Improvement of selective screening strategy for gestational diabetes through a more accurate definition of high-risk groups

Perceptions of Chinese women with a history of gestational diabetes regarding health behaviors and related factors: a directed qualitative content analysis

BACKGROUND

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders during pregnancy and is associated with adverse outcomes in both mothers and their children. After delivery, women who experience GDM are also at higher risk of both subsequent GDM and type 2 diabetes mellitus (T2DM) than those who do not. Therefore, healthcare providers and public health practitioners need to develop targeted and effective interventions for GDM. In this study, we aimed to explore the perceptions regarding health behaviors and related factors during the inter-pregnancy period among Chinese women with a history of GDM through the lens of the theory of planned behavior (TPB).

METHODS

Between December 2021 and September 2022, 16 pregnant Chinese women with a history of GDM were purposively recruited from a tertiary maternity hospital in Shanghai for face-to-face semi-structured interviews. They were asked questions regarding their health behaviors and related factors. The transcribed data were analyzed using a directed qualitative content analysis method based on the theory of TPB.

RESULTS

The health-related behaviors of the women varied substantially. We identified five domains that influenced women's behaviors according to TPB constructs and based on the data collected: behavioral attitude (perceived benefits of healthy behaviors and the relationship between experience and attitude towards the oral glucose tolerance testing); subjective norms (influences of significant others and traditional cultural beliefs); perceived behavior control (knowledge of the disease, multiple-role conflict, the impact of COVID-19, an unfriendly external environment and difficulty adhering to healthy diets), incentive mechanisms (self-reward and external incentives); preferences of professional and institutional support (making full use of social media platform and providing continuous health management).

CONCLUSIONS

The health-related behaviors of women with a history of GDM were found to be affected by multiple factors. Healthcare professionals are recommended to provide women with sufficient information regarding the disease and to take advantage of the power of the family and other social support networks to improve women's subjective norms and to promote the adoption of a healthy lifestyle.

Development of machine learning models to predict gestational diabetes risk in the first half of pregnancy

BACKGROUND

Early prediction of Gestational Diabetes Mellitus (GDM) risk is of particular importance as it may enable more efficacious interventions and reduce cumulative injury to mother and fetus. The aim of this study is to develop machine learning (ML) models, for the early prediction of GDM using widely available variables, facilitating early intervention, and making possible to apply the prediction models in places where there is no access to more complex examinations.

METHODS

The dataset used in this study includes registries from 1,611 pregnancies. Twelve different ML models and their hyperparameters were optimized to achieve early and high prediction performance of GDM. A data augmentation method was used in training to improve prediction results. Three methods were used to select the most relevant variables for GDM prediction. After training, the models ranked with the highest Area under the Receiver Operating Characteristic Curve (AUCROC), were assessed on the validation set. Models with the best results were assessed in the test set as a measure of generalization performance.

RESULTS

Our method allows identifying many possible models for various levels of sensitivity and specificity. Four models achieved a high sensitivity of 0.82, a specificity in the range 0.72-0.74, accuracy between 0.73-0.75, and AUCROC of 0.81. These models required between 7 and 12 input variables. Another possible choice could be a model with sensitivity of 0.89 that requires just 5 variables reaching an accuracy of 0.65, a specificity of 0.62, and AUCROC of 0.82.

CONCLUSIONS

The principal findings of our study are: Early prediction of GDM within early stages of pregnancy using regular examinations/exams; the development and optimization of twelve different ML models and their hyperparameters to achieve the highest prediction performance; a novel data augmentation method is proposed to allow reaching excellent GDM prediction results with various models.

Clinical First-Trimester Prediction Models for Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis

BACKGROUND

Gestational diabetes mellitus (GDM) is a common pregnancy complication that negatively impacts the health of both the mother and child. Early prediction of the risk of GDM may permit prompt and effective interventions. This systematic review and meta-analysis aimed to summarize the study characteristics, methodological quality, and model performance of first-trimester prediction model studies for GDM.

METHODS

Five electronic databases, one clinical trial register, and gray literature were searched from the inception date to March 19, 2022. Studies developing or validating a first-trimester prediction model for GDM were included. Two reviewers independently extracted data according to an established checklist and assessed the risk of bias by the Prediction Model Risk of Bias Assessment Tool (PROBAST). We used a random-effects model to perform a quantitative meta-analysis of the predictive power of models that were externally validated at least three times.

RESULTS

We identified 43 model development studies, six model development and external validation studies, and five external validation-only studies. Body mass index, maternal age, and fasting plasma glucose were the most commonly included predictors across all models. Multiple estimates of performance measures were available for eight of the models. Summary estimates range from 0.68 to 0.78 (I² ranged from 0% to 97%).

CONCLUSION

Most studies were assessed as having a high overall risk of bias. Only eight prediction models for GDM have been externally validated at least three times. Future research needs to focus on updating and externally validating existing models.

Myo-inositol supplementation for the prevention of gestational diabetes: A meta-analysis of randomized controlled trials

INTRODUCTION

It is elusive to use myo-inositol supplementation to prevent gestational diabetes, and this meta-analysis aims to study the efficacy of myo-inositol supplementation for the prevention of gestational diabetes.

METHODS

Several databases including PubMed, EMbase, Web of science, EBSCO, and Cochrane library databases were systemically searched from inception to October 2021, and we included the randomized controlled trials (RCTs) assessing the effect of myo-inositol supplementation on the incidence of gestational diabetes.

RESULTS

Seven eligible RCTs were included in this meta-analysis. Compared with control group in pregnant women, myo-inositol supplementation could lead to remarkably reduced incidence of gestational diabetes (OR = 0.32; 95% CI = 0.15 to 0.72; P = 0.005), reduced 2-h glucose OGTT (MD = -5.29; 95% CI = -10.24 to -0.34; P = 0.04), increased gestational age at birth (MD = 0.96; 95% CI = -1.67 to 3.87; P = 0.005) and decreased incidence of preterm delivery (OR = 0.35; 95% CI = 0.17 to 0.70; P = 0.003), but exhibited no obvious influence on birth weight (MD = -22.82; 95% CI = -121.95 to 76.32; P = 0.65).

