Trial of Hybrid Closed-Loop Control in Young Children with Type 1 Diabetes.

BACKGROUND: Closed-loop control systems of insulin delivery may improve glycemic outcomes in young children with type 1 diabetes. The efficacy and safety of initiating a closed-loop system virtually are unclear. METHODS: In this 13-week, multicenter trial, we randomly assigned, in a 2:1 ratio, children who were at least 2 years of age but younger than 6 years of age who had type 1 diabetes to receive treatment with a closed-loop system of insulin delivery or standard care that included either an insulin pump or multiple daily injections of insulin plus a continuous glucose monitor. The primary outcome was the percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter, as measured by continuous glucose monitoring. Secondary outcomes included the percentage of time that the glucose level was above 250 mg per deciliter or below 70 mg per deciliter, the mean glucose level, the glycated hemoglobin level, and safety outcomes. RESULTS: A total of 102 children underwent randomization (68 to the closed-loop group and 34 to the standard-care group); the glycated hemoglobin levels at baseline ranged from 5.2 to 11.5%. Initiation of the closed-loop system was virtual in 55 patients (81%). The mean (±SD) percentage of time that the glucose level was within the target range increased from 56.7±18.0% at baseline to 69.3±11.1% during the 13-week follow-up period in the closed-loop group and from 54.9±14.7% to 55.9±12.6% in the standard-care group (mean adjusted difference, 12.4 percentage points [equivalent to approximately 3 hours per day]; 95% confidence interval, 9.5 to 15.3; P<0.001). We observed similar treatment effects (favoring the closed-loop system) on the percentage of time that the glucose level was above 250 mg per deciliter, on the mean glucose level, and on the glycated hemoglobin level, with no significant between-group difference in the percentage of time that the glucose level was below 70 mg per deciliter. There were two cases of severe hypoglycemia in the closed-loop group and one case in the standard-care group. One case of diabetic ketoacidosis occurred in the closed-loop group. CONCLUSIONS: In this trial involving young children with type 1 diabetes, the glucose level was in the target range for a greater percentage of time with a closed-loop system than with standard care. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases; PEDAP ClinicalTrials.gov number, NCT04796779.).

Managing Diabetes in Pregnancy Before, During, and After COVID-19.

Background: Pregnant women with diabetes are identified as being more vulnerable to the severe effects of COVID-19 and advised to stringently follow social distancing measures. Here, we review the management of diabetes in pregnancy before and during the lockdown. Methods: Majority of antenatal diabetes and obstetric visits are provided remotely, with pregnant women attending hospital clinics only for essential ultrasound scans and labor and delivery. Online resources for supporting women planning pregnancy and for self-management of pregnant women with type 1 diabetes (T1D) using intermittent or continuous glucose monitoring are provided. Retinal screening procedures, intrapartum care, and the varying impact of lockdown on maternal glycemic control are considered. Alternative screening procedures for diagnosing hyperglycemia during pregnancy and gestational diabetes mellitus (GDM) are discussed. Case histories describe the remote initiation of insulin pump therapy and automated insulin delivery in T1D pregnancy. Results: Initial feedback suggests that video consultations are well received and that the patient experiences for women requiring face-to-face visits are greatly improved. As the pandemic eases, formal evaluation of remote models of diabetes education and technology implementation, including women's views, will be important. Conclusions: Research and audit activities will resume and we will find new ways for supporting pregnant women with diabetes to choose their preferred glucose monitoring and insulin delivery.

Outpatient Randomized Crossover Comparison of Zone Model Predictive Control Automated Insulin Delivery with Weekly Data Driven Adaptation Versus Sensor-Augmented Pump: Results from the International Diabetes Closed-Loop Trial 4.

