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Metabolic Risk/Epidemiology
Gestational Diabetes Mellitus and Its Implications across the Life Span
Brandy Wicklow, Ravi Retnakaran
Diabetes Metab J. 2023;47(3):333-344.   Published online February 8, 2023
DOI: https://doi.org/10.4093/dmj.2022.0348
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  • 439 Download
  • 7 Web of Science
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AbstractAbstract PDFPubReader   ePub   
Gestational diabetes mellitus (GDM) has historically been perceived as a medical complication of pregnancy that also serves as a harbinger of maternal risk of developing type 2 diabetes mellitus (T2DM) in the future. In recent decades, a growing body of evidence has detailed additional lifelong implications that extend beyond T2DM, including an elevated risk of ultimately developing cardiovascular disease. Furthermore, the risk factors that mediate this lifetime cardiovascular risk are evident not only after delivery but are present even before the pregnancy in which GDM is first diagnosed. The concept thus emerging from these data is that the diagnosis of GDM enables the identification of women who are already on an enhanced track of cardiometabolic risk that starts early in life. Studies of the offspring of pregnancies complicated by diabetes now suggest that the earliest underpinnings of this cardiometabolic risk profile may be determined in utero and may first manifest clinically in childhood. Accordingly, from this perspective, GDM is now seen as a chronic metabolic disorder that holds implications across the life span of both mother and child.

Citations

Citations to this article as recorded by  
  • ATP5me alleviates high glucose-induced myocardial cell injury
    Qingsha Hou, Fang Yan, Xiuling Li, Huanling Liu, Xiang Yang, Xudong Dong
    International Immunopharmacology.2024; 129: 111626.     CrossRef
  • Prevalence and Predictors of Gestational Diabetes Mellitus and Overt Diabetes in Pregnancy: A Secondary Analysis of Nationwide Data from India
    Saurav Basu, Vansh Maheshwari, Rutul Gokalani, Chandrakant Lahariya
    Preventive Medicine: Research & Reviews.2024; 1(1): 52.     CrossRef
  • Serum betaine and dimethylglycine in mid-pregnancy and the risk of gestational diabetes mellitus: a case-control study
    Ziqing Zhou, Yao Yao, Yanan Sun, Xin Wang, Shang Huang, Jianli Hou, Lijun Wang, Fengxiang Wei
    Endocrine.2024;[Epub]     CrossRef
  • Quality assessment of videos on social media platforms related to gestational diabetes mellitus in China: A cross-section study
    Qin-Yu Cai, Jing Tang, Si-Zhe Meng, Yi Sun, Xia Lan, Tai-Hang Liu
    Heliyon.2024; 10(7): e29020.     CrossRef
  • Inflammation and decreased cardiovagal modulation are linked to stress and depression at 36th week of pregnancy in gestational diabetes mellitus
    Manoharan Renugasundari, Gopal Krushna Pal, Latha Chaturvedula, Nivedita Nanda, K. T. Harichandrakumar, Thiyagarajan Durgadevi
    Scientific Reports.2023;[Epub]     CrossRef
  • Women with gestational diabetes mellitus, controlled for plasma glucose level, exhibit maternal and fetal dyslipidaemia that may warrant treatment
    Barbara J. Meyer, Colin Cortie, Marloes Dekker-Nitert, Helen L. Barrett, Dilys J. Freeman
    Diabetes Research and Clinical Practice.2023; 204: 110929.     CrossRef
  • Pregnancy diet to prevent gestational diabetes: study design and dietary assessments
    Sylvia H. Ley
    The American Journal of Clinical Nutrition.2023; 118(5): 847.     CrossRef
Original Articles
Basic Research
Long Non-Coding RNA TUG1 Attenuates Insulin Resistance in Mice with Gestational Diabetes Mellitus via Regulation of the MicroRNA-328-3p/SREBP-2/ERK Axis
Xuwen Tang, Qingxin Qin, Wenjing Xu, Xuezhen Zhang
Diabetes Metab J. 2023;47(2):267-286.   Published online January 19, 2023
DOI: https://doi.org/10.4093/dmj.2021.0216
  • 3,072 View
  • 190 Download
  • 6 Web of Science
  • 5 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Long non-coding RNAs (lncRNAs) have been illustrated to contribute to the development of gestational diabetes mellitus (GDM). In the present study, we aimed to elucidate how lncRNA taurine upregulated gene 1 (TUG1) influences insulin resistance (IR) in a high-fat diet (HFD)-induced mouse model of GDM.
Methods
We initially developed a mouse model of HFD-induced GDM, from which islet tissues were collected for RNA and protein extraction. Interactions among lncRNA TUG1/microRNA (miR)-328-3p/sterol regulatory element binding protein 2 (SREBP-2) were assessed by dual-luciferase reporter assay. Fasting blood glucose (FBG), fasting insulin (FINS), homeostasis model assessment of insulin resistance (HOMA-IR), HOMA pancreatic β-cell function (HOMA-β), insulin sensitivity index for oral glucose tolerance tests (ISOGTT) and insulinogenic index (IGI) levels in mouse serum were measured through conducting gain- and loss-of-function experiments.
Results
Abundant expression of miR-328 and deficient expression of lncRNA TUG1 and SREBP-2 were characterized in the islet tissues of mice with HFD-induced GDM. LncRNA TUG1 competitively bound to miR-328-3p, which specifically targeted SREBP-2. Either depletion of miR-328-3p or restoration of lncRNA TUG1 and SREBP-2 reduced the FBG, FINS, HOMA-β, and HOMA-IR levels while increasing ISOGTT and IGI levels, promoting the expression of the extracellular signal-regulated kinase (ERK) signaling pathway-related genes, and inhibiting apoptosis of islet cells in GDM mice. Upregulation miR-328-3p reversed the alleviative effects of SREBP-2 and lncRNA TUG1 on IR.
Conclusion
Our study provides evidence that the lncRNA TUG1 may prevent IR following GDM through competitively binding to miR-328-3p and promoting the SREBP-2-mediated ERK signaling pathway inactivation.

