Review of Automated Insulin Delivery Systems for Individuals with Type 1 Diabetes: Tailored Solutions for Subpopulations.
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ABSTRACT:
SUBMITTER: Aiello EM
PROVIDER: S-EPMC8336917 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature
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Review of Automated Insulin Delivery Systems for Individuals with Type 1 Diabetes: Tailored Solutions for Subpopulations.
Aiello Eleonora M EM Deshpande Sunil S Ozaslan Basak B Wolkowicz Kelilah L KL Dassau Eyal E Pinsker Jordan E JE Doyle Francis J FJ
Current opinion in biomedical engineering 20210618
Automated insulin delivery (AID) systems have proven safe and effective in improving glycemic outcomes in individuals with type 1 diabetes (T1D). Clinical evaluation of this technology has progressed to large randomized, controlled outpatient studies and recent commercial approval of AID systems for children and adults. However, several challenges remain in improving these systems for different subpopulations (e.g., young children, athletes, pregnant women, seniors and those with hypoglycemia un ...[more]
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Project description:BackgroundAutomated insulin delivery (AID) systems have shown to improve glycemic control in a range of populations and settings. At the start of this study, only one commercial AID system had entered the Austrian market (MiniMed 670G, Medtronic). However, there is an ever-growing community of people living with type 1 diabetes (PWT1D) using open-source (OS) AID systems.Materials and methodsA total of 144 PWT1D who used either the MiniMed 670G (670G) or OS-AID systems routinely for a period of at least three to a maximum of six months, between February 18, 2020 and January 15, 2023, were retrospectively analyzed (116 670G aged from 2.6 to 71.8 years and 28 OS-AID aged from 3.4 to 53.5 years). The goal is to evaluate and compare the quality of glycemic control of commercially available AID and OS-AID systems and to present all data by an in-depth descriptive analysis of the population. No statistical tests were performed.ResultsThe PWT1D using OS-AID systems spent more time in range (TIR)70-180 mg/dL (81.7% vs 73.9%), less time above range (TAR)181-250 mg/dL (11.1% vs 19.6%), less TAR>250 mg/dL (2.5% vs 4.3%), and more time below range (TBR)54-69 mg/dL (2.2% vs 1.7%) than PWT1D using the 670G system. The TBR<54 mg/dL was comparable in both groups (0.3% vs 0.4%). In the OS-AID group, median glucose level and glycated hemoglobin (HbA1c) were lower than in the 670G system group (130 vs 150 mg/dL; 6.2% vs 7.0%).ConclusionIn conclusion, both groups were able to achieve satisfactory glycemic outcomes independent of age, gender, and diabetes duration. However, the PWT1D using OS-AID systems attained an even better glycemic control with no clinical safety concerns.
| S-EPMC11571566 | biostudies-literature
Project description:BackgroundClinical trials have demonstrated the efficacy and safety of hybrid closed-loop (HCL) systems, yet few studies have compared outcomes in the real-world setting.MethodThis 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.ResultOf 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.ConclusionThere 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.
| S-EPMC11571516 | biostudies-literature
Project description:Automated insulin delivery (AID) systems play an important role in the management of type 1 diabetes mellitus (T1DM). These systems include three components: a continuous glucose monitor (CGM), an insulin pump and an algorithm that adjusts the pump based on the CGM sensor glucose readings. They are not fully automated and still require the user to administer bolus insulin doses for food. Some AID systems have automatic correction boluses, while others only have automatic basal or background insulin adjustments. As CGM has become more accurate and the technology has evolved, AID systems have demonstrated improved glycaemic outcomes. The clinical evaluation of AID systems in randomized controlled trials and real-world studies have shown their utility in helping glycaemic management. In this review, we compare AID systems that are commercially available in the US and summarize the literature, with a special focus on time in range in T1DM. The review also discusses new AID systems on the horizon and explores considerations for personalized care.
