Gestational diabetes-Predictors of response to treatment and obstetric outcome

The Impact of Overweight and Obesity on Pregnancy: A Narrative Review of Physiological Consequences, Risks and Challenges in Prenatal Care, and Early Intervention Strategies

BACKGROUND

While substantial literature exists on the intersection of overweight/obesity (OWO) and pregnancy, much of it focuses on specific aspects, making it difficult to maintain an overview of clinically relevant factors for optimal care of OWO women throughout pregnancy.

OBJECTIVES

To provide a comprehensive synthesis of the existing literature, covering the full spectrum of clinically relevant information needed to manage OWO women from preconception to birth.

METHODS

For this narrative review a literature search was conducted on PubMed in January 2025. Eligible studies included full-text English articles with data from human subjects, with no restrictions on publication date.

FINDINGS

The impact of OWO on pregnancy is multifaceted, encompassing four interrelated themes: physiological consequences, emerging risks, challenges in prenatal care, and intervention strategies. OWO women exhibit differences in metabolic and inflammatory pathways compared to normal-weight women, reflected in altered laboratory tests. When managing gestational diabetes and preeclampsia, obesity-related characteristics must be considered. Clinicians need to be alert of obesity-mediated fetal complications, including overgrowth, malformations, stillbirth, and preterm birth, while navigating challenges in ultrasound measurements. Interventions during the preconception and prenatal periods provide key opportunities to optimize maternal weight and reduce the risk of long-term disease development.

CONCLUSION

The review's insights enhance clinical practice and call on researchers and policymakers to prioritize strategies that offer early counseling for obese pregnant women. These initiatives aim to optimize outcomes for both mother and child and contribute to combating the global obesity crisis.

Multifaceted therapeutic approach via thiazolidinedione-infused magnolol in chitosan nanoparticles targeting hyperlipidemia and oxidative stress in gestational diabetes mellitus in experimental mice

Recent advancements in nanotechnology have sparked interest in the synthesis of chitosan nanoparticles and their potential applications in medicine. This study investigates the synthesis of chitosan nanoparticles infused with thiazolidinedione and magnolol (TZ/ML-ChNPs) and their therapeutic effects on gestational diabetes mellitus (GDM) in experimental mice. Using streptozotocin-induced diabetic pregnant mice as a model, the study examines the anti-diabetic effects of TZ/ML-ChNPs in vitro and explores possible mechanisms of action. Results show a notable decrease in α-amylase and α-glucosidase activities in TZ/ML-ChNPs-treated samples. Cytocompatibility and flow cytometry analysis in streptozotocin-induced diabetic pregnant mice conducted on RIN-5F cell line demonstrate the safety profile of TZ/ML-ChNPs. The primary objective of this research is to assess whether TZ/ML-ChNPs can mitigate hyperlipidemia and oxidative stress in diabetic pregnant mice. Chitosan nanoparticles with thiazolidinedione and magnolol have therapeutic effects that may be used in clinical and pharmaceutical applications.

The User-Centered Design of a Clinical Dashboard and Patient-Facing App for Gestational Diabetes

BACKGROUND

The number of pregnancies affected by gestational diabetes mellitus (GDM) is growing. With the increased use of smartphones and predictive modeling, a mobile health (mHealth) solution could be developed to improve care and management of GDM while streamlining care through risk stratification.

METHODS

A user-centered mHealth tool was designed from ethnographic observations and 11 semi-structured interviews (six health care professionals [HCPs] and five women with GDM), followed by iterative changes and evaluation from three feedback groups with 31 participants (17 HCPs, 14 researchers) and 13 questionnaires with women with GDM.

RESULTS

"MyGDM" includes a clinical dashboard that centralizes the clinic's patients, highlighting off-target blood glucose and predicting the need for pharmacological intervention. It is linked with a patient-facing app that includes structured education, culturally inclusive language options, and meal ideas. Through the feedback sessions, iterative changes were made around visualization and patient safety, and participants were positive toward the potential user experience. In the 13 questionnaires with women with GDM, 100% said it would fit into their lifestyle and help them manage GDM. Educational resources and the "request a call" functions were well received with 61.5% (8/13) and 69.2% (9/13) saying they were very likely or likely to use these, respectively.