Citations

Citations to this article as recorded by  
  • Diabetes and diabetic associative diseases: An overview of epigenetic regulations of TUG1
    Mohammed Ageeli Hakami
    Saudi Journal of Biological Sciences.2024; 31(5): 103976.     CrossRef
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    Ritu Rani, Havagiray Chitme, Avinash Kumar Sharma
    Women & Health.2023; 63(5): 359.     CrossRef
  • Therapeutic Effect of Tinospora cordifolia (Willd) Extracts on Letrozole-Induced Polycystic Ovarian Syndrome and its Complications in Murine Model
    Ritu Rani, Avinash Kumar Sharma, Havagiray R Chitme
    Clinical Medicine Insights: Endocrinology and Diabetes.2023;[Epub]     CrossRef
  • The role of ncRNA regulatory mechanisms in diseases—case on gestational diabetes
    Dong Gao, Liping Ren, Yu-Duo Hao, Nalini Schaduangrat, Xiao-Wei Liu, Shi-Shi Yuan, Yu-He Yang, Yan Wang, Watshara Shoombuatong, Hui Ding
    Briefings in Bioinformatics.2023;[Epub]     CrossRef
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    Habib Haybar, Narjes Sadat Sadati, Daryush Purrahman, Mohammad Reza Mahmoudian-Sani, Najmaldin Saki
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Others
Influence of Maternal Diabetes on the Risk of Neurodevelopmental Disorders in Offspring in the Prenatal and Postnatal Periods
Verónica Perea, Xavier Urquizu, Maite Valverde, Marina Macias, Anna Carmona, Esther Esteve, Gemma Escribano, Nuria Pons, Oriol Giménez, Teresa Gironés, Andreu Simó-Servat, Andrea Domenech, Núria Alonso-Carril, Carme Quirós, Antonio J. Amor, Eva López, Maria José Barahona
Diabetes Metab J. 2022;46(6):912-922.   Published online April 29, 2022
DOI: https://doi.org/10.4093/dmj.2021.0340
  • 5,020 View
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  • 5 Web of Science
  • 6 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
This study aimed to evaluate the influence of maternal diabetes in the risk of neurodevelopmental disorders in offspring in the prenatal and postnatal periods.
Methods
This cohort study included singleton gestational diabetes mellitus (GDM) pregnancies >22 weeks’ gestation with live newborns between 1991 and 2008. The control group was randomly selected and matched (1:2) for maternal age, weeks of gestation and birth year. Cox regression models estimated the effect of GDM on the risk of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and maternal type 2 diabetes mellitus (T2DM). Moreover, interaction between maternal T2DM and GDM-ADHD relationship was evaluated.
Results
Children (n=3,123) were included (1,073 GDM; 2,050 control group). The median follow-up was 18.2 years (interquartile range, 14.2 to 22.3) (n=323 with ADHD, n=36 with ASD, and n=275 from women who developed T2DM). GDM exposure was associated with ADHD (hazard ratio [HR]crude, 1.67; 95% confidence interval [CI], 1.33 to 2.07) (HRadjusted, 1.64; 95% CI, 1.31 to 2.05). This association remained significant regardless of the treatment (diet or insulin) and diagnosis after 26 weeks of gestation. Children of mothers who developed T2DM presented higher rates of ADHD (14.2 vs. 10%, P=0.029). However, no interaction was found when T2DM was included in the GDM and ADHD models (P>0.05). GDM was not associated with an increased risk of ASD (HRadjusted, 1.46; 95% CI, 0.74 to 2.84).
Conclusion
Prenatal exposure to GDM increases the risk of ADHD in offspring, regardless of GDM treatment complexity. However, postnatal exposure to maternal T2DM was not related to the development of ADHD.

Citations

Citations to this article as recorded by  
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    Vishal Chavda, Dhananjay Yadav, Snehal Patel, Minseok Song
    Brain Sciences.2024; 14(3): 284.     CrossRef
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    Sukanya Shyamasundar, Seshadri Ramya, Deepika Kandilya, Dinesh Kumar Srinivasan, Boon Huat Bay, Suraiya Anjum Ansari, S Thameem Dheen
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    Verónica Perea, Andreu Simó-Servat, Carmen Quirós, Nuria Alonso-Carril, Maite Valverde, Xavier Urquizu, Antonio J Amor, Eva López, Maria-José Barahona
    The Journal of Clinical Endocrinology & Metabolism.2022; 107(10): e4203.     CrossRef
Metabolic Risk/Epidemiology
Higher Muscle Mass Protects Women with Gestational Diabetes Mellitus from Progression to Type 2 Diabetes Mellitus
Yujin Shin, Joon Ho Moon, Tae Jung Oh, Chang Ho Ahn, Jae Hoon Moon, Sung Hee Choi, Hak Chul Jang
Diabetes Metab J. 2022;46(6):890-900.   Published online April 28, 2022
DOI: https://doi.org/10.4093/dmj.2021.0334
  • 4,945 View
  • 228 Download
  • 2 Web of Science
  • 3 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
We evaluated whether postpartum muscle mass affects the risk of type 2 diabetes mellitus (T2DM) in Korean women with gestational diabetes mellitus (GDM).
Methods
A total of 305 women with GDM (mean age, 34.9 years) was prospectively evaluated for incident prediabetes and T2DM from 2 months after delivery and annually thereafter. Appendicular skeletal muscle mass (ASM) was assessed with bioelectrical impedance analysis at the initial postpartum visit, and ASM, either divided by body mass index (BMI) or squared height, and the absolute ASM were used as muscle mass indices. The risk of incident prediabetes and T2DM was assessed according to tertiles of these indices using a logistic regression model.
Results
After a mean follow-up duration of 3.3 years, the highest ASM/BMI tertile group had a 61% lower risk of incident prediabetes and T2DM compared to the lowest tertile group, and this remained significant after we adjusted for covariates (adjusted odds ratio, 0.37; 95% confidence interval [CI], 0.15 to 0.92; P=0.032). Equivalent findings were observed in normal weight women (BMI <23 kg/m2), but this association was not significant for overweight women (BMI ≥23 kg/m2). Absolute ASM or ASM/height2 was not associated with the risk of postpartum T2DM.
Conclusion
A higher muscle mass, as defined by the ASM/BMI index, was associated with a lower risk of postpartum prediabetes and T2DM in Korean women with GDM.

