Predictors of postpartum glucose intolerance in women with gestational diabetes mellitus: a prospective cohort study in Ethiopia based on the updated diagnostic criteria

Fasting glucose levels at diagnosis and delivery are associated with postpartum glucose abnormalities in GDM women

Women with a history of gestational diabetes mellitus (GDM) significantly increase the risk of developing type 2 diabetes later in life. Although the increased glucose levels typically return to normal range after delivery for most GDM women, a significant proportion of GDM women develop impaired glucose tolerance or overt diabetes after delivery. Several factors associated with postpartum glucose abnormalities have been identified, yet the link between fasting glucose levels at diagnosis of GDM and postpartum glucose abnormalities remains unclear. In this retrospective study with 866 GDM women, we found that 12.5% presented with abnormal postpartum fasting glucose levels (prediabetes). Among those with postpartum fasting glucose abnormalities (n = 109), 63 (57%) women had abnormal fasting glucose levels at diagnosis, indicating an odds ratio of 1.662 (95% CI: 1.12, 2.479, p < 0.001) for these GDM women developing postpartum fasting glucose abnormalities, compared to those GDM women with normal postpartum fasting glucose levels. Additionally, of GDM women with abnormal postpartum glucose levels (n = 109),70 (64%) presented with abnormal fasting glucose levels one day before delivery. The odds ratio for these GDM women presenting with abnormal postpartum fasting glucose levels was 3.751 (95% CI: 2.462, 5.664, p < 0.001) compared to those GDM women with normal postpartum fasting glucose levels. Furthermore, GDM women with additional insulin treatment or delivered an LGA infant significantly increased the risk of developing postpartum fasting glucose abnormalities. Our findings suggest that abnormal fasting glucose levels at diagnosis or shortly before delivery could be a predictive indicator for postpartum glucose abnormalities in GDM women.

Metabolic profiling identifies potential biomarkers associated with progression from gestational diabetes mellitus to prediabetes postpartum

The current study aims to identify potential metabolic biomarkers that predict the progression to prediabetes in women with a history of gestational diabetes mellitus (GDM). We constructed a prediabetes group ( n = 42) and a control group ( n = 40) based on a2-hour 75 g oral glucose tolerance test for women with a history of GDM from six weeks to six months postpartum, and collected their clinical data and biochemical test results. We performed the plasma metabolomics analysis of the subjects at the fasting and 2-hour post-load time points by using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS). We found that the prediabetes group was older and had higher 2-hour post-load glucose levels during pregnancy than the control group. The metabolomic analysis identified 164 differential metabolites between the groups. Compared with the control group, 15 metabolites in the prediabetes group exhibited consistent change trends at both time points, including three increased and 12 decreased metabolites. By building a prediction model of the progression from GDM to prediabetes, we found a combination of three clinical markers yielded an area under thecurve (AUC) of 0.71 (95% confidence interval [CI], 0.60-0.82). We also assessed the discriminative power of the panel of 15 metabolites for distinguishing between postpartum prediabetes and normal glucose tolerance of the subjects at the fasting (AUC, 0.98; 95% CI, 0.94-1.00) and 2-hour post-load (AUC, 0.99; 95% CI, 0.97-1.00) time points. The metabolic pathway analysis indicated that energy metabolism and branched-chain amino acids played a role in the development of prediabetes in women with a history of GDM during early postpartum. In conclusion, this study identified potential metabolic biomarkers and pathways associated with the progression from GDM to prediabetes in the early postpartum period. A panel of 15 metabolites showed promising discriminative power for distinguishing between postpartum prediabetes and normal glucose tolerance. These findings provide insights into the underlying pathophysiology of this transition and suggest the feasibility of developing a metabolic profiling test for the early identification of women at high risk of prediabetes following GDM.

Risk prediction models for postpartum glucose intolerance in women with a history of gestational diabetes mellitus: a scoping review

Objective

The objective of this scoping review was to investigate the effectiveness and limitations of risk prediction models for postpartum glucose intolerance in women with gestational diabetes mellitus (GDM). The aim was to provide valuable insights for healthcare professionals in the development of robust risk prediction models.

Methods

A comprehensive literature search was conducted across multiple databases, including PubMed, EBSCO, Web of Science Core Collection, Ovid Full-Text Medical Journal Database, ProQuest, Elsevier ClinicalKey, China National Knowledge Infrastructure, China Biology Medicine, and WanFang Database, spanning from January 1990 to July 2023. To assess the quality of the included models, the Predictive Model Risk of Bias Assessment Tool (PROBAST) was employed.

