Real-world use of Control-IQ™ technology automated insulin delivery in pregnancy: A case series with qualitative interviews

Real-World Evidence of Off-Label Use of Commercially Automated Insulin Delivery Systems Compared to Multiple Daily Insulin Injections in Pregnancies Complicated by Type 1 Diabetes

Aims: To compare glycemic control and maternal-fetal outcomes of women with type 1 diabetes (T1D) using hybrid closed loop (HCL) versus multiple daily insulin injections (MDI) plus continuous glucose monitoring. Methods: Multicenter prospective cohort study of pregnant women with T1D in Spain. We evaluated HbA1c and time spent within (TIR), below (TBR), and above (TAR) the pregnancy-specific glucose range of 3.5-7.8 mmol/L. Adjusted models were performed for adverse pregnancy outcomes, including baseline maternal characteristics and center. Results: One hundred twelve women were included (HCL n = 59). Women in the HCL group had a longer duration of diabetes and higher rates of prepregnancy care. There was no between-group difference in HbA1c in any trimester. However, in the second trimester, MDI users had a greater decrease in HbA1c (-6.12 ± 9.06 vs. -2.16 ± 7.42 mmol/mol, P = 0.031). No difference in TIR (3.5-7.8 mmol/L) and TAR was observed between HCL and MDI users, but with a higher total insulin dose in the second trimester [+0.13 IU/kg·day)]. HCL therapy was associated with increased maternal weight gain during pregnancy (βadjusted = 3.20 kg, 95% confidence interval [CI] 0.90-5.50). Regarding neonatal outcomes, newborns of HCL users were more likely to have higher birthweight (βadjusted = 279.0 g, 95% CI 39.5-518.5) and macrosomia (ORadjusted = 3.18, 95% CI 1.05-9.67) compared to MDI users. These associations disappeared when maternal weight gain or third trimester HbA1c was included in the models. Conclusions: In a real-world setting, HCL users gained more weight during pregnancy and had larger newborns than MDI users, while achieving similar glycemic control in terms of HbA1c and TIR.

Real-world data on the Minimed 780G advanced hybrid closed-loop system use during type 1 diabetes pregnancy: One centre observational study

Aim The efficacy of hybrid closed-loop systems (HCLs) in managing glycemic control in pregnant women with type 1 diabetes remains inadequately characterized. We evaluated the use of the Medtronic Minimed 780G HCLs.

METHODS

The retrospective observational study analyzed the glycemic and perinatal outcomes of pregnant women using the HCLs, followed at our tertiary centre. Independent t-tests were employed to compare data among trimesters based on pre-pregnancy HbA1c. The associations between glycemic parameters and perinatal outcomes were explored using Spearman rho.

RESULTS

Among the 21 women (age: 33.5 ± 4.2 years, diabetes duration: 21.2 ± 7.6 years, pre-pregnancy HbA1c 7.0 ± 1.1 % (52.9 ± 11.9 mmol/mol)) time in range (pTIR, 63-140 mg/dl; 3.5-7.8 mmol/l) increased progressively throughout pregnancy (trimesters: first: 64.0 ± 9.0 %; second:71.3 ± 11.8 %; third: 75.7 ± 8.1 %). Simultaneously, mean sensor glucose decreased (trimesters: first: 130 ± 10.4 mg/dl (7.2 ± 0.6 mmol/l); second: 120.9 ± 13.4 mg/dl (6.7 ± 0.7 mmol/l); third: 117.3 ± 9.1 mg/dl (6.5 ± 0.5 mmol/l)). Although a majority of women achieved the target pTIR until the third trimester, this did not consistently prevent the delivery of a large-for-gestational-age baby. Notably, one ketoacidosis event occurred, and there were no reported instances of severe hypoglycemia.

CONCLUSION

Use of the Minimed 780G HCLs enabled the attainment of recommended pregnancy glycemic targets for most women with type 1 diabetes in a real-world setting.

An automated insulin delivery system from pregestational care to postpartum in women with type 1 diabetes. Preliminary experience with telemedicine in 6 patients

INTRODUCTION

The use of most commercially available automated insulin delivery (AID) systems is off-label in pregnancy. However, an increasing number of women with type 1 diabetes (T1D) use such devices throughout pregnancy and delivery. We analysed the data of six women with T1D from a single centre (Diabetology Outpatient Clinic of District-63/Asl Salerno, Italy) who were able to start and maintain AID therapy with the MiniMed™ 780G (Medtronic, Minneapolis, MN, USA) throughout the pregestational care period, pregnancy, delivery, and postpartum.