Background: Automated insulin delivery (AID) systems have proven effective in increasing time-in-range during both clinical trials and real-world use. Further improvements in outcomes for single-hormone (insulin only) AID may be limited by suboptimal insulin delivery settings. Methods: Adults (≥18 years of age) with type 1 diabetes were randomized to either sensor-augmented pump (SAP) (inclusive of predictive low-glucose suspend) or adaptive zone model predictive control AID for 13 weeks, then crossed over to the other arm. Each week, the AID insulin delivery settings were sequentially and automatically updated by an adaptation system running on the study phone. Primary outcome was sensor glucose time-in-range 70-180 mg/dL, with noninferiority in percent time below 54 mg/dL as a hierarchical outcome. Results: Thirty-five participants completed the trial (mean age 39 ± 16 years, HbA1c at enrollment 6.9% ± 1.0%). Mean time-in-range 70-180 mg/dL was 66% with SAP versus 69% with AID (mean adjusted difference +2% [95% confidence interval: -1% to +6%], P = 0.22). Median time <70 mg/dL improved from 3.0% with SAP to 1.6% with AID (-1.5% [-2.4% to -0.5%], P = 0.002). The adaptation system decreased initial basal rates by a median of 4% (-8%, 16%) and increased initial carbohydrate ratios by a median of 45% (32%, 59%) after 13 weeks. Conclusions: Automated adaptation of insulin delivery settings with AID use did not significantly improve time-in-range in this very well-controlled population. Additional study and further refinement of the adaptation system are needed, especially in populations with differing degrees of baseline glycemic control, who may show larger benefits from adaptation.

Closed-Loop Insulin Therapy in Older Adults with Type 1 Diabetes: Real-World Data.

Objective: To assess the impact of initiation of closed-loop control (CLC) on glycemic metrics in older adults with type 1 diabetes (T1D) in the real world. Methods: Retrospective analysis of electronic health records from a single tertiary diabetes center of older adults prescribed CLC between January and December 2020. Results: Forty-eight patients (mean age 70 ± 4 years, T1D duration 42 ± 14 years) were prescribed CLC and 39/48 started on the CLC. Among the CLC starters, 97.5% and 95% were prior pump and continuous glucose monitoring (CGM) users, respectively. CGM metrics showed an increase in time-in-range (62% ± 13% to 76% ± 9%; P < 0.001), a reduction in both time spent <70 mg/dL [2% (1%-3%) to 1% (1%-2%); P = 0.03] and >180 mg/dL (30% ± 11% to 20% ± 9%; P < 0.001) at 3 months. Conclusion: In this real-world data most of the older patients with T1D initiating CLC were prior pump and CGM users. Initiation of CLC improved glycemic control and reduced time spent in hypoglycemia compared with prior therapy.

Hybrid closed-loop glucose control compared with sensor augmented pump therapy in older adults with type 1 diabetes: an open-label multicentre, multinational, randomised, crossover study.

Background: Older adults with type 1 diabetes have distinct characteristics that can make optimising glycaemic control challenging. We sought to test our hypothesis that hybrid closed-loop glucose control is safe and more effective than sensor-augmented pump (SAP) therapy in older adults with type 1 diabetes. Methods: In an open-label, multicentre, multinational (UK and Austria), randomised, crossover study, adults aged 60 years and older with type 1 diabetes using insulin pump therapy underwent two 16-week periods comparing hybrid closed-loop (CamAPS FX, CamDiab, Cambridge, UK) and SAP therapy in random order. Block randomisation by means of central randomisation software to one of two treatment sequences was stratified by centre. The primary endpoint was the proportion of time sensor glucose was in target range between 3·9 and 10·0 mmol/L. Analysis for the primary endpoint and adverse events was by intention-to-treat. The study has completed and is registered at ClinicalTrials.gov NCT04025762. Findings: 38 participants were enrolled. One participant withdrew during run-in because of difficulties with the study pump infusion sets. 37 participants (median [IQR] age 68 [63-70] years, mean [SD] baseline glycated haemoglobin [HbA1c]; 7·4% [0·9%]; 57 [10] mmol/mol) were randomly assigned between Sept 4, 2019, and Oct 2, 2020. The proportion of time with glucose between 3·9 and 10·0 mmol/L was significantly higher in the closed-loop group compared to the SAP group (79·9% [SD 7·9] vs 71·4% [13·2], difference 8·6 percentage points [95% CI 6·3 to 11·0]; p<0·0001). Two severe hypoglycaemia events occurred during the SAP period. There were two non-treatment related serious adverse events: cardiac arrest from pulmonary embolism associated with COVID-19 during the SAP period resulting in death, and a hospital presentation for parenteral hydrocortisone because of COVID-19 in a participant with adrenal insufficiency during the run-in period. Interpretation: Hybrid closed-loop insulin delivery is safe and achieves superior glycaemic control to SAP therapy in older adults with long duration of type 1 diabetes. Importantly this was achieved without increasing the risk of hypoglycaemia in this population with risk factors for severe hypoglycaemia. This suggests that hybrid closed-loop therapy is a clinically important treatment option for older adults with type 1 diabetes.