CONCLUSIONS

Myo-inositol supplementation is recommended to prevent gestational diabetes with caution due to some heterogeneity.

Fasting plasma glucose level to guide the need for an OGTT to screen for gestational diabetes mellitus

AIMS

To determine the fasting plasma glucose (FPG) level at which an oral glucose tolerance test (OGTT) could be avoided to screen for gestational diabetes (GDM) and to evaluate the characteristics of women across this FPG threshold.

METHODS

A multi-centric prospective cohort study with 1843 women receiving universal screening for GDM with a 75 g OGTT.

RESULTS

In the total population, GDM prevalence was 12.5% (231). A FPG < 78 mg/dL was the cut-off with best trade-off to limit the number of missed GDM cases [44 (19.0%)] with a negative predictive value of 97.3% (95% CI 96.5-98.0) for GDM, while avoiding 52.2% OGTTs. Compared to GDM with FPG ≥ 78 mg/dL [187 (81.0%)], GDM women with FPG < 78 mg/dL had a significantly lower BMI (27.1 ± 4.5 vs. 29.6 ± 5.2 kg/m², p = 0.003), less insulin resistance [Matsuda: 0.4 (0.4-0.7) vs. 0.3 (0.2-0.5), p < 0.001] and better β-cell function [ISSI-2: 0.13 (0.08-0.25) vs. 0.09 (0.04-0.15), p = 0.004]. Compared to NGT women (1612) with FPG ≥ 78 mg/dL [846 (52.5%)], NGT with FPG < 78 mg/dL [766 (47.5%)] had a significantly lower BMI (26.0 ± 3.9 vs. 27.8 ± 4.7 kg/m², p < 0.001), less insulin resistance [Matsuda: 0.7 (0.5-0.9) vs. 0.5 (0.4-0.7), p < 0.001], better β-cell function [ISSI-2: 0.17 (0.10-0.30) vs. 0.12 (0.07-0.21), p < 0.001], and less often large-for-gestational age infants [9.2 (70) vs. 16.2% (136), p < 0.001].

CONCLUSIONS

FPG < 78 mg/dL can be used to limit the number of OGTTs when screening for GDM. Women with FPG < 78 mg/dL had a better metabolic profile and in NGT women also less fetal overgrowth.

The Analytical Reliability of the Oral Glucose Tolerance Test for the Diagnosis of Gestational Diabetes: An Observational, Retrospective Study in a Caucasian Population

The Oral Glucose Tolerance Test (OGTT) is currently the gold standard reference test for the diagnosis of gestational diabetes mellitus (GDM). Several critical issues related to analytical variables have challenged its reproducibility and accuracy. This study aimed to assess the analytical reliability of the OGTT for the diagnosis of GDM. A total of 1015 pregnant women underwent a 2 h 75 g OGTT between 24 and 28 weeks of gestation. As recommended by National Academy of Clinical Biochemistry, we considered the total maximum allowable error for glucose plasma measurement as <6.9%. Assuming the possibility of analytical errors within this range for each OGTT glucose plasma value, different scenarios of GDM occurrence were estimated. GDM prevalence with standard criteria was 12.2%, and no hypothetical scenarios have shown a comparable GDM prevalence. Considering all the three OGTT values estimated at the lowest or the highest allowed value according to total maximum allowable error, GDM prevalence significantly varied (4.5% and 25.3%, respectively). Our results indicate that the OGTT is not completely accurate for GDM diagnosis.

Gestational Diabetes Mellitus in Europe: A Systematic Review and Meta-Analysis of Prevalence Studies

Background

Gestational Diabetes Mellitus (GDM) is defined as the type of hyperglycemia diagnosed for the first-time during pregnancy, presenting with intermediate glucose levels between normal levels for pregnancy and glucose levels diagnostic of diabetes in the non-pregnant state. We aimed to systematically review and meta-analyze studies of prevalence of GDM in European countries at regional and sub-regional levels, according to age, trimester, body weight, and GDM diagnostic criteria.

Methods

Systematic search was conducted in five databases to retrieve studies from 2014 to 2019 reporting the prevalence of GDM in Europe. Two authors have independently screened titles and abstracts and full text according to eligibility using Covidence software. A random-effects model was used to quantify weighted GDM prevalence estimates. The National Heart, Lung, and Blood Institute criteria was used to assess the risk of bias.

Results

From the searched databases, 133 research reports were deemed eligible and included in the meta-analysis. The research reports yielded 254 GDM-prevalence studies that tested 15,572,847 pregnant women between 2014 and 2019. The 133 research reports were from 24 countries in Northern Europe (44.4%), Southern Europe (27.1%), Western Europe (24.1%), and Eastern Europe (4.5%). The overall weighted GDM prevalence in the 24 European countries was estimated at 10.9% (95% CI: 10.0-11.8, I2 : 100%). The weighted GDM prevalence was highest in the Eastern Europe (31.5%, 95% CI: 19.8-44.6, I2 : 98.9%), followed by in Southern Europe (12.3%, 95% CI: 10.9-13.9, I2 : 99.6%), Western Europe (10.7%, 95% CI: 9.5-12.0, I2 : 99.9%), and Northern Europe (8.9%, 95% CI: 7.9-10.0, I2 : 100). GDM prevalence was 2.14-fold increased in pregnant women with maternal age ≥30 years (versus 15-29 years old), 1.47-fold if the diagnosis was made in the third trimester (versus second trimester), and 6.79- fold in obese and 2.29-fold in overweight women (versus normal weight).

Conclusions

In Europe, GDM is significant in pregnant women, around 11%, with the highest prevalence in pregnant women of Eastern European countries (31.5%). Findings have implications to guide vigilant public health awareness campaigns about the risk factors associated with developing GDM.

