Exploratory study on glycemic control improvement for patients with diabetes mellitus by appropriate re-education on insulin self-injection technique during COVID-19 pandemic.

AIMS: To conduct a study on glycemic control improvement by appropriate re-education on the self-injection technique (SIT) in patients with diabetes mellitus undergoing insulin therapy. METHODS: Patients who received appropriate SIT and were treated with insulin for more than a year were re-educated. For the observation period of six months, the subjects' SIT was checked, and hemoglobin A1c (HbA1c) levels were measured at each visit. HbA1c levels, insulin doses, and behavioral changes in SIT were investigated at baseline and at the end of the observation period. RESULTS: In the per-protocol set population, the HbA1c level decreased by 0.2 % (2.0 mmol/mol) on average, showing a significant difference (p = 0.009). No significant difference was observed in the proportion of subjects with decreased HbA1c levels, changes in total daily insulin doses, or blood glucose levels. Four of the six SIT items covered by re-education were improved. CONCLUSIONS: Providing re-education on insulin SIT was considered effective in reducing HbA1c levels and improving adherence to proper SIT.

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.

New Digital Health Technologies for Insulin Initiation and Optimization for People With Type 2 Diabetes.

OBJECTIVE: The health and economic burden of type 2 diabetes is of global significance. Many people with type 2 diabetes eventually need insulin to help reduce their risk of serious associated complications. However, barriers to the initiation and/or optimization of insulin expose people with diabetes to sustained hyperglycemia. In this review, we investigated how new and future technologies may provide opportunities to help overcome these barriers to the initiation and/or optimization of insulin. METHODS: A focused literature search of PubMed and key scientific congresses was conducted. Software tools and devices developed to support the initiation and/or optimization of insulin were identified by manually filtering >300 publications and conference abstracts. RESULTS: Most software tools have been developed for smartphone platforms. At present, published data suggest that the use of these technologies is associated with equivalent or improved glycemic outcomes compared with standard care, with additional benefits such as reduced time burden and improved knowledge of diabetes among health care providers. However, there remains paucity of good-quality evidence. Most new devices to support insulin therapy help track the dose and timing of insulin. CONCLUSION: New digital health tools may help to reduce barriers to optimal insulin therapy. An integrated solution that connects glucose monitoring, dose recording, and titration advice as well as records comorbidities and lifestyle factors has the potential to reduce the complexity and burden of treatment and may improve adherence to titration and treatment, resulting in better outcomes for people with diabetes.

Impact of COVID-19 lockdown on glucemic control in children and adolescents with type 1 diabetes mellitus.

BACKGROUND AND AIMS: To face the rapid spread of SARS-CoV2 coronavirus pandemic, home lockdown in Spain was decreed on 15th March 2020. The main objective of this study is to evaluate the impact of this constraint on glycemic control in children and adolescents with type 1 diabetes mellitus (T1D). PATIENTS AND METHODS: Observational, retrospective study in children and adolescents with T1D users of interstitial glucose monitoring systems. The following information corresponding to the last 2 weeks of lockdown was collected for subsequent comparison with data of 2 weeks prior to quarantine: daily insulin needs, mean interstitial glucose, estimated HbA1c, coefficient of variation (CV), time in range (70-180mg/dl), hypoglycemia (<70 and <54mg/dl) and hyperglycemia (>180 and> 250mg/dl), sensor use and number of blood glucose measurements. Data about meal routines, physical exercise, need for adjustments in therapy, acute complications and lockdown of caregivers were assessed via a survey. RESULTS: 80 patients were studied (mean age 12.61±3.32 years, mean time of evolution of the disease 5.85±3.92 years), 66.2% treated with an insulin pump, users of following glucose monitoring systems: Guardian 3 (65%), FreeStyle Libre (18.8%) and Dexcom G6 (16.2%). Time in range in the cohort increased significantly during confinement (72.1±10.5 vs 74.8±10.5%; P=0.011) with lower time in hypoglycemia both <70mg/dl (4.6±3.2 vs 3.2±2.7%; P<0.001) and <54mg/dl (1.2±1.6 vs 0.7±1.2%; P<0.001) and hyperglycemia >250mg/dl (4.6±3.9 vs 3.7±3.7%; P=0.038). CV also decreased (35.8±6.3 vs 33.1±6.1%; P<0.001). Patients treated with multiple doses of insulin and poorer baseline glycemic control experienced greatest improvement. Daily insulin requirements remained stable. Regular practice of physical exercise and caregivers' confinement did not have a significant impact. CONCLUSIONS: Glycemic control in children and adolescents with T1D improved during quarantine, particularly in those with worse baseline control.