Citations

Citations to this article as recorded by  
  • More appendicular lean mass relative to body mass index is associated with lower incident diabetes in middle-aged adults in the CARDIA study
    Melanie S. Haines, Aaron Leong, Bianca C. Porneala, Victor W. Zhong, Cora E. Lewis, Pamela J. Schreiner, Karen K. Miller, James B. Meigs, Mercedes R. Carnethon
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Review
Metabolic Risk/Epidemiology
Gestational Diabetes Mellitus: Diagnostic Approaches and Maternal-Offspring Complications
Joon Ho Moon, Hak Chul Jang
Diabetes Metab J. 2022;46(1):3-14.   Published online January 27, 2022
DOI: https://doi.org/10.4093/dmj.2021.0335
  • 15,700 View
  • 924 Download
  • 60 Web of Science
  • 68 Crossref
Graphical AbstractGraphical Abstract AbstractAbstract PDFPubReader   ePub   
Gestational diabetes mellitus (GDM) is the most common complication during pregnancy and is defined as any degree of glucose intolerance with onset or first recognition during pregnancy. GDM is associated with adverse pregnancy outcomes and long-term offspring and maternal complications. For GDM screening and diagnosis, a two-step approach (1-hour 50 g glucose challenge test followed by 3-hour 100 g oral glucose tolerance test) has been widely used. After the Hyperglycemia and Adverse Pregnancy Outcome study implemented a 75 g oral glucose tolerance test in all pregnant women, a one-step approach was recommended as an option for the diagnosis of GDM after 2010. The one-step approach has more than doubled the incidence of GDM, but its clinical benefit in reducing adverse pregnancy outcomes remains controversial. Long-term complications of mothers with GDM include type 2 diabetes mellitus and cardiovascular disease, and complications of their offspring include childhood obesity and glucose intolerance. The diagnostic criteria of GDM should properly classify women at risk for adverse pregnancy outcomes and long-term complications. The present review summarizes the strengths and weaknesses of the one-step and two-step approaches for the diagnosis of GDM based on recent randomized controlled trials and observational studies. We also describe the long-term maternal and offspring complications of GDM.

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Original Articles
Metabolic Risk/Epidemiology
Postprandial Free Fatty Acids at Mid-Pregnancy Increase the Risk of Large-for-Gestational-Age Newborns in Women with Gestational Diabetes Mellitus
So-Yeon Kim, Young Shin Song, Soo-Kyung Kim, Yong-Wook Cho, Kyung-Soo Kim
Diabetes Metab J. 2022;46(1):140-148.   Published online August 9, 2021
DOI: https://doi.org/10.4093/dmj.2021.0023
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Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
To investigate the association between free fatty acid (FFA) level at mid-pregnancy and large-for-gestational-age (LGA) newborns in women with gestational diabetes mellitus (GDM).
Methods
We enrolled 710 pregnant women diagnosed with GDM from February 2009 to October 2016. GDM was diagnosed by a ‘two-step’ approach with Carpenter and Coustan criteria. We measured plasma lipid profiles including fasting and 2-hour postprandial FFA (2h-FFA) levels at mid-pregnancy. LGA was defined if birthweights of newborns were above the 90th percentile for their gestational age.
Results
Mean age of pregnant women in this study was 33.1 years. Mean pre-pregnancy body mass index (BMI) was 22.4 kg/m2. The prevalence of LGA was 8.3% (n=59). Levels of 2h-FFA were higher in women who delivered LGA newborns than in those who delivered non-LGA newborns (416.7 μEq/L vs. 352.5 μEq/L, P=0.006). However, fasting FFA was not significantly different between the two groups. The prevalence of delivering LGA newborns was increased with increasing tertile of 2h-FFA (T1, 4.3%; T2, 9.8%; T3, 10.7%; P for trend <0.05). After adjustment for maternal age, pre-pregnancy BMI, and fasting plasma glucose, the highest tertile of 2h-FFA was 2.38 times (95% confidence interval, 1.11 to 5.13) more likely to have LGA newborns than the lowest tertile. However, there was no significant difference between groups according to fasting FFA tertiles.
Conclusion
In women with GDM, a high 2h-FFA level (but not fasting FFA) at mid-pregnancy is associated with an increasing risk of delivering LGA newborns.

Citations

Citations to this article as recorded by  
  • Advances in free fatty acid profiles in gestational diabetes mellitus
    Haoyi Du, Danyang Li, Laura Monjowa Molive, Na Wu
    Journal of Translational Medicine.2024;[Epub]     CrossRef
  • Modulation of gut microbiota and lipid metabolism in rats fed high-fat diets by Ganoderma lucidum triterpenoids
    Aijun Tong, Weihao Wu, Zhengxin Chen, Jiahui Wen, Ruibo Jia, Bin Liu, Hui Cao, Chao Zhao
    Current Research in Food Science.2023; 6: 100427.     CrossRef
  • Fetal Abdominal Obesity Detected at 24 to 28 Weeks of Gestation Persists until Delivery Despite Management of Gestational Diabetes Mellitus (Diabetes Metab J 2021;45:547-57)
    Wonjin Kim, Soo Kyung Park, Yoo Lee Kim
    Diabetes & Metabolism Journal.2021; 45(6): 970.     CrossRef
Metabolic Risk/Epidemiology
Fetal Abdominal Obesity Detected At 24 to 28 Weeks of Gestation Persists Until Delivery Despite Management of Gestational Diabetes Mellitus
Wonjin Kim, Soo Kyung Park, Yoo Lee Kim
Diabetes Metab J. 2021;45(4):547-557.   Published online March 5, 2021
DOI: https://doi.org/10.4093/dmj.2020.0078
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Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Fetal abdominal obesity (FAO) has been reported to be affected at gestational diabetes mellitus (GDM) diagnosis at 24 to 28 weeks of gestation in older and/or obese women. This study investigated whether the management of GDM improves FAO in GDM subjects near term.
Methods
Medical records of 7,099 singleton pregnant women delivering at CHA Gangnam Medical Center were reviewed retrospectively. GDM was diagnosed by 100-g oral glucose tolerance test after 50-g glucose challenge test based on Carpenter–Coustan criteria. GDM subjects were divided into four study groups according to maternal age and obesity. FAO was defined as ≥90th percentile of fetal abdominal overgrowth ratios (FAORs) of the ultrasonographically estimated gestational age (GA) of abdominal circumference per actual GA by the last menstruation period, biparietal diameter, or femur length, respectively.
Results
As compared with normal glucose tolerance (NGT) subjects near term, FAORs and odds ratio for FAO were significantly higher in old and/or obese women with GDM but not in young and nonobese women with GDM. For fetuses of GDM subjects with FAO at the time of GDM diagnosis, the odds ratio for exhibiting FAO near term and being large for GA at birth were 7.87 (95% confidence interval [CI], 4.38 to 14.15) and 10.96 (95% CI, 5.58 to 20.53) compared with fetuses of NGT subjects without FAO at GDM diagnosis.
Conclusion
Despite treatment, FAO detected at the time of GDM diagnosis persisted until delivery. Early diagnosis and treatment might be necessary to prevent near term FAO in high-risk older and/or obese women.