Results

Fourteen relevant studies were identified and included in the final review, all focusing on model development. The discrimination ability of the included models ranged from 0.725 to 0.940, indicating satisfactory prediction accuracy. However, a notable limitation was that nine of these models (64.3%) did not provide clear guidelines on the selection of potential predictors. Furthermore, only six models (42.86%) underwent internal validation, with none undergoing external validation. A high risk of bias was observed across the included models. Logistic regression, Cox regression, and machine learning were the primary methods employed in the construction of these models.

Conclusion

The risk prediction models included in this review demonstrated favorable prediction accuracy. However, due to variations in construction methodologies, direct comparison of their performance is challenging. These models exhibited certain shortcomings, such as inadequate handling of missing data and a lack of internal and external validation, resulting in a high risk of bias. Therefore, it is recommended that these models be updated and externally validated. The development of prospective, multi-center studies is encouraged to construct predictive models with low risk of bias and high clinical applicability, ultimately guiding evidence-based clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01330-1.

Risk factors associated with early postpartum glucose intolerance in women with a history of gestational diabetes mellitus: a systematic review and meta-analysis

PURPOSE

This meta-analysis was aimed at exploring the incidence and risk factors of glucose intolerance in women with gestational diabetes mellitus (GDM) at 6-12 weeks postpartum to inform the development of preventive strategies.

METHOD

We searched Pubmed, Embase, Web of Science, the Cochrane Library, Ovid, China Knowledge Resource Integrated Database (CNKI), Wanfang Database and China Biology Medicine Database for entries between January 1990 and September 2022. The search terms included gestational diabetes mellitus, postpartum, glucose intolerance and type 2 diabetes. The meta-analysis was conducted using Stata 14.0.

RESULT

We included 37 studies, with 21 and 16 having low and medium risk of bias, respectively. The incidence of glucose intolerance in women with GDM 6-12 weeks postpartum was 27% (95% CI: 0.22-0.33). The following risk factors for GDM 6-12 weeks postpartum were identified: insulin use during pregnancy (OR = 3.23; 95% CI: 2.35-4.44), family history of diabetes (OR = 2.94; 95% CI: 1.98-4.33), abnormal fasting glucose levels at 24-28 weeks of gestation (OR = 1.15; 95% CI: 1.07-1.25), high pre-pregnancy BMI (OR = 1.63; 95% CI: 1.23-2.15), abnormal triglyceride levels during 28-40 weeks of gestation (OR = 2.18; 95% CI: 1.18-4.03), abnormal HbA1c levels at 28-40 weeks of gestation (OR = 6.62; 95% CI: 4.71-9.30), history of previous GDM (OR = 2.11; 95% CI: 1.27-3.49), and high 1-h glucose levels at 24-28 weeks of gestation (OR = 1.16; 95% CI:1.06-1.28).

CONCLUSION

The incidence of glucose intolerance in GDM patients at 6-12 weeks postpartum was high. To prevent early postpartum glucose intolerance, healthcare providers should develop individualized interventions for GDM patients, depending on existing risk factors.

Prediction of postpartum prediabetes by machine learning methods in women with gestational diabetes mellitus

Early onset of type 2 diabetes and cardiovascular disease are common complications for women diagnosed with gestational diabetes. Prediabetes refers to a condition in which blood glucose levels are higher than normal, but not yet high enough to be diagnosed as type 2 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. Our sparse logistic regression approach selects only two variables - antenatal fasting glucose at OGTT and HbA1c soon after the diagnosis of GDM - as relevant, but gives an area under the receiver operating characteristic curve of 0.72, outperforming all other methods. 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.

Models Predicting Postpartum Glucose Intolerance Among Women with a History of Gestational Diabetes Mellitus: a Systematic Review

PURPOSE OF REVIEW

Despite the crucial role that prediction models play in guiding early risk stratification and timely intervention to prevent type 2 diabetes after gestational diabetes mellitus (GDM), their use is not widespread in clinical practice. The purpose of this review is to examine the methodological characteristics and quality of existing prognostic models predicting postpartum glucose intolerance following GDM.