METHODS

We retrospectively collected data from six patients with T1D who received training and initiation on use of the MiniMed™ 780G and attended follow-up visits throughout pregnancy (these visits were virtual because of the COVID-19 pandemic). All patients maintained their devices in the closed-loop setting throughout pregnancy and during labour and delivery. We analysed data from the pregestational phase to the first 30 days postpartum.

RESULTS

All patients achieved the recommended metabolic goals before conception [median time in range (TIR) of 88% for 70-180 mg/dL; median pregnancy-specific TIR 63-140 mg/dL (ps-TIR) of 66% and maintained the ps-TIR until delivery (median ps-TIR 83%). All patients had slightly better metrics during the night than during the day, with a very low time below range of < 63 mg/dL. Optimal glycaemic values were also maintained on the day of labour and delivery (median ps-TIR 92.5%) and in the first 30 days postpartum, with no severe hypoglycaemia. The only neonatal complications were jaundice in one child and an interatrial defect in another child.

CONCLUSION

In our well-selected and trained patients, use of the MiniMed™ 780G helped to achieve and maintain ps-metrics from the pregestational period to delivery despite the fact that the algorithm is not set to achieve the ambitious glycaemic values recommended for pregnancy.

Neural-Net Artificial Pancreas: A Randomized Crossover Trial of a First-in-Class Automated Insulin Delivery Algorithm

Background: Automated insulin delivery (AID) is now integral to the clinical practice of type 1 diabetes (T1D). The objective of this pilot-feasibility study was to introduce a new regulatory and clinical paradigm-a Neural-Net Artificial Pancreas (NAP)-an encoding of an AID algorithm into a neural network that approximates its action and assess NAP versus the original AID algorithm. Methods: The University of Virginia Model-Predictive Control (UMPC) algorithm was encoded into a neural network, creating its NAP approximation. Seventeen AID users with T1D were recruited and 15 participated in two consecutive 20-h hotel sessions, receiving in random order either NAP or UMPC. Their demographic characteristics were ages 22-68 years old, duration of diabetes 7-58 years, gender 10/5 female/male, White Non-Hispanic/Black 13/2, and baseline glycated hemoglobin 5.4%-8.1%. Results: The time-in-range (TIR) difference between NAP and UMPC, adjusted for entry glucose level, was 1 percentage point, with absolute TIR values of 86% (NAP) and 87% (UMPC). The two algorithms achieved similar times <70 mg/dL of 2.0% versus 1.8% and coefficients of variation of 29.3% (NAP) versus 29.1 (UMPC)%. Under identical inputs, the average absolute insulin-recommendation difference was 0.031 U/h. There were no serious adverse events on either controller. NAP had sixfold lower computational demands than UMPC. Conclusion: In a randomized crossover study, a neural-network encoding of a complex model-predictive control algorithm demonstrated similar performance, at a fraction of the computational demands. Regulatory and clinical doors are therefore open for contemporary machine-learning methods to enter the AID field. Clinical Trial Registration number: NCT05876273.

Use of Advanced Hybrid Closed-Loop System during Pregnancy: Strengths and Limitations of Achieving a Tight Glycemic Control

Background: Pregnant women with type 1 diabetes mellitus (T1DM) face an elevated risk of complications for both themselves and their newborns. Experts recommend strict glycemic control. The advanced hybrid closed-loop (AHCL) system, though not officially approved for pregnant T1DM patients, is promising for optimal glycemic control. Methods: We collected CGM metrics, HbA1c levels, insulin pump settings, and doses from a 33-year-old pregnant woman with 23-year history of T1DM from the 6th week of gestation to birth. She was initially on continuous insulin pump therapy with CGM and switched to the AHCL system (MiniMedTM 780G, Medtronic, Northridge, CA, USA) between weeks 13 and 14. Results: The AHCL system improved glycemic control from weeks 14 to 26, achieving international guidelines with TIR = 72%, TAR = 24%, TBR = 4%. At week 30, TIR was 66%, TAR 31%. By altering diet and adding 'fake carbohydrates', she maintained TIR ≥ 70%, TBR ≤ 4%, TAR ≤ 26% from week 34 to birth. A healthy 4 kg, 53 cm baby boy was born at week 38. Conclusions: The use of the AHCL system holds significant promise for improving glycemic control in pregnancy. Optimal glycemic control with MiniMedTM 780G in pregnancy requires accurate carbohydrate counting, specific timing of insulin doses in relation to meal consumption and dietary choices that reduce the glycemic load of meals continue to be crucial factors in achieving optimal glycemic control during pregnancy using the MiniMedTM 780G system. Further research and clinical studies are needed to explore the full potential of these advanced systems in managing T1DM during pregnancy and optimizing maternal and neonatal outcomes.