Citations

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  • The effects of gestational diabetes mellitus on fetal growth: is it different for low-risk and medium–high-risk pregnant women?
    Jie Wang, Xin Cheng, Zhen-Hua Li, Yi-Cheng Mao, Xin-Qiang Wang, Kang-Di Zhang, Wen-Jie Yu, Ying-Qing Li, Jia-wen Zhao, Mao-Lin Chen, Guo-peng Gao, Cheng-Yang Hu, Xiu-Jun Zhang
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    Scientific Reports.2023;[Epub]     CrossRef
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    Qian-Ren Zhang, Yan Dong, Jian-Gao Fan
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    Wonjin Kim, Soo Kyung Park, Yoo Lee Kim
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Metabolic Risk/Epidemiology
Maternal Hyperglycemia during Pregnancy Increases Adiposity of Offspring
Hye Rim Chung, Joon Ho Moon, Jung Sub Lim, Young Ah Lee, Choong Ho Shin, Joon-Seok Hong, Soo Heon Kwak, Sung Hee Choi, Hak Chul Jang
Diabetes Metab J. 2021;45(5):730-738.   Published online February 22, 2021
DOI: https://doi.org/10.4093/dmj.2020.0154
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Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
The effect of intrauterine hyperglycemia on fat mass and regional fat proportion of the offspring of mothers with gestational diabetes mellitus (OGDM) remains to be determined.
Methods
The body composition of OGDM (n=25) and offspring of normoglycemic mothers (n=49) was compared using dualenergy X-ray absorptiometry at age 5 years. The relationship between maternal glucose concentration during a 100 g oral glucose tolerance test (OGTT) and regional fat mass or proportion was analyzed after adjusting for maternal prepregnancy body mass index (BMI).
Results
BMI was comparable between OGDM and control (median, 16.0 kg/m2 vs. 16.1 kg/m2 ). Total, truncal, and leg fat mass were higher in OGDM compared with control (3,769 g vs. 2,245 g, P=0.004; 1,289 g vs. 870 g, P=0.017; 1,638 g vs. 961 g, P=0.002, respectively), whereas total lean mass was lower in OGDM (15,688 g vs. 16,941 g, P=0.001). Among OGDM, total and truncal fat mass were correlated with fasting and 3-hour glucose concentrations of maternal 100 g OGTT during pregnancy (total fat mass, r=0.49, P=0.018 [fasting], r=0.473, P=0.023 [3-hour]; truncal fat mass, r=0.571, P=0.004 [fasting], r=0.558, P=0.006 [3-hour]), but there was no correlation between OGDM leg fat mass and maternal OGTT during pregnancy. Regional fat indices were not correlated with concurrent maternal 75 g OGTT values.
Conclusion
Intrauterine hyperglycemia is associated with increased fat mass, especially truncal fat, in OGDM aged 5 years.

Citations

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  • Advances in free fatty acid profiles in gestational diabetes mellitus
    Haoyi Du, Danyang Li, Laura Monjowa Molive, Na Wu
    Journal of Translational Medicine.2024;[Epub]     CrossRef
  • High-fat diet during pregnancy lowers fetal weight and has a long-lasting adverse effect on brown adipose tissue in the offspring
    Mihoko Yamaguchi, Jun Mori, Nozomi Nishida, Satoshi Miyagaki, Yasuhiro Kawabe, Takeshi Ota, Hidechika Morimoto, Yusuke Tsuma, Shota Fukuhara, Takehiro Ogata, Takuro Okamaura, Naoko Nakanishi, Masahide Hamaguchi, Hisakazu Nakajima, Michiaki Fukui, Tomoko I
    Journal of Developmental Origins of Health and Disease.2023; 14(2): 261.     CrossRef
  • Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms
    Byung Soo Kang, Seon Ui Lee, Subeen Hong, Sae Kyung Choi, Jae Eun Shin, Jeong Ha Wie, Yun Sung Jo, Yeon Hee Kim, Kicheol Kil, Yoo Hyun Chung, Kyunghoon Jung, Hanul Hong, In Yang Park, Hyun Sun Ko
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    Bingbing Guo, Jingjing Pei, Yin Xu, Yajie Wang, Xinye Jiang
    Scientific Reports.2023;[Epub]     CrossRef
  • Gestational Diabetes Mellitus: Diagnostic Approaches and Maternal-Offspring Complications
    Joon Ho Moon, Hak Chul Jang
    Diabetes & Metabolism Journal.2022; 46(1): 3.     CrossRef
  • Increased Pro-Inflammatory T Cells, Senescent T Cells, and Immune-Check Point Molecules in the Placentas of Patients With Gestational Diabetes Mellitus
    Yea Eun Kang, Hyon-Seung Yi, Min-Kyung Yeo, Jung Tae Kim, Danbit Park, Yewon Jung, Ok Soon Kim, Seong Eun Lee, Ji Min Kim, Kyong Hye Joung, Ju Hee Lee, Bon Jeong Ku, Mina Lee, Hyun Jin Kim
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Metabolic Risk/Epidemiology
A Vegetable Dietary Pattern Is Associated with Lowered Risk of Gestational Diabetes Mellitus in Chinese Women
Qiong Chen, Weiwei Wu, Hailan Yang, Ping Zhang, Yongliang Feng, Keke Wang, Ying Wang, Suping Wang, Yawei Zhang
Diabetes Metab J. 2020;44(6):887-896.   Published online September 11, 2020
DOI: https://doi.org/10.4093/dmj.2019.0138
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Identification of modifiable dietary factors, which are involved in the development of gestational diabetes mellitus (GDM), could inform strategies to prevent GDM.
Methods
We examined the dietary patterns in a Chinese population and evaluated their relationship with GDM risk using a case-control study including 1,464 cases and 8,092 control subjects. Propensity score matching was used to reduce the imbalance of covariates between cases and controls. Dietary patterns were identified using factor analysis while their associations with GDM risk were evaluated using logistic regression models.
Results
A “vegetable” dietary pattern was characterized as the consumption of green leafy vegetables (Chinese little greens and bean seedling), other vegetables (cabbages, carrots, tomatoes, eggplants, potatoes, mushrooms, peppers, bamboo shoots, agarics, and garlic), and bean products (soybean milk, tofu, kidney beans, and cowpea). For every quartile increase in the vegetables factor score during 1 year prior to conception, the first trimester, and the second trimester of pregnancy, the GDM risk lowered by 6% (odds ratio [OR], 0.94; 95% confidence interval [CI], 0.89 to 0.99), 7% (OR, 0.94; 95% CI, 0.88 to 0.99), and 9% (OR, 0.91; 95% CI, 0.86 to 0.96).
Conclusion
In conclusion, our study suggests that the vegetable dietary pattern is associated with lower GDM risk; however, the interpretation of the result should with caution due to the limitations in our study, and additional studies are necessary to explore the underlying mechanism of this relationship.

