Joint impact of gestational diabetes and obesity on perinatal outcomes

A systematic review of the effects of maternal obesity on neonatal outcomes in women with gestational diabetes

Maternal obesity and gestational diabetes mellitus (GDM) prevalence are increasing, with both conditions associated with adverse neonatal outcomes. This review aimed to determine the risk of adverse outcomes in women with obesity and GDM, compared with women with obesity alone. A systematic search identified 28 eligible articles. Meta-analysis was conducted using a random effects model, to generate pooled estimates (odds ratios, OR, or mean difference, MD). Compared with normal-weight controls, women with obesity had increased risks of large for gestational age (LGA, OR 1.98, 95% CI: 1.56, 2.52) and macrosomia (OR 2.93, 95% CI: 1.71, 5.03); the latter's risk almost double in women with obesity than GDM. Birth weight (MD 113 g, 95% CI: 69, 156) and shoulder dystocia (OR 1.23, 95% CI: 0.85, 1.78) risk was also higher. GDM significantly amplified neonatal risk in women with obesity, with a three- to four-fold risk of LGA (OR 3.22, 95% CI: 2.17, 4.79) and macrosomia (OR 3.71, 95% CI: 2.76, 4.98), as well as higher birth weights (MD 176 g, 95% CI: 89, 263), preterm delivery (OR 1.49, 95% CI: 1.25, 1.77), and shoulder dystocia (OR 1.99, 95% CI: 1.31, 3.03), when compared with normal-weight controls. Our findings demonstrate that maternal obesity increases serious neonatal adverse risk, magnified by the presence of GDM. Effective strategies are needed to safeguard against neonatal complications associated with maternal obesity, regardless of GDM status.

Association between prepregnancy body mass index or gestational weight gain and adverse pregnancy outcomes among Chinese women with gestational diabetes mellitus: a systematic review and meta-analysis

OBJECTIVE

The association between prepregnancy body mass index (BMI) or gestational weight gain (GWG) and adverse pregnancy outcomes among Chinese women with gestational diabetes mellitus (GDM) is unknown. This study aims to evaluate such association by synthesising the evidence.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Web of Science, Scopus, EMBASE, China Biology Medicine disc, China National Knowledge Infrastructure, Wangfang, and China Science and Technology Journal Database searched from inception to 11 August 2023.

ELIGIBILITY CRITERIA

Prospective cohort studies, retrospective cohort studies and case-control studies estimating the relationship of abnormal prepregnancy BMI (including underweight, overweight or obesity) or inappropriate GWG (including excess GWG or insufficient GWG) with adverse pregnancy outcomes of interest were included. Outcomes included macrosomia, caesarean section, preterm birth, gestational hypertension, large for gestational age (LGA) and small for gestational age (SGA).

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently selected studies, extracted the data and assessed the risk of bias. OR estimate and its 95% CI were pooled using Stata software fixed-effect model. Subgroup analysis, meta-regression and sensitivity analysis were performed to ensure credibility of the results.

RESULTS

Twenty-three studies (eighteen retrospective cohort studies, three prospective cohort studies and two case control studies) involving 57 013 Chinese women with GDM were identified. Meta-analysis results showed that compared with GDM women with normal weight, GDM women with underweight were at a higher risk of SGA (OR=1.79 (1.54 to 2.07), five studies involving 31 967 women); women with overweight had higher risks of macrosomia (OR=1.65 (1.49 to 1.82), eleven studies involving 41 683 women), caesarean section (OR=1.48 (1.38 to 1.59), ten studies involving 34 935 women), preterm birth (OR=1.27 (1.13 to 1.43), eight studies involving 38 295 women) and LGA (OR=1.73 (1.54 to 1.95), seven studies involving 31 342 women) and women with obesity had higher risks of macrosomia (OR=2.37 (2.04 to 2.76), eleven studies involving 41 683 women), caesarean section (OR=2.07 (1.84 to 2.32), nine studies involving 34 829 women), preterm birth (OR=1.31 (1.09 to 1.57), eight studies involving 38 295 women) and LGA (OR=2.63 (2.15 to 3.21), six studies involving 31 236 women). Regard to GWG, compared with Chinese GDM women with sufficient GWG, GDM women with excessive GWG had higher risks of macrosomia (OR=1.74 (1.58 to 1.92), twelve studies involving 40 966 women), caesarean section (OR=1.44 (1.36 to 1.53), nine studies involving 36 205 women) and LGA (OR=2.12 (1.96 to 2.29), twelve studies involving 42 342 women); women with insufficient GWG conversely had higher risks of preterm birth (OR=1.59 (1.45 to 1.74), nine studies involving 37 461 women) and SGA (OR=1.38 (1.27 to 1.51), ten studies involving 41 080 women).

