Background: Initiating continuous glucose monitoring (CGM) can affect hemoglobin A1c (HbA1c) levels and patients' relationship with their diabetes. We used real-world HbA1c data to quantify short-t...

Change in Hemoglobin A1c and Quality of Life with Real-Time Continuous Glucose Monitoring Use by People with Insulin-Treated Diabetes in the Landmark Study.

OBJECTIVE This study aimed to 1) identify the frequency of severe and level 2 hypoglycemia presenting in individuals with type 1 diabetes using continuous glucose monitoring systems (CGMs), including those with concomitant closed-loop insulin pumps, in a clinical practice setting and 2) evaluate the impact of beliefs around hypoglycemia in the development of severe and level 2 hypoglycemia in this population. RESEARCH DESIGN AND METHODS A cross-sectional survey study in adults with type 1 diabetes using CGMs >6 months was conducted at a large tertiary academic center. Participant demographics, 6-month severe hypoglycemia history, hypoglycemia beliefs (with the Attitude to Awareness of Hypoglycemia questionnaire), and 4-week CGM glucose data were collected. Statistical analysis was performed to assess the presentation of severe and level 2 hypoglycemia and identify associated risk factors. RESULTS A total of 289 participants were recruited (including 257 participants with CGM data within the last 3 months). Of these, 25.6% experienced at least one severe hypoglycemic episode in the last 6 months, and 13.6% presented with ≥1% of time in level 2 hypoglycemia on CGMs. Reporting beliefs about prioritizing hyperglycemia avoidance was associated with severe hypoglycemia development (P < 0.001), while having beliefs of minimal concerns for hypoglycemia was associated with spending ≥1% of time in level 2 hypoglycemia (P = 0.038). CONCLUSIONS Despite the use of advanced diabetes technologies, severe and level 2 hypoglycemia continues to occur in individuals with type 1 diabetes and high hypoglycemia risks. Human factors, including beliefs around hypoglycemia, may continue to impact the effectiveness of glucose self-management.

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Beliefs Around Hypoglycemia and Their Impacts on Hypoglycemia Outcomes in Individuals with Type 1 Diabetes and High Risks for Hypoglycemia Despite Using Advanced Diabetes Technologies

Objective Prior to the Continuous Monitoring and Control of Hypoglycaemia (COACH) study described herein, no study had been powered to evaluate the impact of non-adjunctive RT-CGM use on the rate of debilitating moderate or severe hypoglycaemic events. Research design and methods In this 12-month observational study, adults with insulin-requiring diabetes who were new to RT-CGM participated in a 6-month control phase where insulin dosing decisions were based on self-monitored blood glucose (SMBG) values, followed by a 6-month phase where decisions were based on RT-CGM data (i.e., non-adjunctive RT-CGM use); recommendations for RT-CGM use were made according to sites' usual care. The primary outcome was change in debilitating moderate (requiring second-party assistance) and severe (resulting in seizures or loss of consciousness) hypoglycaemic event frequency. Secondary outcomes included changes in HbA1c and diabetic ketoacidosis (DKA) frequency. Results A total of 519 participants with mean (SD) age 50.3 (16.1) years and baseline HbA1c 8.0% (1.4%) completed the study, of whom 32.8% had impaired hypoglycaemia awareness and 33.5% had type 2 diabetes (T2D). The mean (SE) per-patient frequency of hypoglycaemic events decreased by 63% from 0.08 (0.016) during the SMBG phase to 0.03 (0.010) during the RT-CGM phase (p=0.005). HbA1c decreased during the RT-CGM phase both for participants with type 1 diabetes (T1D) and T2D and there was a trend toward larger reductions among individuals with higher baseline HbA1c. Conclusions Among adults with insulin-requiring diabetes, non-adjunctive use of RT-CGM data is safe, resulting in significantly fewer debilitating hypoglycaemic events than management using SMBG.

Non-adjunctive continuous glucose monitoring for control of hypoglycaemia (COACH): Results of a post-approval observational study.

Due to its simplicity, time-limited eating (TLE) may represent a more feasible approach for treating adolescents with obesity compared to other caloric restriction regimens. This pilot study examines the feasibility and safety of TLE combined with continuous glucose monitoring (CGM) in adolescents. Fifty adolescents with BMI ≥95th percentile were recruited to complete a 12-week study. All received standard nutritional counseling, wore a CGM daily, and were randomized to: (1) Prolonged eating window: 12 h eating/12 h fasting + blinded CGM; (2) TLE (8 h eating/16 h fasting, 5 days per week) + blinded CGM; (3) TLE + real-time CGM feedback. Recruitment, retention, and adherence were recorded as indicators of feasibility. Weight loss, dietary intake, physical activity, eating behaviors, and quality of life over the course of the intervention were explored as secondary outcomes. Forty-five participants completed the study (16.4 ± 1.3 years, 64% female, 49% Hispanic, 75% public insurance). There was high adherence to prescribed eating windows (TLE 5.2 d/wk [SD 1.1]; control 6.1 d/wk [SD 1.4]) and daily CGM wear (5.85 d/wk [SD 4.8]). Most of the adolescents (90%) assigned to TLE reported that limiting their eating window and wearing a CGM was feasible without negative impact on daily functioning or adverse events. There were no between-group difference in terms of weight loss, energy intake, quality of life, physical activity, or eating behaviors. TLE combined with CGM appears feasible and safe among adolescents with obesity. Further investigation in larger samples, with a longer intervention duration and follow-up assessments are needed.