CONCLUSION

A user-centered mHealth tool consisting of a clinical dashboard linked with a patient-facing app for GDM care and management has been designed. Evaluation of the interactive design by end users was positive and showed that it met their needs.

Predictors for pharmacological therapy and perinatal outcomes with metformin treatment in women with gestational diabetes

BACKGROUND

The prevalence of gestational diabetes mellitus (GDM) has been increasing in Australia and worldwide. The study aims were to examine, in comparison with dietary intervention, perinatal outcomes for women with gestational diabetes who were attending a single hospital clinic and to identify predictors for their pharmacological GDM treatment.

METHODS

A prospective, observational study of women with GDM, treated with "Diet, N= 50", "Metformin, N = 35", "Metformin and Insulin, N = 46" or "Insulin, N = 20".

FINDINGS

The mean BMI for the whole cohort was 25.8 ± 4.7 kg/m². The Metformin group, compared to the Diet group, had OR=3.1 (95% CI:1.13 to 8.25) for caesarean section birth (LSCS) compared to normal vaginal birth mode with no longer such a significant association after controlling for the number of their elective LSCS. The insulin treated group had the highest number of small for gestational age neonates (20%, p<0.05) with neonatal hypoglycaemia (25%, p< 0.05). Fasting glucose value on oral GTT (glucose tolerance test) was the strongest predictor for a pharmacological intervention requirement with OR = 2.77 (95CI%: 1.16 to 6.61), followed by timing of OGTT with OR=0.90 (95% CI: 0.83 to 0.97) and previous pregnancy loss with OR=0.28 (95% CI:0.10 to 0.74).

INTERPRETATION

These data suggest that metformin may be a safe alternative treatment to insulin treatment in GDM. Raised fasting glucose on oral GTT was the strongest indicator that GDM women with BMI < 35 kg/m² may require pharmacological therapy. Further studies are needed to identify the most effective and safe management of gestational diabetes within the public hospital setting.

AUSTRALIAN NEW ZEALAND CLINICAL TRIAL REGISTRY ANZCTR TRIAL ID

ACTRN12620000397910.

Predictors of metformin monotherapy failure in gestational diabetes mellitus

Objective

Metformin has emerged as a safe and effective pharmacological alternative to insulin in gestational diabetes mellitus (GDM), being associated with lower maternal weight gain and hypoglycemia risk. Nevertheless, glycemic control is unaccomplished in a considerable proportion of women only treated with metformin. We aim to determine the metformin monotherapy failure rate in GDM and to identify predictors of its occurrence.

Design and methods

This was a retrospective multicenter study including pregnant women with GDM patients who started metformin as a first-line pharmacological treatment (n = 2891). A comparative analysis of clinical and analytical data between the group of women treated with metformin monotherapy and those needing combined therapy with insulin was performed.

Results

In 685 (23.7%) women with GDM, combined therapy to achieve adequate glycemic control was required. Higher pregestational BMI (OR 1.039; CI 95% 1.008-1.071; P-value = 0.013), higher fasting plasma glucose (PG) levels in oral glucose tolerance test (OGTT) (OR 1.047; CI 95% 1.028-1.066; P-value <0.001) and an earlier gestational age (GA) at metformin introduction (0.839; CI 95% 0.796-0.885, P-value < 0.001) were independent predictive factors for metformin monotherapy failure. The best predictive cutoff values were a fasting PG in OGTT ≥87 mg/dL and GA at metformin introduction ≤29 weeks.

Conclusions

In 685 (23.7%) women, combined therapy with insulin to reach glycemic control was required. Higher pre-gestational BMI, fasting PG levels in OGTT ≥87 mg/dL and introduction of metformin ≤29 weeks of GA were independent predictive factors for metformin monotherapy failure. The early recognition of these characteristics can contribute to the establishment of individualized therapeutic strategies and attain better metabolic control during pregnancy.