CONCLUSIONS

For Chinese women with GDM, abnormal prepregnancy BMI or inappropriate GWG were related to higher risks of many adverse pregnancy outcomes. Therefore, medical staff should pay more attention to the weight management of GDM women during pregnancy.

Interventions in preconception and pregnant women at risk of gestational diabetes; a systematic review and meta-analysis of randomised controlled trials

BACKGROUND

Women at risk of gestational diabetes mellitus (GDM) need preventative interventions.

OBJECTIVE

To evaluate targeted interventions before and during pregnancy for women identified as being at risk of developing GDM.

METHODS

Systematic review and meta-analysis conducted following PRISMA guidelines. MEDLINE, EMBASE and the Cochrane Library in addition to reference and citation lists were searched to identify eligible randomised controlled trials (RCTs) utilising risk stratification during the preconception period or in the first/early second trimester. Screening and data extraction were carried out by the authors independently. Quality assessment was conducted based on the Cochrane risk-of-bias tool. Random effects meta-analysis and narrative synthesis were performed.

RESULTS

Eighty-four RCTs were included: two during preconception and 82 in pregnancy, with a pooled sample of 22,568 women. Interventions were behavioural (n = 54), dietary supplementation (n = 19) and pharmacological (n = 11). Predictive factors for risk assessment varied; only one study utilised a validated prediction model. Gestational diabetes was reduced in diet and physical activity interventions (risk difference - 0.03, 95% CI 0.06, - 0.01; I2 58.69%), inositol (risk difference - 0.19, 95% CI 0.33, - 0.06; I2 92.19%), and vitamin D supplements (risk difference - 0.16, 95% CI 0.25, - 0.06; I2 32.27%). Subgroup analysis showed that diet and physical activity interventions were beneficial in women with ≥ 2 GDM risk factors (risk difference - 0.16, 95% CI 0.25, - 0.07; I2 11.23%) while inositol supplementation was effective in women with overweight or obesity (risk difference - 0.17, 95% CI 0.22, - 0.11; I2 0.01%). Effectiveness of all other interventions were not statistically significant.

CONCLUSIONS

This review provides evidence that interventions targeted at women at risk of GDM may be an effective strategy for prevention. Further studies using validated prediction tools or multiple risk factors to target high-risk women for intervention before and during pregnancy are warranted.

Refining the diagnosis of gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Perinatal outcomes vary for women with gestational diabetes mellitus (GDM). The precise factors beyond glycemic status that may refine GDM diagnosis remain unclear. We conducted a systematic review and meta-analysis of potential precision markers for GDM.

METHODS

Systematic literature searches were performed in PubMed and EMBASE from inception to March 2022 for studies comparing perinatal outcomes among women with GDM. We searched for precision markers in the following categories: maternal anthropometrics, clinical/sociocultural factors, non-glycemic biochemical markers, genetics/genomics or other -omics, and fetal biometry. We conducted post-hoc meta-analyses of a subset of studies with data on the association of maternal body mass index (BMI, kg/m2) with offspring macrosomia or large-for-gestational age (LGA).

RESULTS

A total of 5905 titles/abstracts were screened, 775 full-texts reviewed, and 137 studies synthesized. Maternal anthropometrics were the most frequent risk marker. Meta-analysis demonstrated that women with GDM and overweight/obesity vs. GDM with normal range BMI are at higher risk of offspring macrosomia (13 studies [n = 28,763]; odds ratio [OR] 2.65; 95% Confidence Interval [CI] 1.91, 3.68), and LGA (10 studies [n = 20,070]; OR 2.23; 95% CI 2.00, 2.49). Lipids and insulin resistance/secretion indices were the most studied non-glycemic biochemical markers, with increased triglycerides and insulin resistance generally associated with greater risk of offspring macrosomia or LGA. Studies evaluating other markers had inconsistent findings as to whether they could be used as precision markers.