| S-EPMC9354504 | biostudies-literature
Project description:Background: Use of sodium-glucose cotransporter 2 inhibitors (SGLT2i) as adjunct therapy to insulin in type 1 diabetes (T1D) has been previously studied. In this study, we present data from the first free-living trial combining low-dose SGLT2i with commercial automated insulin delivery (AID) or predictive low glucose suspend (PLGS) systems. Methods: In an 8-week, randomized, controlled crossover trial, adults with T1D received 5 mg/day empagliflozin (EMPA) or no drug (NOEMPA) as adjunct to insulin therapy. Participants were also randomized to sequential orders of AID (Control-IQ) and PLGS (Basal-IQ) systems for 4 and 2 weeks, respectively. The primary endpoint was percent time-in-range (TIR) 70-180 mg/dL during daytime (7:00-23:00 h) while on AID (NCT04201496). Findings: A total of 39 subjects were enrolled, 35 were randomized, 34 (EMPA; n = 18 and NOEMPA n = 16) were analyzed according to the intention-to-treat principle, and 32 (EMPA; n = 16 and NOEMPA n = 16) completed the trial. On AID, EMPA versus NOEMPA had higher daytime TIR 81% versus 71% with a mean estimated difference of +9.9% (confidence interval [95% CI] 0.6-19.1); p = 0.04. On PLGS, the EMPA versus NOEMPA daytime TIR was 80% versus 63%, mean estimated difference of +16.5% (95% CI 7.3-25.7); p < 0.001. One subject on SGLT2i and AID had one episode of diabetic ketoacidosis with nonfunctioning insulin pump infusion site occlusion contributory. Interpretation: In an 8-week outpatient study, addition of 5 mg daily empagliflozin to commercially available AID or PLGS systems significantly improved daytime glucose control in individuals with T1D, without increased hypoglycemia risk. However, the risk of ketosis and ketoacidosis remains. Therefore, future studies with SGLT2i will need modifications to closed-loop control algorithms to enhance safety.
| S-EPMC9464084 | biostudies-literature
Project description:ImportanceThere is a need for additional treatment options for people with type 2 diabetes treated with insulin. Given the limited data on the use of automated insulin delivery (AID) systems in type 2 diabetes, studies evaluating their safety and efficacy are important.ObjectiveTo evaluate the association of AID with hemoglobin A1c (HbA1c) levels in a diverse cohort of adults with type 2 diabetes.Design, setting, and participantsThis single-arm prospective trial was conducted at 21 clinical centers in the United States among individuals aged 18 to 75 years with type 2 diabetes who had been using insulin for at least 3 months prior to screening. Participants with AID system use were excluded. The study started with a 14-day standard therapy phase, followed by 13 weeks of treatment with the investigational device. The first participant was enrolled April 11, 2023, and the last participant follow-up visit was February 29, 2024.InterventionParticipants used the Omnipod 5 AID System for 13 weeks following the 14-day standard therapy phase.Main outcomes and measuresPrimary outcome was change in HbA1c level at 13 weeks, tested sequentially for noninferiority (0.3% margin) and superiority, compared with baseline.ResultsAmong 305 participants (mean [SD] age, 57 [11] years; 175 [57%] female; 72 [24%] Black, 66 [22%] Hispanic or Latino, and 153 [50%] White), 289 (95%) completed the trial. At baseline, 223 (73%) were using multiple daily injections, 63 (21%) were using basal insulin without bolus, 17 (6%) were using an insulin pump, 188 (62%) were using continuous glucose monitoring, 168 (55%) were using glucagon-like peptide-1 receptor agonists (GLP-1RAs), and 134 (44%) were using sodium-glucose transport protein 2 inhibitors (SGLT-2is). Following AID use, HbA1c levels decreased from a mean (SD) of 8.2% (1.3) at baseline to 7.4% (0.9) at 13 weeks (mean difference, -0.8 [95% CI, -1.0 to -0.7] percentage points; P < .001 for noninferiority and superiority). Improvement was seen across various subgroups (age, sex, race and ethnicity, insurance), and notably with or without use of GLP-1RAs or SGLT-2is and regardless of pretrial mealtime insulin regimen. Time in target glucose range (70-180 mg/dL) increased from a mean (SD) of 45% (25) to 66% (17) (mean difference, 20 [95% CI, 18 to 22] percentage points; P < .001). Percentage of time in hypoglycemic ranges of less than 54 mg/dL and less than 70 mg/dL was noninferior compared with standard therapy. There was 1 episode of severe hypoglycemia and none of diabetic ketoacidosis or hyperosmolar hyperglycemic syndrome.Conclusions and relevanceIn this nonrandomized clinical trial, HbA1c levels were lower in a diverse cohort of adults with type 2 diabetes following AID initiation, suggesting that AID may be a beneficial and safe option for people with type 2 diabetes using insulin.Trial registrationClinicalTrials.gov Identifier: NCT05815342.