Impact Of Prepregnancy Overweight And Obesity On Treatment Modality And Pregnancy Outcome In Women With Gestational Diabetes Mellitus

BACKGROUND

We aim to evaluate the impact of prepregnancy overweight on treatment modalities of Gestational Diabetes Mellitus (GDM). We assessed the association of increased pregravid Body Mass Index (BMI) with dosing of basal and rapid acting insulin as well as pregnancy outcome.

METHODS

We included 509 gestational diabetic women (normal weight: 200, overweight: 157, obese: 152), attending the pregnancy outpatient clinic at the Department of Obstetrics and Gynecology, Medical University of Vienna, in this retrospective study. We used a prospectively compiled database to assess patient characteristics, treatment approaches - particularly maximum doses of basal and rapid acting insulin or metformin - and pregnancy outcome.

RESULTS

Increased BMI was associated with the need of glucose lowering medication (odds ratio (OR): 1.08 for the increase of 1 kg/m² BMI, 95%CI 1.05-1.11, p<0.001). Mothers with pregestational obesity received the highest amount of insulin. Metformin was more often used in patients with obesity who also required higher daily doses. Maternal BMI was associated with increased risk of cesarean section (OR 1.04, 95%CI 1.01-1.07, p<0.001) and delivering large for gestational age offspring (OR 1.09, 95%CI 1.04-1.13, p<0.001). Birthweight percentiles were highest in patients with obesity who required glucose lowering therapy.

CONCLUSIONS

Treatment modalities and outcome in GDM pregnancies are closely related to the extent of maternal BMI. Patients with obesity required glucose lowering medication more often and were at higher risk of adverse pregnancy outcomes. It is crucial to further explore the underlying pathophysiologic mechanisms to optimize clinical management and individual treatment approaches.

Can maternal abdominal fat thickness predict antenatal insulin therapy in patients with gestational diabetes mellitus?

PURPOSE

This study aimed to investigate the effectiveness of abdominal subcutaneous fat thickness (ASFT) in predicting antenatal insulin therapy (AIT) in patients with gestational diabetes mellitus (GDM).

METHODS

A prospective study was conducted on patients with regulated blood sugar levels (n = 50) and those with unregulated blood sugar (n = 50) although medical nutrition therapy (MNT) was initiated and then AIT was applied. Using receiver operator characteristic (ROC) curve analysis, appropriate ASFT cut-off point values were found for the prediction of cases that required AIT after MNT in GDM pregnancies.

RESULTS

Patients with GDM who needed AIT had a significantly higher ASFT value compared to those with GDM who did not need AIT. The optimal ASFT cutoff was 21.7 mm in predicting cases that required AIT after MNT (sensitivity, specificity, negative, and positive predictive values were 68.0%, 64.0%, 65.8%, and 66.6%, respectively). The risk of AIT increased 3.77-fold in those with ASFT > 21.7 mm in GDM pregnancies (p = 0.001).

CONCLUSION

The ASFT value was significantly higher in cases with GDM, with blood glucose levels not regulated despite MNT and AIT being then needed, compared to patients with blood glucose levels regulated by MNT, and who did not need AIT. Also, patients requiring AIT can be determined with moderate to high sensitivity and specificity using a cut-off value of ASFT > 21.7 mm. The ASFT > 21.7 mm cut-off point was seen to be more effective than BMI ≥ 30 kg/m² in the determination of cases where AIT is required.

Associations between maternal characteristics and pharmaceutical treatment of gestational diabetes: an analysis of the UK Born in Bradford (BiB) cohort study

OBJECTIVES

To identify the maternal characteristics associated with pharmaceutical treatment of gestational diabetes mellitus (GDM).

DESIGN

Prospective birth cohort study.

SETTING

Bradford, UK.

PARTICIPANTS

762 women from the Born in Bradford (BiB) cohort who were treated for GDM in a singleton pregnancy. BiB cohort participants were recruited from 2007 to 2010. All women booked for delivery were screened for GDM between 26 and 28 weeks of gestation using a 75 g 2-hour oral glucose tolerance test (OGTT).