CONCLUSIONS

Maternal overweight/obesity is associated with greater risk of offspring macrosomia or LGA in women with GDM. Pregnancy insulin resistance or hypertriglyceridemia may be useful in GDM risk stratification. Future studies examining non-glycemic biochemical, genetic, other -omic, or sociocultural precision markers among women with GDM are warranted.

Combined Effect of Maternal Obesity and Diabetes on Excessive Fetal Growth: Pregnancy Risk Assessment Monitoring System (PRAMS), United States, 2012-2015

Introduction

Obesity and dysregulation in glucose metabolism are risk factors for excessive fetal growth, but their combined effects are not often examined in a single study.

Methods

Data from the Centers for Disease Control and Prevention's Pregnancy Risk Assessment Monitoring System Phase 7 (2012-2015) were used. Logistic regression was used to investigate the association between maternal prepregnancy BMI and pre-existing diabetes/gestational diabetes on the odds of delivering a large-for-gestational-age infant or an infant with macrosomia.

Results

Complete data for 128,199 singleton births were used. The proportions of large-for-gestational-age infants and infants with macrosomia increased with the degree of obesity (p<0.001) and were higher in women with diabetes than in those without (p<0.001). Compared with the AOR among normal-weight women, the AOR of delivering large-for-gestational-age infants and infants with macrosomia among women with morbid obesity (BMI≥40) were 2.82 (p<0.001) and 2.67 (p<0.001), respectively. Compared with the AOR among nondiabetic women, the AOR of delivering a large-for-gestational-age infant was 1.88 (p<0.001) among those with pre-existing diabetes and 1.49 (p<0.001) among those with gestational diabetes. Except for the underweight group, women with pre-existing diabetes were nearly twice as likely to deliver a large-for-gestational-age infant as those with similar BMI without diabetes. Women with morbid obesity and gestational diabetes were twice as likely to have a large-for-gestational-age infant and an infant with macrosomia as nondiabetic women with normal BMI.

Conclusions

We have shown that when maternal obesity and diabetes, particularly pre-existing diabetes, occur together, the risk of delivering large-for-gestational-age and macrosomia increases significantly. Our findings call for public health attention to address maternal obesity and diabetes to minimize suboptimal fetal growth.

Genetic Risk Factors and Gene-Lifestyle Interactions in Gestational Diabetes

Paralleling the increasing trends of maternal obesity, gestational diabetes (GDM) has become a global health challenge with significant public health repercussions. In addition to short-term adverse outcomes, such as hypertensive pregnancy disorders and fetal macrosomia, in the long term, GDM results in excess cardiometabolic morbidity in both the mother and child. Recent data suggest that women with GDM are characterized by notable phenotypic and genotypic heterogeneity and that frequencies of adverse obstetric and perinatal outcomes are different between physiologic GDM subtypes. However, as of yet, GDM treatment protocols do not differentiate between these subtypes. Mapping the genetic architecture of GDM, as well as accurate phenotypic and genotypic definitions of GDM, could potentially help in the individualization of GDM treatment and assessment of long-term prognoses. In this narrative review, we outline recent studies exploring genetic risk factors of GDM and later type 2 diabetes (T2D) in women with prior GDM. Further, we discuss the current evidence on gene-lifestyle interactions in the development of these diseases. In addition, we point out specific research gaps that still need to be addressed to better understand the complex genetic and metabolic crosstalk within the mother-placenta-fetus triad that contributes to hyperglycemia in pregnancy.

Development, validation and clinical utility of a risk prediction model for adverse pregnancy outcomes in women with gestational diabetes: The PeRSonal GDM model

BACKGROUND

The ability to calculate the absolute risk of adverse pregnancy outcomes for an individual woman with gestational diabetes mellitus (GDM) would allow preventative and therapeutic interventions to be delivered to women at high-risk, sparing women at low-risk from unnecessary care. We aimed to develop, validate and evaluate the clinical utility of a prediction model for adverse pregnancy outcomes in women with GDM.

METHODS

A prediction model development and validation study was conducted on data from a observational cohort. Participants included all women with GDM from three metropolitan tertiary teaching hospitals in Melbourne, Australia. The development cohort comprised those who delivered between 1 July 2017 to 30 June 2018 and the validation cohort those who delivered between 1 July 2018 to 31 December 2018. The main outcome was a composite of critically important maternal and perinatal complications (hypertensive disorders of pregnancy, large-for-gestational age neonate, neonatal hypoglycaemia requiring intravenous therapy, shoulder dystocia, perinatal death, neonatal bone fracture and nerve palsy). Model performance was measured in terms of discrimination and calibration and clinical utility evaluated using decision curve analysis.