Citations

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  • Maternal dietary components in the development of gestational diabetes mellitus: a systematic review of observational studies to timely promotion of health
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    Elaine Luiza Santos Soares de Mendonça, Marilene Brandão Tenório Fragoso, Jerusa Maria de Oliveira, Jadriane Almeida Xavier, Marília Oliveira Fonseca Goulart, Alane Cabral Menezes de Oliveira
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Metabolic Risk/Epidemiology
A Comparison of Predictive Performances between Old versus New Criteria in a Risk-Based Screening Strategy for Gestational Diabetes Mellitus
Subeen Hong, Seung Mi Lee, Soo Heon Kwak, Byoung Jae Kim, Ja Nam Koo, Ig Hwan Oh, Sohee Oh, Sun Min Kim, Sue Shin, Won Kim, Sae Kyung Joo, Errol R. Norwitz, Souphaphone Louangsenlath, Chan-Wook Park, Jong Kwan Jun, Joong Shin Park
Diabetes Metab J. 2020;44(5):726-736.   Published online April 13, 2020
DOI: https://doi.org/10.4093/dmj.2019.0126
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AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

The definition of the high-risk group for gestational diabetes mellitus (GDM) defined by the American College of Obstetricians and Gynecologists was changed from the criteria composed of five historic/demographic factors (old criteria) to the criteria consisting of 11 factors (new criteria) in 2017. To compare the predictive performances between these two sets of criteria.

Methods

This is a secondary analysis of a large prospective cohort study of non-diabetic Korean women with singleton pregnancies designed to examine the risk of GDM in women with nonalcoholic fatty liver disease. Maternal fasting blood was taken at 10 to 14 weeks of gestation and measured for glucose and lipid parameters. GDM was diagnosed by the two-step approach.

Results

Among 820 women, 42 (5.1%) were diagnosed with GDM. Using the old criteria, 29.8% (n=244) of women would have been identified as high risk versus 16.0% (n=131) using the new criteria. Of the 42 women who developed GDM, 45.2% (n=19) would have been mislabeled as not high risk by the old criteria versus 50.0% (n=21) using the new criteria (1-sensitivity, 45.2% vs. 50.0%, P>0.05). Among the 778 patients who did not develop GDM, 28.4% (n=221) would have been identified as high risk using the old criteria versus 14.1% (n=110) using the new criteria (1-specificity, 28.4% vs. 14.1%, P<0.001).

Conclusion

Compared with the old criteria, use of the new criteria would have decreased the number of patients identified as high risk and thus requiring early GDM screening by half (from 244 [29.8%] to 131 [16.0%]).

Citations

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    Young Mi Jung, Seung Mi Lee, Subeen Hong, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Sue Shin, Errol R. Norwitz, Chan‐Wook Park, Jong Kwan Jun, Won Kim, Joong Shin Park
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Metabolic Risk/Epidemiology
Glucose Effectiveness from Short Insulin-Modified IVGTT and Its Application to the Study of Women with Previous Gestational Diabetes Mellitus
Micaela Morettini, Carlo Castriota, Christian Göbl, Alexandra Kautzky-Willer, Giovanni Pacini, Laura Burattini, Andrea Tura
Diabetes Metab J. 2020;44(2):286-294.   Published online January 13, 2020
DOI: https://doi.org/10.4093/dmj.2019.0016
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AbstractAbstract PDFPubReader   
Background

This study aimed to design a simple surrogate marker (i.e., predictor) of the minimal model glucose effectiveness (SG), namely calculated SG (CSG), from a short insulin-modified intravenous glucose tolerance test (IM-IVGTT), and then to apply it to study women with previous gestational diabetes mellitus (pGDM).

Methods

CSG was designed using the stepwise model selection approach on a population of subjects (n=181) ranging from normal tolerance to type 2 diabetes mellitus (T2DM). CSG was then tested on a population of women with pGDM (n=57). Each subject underwent a 3-hour IM-IVGTT; women with pGDM were observed early postpartum and after a follow-up period of up to 7 years and classified as progressors (PROG) or non-progressors (NONPROG) to T2DM. The minimal model analysis provided a reference SG.

Results

CSG was described as CSG=1.06×10−2+5.71×10−2×KG/Gpeak, KG being the mean slope (absolute value) of loge glucose in 10–25- and 25–50-minute intervals, and Gpeak being the maximum of the glucose curve. Good agreement between CSG and SG in the general population and in the pGDM group, both at baseline and follow-up (even in PROG and NONPROG subgroups), was shown by the Bland-Altman plots (<5% observations outside limits of agreement), and by the test for equivalence (equivalence margin not higher than one standard deviation). At baseline, the PROG subgroup showed significantly lower SG and CSG values compared to the NONPROG subgroup (P<0.03).