Effect of artificial pancreas system use on glycaemic control among pregnant women with type 1 diabetes mellitus: A meta-analysis of randomized controlled trials

AIM

To assess the efficacy of artificial pancreas systems (APS) use among pregnant women with type 1 diabetes mellitus (T1DM) by conducting a meta-analysis.

METHODS

We searched five databases, including EMBASE, Web of Science, PubMed, Cochrane Library and SCOPUS, for literature on APS use among pregnant women with T1DM before October 9, 2023. The primary endpoint was 24-hour time in range (TIR; 3.5-7.8 mmol/L). Secondary endpoints included glycaemic metrics for 24-hour (mean blood glucose [MBG], time above range [TAR], time below range [TBR]), and overnight TIR and TBR.

RESULTS

We identified four randomized controlled trials involving 164 participants; one study with 16 participants focused on overnight APS use, and the other three focused on 24-hour APS use. Compared with standard care, APS exhibited a favourable effect on 24-hour TIR (standard mean difference [SMD] = 0.53, 95% confidence interval [CI] 0.25, 0.80, P < 0.001), overnight TIR (SMD = 0.67, 95% CI 0.39, 0.95, P < 0.001), and overnight TBR (<3.5 mmol/L; SMD = -0.49, 95% CI -0.77, -0.21 P < 0.001), while there was no significant difference in 24-hour TAR, 24-hour TBR, or MBG between the two groups. We further conducted subgroup analyses after removing the trial focused on overnight APS use and showed that 24-hour APS use reduced not only the 24-hour TIR (SMD = 0.41, 95% CI 0.12, 0.71; P = 0.007) but also the 24-hour TBR (<2.8 mmol/L; SMD = -0.77, 95% CI -1.32, -0.23, P = 0.006).

CONCLUSION

Our findings suggest that APS might improve 24-hour TIR and overnight glycaemic control, and 24-hour APS use also significantly reduced 24-hour TBR (2.8 mmol/L) among pregnant women with T1DM.

Automated Insulin Delivery for Pregnant Women With Type 1 Diabetes: Where do we stand?

Automated insulin delivery (AID) systems mimic an artificial pancreas via a predictive algorithm integrated with continuous glucose monitoring (CGM) and an insulin pump, thereby providing AID. Outside of pregnancy, AID has led to a paradigm shift in the management of people with type 1 diabetes (T1D), leading to improvements in glycemic control with lower risk for hypoglycemia and improved quality of life. As the use of AID in clinical practice is increasing, the number of women of reproductive age becoming pregnant while using AID is also expected to increase. The requirement for lower glucose targets than outside of pregnancy and for frequent adjustments of insulin doses during pregnancy may impact the effectiveness and safety of AID when using algorithms for non-pregnant populations with T1D. Currently, the CamAPS® FX is the only AID approved for use in pregnancy. A recent randomized controlled trial (RCT) with CamAPS® FX demonstrated a 10% increase in time in range in a pregnant population with T1D and a baseline glycated hemoglobin (HbA1c) ≥ 48 mmol/mol (6.5%). Off-label use of AID not approved for pregnancy are currently also being evaluated in ongoing RCTs. More evidence is needed on the impact of AID on maternal and neonatal outcomes. We review the current evidence on the use of AID in pregnancy and provide an overview of the completed and ongoing RCTs evaluating AID in pregnancy. In addition, we discuss the advantages and challenges of the use of current AID in pregnancy and future directions for research.

Off-label use of an automated insulin delivery system in pregnant women with type 1 diabetes

Using commercially available automated insulin delivery (AID) systems for treating type 1 diabetes during pregnancy remains controversial. This retrospective study assessed six pregnant women with type 1 diabetes who underwent AID therapy. Our observations revealed that AID treatment, in most cases, did not achieve the desired glycemic targets for pregnancy.