FINDINGS

The final PeRSonal (Prediction for Risk Stratified care for women with GDM) model included body mass index, maternal age, fasting and 1-hour glucose values (75-g oral glucose tolerance test), gestational age at GDM diagnosis, Southern and Central Asian ethnicity, East Asian ethnicity, nulliparity, past delivery of an large-for-gestational age neonate, past pre-eclampsia, GWG until GDM diagnosis, and family history of diabetes. The composite adverse pregnancy outcome occurred in 27% (476/1747) of women in the development (1747 women) and in 26% (244/955) in the validation (955 women) cohorts. The model showed excellent calibration with slope of 0.99 (95% CI 0.75 to 1.23) and acceptable discrimination (c-statistic 0.68; 95% CI 0.64 to 0.72) when temporally validated. Decision curve analysis demonstrated that the model was useful across a range of predicted probability thresholds between 0.15 and 0.85 for adverse pregnancy outcomes compared to the alternatives of managing all women with GDM as if they will or will not have an adverse pregnancy outcome.

INTERPRETATION

The PeRSonal GDM model comprising of routinely available clinical data shows compelling performance, is transportable across time, and has clinical utility across a range of predicted probabilities. Further external validation of the model to a more disparate population is now needed to assess the generalisability to different centres, community based care and low resource settings, other healthcare systems and to different GDM diagnostic criteria.

FUNDING

This work is supported by the Mothers and Gestational Diabetes in Australia 2 NHMRC funded project #1170847.

Blood Pressure Monitoring and Perinatal Outcomes in Normotensive Women with Gestational Diabetes Mellitus

Alterations in ambulatory blood pressure detected by monitoring (ABPM) have been associated with perinatal complications in hypertensive pregnant women. Aim: To establish the relationships between the blood pressure (BP) profiles detected by ABPM and adverse perinatal outcomes in normotensive women with gestational diabetes mellitus (GDM). Methods: A prospective study of normotensive women in whom 24 h ABPM was performed at 28–32 weeks of pregnancy. The obstetric and perinatal outcomes were evaluated. Results: Two hundred patients were included. Thirty-seven women with GDM and obesity had significantly higher mean systolic BP (SBP) and nocturnal SBP and diastolic BP (DBP) compared to women with only GDM (n = 86). Nocturnal SBP (OR = 1.077; p = 0.015) and obesity (OR = 1.131; p = 0.035) were risk factors for the development of hypertensive disorders of pregnancy (HDPs). Mothers of newborns with neonatal complications (n = 27) had higher nocturnal SBP (103.8 vs. 100 mmHg; p = 0.047) and DBP (62.7 vs. 59.4; p = 0.016). Women who delivered preterm (n = 10) had higher BP and a non-dipper pattern (p = 0.005). Conclusions: Nocturnal SBP was a predictor of HDPs in normotensive women with obesity or GDM. Alterations in ABPM in these patients were associated with poor obstetric and perinatal outcomes.

Comparison of elasticity values in normal and gestational diabetic pregnancies in the third trimester

Placental elasticity was compared by using Shear wave elastography (SWE) in patients with gestational diabetes mellitus (GDM) with and without insulin to non-diabetic controls. Three groups were created as follows: Group 1 (n = 79, GDM with insulin therapy), Group 2 (n = 90, GDM with only diet) and Group 3 (n = 150, healthy controls) All patients were above 36 gestational weeks with anterior placenta. Clinical trial number was also received (NCT04455880). Group 1 had higher BMI while group 3 had lowest rate of C/S. Birthweight in GDM groups was statistically significantly higher than controls (p = .001). Although there was no significant difference between APGAR scores, Group 1 had higher rates of neonatal intensive care unit (NICU) admission. SWE values were significantly higher in GDM patients treated with insulin or diet than controls. SWE may be an alternatively supplementary management modality in GDM.IMPACT STATEMENTWhat is already known on this subject? Shear wave elastography (SWE), is one of the types of sono elastography methods that are used to measure the stiffness and elasticity of soft tissues. Recently, it became popular for screening the stiffness and elasticity of the placenta in high-risk pregnancies like preeclampsia, intrauterine growth restriction (IUGR), and placental dysfunction.What the results of this study add? All SWE velocities on the maternal side were statistically significantly different between groups. Regarding foetal side velocities, GDM groups had statistically significantly higher values (stiffer tissue) compared to controls.What the implications are of these findings for clinical practice and/or further research? SWE may be a Supplementary method in the diagnosis and management of GDM. Placental SWE should be measured at 24-28 weeks of gestation in patients with GDM and diagnosis confirmation and their responses to the treatment should be examined.

