scholarly journals Establishment of a nomogram model to predict macrosomia in pregnant women with gestational diabetes mellitus

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yujiao Zou ◽  
Yan Zhang ◽  
Zhenhua Yin ◽  
Lili Wei ◽  
Bohan Lv ◽  
...  

Abstract Aim To establish a nomogram model to predict the risk of macrosomia in pregnant women with gestational diabetes mellitus in China. Methods We retrospectively collected the medical records of 783 pregnant women with gestational diabetes who underwent prenatal examinations and delivered at the Affiliated Hospital of Qingdao University from October 2019 to October 2020. The pregnant women were randomly divided into two groups in a 4:1 ratio to generate and validate the model. The independent risk factors for macrosomia in pregnant women with gestational diabetes mellitus were analyzed by multivariate logistic regression, and the nomogram model to predict the risk of macrosomia in pregnant women with gestational diabetes mellitus was established and verified by R software. Results Logistic regression analysis showed that prepregnancy body mass index, weight gain during pregnancy, fasting plasma glucose, triglycerides, biparietal diameter and amniotic fluid index were independent risk factors for macrosomia (P < 0.05). The areas under the ROC curve for internal and external validation of the model were 0.813 (95 % confidence interval 0.754–0.862) and 0.903 (95 % confidence interval 0.588–0.967), respectively. The calibration curve was a straight line with a slope close to 1. Conclusions In this study, we constructed a nomogram model to predict the risk of macrosomia in pregnant women with gestational diabetes mellitus. The model has good discrimination and calibration abilities, which can help clinical healthcare staff accurately predict macrosomia in pregnant women with gestational diabetes mellitus.

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Mayu Watanabe ◽  
Akihiro Katayama ◽  
Hidetoshi Kagawa ◽  
Daisuke Ogawa ◽  
Jun Wada

Poor maternal glycemic control increases maternal and fetal risk for adverse outcomes, and strict management of gestational diabetes mellitus (GDM) is recommended to prevent neonatal and maternal complications. However, risk factors for the requirement of antenatal insulin treatment (AIT) are not well-investigated in the pregnant women with GDM. We enrolled 37 pregnant women with GDM and investigated the risk for AIT by comparing the patients with AIT (AIT group;n=10) and without insulin therapy (Diet group;n=27). The 1-h and 2-h plasma glucose levels and the number of abnormal values in 75 g OGTT were significantly higher in AIT group compared with Diet group. By logistic regression analysis, plasma glucose level at 1-h was significant predictor for AIT and the odds ratios were 1.115 (1.004–1.239) using forward selection method and 1.192 (1.006–1.413) using backward elimination method. There were no significant differences in obstetrical outcomes and neonatal complications. 1-h plasma glucose levels in 75 g OGTT are useful parameters in predicting the requirement for AIT in GDM. Both maternal and neonatal complications are comparable in GDM patients with and without insulin therapy.


2021 ◽  
Vol 12 ◽  
Author(s):  
Dongjian Yang ◽  
Jingbo Qiu ◽  
An Qin ◽  
Lei Chen ◽  
Ya Yang ◽  
...  

BackgroundPrevious evidence indicates that birth season is associated with type 2 diabetes in adults. However, information on the association of birth with gestational diabetes mellitus (GDM) is lacking. The present study explores the association between birth seasonality and GDM in East China.MethodsThis retrospective cohort study was conducted at the International Peace Maternal and child health hospital between 2014 and 2019. A total of 79, 292 pregnant women were included in the study after excluding participants with previous GDM, stillbirth, polycystic ovary syndrome, and lack of GDM laboratory records. The multivariate logistic regression model was employed to estimate the odds ratio and 95% confidence interval. After log transformation of blood glucose level, the percentage change and 95% confidence interval were estimated by a multivariate linear model.ResultsThe risk of GDM among pregnant women born in spring, autumn, and winter was not significantly different compared to that among participants born in summer. Pregnant women born in autumn had significantly higher 1-hour postprandial blood glucose (PBG-1h) and 2-hour postprandial blood glucose (PBG-2h) levels than pregnant women born in summer. Compared to pregnant women born in August, the PBG-1h level of pregnant women born in October, November, and December increased significantly, whereas the PBG-2h levels of pregnant women born in November and December increased significantly.ConclusionPregnant women born in autumn exhibit higher postprandial blood glucose levels during pregnancy than in those born in summer. The findings provide evidence that exposure to seasonal changes in early life may influence blood glucose metabolism during pregnancy.