OUTCOME MEASURE

GDM treatment type: lifestyle changes advice (lifestyle changes), lifestyle changes advice with supplementary insulin (insulin) and lifestyle changes advice with supplementary metformin (metformin).

RESULTS

244 (32%) women were prescribed lifestyle changes advice alone while 518 (68%) were offered supplemental pharmaceutical treatment. The odds of receiving pharmaceutical treatment relative to lifestyle changes advice alone were increased for mothers who were obese (OR 4.6, 95% CI 2.8 to 7.5), those who smoked (OR 2.6, 95% CI 1.2 to 5.5) and had higher fasting glucose levels at OGTT (OR 2.1, 95% CI 1.6 to 2.7). The odds of being prescribed pharmaceutical treatment rather than lifestyle changes advice were lower for Pakistani women (OR 0.7, 95% CI 0.4 to 1.0)) than White British women. Relative to insulin treatment, metformin was more likely to be offered to obese women than normal weight women (relative risk ratio, RRR 3.2, 95% CI 1.3 to 7.8) and less likely to be prescribed to women with higher fasting glucose concentrations at OGTT (RRR 0.3, 95% CI 0.2 to 0.6).

CONCLUSIONS

In the BiB cohort, GDM pharmaceutical treatment tended to be prescribed to women who were obese, White British, who smoked and had more severe hyperglycaemia. The characteristics of metformin-treated mothers differed from those of insulin-treated mothers as they were more likely to be obese but had lower glucose concentrations at diagnosis.

Toward a Multivariate Prediction Model of Pharmacological Treatment for Women With Gestational Diabetes Mellitus: Algorithm Development and Validation

BACKGROUND

Successful management of gestational diabetes mellitus (GDM) reduces the risk of morbidity in women and newborns. A woman's blood glucose readings and risk factors are used by clinical staff to make decisions regarding the initiation of pharmacological treatment in women with GDM. Mobile health (mHealth) solutions allow the real-time follow-up of women with GDM and allow timely treatment and management. Machine learning offers the opportunity to quickly analyze large quantities of data to automatically flag women at risk of requiring pharmacological treatment.

OBJECTIVE

The aim of this study is to assess whether data collected through an mHealth system can be analyzed to automatically evaluate the switch to pharmacological treatment from diet-based management of GDM.

METHODS

We collected data from 3029 patients to design a machine learning model that can identify when a woman with GDM needs to switch to medications (insulin or metformin) by analyzing the data related to blood glucose and other risk factors.

RESULTS

Through the analysis of 411,785 blood glucose readings, we designed a machine learning model that can predict the timing of initiation of pharmacological treatment. After 100 experimental repetitions, we obtained an average area under the receiver operating characteristic curve of 0.80 (SD 0.02) and an algorithm that allows the flexibility of setting the operating point rather than relying on a static heuristic method, which is currently used in clinical practice.

CONCLUSIONS

Using real-time data collected via an mHealth system may further improve the timeliness of the intervention and potentially improve patient care. Further real-time clinical testing will enable the validation of our algorithm using real-world data.

Maternal and Fetal Outcomes in Women with Diabetes in Pregnancy Treated before and after the Introduction of a Standardized Multidisciplinary Management Protocol

BACKGROUND

Diabetes in pregnancy is associated with an increased risk to the woman and to the developing fetus. Currently, there is no consensus on the optimal management strategies for the follow-up and the timing of delivery of pregnancies affected by gestational and pregestational diabetes, with different international guidelines suggesting different management options.

MATERIALS AND METHODS

We conducted a retrospective cohort study from January 2017 to January 2021, to compare maternal and neonatal outcomes of pregnancies complicated by gestational and pregestational diabetes, followed-up and delivered in a third level referral center before and after the introduction of a standardized multidisciplinary management protocol including diagnostic, screening, and management criteria.