The Need for Personalized Risk-Stratified Approaches to Treatment for Gestational Diabetes: A Narrative Review

Gestational diabetes mellitus (GDM) is common and is associated with an increased risk of adverse pregnancy outcomes. However, the prevailing one-size-fits-all approach that treats all women with GDM as having equivalent risk needs revision, given the clinical heterogeneity of GDM, the limitations of a population-based approach to risk, and the need to move beyond a glucocentric focus to address other intersecting risk factors. To address these challenges, we propose using a clinical prediction model for adverse pregnancy outcomes to guide risk-stratified approaches to treatment tailored to the individual needs of women with GDM. This will allow preventative and therapeutic interventions to be delivered to those who will maximally benefit, sparing expense, and harm for those at a lower risk.

Maternal and Perinatal Outcome of Maternal Obesity at RSCM in 2014-2019

Obesity is a pandemic found in many countries. It is estimated that, in 2025, more than 21% of women in the world will suffer from obesity and its number keeps increasing yearly. Obesity in pregnancy is one of the important challenges in obstetric services given the prevalence and potential adverse effects on the mother and fetus. Obese women have a higher risk of developing gestational diabetes, gestational hypertension, preeclampsia, venous thromboembolism, postpartum hemorrhage, cesarean delivery, and maternal death. The aim of this research is to determine the prevalence of maternal and perinatal complication in various obesity grades. This research was an observational descriptive study using the cross-sectional design. The inclusion criterion is obese pregnant women whose delivery was done in Dr. Cipto Mangunkusumo National General Hospital (RSCM) from 2014 to 2019. The exclusion criterion in this study is the incomplete medical record. A total of 111 subjects were included in the study. Obesity grades in this study were based on World Health Organization (WHO) obesity, divided into 3 classifications which are obese I (30–34.9 kg/m²), obese II (35–39.9 kg/m²), and obese III (≥40 kg/m²). Maternal outcomes in this study were birth method, gestational diabetes, preeclampsia, and premature rupture of membrane (PROM). Perinatal outcomes in this study were preterm birth, birth weight, APGAR score, and postdelivery neonatal care. In this study, obese patients had a mean age of 31.23 years, mean gravida 2, parity 1, and abortion 0. Most of these patients used an intrauterine device (IUD) for family planning (74.8%). There were no differences in age, parity status, and family planning methods in each group of patients with different body mass index (p > 0.05). Maternal characteristics are the majority of deliveries performed cesarean delivery (86.5%), cases of diabetes mellitus are more common in obese I patients (50%), preeclampsia is more prevalent in obese grade II patients (34,4%), and premature rupture of membranes (PROM) is more common in patients with obese II (52,4%). However, there was no difference in the prevalence of maternal outcomes between groups. There was a median gestational age of 37 weeks in all obesity grades, the highest percentage of preterm births owned by obese II patients (32,6%), the mean birth weight of babies tends to increase along with the weighting of the body mass index group, and neonatal intensive care unit (NICU) treatment rooms were mostly occupied from mother with obese II groups (18%). There was no difference in the first-minute and fifth-minute APGAR scores between study groups (p > 0.05). There were no differences in perinatal outcomes between groups. There were no significant differences in maternal and perinatal outcomes prevalence between different obesity grades. However, the rate of maternal and perinatal complications in obese women is higher than the normal population, thus requiring sophisticated prevention and approach toward handling the pregnancy.