Systematic Review Registration

PROSPERO [https://www.crd.york.ac.uk/PROSPERO/], identifier CRD42020161857.

Performance of early risk assessment tools to predict the later development of gestational diabetes

BACKGROUND

Several prognostic models for gestational diabetes mellitus (GDM) are provided in the literature; however, their clinical significance has not been thoroughly evaluated, especially with regard to application at early gestation and in accordance with the most recent diagnostic criteria. This external validation study aimed to assess the predictive accuracy of published risk estimation models for the later development of GDM at early pregnancy.

METHODS

In this cohort study, we prospectively included 1132 pregnant women. Risk evaluation was performed before 16 + 0 weeks of gestation including a routine laboratory examination. Study participants were followed-up until delivery to assess GDM status according to the IADPSG 2010 diagnostic criteria. Fifteen clinical prediction models were calculated according to the published literature.

RESULTS

Gestational diabetes mellitus was diagnosed in 239 women, that is 21.1% of the study participants. Discrimination was assessed by the area under the ROC curve and ranged between 60.7% and 76.9%, corresponding to an acceptable accuracy. With some exceptions, calibration performance was poor as most models were developed based on older diagnostic criteria with lower prevalence and therefore tended to underestimate the risk of GDM. The highest variable importance scores were observed for history of GDM and routine laboratory parameters.

CONCLUSIONS

Most prediction models showed acceptable accuracy in terms of discrimination but lacked in calibration, which was strongly dependent on study settings. Simple biochemical variables such as fasting glucose, HbA1c and triglycerides can improve risk prediction. One model consisting of clinical and laboratory parameters showed satisfactory accuracy and could be used for further investigations.

Identifying women with gestational diabetes based on maternal characteristics: an analysis of four Norwegian prospective studies

Background

There is still no worldwide agreement on the best diagnostic thresholds to define gestational diabetes (GDM) or the optimal approach for identifying women with GDM. Should all pregnant women perform an oral glucose tolerance test (OGTT) or can easily available maternal characteristics, such as age, BMI and ethnicity, indicate which women to test? The aim of this study was to assess the prevalence of GDM by three diagnostic criteria and the predictive accuracy of commonly used risk factors.

Methods

We merged data from four Norwegian cohorts (2002–2013), encompassing 2981 women with complete results from a universally offered OGTT. Prevalences were estimated based on the following diagnostic criteria: ₁₉₉₉WHO (fasting plasma glucose (FPG) ≥7.0 or 2-h glucose ≥7.8 mmol/L), ₂₀₁₃WHO (FPG ≥5.1 or 2-h glucose ≥8.5 mmol/L), and ₂₀₁₇Norwegian (FPG ≥5.3 or 2-h glucose ≥9 mmol/L). Multiple logistic regression models examined associations between GDM and maternal factors. We applied the ₂₀₁₃WHO and ₂₀₁₇Norwegian criteria to evaluate the performance of different thresholds of age and BMI.

Results

The prevalence of GDM was 10.7, 16.9 and 10.3%, applying the ₁₉₉₉WHO, ₂₀₁₃WHO, and the ₂₀₁₇Norwegian criteria, respectively, but was higher for women with non-European background when compared to European women (14.5 vs 10.2%, 37.7 vs 13.8% and 27.0 vs 7.8%). While advancing age and elevated BMI increased the risk of GDM, no risk factors, isolated or in combination, could identify more than 80% of women with GDM by the latter two diagnostic criteria, unless at least 70–80% of women were offered an OGTT. Using the ₂₀₁₇Norwegian criteria, the combination “age≥25 years or BMI≥25 kg/m²” achieved the highest sensitivity (96.5%) with an OGTT required for 93% of European women. The predictive accuracy of risk factors for identifying GDM was even lower for non-European women.

Conclusions

The prevalence of GDM was similar using the ₁₉₉₉WHO and ₂₀₁₇Norwegian criteria, but substantially higher with the ₂₀₁₃WHO criteria, in particular for ethnic non-European women. Using clinical risk factors such as age and BMI is a poor pre-diagnostic screening method, as this approach failed to identify a substantial proportion of women with GDM unless at least 70–80% were tested.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-021-04086-9.

Screening of postpartum diabetes in women with gestational diabetes: high-risk subgroups and areas for improvements-the STRONG observational study

AIMS

To assess the proportion of women with gestational diabetes (GDM) by performing postpartum Oral Glucose Tolerance Test (OGTT) and to identify GDM phenotypes at high-risk of postpartum dysglycemia (PPD).

METHODS

Observational, retrospective, multicenter study involving consecutive GDM women. Recursive partitioning (RECPAM) analysis was used to identify distinct and homogeneous subgroups of women at different PPD risk.

RESULTS

From a sample of 2,736 women, OGTT was performed in 941 (34.4%) women, of whom 217 (23.0%) developed PPD. Insulin-treated women having family history of diabetes represented the subgroup with the highest PPD risk (OR 5.57, 95% CI 3.60-8.63) compared to the reference class (women on diet with pre-pregnancy BMI <  = 28.1 kg/m2). Insulin-treated women without family diabetes history and women on diet with pre-pregnancy BMI > 28.1 kg/m2 showed a two-fold PPD risk. Previous GDM and socioeconomic status represent additional predictors. Fasting more than post-prandial glycemia plays a predictive role, with values of 81-87 mg/dl (4.5-4.8 mmol/l) (lower than the current diagnostic GDM threshold) being associated with PPD risk.

CONCLUSIONS

Increasing compliance to postpartum OGTT to prevent/delay PPD is a priority. Easily available characteristics identify subgroups of women more likely to benefit from preventive strategies. Fasting BG values during pregnancy lower than those usually considered deserve attention.