2016 ◽  
Vol 06 (04) ◽  
pp. 269-276 ◽  
Author(s):  
Jean Baptsite Niyibizi ◽  
Florien Safari ◽  
Jean Bosco Ahishakiye ◽  
Jean Bosco Habimana ◽  
Herbert Mapira ◽  
...  

2019 ◽  
Vol 10 (2) ◽  
pp. 26-30
Author(s):  
Vivek Sinha ◽  
Poonam Kachhawa

Background: Gestational diabetes mellitus (GDM) is a common medical condition that complicates pregnancies..Gestational diabetes mellitus (GDM) is a diabetic metabolic disorder that occurs in 4% of all pregnant women and 14% of ethnic groups with more prevalence of type II diabetes. It can be defined as increased or abnormal insulin resistance, decreased insulin sensitivity or glucose intolerance with first diagnosis during pregnancy. Aims and Objectives: The purpose of this study was to evaluate the diagnostic screening value of the HbA1c, prevalence of GDM and associated risk factors. Materials and Methods: The study was conducted at the metabolic clinic; in the department of Biochemistry located at SIMS, Hapur. A semi-structured pretested questionnaire was used for data collection. Following the DIPSI guidelines, patients with plasma glucose values >140 mg/dl were labeled as GDM. Statistical methods used were OR (CI95%), percentage, Chi square. Results: Out of 500, 6.72% had GDM. Among all GDM patients, 64.71% had age more than 30 years, 70.59% had BMI more than 25, 41.18% had gravida more than 3 and p- value was significant with regard to age and BMI. P value was found to be significant for risk factors namely positive family history of Diabetes Mellitus, history of big baby and presence of more than one risk factor. Conclusion: GDM is associated with high BMI, early pregnancy loss, family history of DM and previous history of big baby and there could be more than one risk factor. Thus universal screening followed by close monitoring of the pregnant women for early detection of GDM may help improving maternal and fetal outcomes.


2015 ◽  
Vol 7 (S1) ◽  
Author(s):  
Renata Selbach Pons ◽  
Fernanda Camboim Rockett ◽  
Bibiana de Almeida Rubin ◽  
Maria Lúcia Rocha Oppermann ◽  
Vera Lúcia Bosa

Author(s):  
Martina Gáborová ◽  
Viera Doničová ◽  
Ivana Bačová ◽  
Mária Pallayová ◽  
Martin Bona ◽  
...  

Background: The aim of the study was to compare the continuous glucose monitoring (CGM)-determined glycaemic variability (GV) of pregnant women with gestational diabetes mellitus (GDM) and without GDM (CG; control group). The secondary aim was to evaluate the association between risk factors of diabetes in pregnancy and parameters of glyceamic control. Methods: Demographic, biometric and biochemical parameters were obtained for pregnant women (20–38 years old) who after an oral glucose tolerance test were examined by 7-day continuous glucose monitoring using a iPro®2 Professional CGM. Results: The differences in GV between women with GDM and CG compared by total area under glucose curve (total AUC, (mmol·day/L) was statistically significant (p = 0.006). Other parameters of glycaemic control such as mean glucose, standard deviation, coefficient of variation, J-index, % time-above target range 7.8 mmol/L (%TAR), % time-in range 3.5–7.8 mmol/L (%TIR), time-below target range 3.5 mmol/L (%TBR), glycated haemoglobin were not significantly different in the study groups. Risk factors (a family history of diabetes, pre-pregnancy BMI, higher weight gain and age) correlated with parameters of glycaemic control. Conclusions: We found a significant difference in GV of women with and without GDM by total AUC determined from CGM. TIR metrics were close to significance. Our work points at an increased GV in relation to the risk factors of GDM. Pregnant women with risk factors have higher probability of severe GV with its consequences on maternal and fetal health state.


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