Risk factors for abnormal postpartum glucose outcome in women with gestational diabetes mellitus diagnosed by modified The International Association of the Diabetes and Pregnancy Study Groups criteria

Wang, Teng; Zheng, Wei; Huang, Wenyu; Zhang, Li; Tian, Zhihong; Zhang, Ting; Qi, Yan; Li, Guanghui

doi:10.1111/jog.14009

Cited by 13 publications

(4 citation statements)

References 25 publications

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“…Pre-pregnancy obesity or overweight is closely related to neonatal blood sugar. Wang and Luo [20] reported that pre-pregnancy BMI ≥ 25 kg/m 2 was a risk factor for GDM and neonatal hypoglycemia. This study adopted the “Chinese Adult Overweight and Obesity Prevention and Control Guidelines” standard and regarded BMI ≥ 24 kg/m 2 as overweight.…”

Section: Discussionmentioning

confidence: 99%

Analysis of risk factors of neonatal hypoglycemia and its correlation with blood glucose control of gestational diabetes mellitus: A retrospective study

Cao,

Yang,

Liu

et al. 2023

Medicine

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This study aimed to investigate the risk factors associated with neonatal hypoglycemia and its correlation with blood glucose control in patients with gestational diabetes mellitus (GDM). This study was a retrospective study. 880 pregnant women with GDM and their newborns were hospitalized from January 2018 to December 2022 in our hospital. The clinical information of GDM pregnant women and their newborns were reviewed and the hemoglobin A1c (HbA1c) values measured within 1 week before delivery were collected. According to the occurrence of neonatal hypoglycemia, which was divided into the control and observation groups. Logistic regression model was used to estimate the potential factors associated with neonatal hypoglycemia. The association between HbA1c of pregnant women before delivery and abnormal glucose metabolism in newborns was examined using spearman correlation analysis. A total of 104 cases of hypoglycemia occurred in neonates delivered by 880 GDM women and the incidence of neonatal hypoglycemia was 11.82%. There were significant differences in pre-pregnancy overweight or obesity, delivery mode, maternal blood sugar control effect and neonatal feeding standard between the 2 groups of GDM women (P < .05). Pre-pregnancy overweight or obesity, poor blood sugar control in GDM women, and improper neonatal feeding were risk factors for neonatal hypoglycemia. The results of logistic regression analysis showed that abnormal glucose metabolism in newborn (odds ratio [OR]: 2.43, 95% confidence interval [CI]: 1.12–4.73) and neonatal hypoglycemia (OR: 3.04, 95% CI: 1.33–5.79) were a risk factor. We also conducted the logistic analysis to evaluate the correlation between HbA1c before delivery and abnormal glucose metabolism in newborns of pregnant women with GDM through adjusting some potential factors. The results were still significant in the abnormal glucose metabolism in newborn (OR: 2.84, 95% CI: 1.23–6.63) and neonatal hypoglycemia (OR: 3.64, 95% CI: 1.46–8.18). Overweight or obesity of GDM parturient before pregnancy, poor blood glucose control of GDM parturient and improper feeding of newborns are all risk factors for neonatal hypoglycemia. HbA1c before delivery has a certain predictive value for abnormal glucose metabolism in newborns.

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Section: Discussionmentioning

confidence: 99%

Analysis of risk factors of neonatal hypoglycemia and its correlation with blood glucose control of gestational diabetes mellitus: A retrospective study

Cao,

Yang,

Liu

et al. 2023

Medicine

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“…After the widespread adoption of IADPSG criteria for the diagnosis of GDM, the incidences of postpartum preDM and DM reported in women with GDM have decreased mainly because of the lower thresholds in IADPSG criteria. Wang et al (26) found that the incidence of postpartum preDM and DM in women with GDM was 29.9% and 2.9% after using IADPSG criteria. We included patients diagnosed with GDM both in one-(27.6%) and two-step approaches (72.4%).…”

Section: Discussionmentioning

confidence: 99%

Postpartum Metabolic Outcomes and Related Factors in Women with Gestational Diabetes Mellitus History