Effect of Excessive Body Weight and Emotional Disorders on the Course of Pregnancy and Well-Being of a Newborn before and during COVID-19 Pandemic

This study aimed to evaluate whether excessive body weight and the COVID-19 pandemic affect depression, and subsequently whether depression, excessive body weight, and the COVID-19 pandemic affect the course of pregnancy, as well as the well-being of a newborn. The research material included data retrieved from the medical records of 280 pregnant women who were provided with care by medical facilities in Lublin (100 women with normal weight, 100 overweight women, 50 with Class I and 30 with Class II obesity). They completed a Beck depression inventory (BDI) in pregnancy twice, in order to assess the risk of occurrence of postpartum depression. Pre-pregnancy BMI positively correlated with the severity of depression, both at 10–13 weeks of pregnancy (p < 0.001), and at 32 weeks of pregnancy (p < 0.001). The higher the pre-pregnancy BMI, on average the higher the severity of depression. The severity of depression was significantly higher during the pandemic than before it in women with normal body weight before pregnancy (p < 0.001), as well as in those overweight (p < 0.001) and with Class II obesity (p = 0.015). Excessive body weight before pregnancy leads to depressive disorders during pregnancy, increases the risk of preterm delivery, and exerts a negative effect on the state of a newborn. Depressive symptoms among pregnant, overweight and obese women intensified during the COVID-19 pandemic.

Does Universal Screening for Gestational Diabetes Mellitus Improve Neonatal Outcomes in a Socially Vulnerable Population: A Prospective Study in French Guiana

AIMS/INTRODUCTION

French Guiana has a high prevalence of metabolic diseases, which are risk factors for gestational diabetes mellitus. Despite routine screening for gestational diabetes, treatment is still challenging because of health inequalities and different cultural representations of disease and pregnancy. This study was conducted to assess the role of early and universal GDM screening on obstetrical and neonatal complications in a socially deprived population.

MATERIALS AND METHODS

A prospective study was conducted, in the level III maternity in French Guiana. Of 2136 deliveries, 223 had gestational diabetes mellitus, 110 of whom were followed-up for 6 month to detail their social and laboratory parameters.

RESULTS

The prevalence of gestational diabetes in French Guiana (Cayenne Hospital) was estimated at 10.3%. The study population was very precarious with 70% of patients on welfare (universal health coverage or state medical assistance). The following obstetrical complications were observed: cesarean delivery (32%), history of miscarriage (26%) and preeclampsia (7.4%). Nevertheless, neonatal complications were rarely present and included hypoglycemia (2.8%) and macrosomia (2.8%).

CONCLUSION

In French Guiana, gestational diabetes mellitus is very common. However, in a context of widespread poverty and diverse cultural representations, universal screening and monitoring limited the risk of macrosomia.

I/D Polymorphism Gene ACE and Risk of Preeclampsia in Women with Gestational Diabetes Mellitus

Preeclampsia (PE) and gestational diabetes mellitus (GDM) are the most common complications of pregnancy, which result in adverse outcomes for the mother and the fetus. GDM is regarded as a separate independent risk factor for PE development, as evidenced by a higher preeclampsia rate in gestational diabetes mellitus than in the general population. The role the endothelial cell dysfunction plays is considered to be the most reasonable one in the origin of these diseases. The activity of plasma and tissue angiotensin converting enzyme (ACE) is believed to be genetically controlled. The available data suggests that increased ACE activity due to deletion (D)/insertion (I) in the 16th intron of ACE gene, which is called ACE gene I/D polymorphism, is associated with preeclampsia and varies depending on the studied population and the geography. We did not find any literature data that estimates the influence of ACE gene I/D polymorphism on PE rate in pregnant women with GDM. Therefore, the present study aimed to investigate a relationship between ACE gene I/D polymorphism and preeclampsia development in the case of GDM in the Russian population. The study used the genomic DNA derived by phenol-chloroform extraction method from venous blood samples in 137 pregnant women, including samples of 74 women with GDM accompanied with PE and the blood samples of 63 women with GDM w/o preeclampsia. Genotyping of insertion/deletion in the I/D region (16 intron of АСЕ gene) was conducted by real-time PCR using the TaqMan competing probe technology. The particular features in the frequency array of alleles and genotypes of the ACE gen I/D polymorphism under review, as associated with preeclampsia development risk in pregnant women with GDM, were identified. The acquired data testify to the need to further study of ACE gene I/D region polymorphism association in a large patient sample taking into account the PE and GDM risk factors estimated in the clinical practice.