Glycemic Control in Relation to Technology Use in a Single-Center Cohort of Children with Type 1 Diabetes.

Background: Technology for patients with type 1 diabetes (T1D), including continuous glucose monitoring (CGM), insulin pumps, and hybrid closed-loop (HCL) systems, is improving, being used more commonly in the pediatric population, and impacts glycemic control. Materials and Methods: We evaluated the use of these technologies and their impact on glycemic control among patients with T1D who were seen at the Barbara Davis Center (n = 4003) between January 2018 and December 2020, <22 years old, with diabetes duration >3 months. Data were analyzed by age group and technology-use group defined as multiple daily injection with blood glucose meter (MDI/BGM), pump with BGM (pump/BGM), MDI with CGM (MDI/CGM), and pump with CGM (pump/CGM). Glycemic control was compared using analysis of covariance (ANCOVA) and controlling for diabetes duration, race, and insurance. Results: Among 4003 patients, 20% used MDI/BGM (mean hemoglobin A1c [HbA1c] = 10.0%); 14.4% used pump/BGM (mean HbA1c = 10.0%); 15.4% used MDI/CGM (mean HbA1c = 8.6%); and 49.8% used pump/CGM (mean HbA1c = 8.1%). Compared with MDI/BGM patients, MDI/CGM and pump/CGM users had a lower HbA1c and were more likely to reach an HbA1c <7.0% (all P < 0.0001). Among pump/CGM users, 35% used HCL technology (mean HbA1c = 7.6%) and had a lower HbA1c and were more likely to reach an HbA1c <7% than non-HCL users (P < 0.001). Conclusions: CGM use was associated with a lower HbA1c in both MDI and pump users. Pump use was only associated with a lower HbA1c if used with CGM. HCL was associated with the lowest HbA1c. Spanish language and minority race/ethnicity were associated with lower rates of pump and CGM use, highlighting the need to reduce disparities.

Impact of COVID-19 lockdown on glycemic control in type 1 diabetes.

AIM: The COVID-19 pandemic has forced governments to impose lockdown policies, thus impacting patients with chronic diseases, such as type 1 diabetes. The aim of this study was to evaluate the impact of lockdown on glycemic control in type 1 diabetes patients. PATIENTS AND METHODS: We retrospectively evaluated patients using a continuous subcutaneous insulin infusion device during the nationwide lockdown. Children and adolescents aged 2-18 years followed up at the Pediatric Endocrinology Unit of Hospitalar São João in Portugal were included in the study. We collected data on the age, weight, insulin doses, and glycemic control of the patients before and after the restrictions. RESULTS: The study included 100 patients, 59 males, with a mean age of 12.5 years. Baseline data showed a suboptimal glycemic control with a median HbA1c of 7.9%. The lockdown was associated with an increase in the body mass index (BMI) of all patients (p = 0.009), particularly girls and older teenagers. Metabolic control deteriorated in the 10-13 age group (p = 0.03), with a 0.4% increase in HbA1c. CONCLUSION: To date, this is the largest study on the impact of lockdown on type 1 diabetes in patients using an insulin pump. The results highlight the importance of physical activity, parental supervision, and continuation of healthcare assistance through telemedicine in young individuals with type 1 diabetes.

