Continuous Glucose Monitoring and Time in Range: Association with Adverse Outcomes among People with Type 2 or Gestational Diabetes Mellitus

Machine Learning-Based Prediction of Large-for-Gestational-Age Infants in Mothers With Gestational Diabetes Mellitus

CONTEXT

Large-for-gestational-age (LGA), one of the most common complications of gestational diabetes mellitus (GDM), has become a global concern. The predictive performance of common continuous glucose monitoring (CGM) metrics for LGA is limited.

OBJECTIVE

We aimed to develop and validate an artificial intelligence (AI)-based model to determine the probability of women with GDM giving birth to LGA infants during pregnancy using CGM measurements together with demographic data and metabolic indicators.

METHODS

A total of 371 women with GDM from a prospective cohort at a university hospital were included. CGM was performed during 20 to 34 gestational weeks, and glycemic fluctuations were evaluated and visualized in women with GDM who gave birth to LGA and non-LGA infants. A convolutional neural network (CNN)-based fusion model was developed to predict LGA. Comparisons among the novel fusion model and 3 conventional models were made using the area under the receiver operating characteristic curve (AUCROC) and accuracy.

RESULTS

Overall, 76 (20.5%) out of 371 GDM women developed LGA neonates. The visualized 24-hour glucose profiles differed at midmorning. This difference was consistent among subgroups categorized by pregestational body mass index, therapeutic protocol, and CGM administration period. The AI-based fusion prediction model using 24-hour CGM data and 15 clinical variables for LGA prediction (AUCROC 0.852; 95% CI, 0.680-0.966; accuracy 84.4%) showed superior discriminative power compared with the 3 classic models.

CONCLUSION

We demonstrated better performance in predicting LGA infants among women with GDM using the AI-based fusion model. The characteristics of the CGM profiles allowed us to determine the appropriate window for intervention.

Use of continuous glucose monitoring and hybrid closed-loop therapy in pregnancy

Continuous glucose monitoring (CGM) has led to a paradigm shift in the management of pregnant women with type 1 diabetes (T1D), with improved glycaemic control, less hypoglycaemia and fewer pregnancy complications. Data on CGM use in pregnant women with type 2 diabetes (T2D) are limited. A large randomized controlled trial (RCT) on CGM use in people with T2D in pregnancy is ongoing. Small studies on CGM use in women with gestational diabetes (GDM) have suggested improved glycaemic control and better qualification when insulin is needed. However, none of these studies was powered to evaluate pregnancy outcomes. Several large RCTs are ongoing in women with GDM. In addition to CGM, other technologies, such as advanced hybrid closed-loop (AHCL) systems have further improved glycaemic management in people with T1D. AHCL therapy adapts insulin delivery via a predictive algorithm integrated with CGM and an insulin pump. A large RCT with the AHCL CamAPS® FX demonstrated a 10% increase in time in range compared to standard insulin therapy in a pregnant population with T1D. Recently, an RCT of an AHCL system not approved for use in pregnancy (780G MiniMed) has also demonstrated additional benefits of AHCL therapy compared to standard insulin therapy, with improved time in range overnight, less hypoglycaemia and improved treatment satisfaction. More evidence is needed on the impact of AHCL therapy on maternal and neonatal outcomes and on which glycaemic targets with CGM should be used in pregnant women with T2D and GDM. We review the current evidence on the use of CGM and AHCL therapy in pregnancy.

Continuous Glucose Monitoring-Derived Differences in Pregnancies With and Without Adverse Perinatal Outcomes

OBJECTIVE

To evaluate whether continuous glucose monitoring (CGM)-derived glycemic patterns observed throughout pregnancy were associated with adverse perinatal outcomes, specifically fetal growth disorders and hypertensive disorders of pregnancy (HDP).

METHODS

We conducted a prospective observational study of individuals with viable singleton pregnancies and screening hemoglobin A 1c levels less than 6.5%. Those with preexisting diabetes were excluded. Enrollment occurred at the earliest gestational age before 17 weeks. Participants wore blinded continuous glucose monitors consecutively as willing until delivery. Those with at least 14 days of CGM data were included in analysis. Rates of large-for-gestational-age (LGA) neonates, small-for-gestational age (SGA) neonates, and HDP were assessed. Continuous glucose monitoring-derived glycemic metrics were calculated, including mean glucose level and percent time above and below thresholds. Two-sample t tests were used to compare glycemic metrics between participants with and without adverse perinatal outcomes.

RESULTS

Of 937 participants enrolled, 760 met inclusion criteria. Those delivering LGA neonates or who were diagnosed with HDP had higher mean glucose levels (102±9 vs 100±8, P =.01 and 103±8 vs 99±8, P <.001) and spent more time above 120 mg/dL (median 16% vs 12%, P =.006, and 16% vs 12%, P <.001, respectively) and above 140 mg/dL (median 3.9% vs 2.8%, P =.006, and 3.5% vs 2.8%, P <.001, respectively) throughout gestation than those without these outcomes. These findings were present regardless of gestational diabetes mellitus status. Participants with SGA neonates had lower mean glucose levels (97±7 vs 101±8, P =.01) and spent less time above 140 mg/dL (median 1.6% vs 2.3%, P =.01) and more time below 63 mg/dL (median 3.0% vs 2.3%, P =.02) than those without SGA neonates.