Protocol for development and validation of a clinical prediction model for adverse pregnancy outcomes in women with gestational diabetes

INTRODUCTION

Gestational diabetes (GDM) is a common yet highly heterogeneous condition. The ability to calculate the absolute risk of adverse pregnancy outcomes for an individual woman with GDM would allow preventative and therapeutic interventions to be delivered to women at high-risk, sparing women at low-risk from unnecessary care. The Prediction for Risk-Stratified care for women with GDM (PeRSonal GDM) study will develop, validate and evaluate the clinical utility of a prediction model for adverse pregnancy outcomes in women with GDM.

METHODS AND ANALYSIS

We undertook formative research to conceptualise and design the prediction model. Informed by these findings, we will conduct a model development and validation study using a retrospective cohort design with participant data collected as part of routine clinical care across three hospitals. The study will include all pregnancies resulting in births from 1 July 2017 to 31 December 2018 coded for a diagnosis of GDM (estimated sample size 2430 pregnancies). We will use a temporal split-sample development and validation strategy. A multivariable logistic regression model will be fitted. The performance of this model will be assessed, and the validated model will also be evaluated using decision curve analysis. Finally, we will explore modes of model presentation suited to clinical use, including electronic risk calculators.

ETHICS AND DISSEMINATION

This study was approved by the Human Research Ethics Committee of Monash Health (RES-19-0000713 L). We will disseminate results via presentations at scientific meetings and publication in peer-reviewed journals.

TRIAL REGISTRATION DETAILS

Systematic review proceeding this work was registered on PROSPERO (CRD42019115223) and the study was registered on the Australian and New Zealand Clinical Trials Registry (ACTRN12620000915954); Pre-results.

The Influence of Preeclampsia, Advanced Maternal Age and Maternal Obesity in Neonatal Outcomes Among Women with Gestational Diabetes

OBJECTIVE

 The present study aims to analyze adverse fetal or neonatal outcomes in women with gestational diabetes, including fetal death, preterm deliveries, birthweight, neonatal morbidity and mortality, as well as the synergic effect of concomitant pregnancy risk factors and poor obstetric outcomes, as advanced maternal age, maternal obesity and pre-eclampsia in their worsening.

METHODS

 The present cohort retrospective study included all pregnant women with gestational diabetes, with surveillance and childbirth at the Hospital da Senhora da Oliveira during the years of 2017 and 2018. The data were collected from the medical electronic records registered in health informatic programs Sclinico and Obscare, and statistical simple and multivariate analysis was done using IBM SPSS Statistics.

RESULTS

 The study participants included 301 pregnant women that contributed to 7.36% of the total institution childbirths of the same years, in a total of 300 live births. It was analyzed the influence of pre-eclampsia coexistence in neonatal morbidity (p = 0.004), in the occurrence of newborns of low and very low birthweight (p < 0.01) and in preterm deliveries (p < 0.01). The influence of maternal obesity (p = 0.270; p = 0.992; p = 0.684) and of advanced maternal age in these 3 outcomes was also analyzed (p = 0,806; p = 0.879; p = 0.985).Using a multivariate analysis, the only models with statistic significance to predict the three neonatal outcomes included only pre-eclampsia (p = 0.04; p < 0.01; p < 0.01).

CONCLUSION

 Only coexistence of pre-eclampsia showed an association with adverse neonatal outcomes (neonatal morbidity, newborns of low and very low birthweight and preterm deliveries) and can be used as a predictor of them in women with gestational diabetes.

The Unrealised Potential for Predicting Pregnancy Complications in Women with Gestational Diabetes: A Systematic Review and Critical Appraisal

Gestational diabetes (GDM) increases the risk of pregnancy complications. However, these risks are not the same for all affected women and may be mediated by inter-related factors including ethnicity, body mass index and gestational weight gain. This study was conducted to identify, compare, and critically appraise prognostic prediction models for pregnancy complications in women with gestational diabetes (GDM). A systematic review of prognostic prediction models for pregnancy complications in women with GDM was conducted. Critical appraisal was conducted using the prediction model risk of bias assessment tool (PROBAST). Five prediction modelling studies were identified, from which ten prognostic models primarily intended to predict pregnancy complications related to GDM were developed. While the composition of the pregnancy complications predicted varied, the delivery of a large-for-gestational age neonate was the subject of prediction in four studies, either alone or as a component of a composite outcome. Glycaemic measures and body mass index were selected as predictors in four studies. Model evaluation was limited to internal validation in four studies and not reported in the fifth. Performance was inadequately reported with no useful measures of calibration nor formal evaluation of clinical usefulness. Critical appraisal using PROBAST revealed that all studies were subject to a high risk of bias overall driven by methodologic limitations in statistical analysis. This review demonstrates the potential for prediction models to provide an individualised absolute risk of pregnancy complications for women affected by GDM. However, at present, a lack of external validation and high risk of bias limit clinical application. Future model development and validation should utilise the latest methodological advances in prediction modelling to achieve the evolution required to create a useful clinical tool. Such a tool may enhance clinical decision-making and support a risk-stratified approach to the management of GDM. Systematic review registration: PROSPERO CRD42019115223.