Current provision and HCP experiences of remote care delivery and diabetes technology training for people with type 1 diabetes in the UK during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has led to the rapid implementation of remote care delivery in type 1 diabetes. We studied current modes of care delivery, healthcare professional experiences and impact on insulin pump training in type 1 diabetes care in the United Kingdom (UK). METHODS: The UK Diabetes Technology Network designed a 48-question survey aimed at healthcare professionals providing care in type 1 diabetes. RESULTS: One hundred and forty-three healthcare professionals (48% diabetes physicians, 52% diabetes educators and 88% working in adult services) from approximately 75 UK centres (52% university hospitals, 46% general and community hospitals), responded to the survey. Telephone consultations were the main modality of care delivery. There was a higher reported time taken for video consultations versus telephone (p < 0.001). Common barriers to remote consultations were patient familiarity with technology (72%) and access to patient device data (67%). We assessed the impact on insulin pump training. A reduction in total new pump starts (73%) and renewals (61%) was highlighted. Common barriers included patient digital literacy (61%), limited healthcare professional experience (46%) and time required per patient (44%). When grouped according to size of insulin pump service, pump starts and renewals in larger services were less impacted by the pandemic compared to smaller services. CONCLUSION: This survey highlights UK healthcare professional experiences of remote care delivery. While supportive of virtual care models, a number of factors highlighted, especially patient digital literacy, need to be addressed to improve virtual care delivery and device training.

Glucose control in home-isolated adults with type 1 diabetes affected by COVID-19 using continuous glucose monitoring.

PURPOSE: This study is aimed at evaluating changes in metrics of glucose control in home-isolated patients with type 1 diabetes and COVID-19 using a continuous glucose monitoring (CGM) system. METHODS: We included adults aged 18-45 years with type 1 diabetes, using CGM, followed by telemedicine at a Southern Italian University Hospital. Thirty-two home-quarantined subjects with SARS-CoV-2 positive swab constituted the COVID-19 group. Thirty age-matched diabetic individuals without COVID-19 formed the control group. The effects of COVID-19 on glycemic control in patients infected were assessed at different time points [2 weeks before-COVID-19 (Time 1), 2 weeks during-COVID-19 (Time 2) and 2 weeks after COVID-19 (Time 3)] and compared with those without infection. RESULTS: A significant reduction of TIR (Time 1 vs Time 2, %, 60.1 ± 16.6 vs 55.4 ± 19.2, P = 0.03), associated with a significant increase of TAR level 2 (10.1 ± 7.3 vs 16.7 ± 12.9, P < 0.001), GMI (7.1 ± 0.6 vs 7.5 ± 0.8, P < 0.001), CV (37.3 ± 7.1 vs 39.6 ± 7.0, P = 0.04), mean glucose values (mg/dL, 160.2 ± 26.5 vs 175.5 ± 32.6, P = 0.001) and standard deviation (59.2 ± 13.1 vs 68.6 ± 17.7, P = 0.001) was observed in patients with COVID-19. No significant change of glycemic metrics was found in the NO COVID-19 group across the time. CONCLUSION: Young home-isolated patients with type 1 diabetes and COVID-19 showed a worsening of glucose control during COVID-19, as compared with age-matched diabetic subjects without the infection.

COVID-19 Pandemic and Pediatric Type 1 Diabetes: No Significant Change in Glycemic Control During The Pandemic Lockdown of 2020.