Protocol for a randomized controlled trial of pre-pregnancy lifestyle intervention to reduce recurrence of gestational diabetes: Gestational Diabetes Prevention/Prevención de la Diabetes Gestacional

BACKGROUND

Gestational diabetes mellitus (GDM) is associated with several maternal complications in pregnancy, including preeclampsia, preterm labor, need for induction of labor, and cesarean delivery as well as increased long-term risks of type 2 diabetes, metabolic syndrome, and cardiovascular disease. Intrauterine exposure to GDM raises the risk for complications in offspring as well, including stillbirth, macrosomia, and birth trauma, and long-term risk of metabolic disease. One of the strongest risk factors for GDM is the occurrence of GDM in a prior pregnancy. Preliminary data from epidemiologic and bariatric surgery studies suggest that reducing body weight before pregnancy can prevent the development of GDM, but no adequately powered trial has tested the effects of a maternal lifestyle intervention before pregnancy to reduce body weight and prevent GDM recurrence.

METHODS

The principal aim of the Gestational Diabetes Prevention/Prevención de la Diabetes Gestacional is to determine whether a lifestyle intervention to reduce body weight before pregnancy can reduce GDM recurrence. This two-site trial targets recruitment of 252 women with overweight and obesity who have previous histories of GDM and who plan to have another pregnancy in the next 1-3 years. Women are randomized within site to a comprehensive pre-pregnancy lifestyle intervention to promote weight loss with ongoing treatment until conception or an educational control group. Participants are assessed preconceptionally (at study entry, after 4 months, and at brief quarterly visits until conception), during pregnancy (at 26 weeks' gestation), and at 6 weeks postpartum. The primary outcome is GDM recurrence, and secondary outcomes include fasting glucose, biomarkers of cardiometabolic disease, prenatal and perinatal complications, and changes over time in weight, diet, physical activity, and psychosocial measures.

DISCUSSION

The Gestational Diabetes Prevention /Prevención de la Diabetes Gestacional is the first randomized controlled trial to evaluate the effects of a lifestyle intervention delivered before pregnancy to prevent GDM recurrence. If found effective, the proposed lifestyle intervention could lay the groundwork for shifting current treatment practices towards the interconception period and provide evidence-based preconception counseling to optimize reproductive outcomes and prevent GDM and associated health risks.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02763150 . Registered on May 5, 2016.

Limiting the Use of Oral Glucose Tolerance Tests to Screen for Hyperglycemia in Pregnancy during Pandemics

We aimed to evaluate each proposal of Australian–New Zealand Societies to limit the number of oral glucose tolerance tests (OGTTs) to diagnose hyperglycemia in pregnancy (HIP) during the coronavirus disease 2019 (COVID-19) pandemic. At our university hospital (2012–2016), we retrospectively applied in 4245 women who had OGTT between 22 and 30 weeks of gestation (reference standard: WHO criteria) the proposals in which OGTT is performed only in high-risk women; in all (Option 1) or high-risk (Option 1-Sel) women with fasting plasma glucose (FPG) 4.7–5.0 mmol/L; in all (Option 2) or high-risk (Option 2-Sel) women without history of HIP and with FPG 4.7–5.0 mmol/L. We also tested FPG measurement alone in all high-risk women. Measuring FPG alone had a sensitivity of 49% (95% confidence interval 45–54) applying universal screening. Option 2 appeared to have the best balance considering the needed OGTT (17.3%), sensitivity (72% (67–76)) and rates of a composite outcome (true negative cases: 10.6%, false positive cases: 24.4%; true positive cases: 19.5%; false negative cases: 10.2%). Consideration of a history of HIP and measuring first FPG can avoid more than 80% of OGTTs and identify women with the highest risk of adverse HIP-related events.

Machine Learning Prediction Models for Gestational Diabetes Mellitus: A meta- analysis (Preprint)

Background

Gestational diabetes mellitus (GDM) is a common endocrine metabolic disease, involving a carbohydrate intolerance of variable severity during pregnancy. The incidence of GDM-related complications and adverse pregnancy outcomes has declined, in part, due to early screening. Machine learning (ML) models are increasingly used to identify risk factors and enable the early prediction of GDM.

Objective

The aim of this study was to perform a meta-analysis and comparison of published prognostic models for predicting the risk of GDM and identify predictors applicable to the models.

Methods

Four reliable electronic databases were searched for studies that developed ML prediction models for GDM in the general population instead of among high-risk groups only. The novel Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias of the ML models. The Meta-DiSc software program (version 1.4) was used to perform the meta-analysis and determination of heterogeneity. To limit the influence of heterogeneity, we also performed sensitivity analyses, a meta-regression, and subgroup analysis.

Results

A total of 25 studies that included women older than 18 years without a history of vital disease were analyzed. The pooled area under the receiver operating characteristic curve (AUROC) for ML models predicting GDM was 0.8492; the pooled sensitivity was 0.69 (95% CI 0.68-0.69; P<.001; I²=99.6%) and the pooled specificity was 0.75 (95% CI 0.75-0.75; P<.001; I²=100%). As one of the most commonly employed ML methods, logistic regression achieved an overall pooled AUROC of 0.8151, while non–logistic regression models performed better, with an overall pooled AUROC of 0.8891. Additionally, maternal age, family history of diabetes, BMI, and fasting blood glucose were the four most commonly used features of models established by the various feature selection methods.

Conclusions

Compared to current screening strategies, ML methods are attractive for predicting GDM. To expand their use, the importance of quality assessments and unified diagnostic criteria should be further emphasized.

Myo-inositol supplementation to prevent gestational diabetes in overweight non-obese women: bioelectrical impedance analysis, metabolic aspects, obstetric and neonatal outcomes - a randomized and open-label, placebo-controlled clinical trial

This study aims to evaluate the effects of myo-inositol supplementation on gestational diabetes mellitus (GDM) rates and body water distribution in overweight non-obese women. 223 overweight non-obese women pregnant were randomly assigned to the treatment group (2 g of myo-inositol plus 200 µg of folic acid) or to the placebo one (200 µg of folic acid). The treatment lasted until three weeks after delivery. A tetrapolar impedance analyser was used to study body composition. The incidence of GDM was significantly reduced in the myo-inositol group compared with the placebo group. There was a significant increase in TBW, ECW and ICW values in the placebo group compared to the myo-inositol group. We have recorded a significant reduction in the overall incidence of pregnancy-induced hypertension in the myo-inositol group compared with the placebo group. Our results demonstrate the effectiveness of myo-inositol supplementation in preventing GDM in overweight non-obese pregnant women.

