Closed-Loop Artificial Pancreas Therapy for Type 1 Diabetes

Do hybrid closed loop insulin pump systems improve glycemic control and reduce hospitalizations in poorly controlled type 1 diabetes?

OBJECTIVES

Hybrid closed-loop (HCL) systems improve glycemic control in type 1 diabetes mellitus (T1D), but their effectiveness in young, poorly controlled populations is not established and requires study.

METHODS

A pre-post study was performed using electronic health records of patients 3-24 years with baseline HbA1c≥9 % prescribed HCL within the New York City Health+Hospitals System assessing HbA1c levels and hospitalizations before and after HCL initiation and factors associated with achieving HbA1c<9 % after HCL initiation.

RESULTS

Of 47 children and adolescents who met inclusion criteria, 4.68 % female, 95.72 % non-White, and 82.22 % covered by public insurance, with a baseline average HbA1c 10.6 % (2.28 IQR). The most prevalent pump type was Omnipod 5 (70.21 %). The HbA1c was significantly lower in the postperiod than baseline (HbA1c before=median 10.6 (IQR2.28), HbA1c after=median 9.33 (IQR 2.97), difference 1.00 (IQR 1.64), p<0.05) with a decrease in median diabetes-related hospitalizations (preperiod 1.00 (IQR 1.00), postperiod 0.00 (IQR 1.00), difference -1.00, IQR 2, p<0.05). Lower baseline HbA1c levels made reaching HbA1c<9 % more likely. Multivariable analysis showed that the odds of having HbA1c of <9 % was 2.1 times less likely for every one point increase in baseline HbA1c and 12.5 times less likely for those with a pump at (p<0.05).

CONCLUSIONS

HCL therapy improved glycemic control and decreased diabetes-related hospitalizations in youth with poorly controlled T1DM. Higher baseline HbA1c levels predicted less success with HCL therapy so those who stand to benefit most benefit least.

Recent advances in the precision control strategy of artificial pancreas

The scientific diagnosis and treatment of patients with diabetes require frequent blood glucose testing and insulin delivery to normoglycemia. Therefore, an artificial pancreas with a continuous blood glucose (BG) monitoring function is an urgent research target in the medical industry. The problem of closed-loop algorithmic control of the BG with a time delay is a key and difficult issue that needs to be overcome in the development of an artificial pancreas. Firstly, the composition, structure, and control characteristics of the artificial pancreas are introduced. Subsequently, the research progress of artificial pancreas control algorithms is reviewed, and the characteristics, advantages, and disadvantages of proportional-integral-differential control, model predictive control, and artificial intelligence control are compared and analyzed to determine whether they are suitable for the practical application of the artificial pancreas. Additionally, key advancements in areas such as blood glucose data monitoring, adaptive models, wearable devices, and fully automated artificial pancreas systems are also reviewed. Finally, this review highlights that meal prediction, control safety, integration, streamlining the optimization of control algorithms, constant temperature preservation of insulin, and dual-hormone artificial pancreas are issues that require further attention in the future.

Comparative Effectiveness of Hybrid Closed-Loop Automated Insulin Delivery Systems Among Patients with Type 1 Diabetes

BACKGROUND

Clinical trials have demonstrated the efficacy and safety of hybrid closed-loop (HCL) systems, yet few studies have compared outcomes in the real-world setting.

METHOD

This retrospective study analyzed patients from an academic endocrinology practice between January 1, 2018, and November 18, 2022. The inclusion criteria were diagnosis code for type I diabetes (T1D), >18 years of age, new to any HCL system [Medtronic 670G/770G (MT), Tandem Control IQ (CIQ), or Omnipod 5 (OP5)], and availability of a pump download within three months. The outcomes included %time in range (TIR) of 70 to 180 mg/dL, %time below range (TBR) <70 mg/dL at 90 days, and HbA1c for 91 to 180 days.