Işiktaş¹,

Oğuz²,

Şahin³

et al. 2021

Turk J Endocrinol Metab

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Objective: This study aimed to investigate early and late postpartum glycemic abnormalities and related factors in women with a history of gestational diabetes mellitus (GDM). Material and Methods: This study included 152 women aged 18-40 years who were diagnosed with GDM either by one-or two-step oral glucose tolerance test (OGTT). Sociodemographic characteristics, body mass index (BMI), biochemical parameters, and OGTT results of the participants were recorded from files. In addition, BMI, fasting plasma glucose, lipid parameters, and glycosylated hemoglobin (HbA1c) levels were measured, and OGTT was performed between 4 and 12 weeks after postpartum and at the first year. Results: The mean age of the participants was 31.86±6.096 years, and their mean BMI was 26.23±3.67 kg/m 2 . In the early postpartum period (4-6 weeks) after 75 g OGTT, 70.4% of patients had normal glucose tolerance (NGT), 25% had prediabetes (preDM), and 4.6% had diabetes mellitus (DM). In the late postpartum period, 48.0% of patients had NGT, 45.4% had preDM, and 6.6% had DM. BMI and HbA1c levels were significantly higher in patients with both preDM and DM than women with NGT in both early and late periods (p<0.05). In addition, BMI before and 1 year after pregnancy and HbA1c level between 4 and 6 weeks after delivery were independent risk factors for the development of dysglycemia (OR: 1.004, p<0.001; OR: 2.848, p<0.001; and OR: 4.437, p=0.016, respectively). Conclusion: Women with GDM have a high risk of developing preDM and type 2 DM in the first year after delivery.

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“…There is some evidence that glucose levels during pregnancy are predictive of prediabetes. 8, 9 Retnakaran et al 10 have shown that the risk of dysglycaemia at 12 weeks postpartum increases across the groups from normal Glucose Challenge Test (GCT) and Normal Glucose Tolerance (NGT), to abnormal GCT and NGT, to Gestational Impaired Glucose Tolerance (GIGT), to GDM. This has been supported by other studies.…”

Section: Introductionmentioning

confidence: 99%

Machine learning prediction of early postpartum prediabetes in women with gestational diabetes mellitus

Parkhi

Periyathambi

Ghebremichael‐Weldeselassie

et al. 2023

Preprint

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Background: Early onset of type 2 diabetes and cardiovascular disease are common complications for women diagnosed with gestational diabetes. About half of the women with gestational diabetes develop postpartum prediabetes within 10 years of the index pregnancy. These women also have double the risk of developing cardiovascular disease than women without a history of gestational diabetes. Currently, there is no accurate way of knowing which women with gestational diabetes are likely to develop postpartum prediabetes. This study aims to predict the risk of postpartum prediabetes in women diagnosed with gestational diabetes. Methods: We build a sparse logistic regression-based machine learning model to learn key variables significant for the prediction of postpartum prediabetes, from antenatal data with maternal anthropometric and biochemical variables as well as neonatal characteristics of 607 UK women diagnosed with gestational diabetes. We evaluate the performance of the proposed model in addition to other more advanced machine learning methods using established metrics such as the area under the receiver operating characteristic curve and specificity for pre-determined values of sensitivity. We use K-L divergence and information graphs to evaluate and compare different thresholds of classification for targeted screening options in resource-constrained settings. We also perform a decision curve analysis to study the net standardized benefit of our model compared to the universal screening approach. Results: Strikingly, our sparse logistic regression approach selects only two variables as relevant but gives an area under the receiver operating characteristic curve of 0.72, outperforming all other methods. It can identify postpartum prediabetes in women with gestational diabetes using the Rule-in test with 92\% specificity at an optimal probability threshold of 0.381 and using the Rule-out test with 92\% sensitivity at an optimal probability threshold of 0.140. Conclusion: We propose a simple logistic regression model, which needs only the antenatal fasting glucose at OGTT and HbA1c soon after the diagnosis of GDM, to predict, with remarkable accuracy, the probability of postpartum prediabetes in women with gestational diabetes. We envision this to be a practical solution, which coupled with a targeted follow-up of high-risk women, could yield better cardiometabolic outcomes in women with a history of GDM.

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Risk factors for abnormal postpartum glucose outcome in women with gestational diabetes mellitus diagnosed by modified The International Association of the Diabetes and Pregnancy Study Groups criteria

Cited by 13 publications

References 25 publications

Analysis of risk factors of neonatal hypoglycemia and its correlation with blood glucose control of gestational diabetes mellitus: A retrospective study

Analysis of risk factors of neonatal hypoglycemia and its correlation with blood glucose control of gestational diabetes mellitus: A retrospective study

Postpartum Metabolic Outcomes and Related Factors in Women with Gestational Diabetes Mellitus History

Machine learning prediction of early postpartum prediabetes in women with gestational diabetes mellitus

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