Adolescents with type 1 diabetes can achieve glycemic targets on intensive insulin therapy without excessive weight gain.

INTRODUCTION: The aim of this study was to compare glycemic control and body mass index standard deviation score (BMI-SDS) before and after implementation of intensive insulin therapy using multiple daily injection (MDI) or continuous subcutaneous insulin infusion (CSII) in adolescents with type 1 diabetes (T1D) attending a large multidisciplinary paediatric diabetes clinic in Australia. METHODS: Prospective data were collected for cross-sectional comparison of youth aged 10.0-17.9 years (n = 669) from routine follow-up visits to the diabetes clinic in 2004, 2010, and 2016. Outcome measures included HbA1c; BMI-SDS; and insulin regimen. RESULTS: BMI-SDS remained stable between 2004 to 2016 in the 10-13 and 14-17 year age group (0.7 vs. 0.5, p = .12 and 0.7 vs. 0.7, p = .93, respectively). BMI-SDS was not different across HbA1c groups; <53 mmol/mol (7.0%), 53 to <75 mmol/mol (<7.0 to <9.0%) and >75 mmol/mol (>9.0%) in 2004 (p = .873), 2010 (p = .10) or 2016 (p = .630). Mean HbA1c decreased from 2004 to 2016 in the 10-13 year (69 mmol/mol (8.4%) vs. 57 mmol/mol (7.4%), p = <.001) and 14-17 year group (72 mmol/mol (8.7%) vs. 63 mmol/mol (7.9%), p = <.001). Prior to the implementation of MDI and CSII in 2004 only 10% of 10-13 year olds and 8% of 14-17 year olds achieved the international target for glycemic control (HbA1c 53 mmol/mol [<7.0%]). In 2016, this increased to 31% of 10-13 year olds and 21% of 14-17 year olds. CONCLUSIONS: BMI-SDS did not increase with the change to intensive insulin therapy despite a doubling in the number of adolescents achieving the recommended glycemic target of <7.0% (53 mmol/mol). HbA1c was not associated with weight gain.

Assessment of Insulin Infusion Requirements in COVID-19-Infected Patients With Diabetic Ketoacidosis.

BACKGROUND/OBJECTIVE: Coronavirus disease 2019 (COVID-19) is thought to contribute to diabetic ketoacidosis (DKA) and worse outcomes in patients with diabetes. This study compared the cumulative insulin dose required to achieve DKA resolution in the intensive care unit among patients with type 2 diabetes and COVID-19 infection versus without COVID-19 infection. METHODS: This retrospective cohort study evaluated 100 patients-50 patients with COVID-19 in cohort 1 and 50 patients without COVID-19 in cohort 2-treated with insulin infusions for DKA at a tertiary care teaching hospital. The primary outcome was to compare the cumulative insulin dose required to achieve DKA resolution in each cohort. The secondary outcomes included time to DKA resolution, mean insulin infusion rate, and mean weight-based cumulative insulin infusion dose required to achieve DKA resolution. All endpoints were adjusted for confounders. RESULTS: The mean cumulative insulin dose was 190.3 units in cohort 1 versus 116.4 units in cohort 2 (P = .0038). Patients receiving steroids had a mean time to DKA resolution of 35.9 hours in cohort 1 versus 15.6 hours in cohort 2 (P = .0014). In cohort 1 versus cohort 2, the mean insulin infusion rate was 7.1 units/hour versus 5.3 units/hour (P = .0025), whereas the mean weight-based cumulative insulin infusion dose was 2.1 units/kg versus 1.5 units/kg (P = .0437), respectively. CONCLUSION: COVID-19-infected patients required a significantly larger cumulative insulin dose, longer time to DKA resolution, higher insulin infusion rate, and higher weight-based insulin infusion dose to achieve DKA resolution versus non-COVID-19-infected patients with type 2 diabetes.