Conclusion

CSG is a valid SG predictor. In the pGDM group, glucose effectiveness appeared to be impaired in women progressing to T2DM.

Citations

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  • Postprandial Free Fatty Acids at Mid-Pregnancy Increase the Risk of Large-for-Gestational-Age Newborns in Women with Gestational Diabetes Mellitus
    So-Yeon Kim, Young Shin Song, Soo-Kyung Kim, Yong-Wook Cho, Kyung-Soo Kim
    Diabetes & Metabolism Journal.2022; 46(1): 140.     CrossRef
  • Unraveling the Factors Determining Development of Type 2 Diabetes in Women With a History of Gestational Diabetes Mellitus Through Machine-Learning Techniques
    Ludovica Ilari, Agnese Piersanti, Christian Göbl, Laura Burattini, Alexandra Kautzky-Willer, Andrea Tura, Micaela Morettini
    Frontiers in Physiology.2022;[Epub]     CrossRef
  • The Clinical Characteristics of Gestational Diabetes Mellitus in Korea: A National Health Information Database Study
    Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
    Endocrinology and Metabolism.2021; 36(3): 628.     CrossRef
Clinical Diabetes & Therapeutics
Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction?
Veronica Falcone, Grammata Kotzaeridi, Melanie Hanne Breil, Ingo Rosicky, Tina Stopp, Gülen Yerlikaya-Schatten, Michael Feichtinger, Wolfgang Eppel, Peter Husslein, Andrea Tura, Christian S. Göbl
Diabetes Metab J. 2019;43(6):785-793.   Published online March 12, 2019
DOI: https://doi.org/10.4093/dmj.2018.0218
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AbstractAbstract PDFPubReader   
Background

An early identification of the risk groups might be beneficial in reducing morbidities in patients with gestational diabetes mellitus (GDM). Therefore, this study aimed to assess the biochemical predictors of glycemic conditions, in addition to fasting indices of glucose disposal, to predict the development of GDM in later stage and the need of glucose-lowering medication.

Methods

A total of 574 pregnant females (103 with GDM and 471 with normal glucose tolerance [NGT]) were included. A metabolic characterization was performed before 15+6 weeks of gestation by assessing fasting plasma glucose (FPG), fasting insulin (FI), fasting C-peptide (FCP), and glycosylated hemoglobin (HbA1c). Thereafter, the patients were followed-up until the delivery.

Results

Females with NGT had lower levels of FPG, FI, FCP, or HbA1c at the early stage of pregnancy, and therefore, showed an improved insulin action as compared to that in females who developed GDM. Higher fasting levels of FPG and FCP were associated with a higher risk of developing GDM. Moreover, the predictive accuracy of this metabolic profiling was also good to distinguish the patients who required glucose-lowering medications. Indices of glucose disposal based on C-peptide improved the predictive accuracy compared to that based on insulin. A modified quantitative insulin sensitivity check index (QUICKIc) showed the best differentiation in terms of predicting GDM (area under the receiver operating characteristics curve [ROC-AUC], 72.1%) or need for pharmacotherapy (ROC-AUC, 83.7%).

Conclusion

Fasting measurements of glucose and C-peptide as well as the surrogate indices of glycemic condition could be used for stratifying pregnant females with higher risk of GDM at the beginning of pregnancy.

