Real-World User and Clinician Perspective and Experience with MiniMed™ 780G Advanced Hybrid Closed Loop System.

INTRODUCTION: The advanced hybrid closed loop (AHCL) MiniMed™ 780G system changes basal insulin delivery every 5 min and auto bolus in response to sensor glucose values. We assessed the performance of the AHCL system in real-world settings for individuals with type 1 diabetes (T1DM) as well as user and clinician perspectives and satisfaction. METHODS: We held two peer group discussions: one having adults with T1DM/parents of children and adolescents with T1DM to understand their experiences with the AHCL system and another with healthcare providers (HCPs). Responses from the discussions were analyzed and categorized into themes by two independent researchers, with any inconsistencies resolved by consensus. We also analyzed data from the system uploaded to CareLink personal software. Glycemic outcomes, including time in range (TIR), time below range (TBR), time above range (TAR), mean sensor glucose (SG) levels, glucose management indicator (GMI), sensor use, and percentage of time spent in AHCL, were determined. RESULTS: The peer group discussions revealed numerous key themes and issues for each group, such as the significance of setting reasonable expectations, carbohydrate counting and bolus dosing, technical difficulties, and overall user experience. The users (n = 25; T1DM; 17 female; age 13.8 ± 7.49 years; A1C 6.54 ± 0.45%; duration of diabetes 6 ± 6.78 years) were very satisfied with the system. Most users experienced consistent blood glucose values with very few hypoglycemic episodes. However, there were a few limitations reported, such as hyperglycemic episodes caused by inaccuracies in carb counting, issues with sensor connectivity, and cannula blockages or kinking for those using insulin Fiasp. Users achieved a mean GMI of 6.4 ± 0.26%, TIR of 83.0 ± 8.12%, TBR (54-70 mg/dL) of 2.0 ± 0.81%, TBR* (< 54 mg/dL) of 0%. All of the users achieved a TIR of > 70%. CONCLUSION: The use of the AHCL system in T1DM resulted in robust glycemic control, minimizing hypoglycemia. Providing training to both users and HCPs can help them use the system effectively.

Empowering Patients with Type 1 Diabetes through a Multidisciplinary Team-assisted, Technology-Enabled Education Program.

BACKGROUND: Carbohydrate counting is a tool that helps patients with type 1 diabetes (T1D) to control their blood glucose. It calculates the bolus insulin dose needed from the total amount of carbohydrates consumed at each meal. However, carbohydrate counting can be quite challenging. The Diabetes Tele Management System® (DTMS®) is a telemedicine-based program that enables the patient to interact directly with a professionally trained, multidisciplinary team (MDT) of experts. This, along with technology-enabled education programs, could allow people with T1D to achieve glycemic control. METHODS: Fifty patients with T1D between 5 and 35 years with a diabetes duration of at least 6 months, baseline HbA1c of 7 or above, using SCII or MDI and willing to take part in the study were invited to participate in an MDT-assisted technology-enabled program and trained trimonthly on carbohydrate counting. The control group went on to perform carbohydrate counting independently and used technologies at their convenience. The test group additionally received continuous individual assistance from the MDT. RESULTS: The MDT-assisted patients had significantly decreased HbA1c, blood glucose levels, decreased episodes of hyperglycemia and hypoglycemia, and reported a more positive outlook on life. CONCLUSION: Carbohydrate counting remains a challenge for youth with T1D, and errors in counting can have a clinical impact. Our data suggested that the assistance from an MDT of experts was associated with improved carbohydrate counting, which led to improved glycemic control and reduced complications.

A new interventional home care model for COVID management: Virtual Covid IP.

AIM: Amidst COVID-19 pandemic, the health care delivery in India faces major challenges owing to the overwhelming hospitals, exhausted healthcare workers, and shortage of crucial medical supplies such as ventilators and oxygen. The study aims to propose a novel successful interventional home care model, the Virtual COVID In-Patient (VCIP) care for effective COVID management. METHODS: The Covid-19 positive patients enrolled in VCIP were chosen for the study. A 24/7 active multidisciplinary WhatsApp group was created for each patient, for remote monitoring of temperature, blood pressure, blood glucose, respiratory and pulse rate along with the symptoms. Advice on sleep and exercises were given along with the medication via video-audio consultations. Lab facility was provided at the doorstep. Training on various devices, medications including steroids, delivering subcutaneous injections etc were given via video platforms. RESULTS: Among the 220 patients who availed the VCIP facility, only two were hospitalized, yielding a 99.5 % success rate in preventing hospitalizations and patients enrolled have been immensely satisfied with their experience. CONCLUSIONS: With similar pandemics anticipated in near future, VCIP model may be considered for successful domiciliary treatment and overcoming the challenges.

Assessing the Therapeutic Utility of Professional Continuous Glucose Monitoring in Type 2 Diabetes Across Various Therapies: A Retrospective Evaluation.

BACKGROUND: There have been few large studies that have analyzed the effect of professional (masked) continuous glucose monitoring (P-CGM) on glycemic control in patients with type 2 diabetes (T2DM) who were on a broad spectrum of baseline therapies. METHODS: We performed a retrospective, blinded evaluation of glycemic control in 296 T2DM adults for 6 months following a 6- to 7-day study of their glycemic profile using masked P-CGM. At baseline, 91% of the patients were on some form of insulin treatment with oral hypoglycemic agents (OHA), while 7% were on one or more OHAs without insulin, and the remaining 2% were on GLP-1RAs. On the basis of the masked CGM profile, patients were counselled on diet and exercise change(s) in their baseline diabetes therapy by our professionally trained diabetes team. They also continued to receive regular treatment advice and dose titrations through our Diabetes Tele-Management System (DTMS®). The baseline changes in hemoglobin A1C (A1C) observed in these patients after 6 months of undergoing P-CGM was compared to a matched control group. RESULTS: P-CGM revealed that the predominant pattern of hyperglycemia was postprandial while previously unknown hypoglycemia was found in 38% of the patients; over half of the cases of hypoglycemia were nocturnal. The mean A1C of the P-CGM group dropped from 7.5 ± 1.4% at baseline vs. 7.0 ± 0.9% at 6 months (p < 0.0001). The frequency of performing self-monitoring of blood glucose (SMBG) was also found to be significantly increased in these patients from the baseline. Meanwhile, no significant improvement in A1C was noted in the control group during the same time frame (7.7 ± 1.1% at baseline vs. 7.4 ± 1.1% at 6 months; p = 0.0663) and frequency of SMBG remained almost unchanged. CONCLUSIONS: P-CGM can provide actionable data and motivate patients for diabetes self-care practices, resulting in an improvement in glycemic control over a wide range of baseline therapies.