Importance: There is no consensus on the impact of the 2020 COVID-19 pandemic lockdown on glycemic control in children and adolescents with type 1 diabetes (T1D) in the US. Aim: To determine the impact of the pandemic lockdown of March 15th through July 6th, 2020 on glycemic control after controlling for confounders. Subjects and Methods: An observational study of 110 subjects of mean age 14.8 ± 4.9 years(y), [male 15.4 ± 4.0y, (n=57); female 14.1 ± 3.8y, (n=53), p=0.07] with T1D of 6.31 ± 4.3y (95% CI 1.0-19.7y). Data were collected at 1-4 months before the lockdown and 1-4 months following the lifting of the lockdown at their first post-lockdown clinic visit. Results: There was no significant change in A1c between the pre- and post-pandemic lockdown periods, 0.18 ± 1.2%, (95% CI -0.05 to 0.41), p=0.13. There were equally no significant differences in A1c between the male and female subjects, -0.16 ± 1.2 vs -0.19 ± 1.2%, p=0.8; insulin pump users and non-pump users, -0.25 ± 1.0 vs -0.12 ± 1.4%, p=0.5; and pubertal vs prepubertal subjects, 0.18 ± 1.3 vs -0.11 ± 0.3%, p=0.6. The significant predictors of decrease in A1c were pre-lockdown A1c (p<0.0001) and the use of CGM (p=0.019). The CGM users had significant reductions in point-of-care A1c (0.4 ± 0.6%, p=0.0012), the CGM-estimated A1c (p=0.0076), mean glucose concentration (p=0.022), a significant increase in sensor usage (p=0.012), with no change in total daily dose of insulin (TDDI). The non-CGM users had significantly increased TDDI (p<0.0001) but no change in HbA1c, 0.06 ± 1.8%, p=0.86. Conclusions: There was no change in glycemic control during the pandemic lockdown of 2020 in US children.

Remote Continuous Glucose Monitoring With a Computerized Insulin Infusion Protocol for Critically Ill Patients in a COVID-19 Medical ICU: Proof of Concept.

OBJECTIVE: The use of remote real-time continuous glucose monitoring (CGM) in the hospital has rapidly emerged to preserve personal protective equipment and reduce potential exposures during coronavirus disease 2019 (COVID-19). RESEARCH DESIGN AND METHODS: We linked a hybrid CGM and point-of-care (POC) glucose testing protocol to a computerized decision support system for continuous insulin infusion and integrated a validation system for sensor glucose values into the electronic health record. We report our proof-of-concept experience in a COVID-19 intensive care unit. RESULTS: All nine patients required mechanical ventilation and corticosteroids. During the protocol, 75.7% of sensor values were within 20% of the reference POC glucose with an associated average reduction in POC of 63%. Mean time in range (70-180 mg/dL) was 71.4 ± 13.9%. Sensor accuracy was impacted by mechanical interferences in four patients. CONCLUSIONS: A hybrid protocol integrating real-time CGM and POC is helpful for managing critically ill patients with COVID-19 requiring insulin infusion.

Virtual training on the hybrid close loop system in people with type 1 diabetes (T1D) during the COVID-19 pandemic.

BACKGROUND AND AIMS: In Colombia, the government established mandatory isolation after the first case of COVID-19 was reported. As a diabetes care center specialized in technology, we developed a virtual training program for patients with type 1 diabetes (T1D) who were upgrading to hybrid closed loop (HCL) system. The aim of this study is to describe the efficacy and safety outcomes of the virtual training program. METHOD: ology: A prospective observational cohort study was performed, including patients with diagnosis of T1D previously treated with multiple doses of insulin (MDI) or sensor augmented pump therapy (SAP) who were updating to HCL system, from March to July 2020. Virtual training and follow-up were done through the Zoom video conferencing application and Medtronic Carelink System version 3.1 software. CGM data were analyzed to compare the time in range (TIR), time below range (TBR) and glycemic variability, during the first two weeks corresponding to manual mode with the final two weeks of follow-up in automatic mode. RESULTS: 91 patients were included. Mean TIR achieved with manual mode was 77.3 ± 11.3, increasing to 81.6% ± 7.6 (p < 0.001) after two weeks of auto mode use. A significant reduction in TBR <70 mg/dL (2,7% ± 2,28 vs 1,83% ± 1,67, p < 0,001) and in glycemic variability (% coefficient of variation 32.4 vs 29.7, p < 0.001) was evident, independently of baseline therapy. CONCLUSION: HCL systems allows T1D patients to improve TIR, TBR and glycemic variability independently of previous treatment. Virtual training can be used during situations that limit the access of patients to follow-up centers.