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  • Maternal fasting serum C-peptide concentrations in the first and second trimesters and subsequent risk of gestational diabetes mellitus: A nested case-control study among Chinese women
    Chuanyu Zhao, Haiyan Liu, Yuzhi Deng, Hanbin Wu, Shuo Wang, Xinyi Lyu, Jueming Lei, Haishan Yang, Meina Hu, Yinzhu Zhao, Xu Ma, Xiaoxuan Zou, Ying Yang
    Diabetes Research and Clinical Practice.2024; 208: 111111.     CrossRef
  • Future clinical prospects of C-peptide testing in the early diagnosis of gestational diabetes
    Charalampos Milionis, Ioannis Ilias, Anastasia Lekkou, Evangelia Venaki, Eftychia Koukkou
    World Journal of Experimental Medicine.2024;[Epub]     CrossRef
  • Early prediction of gestational diabetes mellitus using maternal demographic and clinical risk factors
    Yanqi Wu, Paul Hamelmann, Myrthe van der Ven, Sima Asvadi, M. Beatrijs van der Hout-van der Jagt, S. Guid Oei, Massimo Mischi, Jan Bergmans, Xi Long
    BMC Research Notes.2024;[Epub]     CrossRef
  • Gestationsdiabetes (GDM) (Update 2023)
    Alexandra Kautzky-Willer, Yvonne Winhofer, Herbert Kiss, Veronica Falcone, Angelika Berger, Monika Lechleitner, Raimund Weitgasser, Jürgen Harreiter
    Wiener klinische Wochenschrift.2023; 135(S1): 115.     CrossRef
  • MIDO GDM: an innovative artificial intelligence-based prediction model for the development of gestational diabetes in Mexican women
    Héctor Gallardo-Rincón, María Jesús Ríos-Blancas, Janinne Ortega-Montiel, Alejandra Montoya, Luis Alberto Martinez-Juarez, Julieta Lomelín-Gascón, Rodrigo Saucedo-Martínez, Ricardo Mújica-Rosales, Victoria Galicia-Hernández, Linda Morales-Juárez, Lucía Ma
    Scientific Reports.2023;[Epub]     CrossRef
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    欢欢 赵
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  • HOMA‐IR as a risk factor of gestational diabetes mellitus and a novel simple surrogate index in early pregnancy
    Shuoning Song, Yuemei Zhang, Xiaolin Qiao, Yanbei Duo, Jiyu Xu, Zhenyao Peng, Jing Zhang, Yan Chen, Xiaorui Nie, Qiujin Sun, Xianchun Yang, Zechun Lu, Shixuan Liu, Tianyi Zhao, Tao Yuan, Yong Fu, Yingyue Dong, Weigang Zhao, Wei Sun, Ailing Wang
    International Journal of Gynecology & Obstetrics.2022; 157(3): 694.     CrossRef
  • The diagnostic value of glycosylated hemoglobin for gestational diabetes mellitus in Asian populations: A systematic review and meta‐analysis
    Jiani Zhang, Fan Zhou, Tingting Xu, Jinfeng Xu, Yaqian Li, Li Lin, Qi Cao, Xiaodong Wang
    Journal of Obstetrics and Gynaecology Research.2022; 48(4): 902.     CrossRef
  • Postprandial Free Fatty Acids at Mid-Pregnancy Increase the Risk of Large-for-Gestational-Age Newborns in Women with Gestational Diabetes Mellitus
    So-Yeon Kim, Young Shin Song, Soo-Kyung Kim, Yong-Wook Cho, Kyung-Soo Kim
    Diabetes & Metabolism Journal.2022; 46(1): 140.     CrossRef
  • Gestational Diabetes Mellitus in Pregnant Women with Beta-Thalassemia Minor: A Matched Case-Control Study
    Veronica Falcone, Florian Heinzl, Bianca Karla Itariu, Theresa Reischer, Stephanie Springer, Dana Anaïs Muin, Petra Pateisky, Philipp Foessleitner, Johannes Ott, Alex Farr, Klara Rosta
    Journal of Clinical Medicine.2022; 11(7): 2050.     CrossRef
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    Nahal Habibi, Aya Mousa, Chau Thien Tay, Mahnaz Bahri Khomami, Rhiannon K. Patten, Prabha H. Andraweera, Molla Wassie, Jared Vandersluys, Ali Aflatounian, Tina Bianco‐Miotto, Shao J. Zhou, Jessica A. Grieger
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  • Impact Of Prepregnancy Overweight And Obesity On Treatment Modality And Pregnancy Outcome In Women With Gestational Diabetes Mellitus
    Tina Linder, Anna Eder, Cécile Monod, Ingo Rosicky, Daniel Eppel, Katharina Redling, Franziska Geissler, Evelyn A. Huhn, Irene Hösli, Christian S. Göbl
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    Weichun Tang, Xiaoyu Wang, Liping Chen, Yiling Lu, Xinyi Kang
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    Xue Yang, Yi Ye, Yi Wang, Ping Wu, Qi Lu, Yan Liu, Jiaying Yuan, Xingyue Song, Shijiao Yan, Xiaorong Qi, Yi-Xin Wang, Ying Wen, Gang Liu, Chuanzhu Lv, Chun-Xia Yang, An Pan, Jianli Zhang, Xiong-Fei Pan
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    Ayla Coussa, Hayder A. Hasan, Thomas M. Barber
    Endocrine Practice.2021; 27(6): 579.     CrossRef
  • The Clinical Characteristics of Gestational Diabetes Mellitus in Korea: A National Health Information Database Study
    Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
    Endocrinology and Metabolism.2021; 36(3): 628.     CrossRef
  • Early Gestational Diabetes Mellitus: Diagnostic Strategies and Clinical Implications
    Saptarshi Bhattacharya, Lakshmi Nagendra, Aishwarya Krishnamurthy, Om J. Lakhani, Nitin Kapoor, Bharti Kalra, Sanjay Kalra
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    Vedrana Ivić, Jasenka Wagner, Andrijana Müller, Lada Zibar, Marta Kadivnik, Barbara Viljetić, Jelena Omazić
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  • Response: Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction? (Diabetes Metab J 2019;43:785–93)
    Christian S. Göbl, Andrea Tura
    Diabetes & Metabolism Journal.2020; 44(1): 209.     CrossRef
  • First-trimester fasting glycemia as a predictor of gestational diabetes (GDM) and adverse pregnancy outcomes
    G. Sesmilo, P. Prats, S. Garcia, I. Rodríguez, A. Rodríguez-Melcón, I. Berges, B. Serra
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  • Letter: Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction? (Diabetes Metab J 2019;43:785–93)
    Ye Seul Yang, Hye Seung Jung
    Diabetes & Metabolism Journal.2020; 44(1): 199.     CrossRef
  • Auch schon im 1. Trimenon ist Nüchternglukose Prädiktor für Gestationsdiabetes
    Jens Stupin
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    Yunzhen Ye, Yu Xiong, Qiongjie Zhou, Jiangnan Wu, Xiaotian Li, Xirong Xiao
    Journal of Diabetes Research.2020; 2020: 1.     CrossRef
  • Predictive Power of Unconjugated Estriol in Diagnosis of Gestational Diabetes: A Cohort Study
    Azam Amirian, Nourossadat Kariman, Mehdi Hedayati, Nasrin Borumandnia, Zohre Sheikhan
    Iranian Red Crescent Medical Journal.2019;[Epub]     CrossRef
Clinical Care/Education
Pregnancy Outcomes of Women Additionally Diagnosed as Gestational Diabetes by the International Association of the Diabetes and Pregnancy Study Groups Criteria
Min Hyoung Kim, Soo Heon Kwak, Sung-Hoon Kim, Joon Seok Hong, Hye Rim Chung, Sung Hee Choi, Moon Young Kim, Hak C. Jang
Diabetes Metab J. 2019;43(6):766-775.   Published online February 28, 2019
DOI: https://doi.org/10.4093/dmj.2018.0192
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AbstractAbstract PDFPubReader   
Background

We investigated the pregnancy outcomes in women who were diagnosed with gestational diabetes mellitus (GDM) by the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria but not by the Carpenter-Coustan (CC) criteria.

Methods

A total of 8,735 Korean pregnant women were identified at two hospitals between 2014 and 2016. Among them, 2,038 women participated in the prospective cohort to investigate pregnancy outcomes. Diagnosis of GDM was made via two-step approach with 50-g glucose challenge test for screening followed by diagnostic 2-hour 75-g oral glucose tolerance test. Women were divided into three groups: non-GDM, GDM diagnosed exclusively by the IADPSG criteria, and GDM diagnosed by the CC criteria.