| S-EPMC11829226 | biostudies-literature
Project description:BackgroundEmerging research suggests that open-source automated insulin delivery (AID) may reduce diabetes burden and improve sleep quality and quality of life (QoL). However, the evidence is mostly qualitative or uses unvalidated, study-specific, single items. Validated person-reported outcome measures (PROMs) have demonstrated the benefits of other diabetes technologies. The relative lack of research investigating open-source AID using PROMs has been considered a missed opportunity.ObjectiveThis study aimed to examine the psychosocial outcomes of adults with type 1 diabetes using and not using open-source AID systems using a comprehensive set of validated PROMs in a real-world, multinational, cross-sectional study.MethodsAdults with type 1 diabetes completed 8 validated measures of general emotional well-being (5-item World Health Organization Well-Being Index), sleep quality (Pittsburgh Sleep Quality Index), diabetes-specific QoL (modified DAWN Impact of Diabetes Profile), diabetes-specific positive well-being (4-item subscale of the 28-item Well-Being Questionnaire), diabetes treatment satisfaction (Diabetes Treatment Satisfaction Questionnaire), diabetes distress (20-item Problem Areas in Diabetes scale), fear of hypoglycemia (short form of the Hypoglycemia Fear Survey II), and a measure of the impact of COVID-19 on QoL. Independent groups 2-tailed t tests and Mann-Whitney U tests compared PROM scores between adults with type 1 diabetes using and not using open-source AID. An analysis of covariance was used to adjust for potentially confounding variables, including all sociodemographic and clinical characteristics that differed by use of open-source AID.ResultsIn total, 592 participants were eligible (attempting at least 1 questionnaire), including 451 using open-source AID (mean age 43, SD 13 years; n=189, 41.9% women) and 141 nonusers (mean age 40, SD 13 years; n=90, 63.8% women). Adults using open-source AID reported significantly better general emotional well-being and subjective sleep quality, as well as better diabetes-specific QoL, positive well-being, and treatment satisfaction. They also reported significantly less diabetes distress, fear of hypoglycemia, and perceived less impact of the COVID-19 pandemic on their QoL. All were medium-to-large effects (Cohen d=0.5-1.5). The differences between groups remained significant after adjusting for sociodemographic and clinical characteristics.ConclusionsAdults with type 1 diabetes using open-source AID report significantly better psychosocial outcomes than those not using these systems, after adjusting for sociodemographic and clinical characteristics. Using validated, quantitative measures, this real-world study corroborates the beneficial psychosocial outcomes described previously in qualitative studies or using unvalidated study-specific items.
| S-EPMC10755653 | biostudies-literature
Project description:AimThe purpose of this study was to develop a questionnaire to examine the future acceptance of Automatic insulin delivery systems (AIDs), their perceived usefulness, ease of use, and trust in the device in subjects with type 1 diabetes (T1D).MethodsA questionnaire in Italian, based on the Technology Acceptance Model, was developed to examine intention to use AIDs, considered as a measure of future acceptance, and its determinants to use the system. A total of 43 questions for children and 46 for parents were included, and a 5-point Likert scale was used.Results239 subjects with T1D using multiple daily injections (MDI) or sensor-augmented pump (SAP) and their parents completed the questionnaire. The completion rate was excellent, with almost 100% of items answered. The overall Cronbach's coefficient for children and adolescents was 0.92 and 0.93 for parents, indicating excellent internal consistency in both groups. Parent-youth agreement was 0.699 (95% confidence interval: 0.689-0.709), indicating a good agreement between the two evaluations. Factor analysis identified measurement factors for the "artificial pancreas (AP)-acceptance labeled benefits and hassles of AIDs, and the internal consistency of the total scale was alpha = 0.94 for subjects with T1D and 0.95 for parents. The level of AP acceptance was more than neutral: 3.91 ± 0.47 and 3.99 ± 0.43 (p = 0.07) for youths and parents, respectively (possible score range 1 to 5, neutral score is 3.0). Parents reported higher scores in the benefit items than children-adolescents (p = 0.04).ConclusionsWe developed a new questionnaire based on the items available in the literature, and we demonstrated that the "AP-acceptance" reveals a meaningful factor structure, good internal reliability, and agreement between parent-young people evaluations. This measure could be a valuable resource for clinicians and researchers to assess AP acceptance in pediatric patients with T1D and their parents. This patient profiling approach could help to enroll candidates for AIDs with proper expectations and who most likely will benefit from the system.