Efficacy of telemedicine for persons with type 1 diabetes during Covid19 lockdown.

BACKGROUND: Starting March 2020 the Italian Government imposed a lockdown to limit the spread of SARS-CoV-2. During lockdown outpatient visits were limited and telemedicine (TM) was encouraged. METHODS: We retrospectively analyzed data from continuous or flash glucose monitoring systems shared through different cloud systems during the lockdown by subjects with type 1 diabetes and compared data obtained 4 weeks before and 4 weeks after structured telephonic visit. Variables considered were mean glucose, time spent in target (70-180 mg/dl), hypoglycemia (<70 mg/dl) and hyperglycemia (>180 mg/dl), coefficient of variation, and length of sensor use. RESULTS: During the 4 weeks following the telephonic visit there was an improvement of glycemic control, with a significant reduction of mean glucose values (161.1 before vs 156.3 mg/dl after, p = 0.001), an increase of the time spent in target (63.6 vs 66.3, p = 0.0009) and a reduction of time spent in hyperglycemia (33.4 vs 30.5, p = 0.002). No changes were observed regarding glucose variability, time spent in hypoglycemia, and length of sensor use. Similar results were observed in subjects treated with multiple daily injections or continuous subcutaneous insulin infusion. CONCLUSIONS: A structured telephonic visit appears to be an effective way to replace or integrate routine visits in particular conditions.

Managing Patients with Insulin Pumps and Continuous Glucose Monitors in the Hospital: to Wear or Not to Wear.

PURPOSE OF REVIEW: As the prevalence of diabetes mellitus in the USA continues to rise, so does the popularity of diabetes management devices such as continuous glucose monitors (CGMs) and insulin pumps. The use of this technology has been shown to improve outpatient glycemic outcomes and quality of life and oftentimes may be continued in the hospital setting. Our aim is to review the current guidelines and available evidence on the continuation of insulin pumps and CGMs in the inpatient setting. RECENT FINDINGS: Patients with diabetes are at higher risk for hospitalizations and complications due to hyper- or hypoglycemia, metabolic co-morbidities, or as seen recently, more severe illness from infections such as SARS-CoV-2. The maintenance of euglycemia is important to decrease both morbidity and mortality in the hospital setting. There is consensus among experts and medical societies that inpatient use of diabetes technology in carefully selected patients with proper institutional protocols is safe and can improve inpatient glycemic outcomes and reduce hypoglycemia. During the COVID-19 pandemic, CGMs played a vital role in managing hyperglycemia in some hospitalized patients. Insulin pumps and CGMs have the potential to transform glycemic management in hospitalized patients. In order for institutions to safely and effectively incorporate these technologies on their inpatient units, hospital-based providers will need to be able to understand how to manage and utilize these devices in their practice in conjunction with diabetes experts.

A Virtual Training Program for the Tandem t:slim X2 Insulin Pump: Implementation and Outcomes.

Insulin pump training has traditionally been performed in-person. The coronavirus disease 2019 (COVID-19) pandemic necessitated vast increases in the number of virtual pump trainings for Tandem t:slim X2 insulin pump starts. A customized structured pump training curriculum specifically tailored to virtual learning was deployed in early 2020, and included (1) preparation for training with use of the t:simulator app, (2) use of the teach-back method during video training, and (3) automating data uploads for follow-up. Retrospective analysis from >23,000 pump training sessions performed from January 1, 2020 to July 28, 2020 showed sensor time-in-range for up to 6 months after training was 72% (60%-81%) for virtual training versus 67% (54%-78%) for in-person training. Higher user satisfaction (4.78 ± 0.52 vs. 4.64 ± 0.68; P < 0.01) and higher user confidence (4.61 ± 0.75 vs. 4.47 ± 0.0.85; P < 0.01) were reported after the virtual sessions. Virtual pump training was well received and proved safe and effective with the new virtual training curriculum.