Results

The incidence of GDM was 2.1% according to the CC criteria, and 4.1% by the IADPSG criteria. Women diagnosed with GDM by the IADPSG criteria had a higher body mass index (22.0±3.1 kg/m2 vs. 21.0±2.8 kg/m2, P<0.001) and an increased risk of preeclampsia (odds ratio [OR], 6.90; 95% confidence interval [CI], 1.84 to 25.87; P=0.004) compared to non-GDM women. Compared to neonates of the non-GDM group, those of the IADPSG GDM group had an increased risk of being large for gestational age (OR, 2.39; 95% CI, 1.50 to 3.81; P<0.001), macrosomia (OR, 2.53; 95% CI, 1.26 to 5.10; P=0.009), and neonatal hypoglycemia (OR, 3.84; 95% CI, 1.01 to 14.74; P=0.049); they were also at an increased risk of requiring phototherapy (OR, 1.57; 95% CI, 1.07 to 2.31; P=0.022) compared to the non-GDM group.

Conclusion

The IADPSG criteria increased the incidence of GDM by nearly three-fold, and women diagnosed with GDM by the IADPSG criteria had an increased risk of adverse pregnancy outcomes in Korea.

Citations

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    Elena Greco, Maria Calanducci, Kypros H. Nicolaides, Eleanor V.H. Barry, Mohammed S.B. Huda, Stamatina Iliodromiti
    American Journal of Obstetrics and Gynecology.2024; 230(2): 213.     CrossRef
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    Kaisa Kariniemi, Marja Vääräsmäki, Tuija Männistö, Sanna Mustaniemi, Eero Kajantie, Sanna Eteläinen, Elina Keikkala, Anneli Pouta, Risto Kaaja, Johan G Eriksson, Hannele Laivuori, Mika Gissler
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    Deutsches Ärzteblatt international.2023;[Epub]     CrossRef
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    Seung-Hwan Lee, Jin Yu, Kyungdo Han, Seung Woo Lee, Sang Youn You, Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon, Mee Kyoung Kim
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Clinical Diabetes & Therapeutics
Progression to Gestational Diabetes Mellitus in Pregnant Women with One Abnormal Value in Repeated Oral Glucose Tolerance Tests
Sunyoung Kang, Min Hyoung Kim, Moon Young Kim, Joon-Seok Hong, Soo Heon Kwak, Sung Hee Choi, Soo Lim, Kyong Soo Park, Hak C. Jang
Diabetes Metab J. 2019;43(5):607-614.   Published online February 28, 2019
DOI: https://doi.org/10.4093/dmj.2018.0159
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AbstractAbstract PDFPubReader   
Background

Women with one abnormal value (OAV) in a 100 g oral glucose tolerance test (OGTT) during pregnancy are reported to have an increased risk of adverse pregnancy outcomes. However, there is limited data about whether women with OAV will progress to gestational diabetes mellitus (GDM) when the OGTT is repeated.

Methods

To identify clinical and metabolic predictors for GDM in women with OAV, we conducted a retrospective study and identified women with OAV in the OGTT done at 24 to 30 weeks gestational age (GA) and repeated the second OGTT between 32 and 34 weeks of GA.

Results

Among 137 women with OAV in the initial OGTT, 58 (42.3%) had normal, 40 (29.2%) had OAV and 39 (28.5%) had GDM in the second OGTT. Maternal age, prepregnancy body mass index, weight gain from prepregnancy to the second OGTT, GA at the time of the OGTT, and parity were similar among normal, OAV, and GDM groups. Plasma glucose levels in screening tests were different (151.8±15.7, 155.8±14.6, 162.5±20.3 mg/dL, P<0.05), but fasting, 1-, 2-, and 3-hour glucose levels in the initial OGTT were not. Compared to women with screen negative, women with untreated OAV had a higher frequency of macrosomia.

Conclusion

We demonstrated that women with OAV in the initial OGTT significantly progressed to GDM in the second OGTT. Clinical parameters predicting progression to GDM were not found. Repeating the OGTT in women with OAV in the initial test may be helpful to detect GDM progression.

Citations

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  • Maternal and fetal outcomes of pregnancies associated with single versus double abnormal values in 100 gr glucose tolerance test
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    Humberto Navarro-Martinez, Juana-Antonia Flores-Le Roux, Gemma Llauradó, Lucia Gortazar, Antonio Payà, Laura Mañé, Juan Pedro-Botet, David Benaiges
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Epidemiology
Oral Glucose Tolerance Testing Allows Better Prediction of Diabetes in Women with a History of Gestational Diabetes Mellitus
Tae Jung Oh, Yeong Gi Kim, Sunyoung Kang, Joon Ho Moon, Soo Heon Kwak, Sung Hee Choi, Soo Lim, Kyong Soo Park, Hak C. Jang, Joon-Seok Hong, Nam H. Cho
Diabetes Metab J. 2019;43(3):342-349.   Published online December 7, 2018
DOI: https://doi.org/10.4093/dmj.2018.0086
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AbstractAbstract PDFPubReader   
Background

We aimed to identify the postpartum metabolic factors that were associated with the development of diabetes in women with a history of gestational diabetes mellitus (GDM). In addition, we examined the role of the oral glucose tolerance test (OGTT) in the prediction of future diabetes.

Methods

We conducted a prospective study of 179 subjects who previously had GDM but did not have diabetes at 2 months postpartum. The initial postpartum examination including a 75-g OGTT and the frequently sampled intravenous glucose tolerance test (FSIVGTT) was performed 12 months after delivery, and annual follow-up visits were made thereafter.

Results

The insulinogenic index (IGI30) obtained from the OGTT was significantly correlated with the acute insulin response to glucose (AIRg) obtained from the FSIVGTT. The disposition indices obtained from the OGTT and FSIVGTT were also significantly correlated. Women who progressed to diabetes had a lower insulin secretory capacity including IGI30, AIRg, and disposition indices obtained from the FSIVGTT and OGTT compared with those who did not. However, the insulin sensitivity indices obtained from the OGTT and FSIVGTT did not differ between the two groups. Multivariate logistic regression analysis showed that the 2-hour glucose and disposition index obtained from the FSIVGTT were significant postpartum metabolic risk factors for the development of diabetes.

Conclusion

We identified a crucial role of β-cell dysfunction in the development of diabetes in Korean women with previous GDM. The 2-hour glucose result from the OGTT is an independent predictor of future diabetes. Therefore, the OGTT is crucial for better prediction of future diabetes in Korean women with previous GDM.

Citations

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