The Oral Glucose Tolerance Test-Is It Time for a Change?-A Literature Review with an Emphasis on Pregnancy

Globally, gestational diabetes (GDM) is increasing at an alarming rate. This increase is linked to the rise in obesity rates among women of reproductive age. GDM poses a major global health problem due to the related micro- and macro-vascular complications of subsequent Type 2 diabetes and the impact on the future health of generations through the long-term impact of GDM on both mothers and their infants. Therefore, correctly identifying subjects as having GDM is of utmost importance. The oral glucose tolerance test (OGTT) has been the mainstay for diagnosing gestational diabetes for decades. However, this test is deeply flawed. In this review, we explore a history of the OGTT, its reproducibility and the many factors that can impact its results with an emphasis on pregnancy.

Prognosis associated with initial care of increased fasting glucose in early pregnancy: A retrospective study

AIM

To evaluate whether the initial care of women with fasting plasma glucose (FPG) levels at 5.1-6.9mmol/L before 22 weeks of gestation (WG), termed 'early fasting hyperglycaemia', is associated with fewer adverse outcomes than no initial care.

METHODS

A total of 523 women with early fasting hyperglycaemia were retrospectively selected in our department (2012-2016) and separated into two groups: (i) those who received immediate care (n=255); and (ii) those who did not (n=268), but had an oral glucose tolerance test (OGTT) at or after 22 WG, with subsequent standard care if hyperglycaemia (by WHO criteria) was present. The number of cases of large-for-gestational age (LGA) infants, shoulder dystocia and preeclampsia with initial care of early fasting hyperglycaemia were compared after propensity score modelling and accounting for covariates.

RESULTS

Of the 268 women with no initial care, 134 had hyperglycaemia after 22 WG and then received care. Women who received initial care vs those who did not were more likely to be insulin-treated during pregnancy (58.0% vs 20.9%, respectively; P<0.00001), gained less gestational weight (8.6±5.4kg vs 10.8±6.1kg, respectively; P<0.00001), had a lower rate of preeclampsia [1.2% vs 2.6%, respectively; adjusted odds ratio (aOR): 0.247 (0.082-0.759), P=0.01], and similar rates of LGA infants (12.2% vs 11.9%, respectively) and shoulder dystocia (1.6% vs 1.5%, respectively). When initial FPG levels were ≥5.5mmol/L (prespecified group, n=137), there was a lower rate of LGA infants [6.7% vs 16.1%, respectively; aOR: 0.332 (0.122-0.898); P=0.03].

CONCLUSION

Treating women with early fasting hyperglycaemia, especially when FPG is ≥5.5mmol/L, may improve pregnancy outcomes, although this now needs to be confirmed by randomized clinical trials.

Initially untreated fasting hyperglycaemia in early pregnancy: prognosis according to occurrence of gestational diabetes mellitus after 22 weeks' gestation: a case-control study

AIMS

To evaluate the percentage of women with untreated fasting hyperglycaemia in early pregnancy who develop gestational diabetes mellitus after 22 weeks' gestation, the determinants of gestational diabetes development in such women and the prognosis of early fasting hyperglycaemia according to whether the women go on to develop gestational diabetes.

METHODS

From a large cohort of women who delivered in our hospital between 2012 and 2016, we retrospectively selected all those who had untreated early fasting hyperglycaemia and separated them into a 'gestational diabetes' and a 'no-gestational diabetes' group according to oral glucose tolerance test results after 22 weeks' gestation. We compared the incidence of a predefined composite outcome (preeclampsia or large-for-gestational-age infant or shoulder dystocia or neonatal hypoglycaemia) in both groups.

RESULTS

A total of 268 women (mean fasting plasma glucose 5.3 ± 0.3 mmol/l at a mean ± sd of 10.2 ± 4.2 weeks' gestation) were included. Gestational diabetes developed in 134 women and was independently associated with early fasting plasma glucose ≥ 5.5 mmol/l [odds ratio 3.16 (95% CI 1.57, 6.33)], age ≥ 30 years [odds ratio 2.78 (95% CI 1.46, 5.31)], preconception obesity [odds ratio 2.12 (95% CI 1.11, 4.02)], family history of diabetes [odds ratio 1.87 (95% CI 1.00, 3.50)] and current employment [odds ratio 0.46 (95% CI 0.26, 0.83)]. Despite treatment, gestational diabetes induced a significant increase in the composite outcome as compared to no gestational diabetes (odds ratio 2.16 [95% CI 1.08, 4.34]). The association disappeared after adjustment for risk factors.

CONCLUSIONS

Only half of the women with early fasting hyperglycaemia and no specific care subsequently developed gestational diabetes, and these women had a poor prognosis despite gestational diabetes treatment. Poor prognosis was mostly attributable to risk factors. Our results suggest that only women with certain risk factors should be screened for early fasting hyperglycaemia.

Guidelines for the screening and diagnosis of gestational diabetes in Italy from 2010 to 2019: critical issues and the potential for improvement

AIMS

In 2010, Italian health professionals rapidly implemented the one-step screening for gestational diabetes mellitus (GDM) based on a 75 g OGTT, to comply with the diagnostic criteria proposed by the International Association of Diabetes and Pregnancy Study Groups (IADPSG). The change was promoted by the two main Italian scientific societies of diabetology, Associazione Medici Diabetologi (AMD) and Società Italiana di Diabetologia (SID), and it took just a few months for the Istituto Superiore di Sanità, together with several scientific societies, to revise the criteria and include them in the National Guidelines System. Over the last 9 years, the implementation of these guidelines has shown some benefits and some drawbacks.

