapy to achieve glycemic control.…”

Section: Subject Datamentioning

confidence: 99%

Visceral Adipose Tissue Inflammatory Factors (TNF-Alpha, SOCS3) in Gestational Diabetes (GDM): Epigenetics as a Clue in GDM Pathophysiology

Rancourt

Ott

Ziska

et al. 2020

IJMS

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Gestational diabetes (GDM) is among the most challenging diseases in westernized countries, affecting mother and child, immediately and in later life. Obesity is a major risk factor for GDM. However, the impact visceral obesity and related epigenetics play for GDM etiopathogenesis have hardly been considered so far. Our recent findings within the prospective ‘EaCH’ cohort study of women with GDM or normal glucose tolerance (NGT), showed the role, critical factors of insulin resistance (i.e., adiponectin, insulin receptor) may have for GDM pathophysiology with epigenetically modified expression in subcutaneous (SAT) and visceral (VAT) adipose tissues. Here we investigated the expression and promoter methylation of key inflammatory candidates, tumor necrosis factor-alpha (TNF-α) and suppressor of cytokine signaling 3 (SOCS3) in maternal adipose tissues collected during caesarian section (GDM, n = 19; NGT, n = 22). The mRNA expression of TNF-α and SOCS3 was significantly increased in VAT, but not in SAT, of GDM patients vs. NGT, accompanied by specific alterations of respective promoter methylation patterns. In conclusion, we propose a critical role of VAT and visceral obesity for the pathogenesis of GDM, with epigenetic alterations of the expression of inflammatory factors as a potential factor.

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Gestationsdiabetes mellitus (GDM)

Cited by 25 publications

References 68 publications

Prevalence, Trend and Determining Factors of Gestational Diabetes in Germany

Prevalence, Trend and Determining Factors of Gestational Diabetes in Germany

The Relevance of Fetal Abdominal Subcutaneous Tissue Recording in Predicting Perinatal Outcome of GDM Pregnancies: A Retrospective Study

Visceral Adipose Tissue Inflammatory Factors (TNF-Alpha, SOCS3) in Gestational Diabetes (GDM): Epigenetics as a Clue in GDM Pathophysiology

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