Impact of overweight and obesity on pregnancy outcomes in women with gestational diabetes - results from a retrospective multicenter study

Objective The aim of this study was to evaluate the impact of pre-pregnancy body mass index (BMI) on pregnancy outcomes in women with gestational diabetes (GD). Subjects and methods Retrospective multicenter study using data from the Portuguese National Register. We included women with GD with a singleton pregnancy. GD diagnosis was according to the International Association of the Diabetes and Pregnancy Study Group criteria. Women were divided into groups according to their pre-pregnancy BMI: < 18.5 kg/m2 (underweight), ≥ 18.5 and < 25.0 kg/m2 (normal weight), ≥ 25 and < 30 kg/m2 (overweight) and ≥ 30 kg/m2 (obese). Results We included 3,103 pregnant women with GD, 29.6% (n = 918) were overweight and 27.3% (n = 846) were obese. Compared to normal weight, the overweight and obese groups had a higher percentage of gestational hypertension (4.0% and 8.5% vs. 2.1%), cesarean delivery (32.8% and 41.3% vs. 27.9%), macrosomia (3.9% and 6.7% vs. 2.4%), and large for gestational age (LGA) newborns (8.3% and 13.5% vs. 6.0%). Obesity increased the risk of gestational hypertension (OR 4.5, p < 0.001), preeclampsia (OR 1.9, p = 0.034), cesarean delivery (OR 2.0, p < 0.001), macrosomia (OR 3.1, p < 0.001) and LGA (OR 2.3, p < 0.001). Conclusion In pregnant women with GD, pregnancy complications increase with pre-pregnancy BMI. In obese women, appropriate diet and counseling prior to gestation and more aggressive medical intervention during pregnancy are needed in order to prevent macrosomic and LGA newborns and to reduce maternal complications.

Prognostic prediction models for pregnancy complications in women with gestational diabetes: a protocol for systematic review, critical appraisal and meta-analysis

BACKGROUND

Gestational diabetes (GDM) is increasingly common and has significant implications during pregnancy and for the long-term health of the mother and offspring. However, it is a heterogeneous condition with inter-related factors including ethnicity, body mass index and gestational weight gain significantly modifying the absolute risk of complications at an individual level. Predicting the risk of pregnancy complications for an individual woman with GDM presents a useful adjunct to therapeutic decision-making and patient education. Diagnostic prediction models for GDM are prevalent. In contrast, prediction models for risk of complications in those with GDM are relatively novel. This study will systematically review published prognostic prediction models for pregnancy complications in women with GDM, describe their characteristics, compare performance and assess methodological quality and applicability.

METHODS

Studies will be identified by searching MEDLINE and Embase electronic databases. Title and abstract screening, full-text review and data extraction will be completed independently by two reviewers. The included studies will be systematically assessed for risk of bias and applicability using appropriate tools designed for prediction modelling studies. Extracted data will be tabulated to facilitate qualitative comparison of published prediction models. Quantitative data on predictive performance of these models will be synthesised with meta-analyses if appropriate.

DISCUSSION

This review will identify and summarise all published prognostic prediction models for pregnancy complications in women with GDM. We will compare model performance across different settings and populations with meta-analysis if appropriate. This work will guide subsequent phases in the prognosis research framework: further model development, external validation and model updating, and impact assessment. The ultimate model will estimate the absolute risk of pregnancy complications for women with GDM and will be implemented into routine care as an evidence-based GDM complication risk prediction model. It is anticipated to offer value to women and their clinicians with individualised risk assessment and may assist decision-making. Ultimately, this systematic review is an important step towards a personalised risk-stratified model-of-care for GDM to allow preventative and therapeutic interventions for the maximal benefit to women and their offspring, whilst sparing expense and harm for those at low risk.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42019115223.