METHODS

In order to evaluate the critical issues arisen from the implementation of the current Italian guidelines for the diagnosis of GDM, the studies published on this topic have been reviewed. The search was performed using the following keywords: "gestational diabetes" AND "diagnostic criteria" OR screening AND Ital*. The study is an expert opinion paper, based on the relevant scientific literature published between 2010 and 2019. The databases screened for the literature review included PubMed, MEDLINE, and Scopus.

RESULTS

The implementation of the Guidelines for Screening and Diagnosis of GDM in Italy present some strengths and some weaknesses. One of the positive aspects is that high-risk women are required to perform an OGTT early in pregnancy. By contrast, there are several aspects in need of improvement: (1) In spite of the current indications, only a minority of high-risk women perform OGTT early in pregnancy; (2) several low-risk women are screened for GDM; (3) in some low-risk women affected by GDM, the diagnosis might be missed with the application of the current guidelines; (4) there is a lack of homogeneity in the risk assessment data from different regions.

CONCLUSIONS

In order to improve the current Italian GDM guidelines, some practical solutions have been suggested.

The risk stratification of adverse neonatal outcomes in women with gestational diabetes (STRONG) study

AIMS

To assess the risk of adverse neonatal outcomes in women with gestational diabetes (GDM) by identifying subgroups of women at higher risk to recognize the characteristics most associated with an excess of risk.

METHODS

Observational, retrospective, multicenter study involving consecutive women with GDM. To identify distinct and homogeneous subgroups of women at a higher risk, the RECursive Partitioning and AMalgamation (RECPAM) method was used. Overall, 2736 pregnancies complicated by GDM were analyzed. The main outcome measure was the occurrence of adverse neonatal outcomes in pregnancies complicated by GDM.

RESULTS

Among study participants (median age 36.8 years, pre-gestational BMI 24.8 kg/m²), six miscarriages, one neonatal death, but no maternal death was recorded. The occurrence of the cumulative adverse outcome (OR 2.48, 95% CI 1.59-3.87), large for gestational age (OR 3.99, 95% CI 2.40-6.63), fetal malformation (OR 2.66, 95% CI 1.00-7.18), and respiratory distress (OR 4.33, 95% CI 1.33-14.12) was associated with previous macrosomia. Large for gestational age was also associated with obesity (OR 1.46, 95% CI 1.00-2.15). Small for gestational age was associated with first trimester glucose levels (OR 1.96, 95% CI 1.04-3.69). Neonatal hypoglycemia was associated with overweight (OR 1.52, 95% CI 1.02-2.27) and obesity (OR 1.62, 95% CI 1.04-2.51). The RECPAM analysis identified high-risk subgroups mainly characterized by high pre-pregnancy BMI (OR 1.68, 95% CI 1.21-2.33 for obese; OR 1.38 95% CI 1.03-1.87 for overweight).

CONCLUSIONS

A deep investigation on the factors associated with adverse neonatal outcomes requires a risk stratification. In particular, great attention must be paid to the prevention and treatment of obesity.

The identification and treatment of women with hyperglycaemia in pregnancy: an analysis of individual participant data, systematic reviews, meta-analyses and an economic evaluation

BACKGROUND

Gestational diabetes mellitus (GDM) is associated with a higher risk of important adverse outcomes. Practice varies and the best strategy for identifying and treating GDM is unclear.

AIM

To estimate the clinical effectiveness and cost-effectiveness of strategies for identifying and treating women with GDM.

METHODS

We analysed individual participant data (IPD) from birth cohorts and conducted systematic reviews to estimate the association of maternal glucose levels with adverse perinatal outcomes; GDM prevalence; maternal characteristics/risk factors for GDM; and the effectiveness and costs of treatments. The cost-effectiveness of various strategies was estimated using a decision tree model, along with a value of information analysis to assess where future research might be worthwhile. Detailed systematic searches of MEDLINE^® and MEDLINE In-Process & Other Non-Indexed Citations^®, EMBASE, Cumulative Index to Nursing and Allied Health Literature Plus, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment database, NHS Economic Evaluation Database, Maternity and Infant Care database and the Cochrane Methodology Register were undertaken from inception up to October 2014.

RESULTS

We identified 58 studies examining maternal glucose levels and outcome associations. Analyses using IPD alone and the systematic review demonstrated continuous linear associations of fasting and post-load glucose levels with adverse perinatal outcomes, with no clear threshold below which there is no increased risk. Using IPD, we estimated glucose thresholds to identify infants at high risk of being born large for gestational age or with high adiposity; for South Asian (SA) women these thresholds were fasting and post-load glucose levels of 5.2 mmol/l and 7.2 mmol/l, respectively and for white British (WB) women they were 5.4 and 7.5 mmol/l, respectively. Prevalence using IPD and published data varied from 1.2% to 24.2% (depending on criteria and population) and was consistently two to three times higher in SA women than in WB women. Lowering thresholds to identify GDM, particularly in women of SA origin, identifies more women at risk, but increases costs. Maternal characteristics did not accurately identify women with GDM; there was limited evidence that in some populations risk factors may be useful for identifying low-risk women. Dietary modification additional to routine care reduced the risk of most adverse perinatal outcomes. Metformin (Glucophage,^® Teva UK Ltd, Eastbourne, UK) and insulin were more effective than glibenclamide (Aurobindo Pharma - Milpharm Ltd, South Ruislip, Middlesex, UK). For all strategies to identify and treat GDM, the costs exceeded the health benefits. A policy of no screening/testing or treatment offered the maximum expected net monetary benefit (NMB) of £1184 at a cost-effectiveness threshold of £20,000 per quality-adjusted life-year (QALY). The NMB for the three best-performing strategies in each category (screen only, then treat; screen, test, then treat; and test all, then treat) ranged between -£1197 and -£1210. Further research to reduce uncertainty around potential longer-term benefits for the mothers and offspring, find ways of improving the accuracy of identifying women with GDM, and reduce costs of identification and treatment would be worthwhile.