CONCLUSION

Individuals with LGA neonates or HDP exhibit a slightly higher mean glucose levels and spend more time hyperglycemic in early pregnancy than those who do not experience these outcomes.

Glycemic Profiles and Hypoglycemia Awareness Among Pregnant Women with Gestational and Pre-existing Diabetes Referred to a Tertiary Center in Sulaimaniyah-Iraq in 2024

Background

Hyperglycemia in pregnancy (HIP) comprises gestational diabetes mellitus (GDM) and pre-existing diabetes; type 1 diabetes (T1DM), type 2 diabetes (T2DM), and undetermined diabetes. Hyperglycemia in pregnancy leads to fetal and maternal complications.

Objectives

To observe and compare glycemic profiles (GP) and hypoglycemia awareness (HA) in women with GDM and pre-existing diabetes.

Methods

This prospective observational comparative study enrolled women with HIP registered at Sulaimani Maternity Teaching Hospital from January to April 2024. Self-monitoring blood glucose (SMBG) was used to document GP through mean blood glucose (MBG) analysis and the proportions of hyperglycemic, euglycemic, and hypoglycemic records. The Gold score was used to assess HA. Statistical analysis was conducted using SPSS version 27.0, employing chi-square, Mann-Whitney, Fisher's exact test, Kruskal-Wallis test, ANOVA, and independent t-tests. A P-value of ≤ 0.05 was considered significant.

Results

One hundred patients were included in the final analysis. Half of the women were over 35 years old, 53% had GDM, and 47% had pre-existing diabetes. The MBG levels at fasting, 1-hour post-breakfast, and post-dinner were significantly highest in T1DM and lowest in GDM, while the levels were similar after lunch. Compared with pre-existing diabetes, women with GDM had a significantly greater proportion of euglycemic records and a lesser proportion of hyperglycemic and hypoglycemic records. Daily insulin requirements were significantly higher in women with pre-existing diabetes than in those with GDM (0.52 ± 0.35 vs 0.24 ± 0.12 units/kg, respectively, P < 0.001). Hypoglycemia episodes (HE) were 5.7 vs 1.83 events/patient/month in pre-existing diabetes vs GDM, respectively (P = 0.002). Using the Gold score to determine HA, 40% of T1DM patients had reduced HA, 40% had borderline HA, while 20% of T1DM and patients with other types of diabetes had normal HA (P < 0.001).

Conclusions

Women with GDM had a significantly more stable GP, fewer HE, and lower insulin requirements than those with pre-existing diabetes. Type 1 diabetes patients had the most unstable GP, with significantly higher proportions of hyperglycemic and hypoglycemic records and reduced HA.

A Review of Third-Trimester Complications in Pregnancies Complicated by Diabetes Mellitus

Pregnancies affected by both pregestational and gestational diabetes mellitus carry an increased risk of adverse maternal and neonatal outcomes. While the risks associated with diabetes in pregnancy have been well documented and span across all trimesters, maternal and neonatal morbidity have been associated with select third-trimester complications. Further, modifiable risk factors have been identified that can help improve pregnancy outcomes. This review aims to examine the relationship between select third-trimester complications (large for gestational age, intrauterine fetal demise, hypertensive disorders of pregnancy, preterm birth, perineal lacerations, shoulder dystocia, and cesarean delivery) and the aforementioned modifiable risk factors, specifically glycemic control, blood pressure control, and gestational weight gain. It also highlights how early optimization of these modifiable risk factors can reduce adverse maternal, fetal, and neonatal outcomes. KEY POINTS: · Diabetes mellitus in pregnancy increases the risk of third-trimester complications.. · Modifiable risk factors exist for these complications.. · Optimizing these modifiable risk factors improves maternal and neonatal outcomes..

Continuous Glucose Monitoring in Pregnancy

Diabetes mellitus in pregnancy is associated with adverse maternal and neonatal outcomes. Optimal glycemic control is associated with improved outcomes. Continuous glucose monitoring is a less invasive alternative to blood glucose measurements. Two types of continuous glucose monitoring are available in the market: real time and intermittently scanned. Continuous glucose monitoring is gaining popularity and is now recommended by some societies for glucose monitoring in pregnant women. In this review, we discuss the differences between the two types of continuous glucose monitoring, optimal treatment goals, and whether there is an improvement in maternal or neonatal outcomes.

Progress and indication for use of continuous glucose monitoring in patients with diabetes in pregnancy: a review

Gestational diabetes mellitus is one of the most common endocrine diseases that occur during pregnancy. Disorders of blood glucose metabolism during pregnancy can increase the risk of adverse pregnancy outcomes, such as pregnancy-related hypertension, preeclampsia, eclampsia, miscarriage, macrosomia, and neonatal hypoglycemia. Continuous glucose monitoring (CGM) can safely and effectively monitor blood glucose changes in patients with gestational hyperglycemia, thereby reducing adverse pregnancy outcomes. Hence, this article aimed to provide a comprehensive review of the progress and indications for using CGM in pregnant patients with diabetes. CGM can reduce blood glucose fluctuations and the occurrence of serious hypoglycemia and hyperglycemia events and can provide time in range (TIR). TIR is an important indicator of blood glucose level. Patients with a higher TIR during pregnancy have better gestational outcomes.