RESULT

Of the 176 participants, 47 were MT, 74 CIQ, and 55 OP5. Median (25%, 75%) change in HbA1c was -0.1 (-0.8, 0.3), -0.6 (-1.1, -0.15), and -0.55 (-0.98, 0)% for MT, CIQ, and OP5, respectively, (P = .04). TIR was 70 (57, 76), 67 (59, 75), and 68 (60, 76)% (P = .95) at 90 days while TBR was 2 (1, 3), 1 (0, 2), and 1 (0, 1)%, respectively, (P = .002). The %time in automated delivery was associated with TIR and change in HbA1c. After controlling other factors including %time in automated delivery, HCL type was not an independent predictor of change in HbA1c nor TIR but remained a significant predictor of TBR.

CONCLUSION

There were significant reductions in HbA1c in CIQ and OP5. TIR was similar across pumps, but TBR was highest with MT. The %time in automated delivery likely explains differences in change in HbA1c but not TBR between HCL systems.

Characteristics associated with having a hemoglobin A1c ≤ 7 % (≤53 mmol/mol) among adults with type 1 diabetes using an automated insulin delivery system

BACKGROUND

We aim to investigate which characteristics are associated with having an HbA1c ≤ 7 % (≤53 mmol/mol) among adult automated insulin delivery (AID) users living with type 1 diabetes (T1D).

METHODS

Cross-sectional study using data from the T1D BETTER registry.

INCLUSION CRITERIA

aged ≥ 18 years old, using a commercial AID system, and with a reported HbA1c range value. Participants were divided into two groups (HbA1c ≤ 7 % group, N = 57; and HbA1c > 7 % group, N = 74).

RESULTS

A total of 131 participants were included: 61.8 % females, median age (Q1-Q3) was 43.0 (30.0, 55.0) years, and median duration of T1D was 24.0 (16.0, 36.0) years. Logistic regression analysis suggested that participants with a bachelor's degree or above were more likely (OR 3.04, 95 %CI 1.22, 7.58; P = 0.017) and with a longer duration of pump use were less likely (OR 0.90, 95 %CI 0.84, 0.98; P = 0.009) to report an HbA1c ≤ 7 % when using an AID, after adjusting for age, sex, body mass index, and annual household income.

CONCLUSIONS

Our study indicates that among AID users, in order to maximize benefits, additional support is needed for those who do not have a bachelor's degree and/or who have been using an insulin pump for a long time.

Emerging Diabetes Technologies: Continuous Glucose Monitors/Artificial Pancreases

Over the past decade there have been many advances in diabetes technologies, such as continuous glucose monitors (CGM s), insulin-delivery devices, and hybrid closed loop systems . Now most CGMs (Medtronic-Guardian, Dexcom-G6, and Abbott-Libre-2) have MARD values of < 10%, in contrast to two decades ago when the MARD used to be > 20%. In addition, the majority of the new CGMs do not require calibrations, and the latest CGMs last for 10-14 days. An implantable 6-months CGM by Eversense-3 is now approved in the USA and Europe. Recently, the FDA approved Libre 3 which provides real-time glucose values every minute. Even though it is approved as an iCGM it is not interoperable with automatic-insulin-delivery (AID) systems. The newer CGMs that are likely to be launched in the next few months in the USA include the 10-11 days Dexcom G7 (60% smaller than the existing G6), and the 7-days Medtronic Guardian 4. Most of the newer CGM have several features like automatic initialization, easy insertion, predictive alarms, and alerts. It has also been noticed that an arm insertion site might have better accuracy than abdomen or other sites, like the buttock for kids. Lag time between YSI and different sensors have been reported differently, sometimes it is down to 2-3 min; however, in many instances, it is still 15-20 min, especially when the rate of change of glucose is > 2 mg/min. We believe that in the next decade there will be a significant increase in the number of people who use CGM for their day-to-day diabetes care.

Advances in insulin therapy from discovery to β-cell replacement

Insulin therapy using insulin purified from porcine or bovine pancreas revolutionized diabetes therapy in the 1920s. A series of advances including cloning human insulin cDNA enabled the development of recombinant human insulin with improved features. Insulin treatment for diabetes may well be upended by β-cell replacement therapy in the coming decades.