| S-EPMC11861114 | biostudies-literature
Project description:Type 1 diabetes (T1D) increases the risk for pregnancy complications. Increased time in the pregnancy glucose target range (63-140 mg/dL as suggested by clinical guidelines) is associated with improved pregnancy outcomes that underscores the need for tight glycemic control. While closed-loop control is highly effective in regulating blood glucose levels in individuals with T1D, its use during pregnancy requires adjustments to meet the tight glycemic control and changing insulin requirements with advancing gestation. In this paper, we tailor a zone model predictive controller (zone-MPC), an optimization-based control strategy that uses model predictions, for use during pregnancy and verify its robustness in-silico through a broad range of scenarios. We customize the existing zone-MPC to satisfy pregnancy-specific glucose control objectives by having (i) lower target glycemic zones (i.e., 80-110 mg/dL daytime and 80-100 mg/dL overnight), (ii) more assertive correction bolus for hyperglycemia, and (iii) a control strategy that results in more aggressive postprandial insulin delivery to keep glucose within the target zone. The emphasis is on leveraging the flexible design of zone-MPC to obtain a controller that satisfies glycemic outcomes recommended for pregnancy based on clinical insight. To verify this pregnancy-specific zone-MPC design, we use the UVA/Padova simulator and conduct in-silico experiments on 10 subjects over 13 scenarios ranging from scenarios with ideal metabolic and treatment parameters for pregnancy to extreme scenarios with such parameters that are highly deviant from the ideal. All scenarios had three meals per day and each meal had 40 grams of carbohydrates. Across 13 scenarios, pregnancy-specific zone-MPC led to a 10.3 ± 5.3% increase in the time in pregnancy target range (baseline zone-MPC: 70.6 ± 15.0%, pregnancy-specific zone-MPC: 80.8 ± 11.3%, p < 0.001) and a 10.7 ± 4.8% reduction in the time above the target range (baseline zone-MPC: 29.0 ± 15.4%, pregnancy-specific zone-MPC: 18.3 ± 12.0, p < 0.001). There was no significant difference in the time below range between the controllers (baseline zone-MPC: 0.5 ± 1.2%, pregnancy-specific zone-MPC: 3.5 ± 1.9%, p = 0.1). The extensive simulation results show improved performance in the pregnancy target range with pregnancy-specific zone MPC, suggest robustness of the zone-MPC in tight glucose control scenarios, and emphasize the need for customized glucose control systems for pregnancy.
| S-EPMC8982146 | biostudies-literature
Project description:Automated insulin delivery systems, also known as closed-loop or 'artificial pancreas' systems, are transforming the management of type 1 diabetes. These systems consist of an algorithm which responds to real-time glucose sensor levels by automatically modulating insulin delivery through an insulin pump. We review the rapidly changing landscape of automated insulin-delivery systems over recent decades, from initial prototypes to the different hybrid closed-loop systems commercially available today. We discuss the growing body of clinical trials and real-world evidence demonstrating their glycaemic and psychosocial benefits. We also address future directions in automated insulin delivery such as dual-hormone systems and adjunct therapy as well as the challenges around ensuring equitable access to closed-loop technology.
| S-EPMC10448576 | biostudies-literature
Project description:BackgroundAutomated insulin delivery (AID) algorithms can benefit from tuning of their aggressiveness to meet individual needs, as insulin requirements vary among and within users. We introduce the Performance-Based Adaptation Index (PAI), a tool designed to enable automatic adjustment of an AID system aggressiveness based on continuous glucose monitoring (CGM) metrics.MethodsPAI integrates two CGM-based metrics-one for hypoglycemia and another for hyperglycemia exposure-over a previous time window into a single index (αθ). We propose two methods to compute αθ: one based on time in range (TIR, 70-180 mg/dL), and the other on glycemic risk indices. Using αθ, we developed a multiplicative strategy to adjust the AID system's aggressiveness, accounting for situations where αθ cannot be reliably calculated. The feasibility of this method was assessed in-silico using the UVA/Padova Type 1 Diabetes Simulator and our full closed-loop algorithm (UVA-model predictive control (MPC)) across five scenarios: optimal tuning (baseline), conservative and aggressive tunings, and temporary and permanent changes in insulin needs. Glycemic outcomes were evaluated from the simulated glucose traces.ResultsNegligible performance variations were observed in the baseline scenario. For the conservative scenario, adjusting αθ improved TIR (35.1% vs 71.8%) and increased total daily insulin (32.1 U vs 41.2 U). Conversely, for the aggressive scenario, it reduced hypoglycemia exposure (TBR: 2.6% vs 1.4%) and overall insulin usage (45.6 U vs 43.0 U).ConclusionIn-silico results demonstrated the safety and efficacy of using PAI to automatically tune the UVA-MPC controller, achieving TIR values above 70% under fully closed-loop conditions and across various physiological states. Clinical validation of these results is warranted.
| S-EPMC11803600 | biostudies-literature