Time-Limited Eating and Continuous Glucose Monitoring in Adolescents with Obesity: A Pilot Study

Glycaemic variabilities: Key questions in pursuit of clarity.

Background: Optional features of continuous glucose monitoring (CGM) systems empower patients and caregivers to understand and manage diabetes in new ways. We examined associations between use of optional features, demographics, and glycemic outcomes. Methods: Retrospective cohort studies were performed with data from US-based users of the G6 CGM System (Dexcom, Inc.). For all cohorts, data included sensor glucose values (SGVs). In separate cohorts, use of alert features (for hyperglycemia, existing hypoglycemia, and impending hypoglycemia), remote data sharing feature (Share), software for retrospective pattern analysis (CLARITY), "virtual assistant" feature that announces the current SGV and trend in response to a spoken request were assessed. Descriptive statistics were used to summarize feature set utilization patterns and relate them to glycemic outcomes. Results: Most individual features were consistently adopted by high proportions of G6 users. Threshold SGVs chosen for activating hyperglycemia and hypoglycemia alerts varied with age and were higher among the youngest and oldest patients. Use of the Share feature was more common among young patients and those with type 1 diabetes. Individuals who used more of the alert and notification features had more favorable glycemic outcomes, including time in range (TIR), than those who used fewer. More extensive engagement with CLARITY notifications was associated with higher TIR. Frequent use of the virtual assistant feature was associated with higher TIR and lower mean SGV. Conclusions: Optional features of the G6 CGM system are acceptable to and appear to benefit patients who use them. Different levels of engagement suggest that demographics and personal circumstances play a role in how patients and caregivers use CGM features to help manage diabetes.

Real-World Evidence and Glycemic Improvement Using Dexcom G6 Features

Modeling thrombus growth in pathological flows allows evaluation of risk under patient-specific pharmacological, hematological, and hemodynamical conditions. We have developed a 3D multiscale framework for the prediction of thrombus growth under flow on a spatially resolved surface presenting collagen and tissue factor (TF). The multiscale framework is composed of four coupled modules: a Neural Network (NN) that accounts for platelet signaling, a Lattice Kinetic Monte Carlo (LKMC) simulation for tracking platelet positions, a Finite Volume Method (FVM) simulator for solving convection-diffusion-reaction equations describing agonist release and transport, and a Lattice Boltzmann (LB) flow solver for computing the blood flow field over the growing thrombus. A reduced model of the coagulation cascade was embedded into the framework to account for TF-driven thrombin production. The 3D model was first tested against in vitro microfluidics experiments of whole blood perfusion with various antiplatelet agents targeting COX-1, P2Y1, or the IP receptor. The model was able to accurately capture the evolution and morphology of the growing thrombus. Certain problems of 2D models for thrombus growth (artifactual dendritic growth) were naturally avoided with realistic trajectories of platelets in 3D flow. The generalizability of the 3D multiscale solver enabled simulations of important clinical situations, such as cylindrical blood vessels and acute flow narrowing (stenosis). Enhanced platelet-platelet bonding at pathologically high shear rates (e.g., von Willebrand factor unfolding) was required for accurately describing thrombus growth in stenotic flows. Overall, the approach allows consideration of patient-specific platelet signaling and vascular geometry for the prediction of thrombotic episodes.

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A three-dimensional multiscale model for the prediction of thrombus growth under flow with single-platelet resolution

Investigating thrombin-loaded fibrin in whole blood clot microfluidic assay via fluorogenic peptide.

The collagen receptor glycoprotein VI (GPVI) drives strong platelet activation, however its role at later stages of clotting remains less clear. Controlled timing of addition of anti-human GPVI Fab (clone E12) with microfluidic venous whole blood flow over collagen (± lipidated tissue factor, TF) produced distinct effects on platelets, fibrin, P-selectin exposure, and phosphatidylserine (PS) exposure. On collagen alone, Fab present initially potently reduced platelet deposition on collagen, while Fab added 90 s after initial platelet deposition, stopped subsequent platelet accumulation (despite the absence of fibrin). With thrombin generation via TF, Fab added at either t = 0 or 90 s had no effect on platelet deposition. However, Fab added initially, but not at 90-s, blocked fibrin formation. Gly-Pro-Arg-Pro ablated fibrin formation without effect on platelet accumulation (regardless of Fab added at t = 0 or 90 s), indicating thrombin signaling can suffice over GPVI signaling. Still, Fab moderately reduced P-selectin exposure with thrombin present and fibrin absent. On collagen/TF, Fab present initially ablated PS exposure, but had no effect when added 30 to 90-s later. The thrombin generated via PS exposure had an important role in driving platelet deposition in the presence of Fab, since inhibition of PS via annexin V binding in the presence of Fab significantly inhibited platelet deposition. We conclude GPVI signaling in the first platelet layer on collagen dictates thrombin and fibrin production, but the role of GPVI at subsequent times after formation of the first monolayer is obscured by thrombin-induced signaling.

Anti-GPVI Fab reveals distinct roles for GPVI signaling in the first platelet layer and subsequent layers during microfluidic clotting on collagen with or without tissue factor.

Kaushik Shankar

Papers

Real-World Evidence and Glycemic Improvement Using Dexcom G6 Features

A three-dimensional multiscale model for the prediction of thrombus growth under flow with single-platelet resolution

Investigating thrombin-loaded fibrin in whole blood clot microfluidic assay via fluorogenic peptide.

Anti-GPVI Fab reveals distinct roles for GPVI signaling in the first platelet layer and subsequent layers during microfluidic clotting on collagen with or without tissue factor.