RESULTS

Of the 131 women included, 55 were managed before the introduction of the multidisciplinary management protocol and included in group 1 (preprotocol), while 76 were managed according to the newly introduced multidisciplinary protocol and included in group 2 (after protocol). We observed an increase in the rates of vaginal delivery, rising from 32.7% to 64.5% (<0.001), and the rate of successful induction of labor improved from 28.6% to 86.2% (P < 0.001). No differences were found in neonatal outcomes, and the only significant difference was demonstrated for the rates of fetal macrosomia (20% versus 5.3%, P: 0.012). Therefore, the improvements observed in the maternal outcomes did not impact negatively on fetal and neonatal outcomes.

CONCLUSION

The introduction of a standardized multidisciplinary management protocol led to an improvement in the rates of vaginal delivery and in the rate of successful induction of labor in our center. A strong cooperation between obstetricians, diabetologists, and neonatologists is crucial to obtain a successful outcome in women with diabetes in pregnancy.

Predictive and diagnostic biomarkers for gestational diabetes and its associated metabolic and cardiovascular diseases

Gestational diabetes mellitus (GDM) is defined as the presence of high blood glucose levels with the onset, or detected for the first time during pregnancy, as a result of increased insulin resistance. GDM may be induced by dysregulation of pancreatic β-cell function and/or by alteration of secreted gestational hormones and peptides related with glucose homeostasis. It may affect one out of five pregnancies, leading to perinatal morbidity and adverse neonatal outcomes, and high risk of chronic metabolic and cardiovascular injuries in both mother and offspring. Currently, GDM diagnosis is based on evaluation of glucose homeostasis at late stages of pregnancy, but increased age and body-weight, and familiar or previous occurrence of GDM, may conditionate this criteria. In addition, an earlier and more specific detection of GDM with associated metabolic and cardiovascular risk could improve GDM development and outcomes. In this sense, 1st-2nd trimester-released biomarkers found in maternal plasma including adipose tissue-derived factors such as adiponectin, visfatin, omentin-1, fatty acid-binding protein-4 and retinol binding-protein-4 have shown correlations with GDM development. Moreover, placenta-related factors such as sex hormone-binding globulin, afamin, fetuin-A, fibroblast growth factors-21/23, ficolin-3 and follistatin, or specific micro-RNAs may participate in GDM progression and be useful for its recognition. Finally, urine-excreted metabolites such as those related with serotonin system, non-polar amino-acids and ketone bodies, may complete a predictive or early-diagnostic panel of biomarkers for GDM.

Predictive factors of subsequent insulin requirement for glycemic control during pregnancy at diagnosis of gestational diabetes mellitus

OBJECTIVE

To determine maternal and biological parameters at diagnosis of gestational diabetes mellitus (GDM) as predictors of antenatal insulin therapy (AIT) for glycemic control.

METHODS

In this planned secondary analysis of a prospective observational study, we recruited women diagnosed with GDM between July 1, 2014, and October 31, 2015. Maternal and biological parameters were analyzed as predictors of AIT using multivariable logistic regression analyses. Predictive accuracy of a cut-off value for a biological predictor was determined using the area under the receiver operating characteristic curve (AUC) and the Youden index (J).

RESULTS

Of 200 women included (mean gestational age 22 ± 6 weeks), 72 (36%) required AIT. No maternal characteristic was associated with AIT. Glycated hemoglobin (HbA1c; adjusted odds ratio [aOR] 3.15, 95% CI 1.03-9.69) and elevated 1-hour oral glucose tolerance test (OGTT; aOR 1.23, 95% CI 1.13-1.46) were predictors of AIT. Analyses suggested inaccurate prediction of AIT, with an optimal cut-off HbA1c value of 5.4% (J=0.14; AUC 0.58, 95% CI 0.48-0.67), and an optimal 1-hour plasma glucose OGTT value of 1.77 mg/dL (J=0.24; AUC 0.62, 95% CI 0.50-0.74).

CONCLUSION

HbA1c at diagnosis of GDM and elevated 1-hour OGTT were independent predictors of AIT for glycemic control. Clinicaltrials.gov: NCT02159378.