LIMITATIONS

We did not have access to IPD from populations in the UK outside of England. Few observational studies reported longer-term associations, and treatment trials have generally reported only perinatal outcomes.

CONCLUSIONS

Using the national standard cost-effectiveness threshold of £20,000 per QALY it is not cost-effective to routinely identify pregnant women for treatment of hyperglycaemia. Further research to provide evidence on longer-term outcomes, and more cost-effective ways to detect and treat GDM, would be valuable.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42013004608.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

The efficacy of myo-inositol supplementation to prevent gestational diabetes onset: a meta-analysis of randomized controlled trials

INTRODUCTION

The efficacy of myo-inositol supplementation to prevent gestational diabetes onset remains controversial. We conducted a systematic review and meta-analysis to explore the influence of myo-inositol supplementation on the incidence of gestational diabetes.

METHODS

We search PubMed, Embase, Web of science, EBSCO, and Cochrane Library databases through November 2017 for randomized controlled trials (RCTs) assessing the effect of myo-inositol supplementation on gestational diabetes onset. This meta-analysis is performed using the random-effect model.

RESULTS

Five randomized controlled trials (RCTs) are included in the meta-analysis. Compared with control group in pregnant women, myo-inositol supplementation is associated with significantly reduced incidence of gestational diabetes (risk ratio (RR) = 0.43; 95%CI = 0.21-0.89; p = .02), and preterm delivery (RR = 0.36; 95%CI = 0.17-0.73; p = .005), but has no substantial impact on 2-h glucose oral glucose tolerance test (OGTT) (mean difference (MD) = -6.90; 95%CI = -15.07 to 1.27; p = .10), gestational age at birth (MD = 0.74; 95%CI = -1.06 to 2.54; p = .42), birth weight (MD = -5.50; 95%CI = -116.99 to 105.99; p = .92), and macrosomia (RR = 0.65; 95%CI = 0.20-2.11; p = .47).

CONCLUSIONS

Myo-inositol supplementation has some ability to reduce the incidence of gestational diabetes and preterm delivery in pregnant women.

High Fasting Plasma Glucose during Early Pregnancy: A Review about Early Gestational Diabetes Mellitus

Fasting plasma glucose (FPG) is nowadays routinely measured during early pregnancy to detect preexisting diabetes (FPG ≥ 7 mmol/L). This screening has concomitantly led to identify early intermediate hyperglycemia, defined as FPG in the 5.1 to 6.9 mmol/L range, also early gestational diabetes mellitus (eGDM). Early FPG has been associated with poor pregnancy outcomes, but the recommendation by the IADPSG to refer women with eGDM for immediate management is more pragmatic than evidence based. Although eGDM is characterized by insulin resistance and associated with classical risk factors for type 2 diabetes and incident diabetes after delivery, it is not necessarily associated with preexisting prediabetes. FPG ≥ 5.1 mmol/L in early pregnancy is actually poorly predictive of gestational diabetes mellitus diagnosed after 24 weeks of gestation. An alternative threshold should be determined but may vary according to ethnicity, gestational age, and body mass index. Finally, observational data suggest that early management of intermediate hyperglycemia may improve prognosis, through reduced gestational weight gain and potential early introduction of hypoglycemic agents. Considering all these issues, we suggest an algorithm for the management of eGDM based on early FPG levels that would be measured in case of risk factors. Nevertheless, interventional randomized trials are still missing.

Prevalence of gestational diabetes mellitus in Europe: A meta-analysis

AIMS

Estimates of the prevalence of gestational diabetes vary widely. It is important to have a clear understanding of the prevalence of this condition to be able to plan interventions and health care provision. This paper describes a meta-analysis of primary research data reporting the prevalence of gestational diabetes mellitus in the general pregnant population of developed countries in Europe.

METHODS

Four electronic databases were systematically searched in May 2016. English language articles reporting gestational diabetes mellitus prevalence using universal screening in general pregnant population samples from developed countries in Europe were included. All papers identified by the search were screened by one author, and then half screened independently by a second author and half by a third author. Data were extracted by one author. Values for the measures of interest were combined using a random effects model and analysis of the effects of moderator variables was carried out.

RESULTS

A total of 3258 abstracts were screened, with 40 studies included in the review. Overall prevalence of gestational diabetes mellitus was 5.4% (3.8-7.8). Maternal age, year of data collection, country, area of Europe, week of gestation at testing, and diagnostic criteria were found to have a significant univariate effect on GDM prevalence, and area, week of gestation at testing and year of data collection remained statistically significant in multivariate analysis. Quality category was significant in multivariate but not univariate analysis.

CONCLUSIONS

This meta-analysis shows prevalence of GDM that is at the upper end of previous estimates in Europe.

A critical appraisal and potentially new conceptual approach to screening and diagnosis of gestational diabetes

The aim of this article was a critical appraisal of current GDM screening and diagnosis status as well as a presentation of a potentially new approach to this perinatologic and public health problem of increasing clinical significance. Medline, EMBASE and Cochrane databases were searched. Most professional organisations recommend universal screening at 24-28 weeks of gestation, while some of them state that selective screening could also be recommended. Expert opinions regarding GDM diagnosis significantly differ throughout the world. Authors call for an open and broad professional and scientific discussion and suggest a combination of screening and diagnosis procedures in a form of one-step 1-h screening method, creation of regional GDM diagnostic criteria and standardisation of outcome-based randomised control trials. They also advise introduction of a conceptually new approach, where the risk of hyperglycaemia rather than insisting on GDM diagnosis itself should be detected.