RECENT FINDINGS

A systematic review was conducted on relevant risk prediction models, resulting in 15 eligible publications from research groups in various countries. Our review found that traditional statistical models were more common than machine learning models, and only two were assessed to have a low risk of bias. Seven were internally validated, but none were externally validated. Model discrimination and calibration were done in 13 and four studies, respectively. Various predictors were identified, including body mass index, fasting glucose concentration during pregnancy, maternal age, family history of diabetes, biochemical variables, oral glucose tolerance test, use of insulin in pregnancy, postnatal fasting glucose level, genetic risk factors, hemoglobin A1c, and weight. The existing prognostic models for glucose intolerance following GDM have various methodological shortcomings, with only a few models being assessed to have low risk of bias and validated internally. Future research should prioritize the development of robust, high-quality risk prediction models that follow appropriate guidelines, in order to advance this area and improve early risk stratification and intervention for glucose intolerance and type 2 diabetes among women who have had GDM.

Predictors of postpartum glucose metabolism disorders in women with gestational diabetes mellitus

BACKGROUND AND AIMS

Postpartum glucose metabolism disorders are a common problem in women with gestational diabetes mellitus (GDM). They are often underdiagnosed since many patients do not attend the postpartum screening. This study aims to assess predictors of postpartum glucose metabolism disorders and type 2 diabetes mellitus (T2DM) after GDM.

MATERIAL AND METHODS

Retrospective study in women with GMD who underwent postpartum screening for glucose metabolism disorders (n = 2688). Logistic regression was used in the statistical analysis.

RESULTS

24.6% of women had postpartum glucose metabolism disorder. In multivariate analysis, pre-pregnancy body mass index (BMI) 25-30 kg/m² (OR 1.46, 95%CI 1.05 to 2.02) or BMI ≥30 kg/m² (OR 2.62, 95%CI 1.72 to 3.96), diagnosis of GDM before 20 weeks of pregnancy (OR 2.33, 95%CI 1.57 to 3.46), fasting plasma glucose after diagnosis of GDM ≥90 mg/dl (OR 2.12, 95%CI 1.50 to 2.98), postprandial glucose ≥100 mg/dl (OR 1.47, 95%CI 1.09 to 2.99), and HbA1c in the third trimester of pregnancy ≥5.3% (2.04, 95%CI, 1.52 to 2.75) were independent predictors for any postpartum glucose metabolism disorder.

CONCLUSION

postpartum screening for T2DM should be performed in all women with GDM, and it is especially important not to lose follow-up in those with one or more predictive factors.

Incidence and risk factors of gestational diabetes mellitus in Goba town, Southeast Ethiopia: a prospective cohort study

OBJECTIVE

Gestational diabetes mellitus (GDM) is becoming a public health concern in low/middle-income countries, and is known to cause severe morbidity and mortality for mothers and newborns. However, evidence reported for the incidence and risk factors of GDM is scant in Ethiopia. We aimed to assess the incidence of, and risk factors for, GDM in Goba town, Southeast Ethiopia.

DESIGN

Prospective cohort study.

SETTING

Goba town, Southeast Ethiopia.

PARTICIPANTS

Four hundred eighty pregnant women on antenatal care follow-up from 30 April to 30 September 2021.

PRIMARY AND SECONDARY OUTCOMES

Incidence and risk factors of GDM using fasting capillary blood glucose. Log-binomial model was used to identify the risk factors of GDM. Adjusted relative risk (aRR), along with 95% CIs, were calculated to estimate the strength of associations.

RESULTS

The cumulative incidence rate of GDM in this study was 15.7% (95% CI: 12.3% to 19.2%). Being unemployed (aRR=2.73; 95% CI: 1.36 to 5.47), having a family history of diabetes mellitus (DM) (3.01; 2.09 to 4.35), low physical activity (2.43; 1.11 to 5.32), inadequate dietary diversity (1.48; 1.29 to 1.92), anaemia (2.51; 1.32 to 3.54) and antenatal depression (4.95; 3.35 to 7.31) were significantly associated with GDM.

CONCLUSION

The cumulative incidence of GDM was relatively high among the study participants. Having antenatal depression symptoms, low physical activity, inadequate dietary diversity, being unemployed, anaemia and a family history of DM were significant risk factors for GDM.

Emerging and Public Health Challenges Existing in Gestational Diabetes Mellitus and Diabetes in Pregnancy

We review the evidence available worldwide on the various challenges in the screening, management, prevention of gestational diabetes mellitus and diabetes in pregnancy. The use of multiple screening and diagnostic tests prescribed by numerous guidelines is challenging for practitioners. Also, sociocultural, demographic and economic challenges affect the prevention and care. Life-course perspectives need to be adopted, as well as an integrated approach in public health care is essential. Tackling these challenges at each phase of life-course, with development and adherence to the country-specific guidelines by practitioners can decrease the burden of gestational diabetes mellitus and diabetes in pregnancy.