Risk factor screening to identify women requiring oral glucose tolerance testing to diagnose gestational diabetes: A systematic review and meta-analysis and analysis of two pregnancy cohorts

BACKGROUND

Easily identifiable risk factors including: obesity and ethnicity at high risk of diabetes are commonly used to indicate which women should be offered the oral glucose tolerance test (OGTT) to diagnose gestational diabetes (GDM). Evidence regarding these risk factors is limited however. We conducted a systematic review (SR) and meta-analysis and individual participant data (IPD) analysis to evaluate the performance of risk factors in identifying women with GDM.

METHODS

We searched MEDLINE, Medline in Process, Embase, Maternity and Infant Care and the Cochrane Central Register of Controlled Trials (CENTRAL) up to August 2016 and conducted additional reference checking. We included observational, cohort, case-control and cross-sectional studies reporting the performance characteristics of risk factors used to identify women at high risk of GDM. We had access to IPD from the Born in Bradford and Atlantic Diabetes in Pregnancy cohorts, all pregnant women in the two cohorts with data on risk factors and OGTT results were included.

RESULTS

Twenty nine published studies with 211,698 women for the SR and a further 14,103 women from two birth cohorts (Born in Bradford and the Atlantic Diabetes in Pregnancy study) for the IPD analysis were included. Six studies assessed the screening performance of guidelines; six examined combinations of risk factors; eight evaluated the number of risk factors and nine examined prediction models or scores. Meta-analysis using data from published studies suggests that irrespective of the method used, risk factors do not identify women with GDM well. Using IPD and combining risk factors to produce the highest sensitivities, results in low specificities (and so higher false positives). Strategies that use the risk factors of age (>25 or >30) and BMI (>25 or 30) perform as well as other strategies with additional risk factors included.

CONCLUSIONS

Risk factor screening methods are poor predictors of which pregnant women will be diagnosed with GDM. A simple approach of offering an OGTT to women 25 years or older and/or with a BMI of 25kg/m2 or more is as good as more complex risk prediction models. Research to identify more accurate (bio)markers is needed. Systematic Review Registration: PROSPERO CRD42013004608.

Are all people with diabetes and cardiovascular risk factors or microvascular complications at very high risk? Findings from the Risk and Prevention Study

AIMS

To verify whether it is possible, in people with diabetes mellitus (DM) considered at very high cardiovascular (CV) risk, stratify this risk better and identify significant modifiable risk factor (including lifestyle habits) to help patients and clinicians improve CV prevention.

METHODS

People with DM and microvascular diseases or one or more CV risk factors (hypertension, hyperlipidemia, smoking, poor dietary habits, overweight, physical inactivity) included in the Risk and Prevention study were selected. We considered the combined endpoint of non-fatal acute myocardial infarction and stroke and CV death. A multivariate Cox proportional analysis was carried out to identify relevant predictors. We also used the RECPAM method to identify subgroups of patients at higher risk.

RESULTS

In our study, the rate of major CV events was lower than expected (5 % in 5 years). Predictors of CV events were age, male, sex, heart failure, previous atherosclerotic disease, atrial fibrillation, insulin treatment, high HbA1c, heart rate and other CV diseases while being physically active was protective. RECPAM analysis indicated that history of atherosclerotic diseases and a low BMI defined worse prognosis (HR 4.51 95 % CI 3.04-6.69). Among subjects with no previous atherosclerotic disease, men with HbA1c more than 8 % were at higher CV risk (HR 2.77; 95 % CI 1.86-4.14) with respect to women.

CONCLUSIONS

In this population, the rate of major CV events was lower than expected. This prediction model could help clinicians identify people with DM at higher CV risk and support them in achieving goals of physical activity and HbA1c.

Prediction models for the risk of gestational diabetes: a systematic review

BACKGROUND

Numerous prediction models for gestational diabetes mellitus (GDM) have been developed, but their methodological quality is unknown. The objective is to systematically review all studies describing first-trimester prediction models for GDM and to assess their methodological quality.

METHODS

MEDLINE and EMBASE were searched until December 2014. Key words for GDM, first trimester of pregnancy, and prediction modeling studies were combined. Prediction models for GDM performed up to 14 weeks of gestation that only include routinely measured predictors were eligible.Data was extracted by the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). Data on risk predictors and performance measures were also extracted. Each study was scored for risk of bias.

RESULTS

Our search yielded 7761 articles, of which 17 were eligible for review (14 development studies and 3 external validation studies). The definition and prevalence of GDM varied widely across studies. Maternal age and body mass index were the most common predictors. Discrimination was acceptable for all studies. Calibration was reported for four studies. Risk of bias for participant selection, predictor assessment, and outcome assessment was low in general. Moderate to high risk of bias was seen for the number of events, attrition, and analysis.

CONCLUSIONS

Most studies showed moderate to low methodological quality, and few prediction models for GDM have been externally validated. External validation is recommended to enhance generalizability and assess their true value in clinical practice.

Myo-inositol may prevent gestational diabetes onset in overweight women: a randomized, controlled trial

OBJECTIVE

To evaluate whether myo-inositol supplementation may reduce gestational diabetes mellitus (GDM) rate in overweight women.

METHODS

In an open-label, randomized trial, myo-inositol (2 g plus 200 μg folic acid twice a day) or placebo (200 μg folic acid twice a day) was administered from the first trimester to delivery in pregnant overweight non-obese women (pre-pregnancy body mass index ≥ 25 and < 30 kg/m(2)). The primary outcome was the incidence of GDM.

RESULTS

From January 2012 to December 2014, 220 pregnant women were randomized at two Italian University hospitals, 110 to myo-inositol and 110 to placebo. The incidence of GDM was significantly lower in the myo-inositol group compared to the placebo group (11.6% versus 27.4%, respectively, p = 0.004). Myo-inositol treatment was associated with a 67% risk reduction of developing GDM (OR 0.33; 95% CI 0.15-0.70).

CONCLUSIONS

Myo-inositol supplementation, administered since early pregnancy, reduces GDM incidence in overweight non-obese women.