While A1C is well established as an important risk marker for diabetes complications, with the increasing use of continuous glucose monitoring (CGM) to help facilitate safe and effective diabetes ...management, it is important to understand how CGM metrics, such as mean glucose, and A1C correlate. Estimated A1C (eA1C) is a measure converting the mean glucose from CGM or self-monitored blood glucose readings, using a formula derived from glucose readings from a population of individuals, into an estimate of a simultaneously measured laboratory A1C. Many patients and clinicians find the eA1C to be a helpful educational tool, but others are often confused or even frustrated if the eA1C and laboratory-measured A1C do not agree. In the U.S., the Food and Drug Administration determined that the nomenclature of eA1C needed to change. This led the authors to work toward a multipart solution to facilitate the retention of such a metric, which includes renaming the eA1C the glucose management indicator (GMI) and generating a new formula for converting CGM-derived mean glucose to GMI based on recent clinical trials using the most accurate CGM systems available. The final aspect of ensuring a smooth transition from the old eA1C to the new GMI is providing new CGM analyses and explanations to further understand how to interpret GMI and use it most effectively in clinical practice. This Perspective will address why a new name for eA1C was needed, why GMI was selected as the new name, how GMI is calculated, and how to understand and explain GMI if one chooses to use GMI as a tool in diabetes education or management.
To determine accuracy, safety and acceptability of the FreeStyle Libre Flash Glucose Monitoring System in the paediatric population.
Eighty-nine study participants, aged 4-17 years, with type 1 ...diabetes were enrolled across 9 diabetes centres in the UK. A factory calibrated sensor was inserted on the back of the upper arm and used for up to 14 days. Sensor glucose measurements were compared with capillary blood glucose (BG) measurements. Sensor results were masked to participants.
Clinical accuracy of sensor results versus BG results was demonstrated, with 83.8% of results in zone A and 99.4% of results in zones A and B of the consensus error grid. Overall mean absolute relative difference (MARD) was 13.9%. Sensor accuracy was unaffected by patient factors such as age, body weight, sex, method of insulin administration or time of use (day vs night). Participants were in the target glucose range (3.9-10.0 mmol/L) ∼50% of the time (mean 12.1 hours/day), with an average of 2.2 hours/day and 9.5 hours/day in hypoglycaemia and hyperglycaemia, respectively. Sensor application, wear/use of the device and comparison to self-monitoring of blood glucose were rated favourably by most participants/caregivers (84.3-100%). Five device related adverse events were reported across a range of participant ages.
Accuracy, safety and user acceptability of the FreeStyle Libre System were demonstrated for the paediatric population. Accuracy of the system was unaffected by subject characteristics, making it suitable for a broad range of children and young people with diabetes.
NCT02388815.
To pilot test a new closed-loop control technology to validate it for a further large clinical trial.
The t:slim X2 insulin pump with Control-IQ Technology (Tandem Diabetes Care) includes a Dexcom G6 ...sensor and a closed-loop algorithm implemented in the pump that
) automates insulin correction boluses,
) has a dedicated hypoglycemia safety system, and
) gradually intensifies control overnight, aiming for blood glucose levels of approximately 100-120 mg/dL every morning.
Five patients with type 1 diabetes (mean age 52.8 years, 2/3 male/female, mean A1C 6.5%) used Control-IQ in an outpatient setting (hotel) for approximately 37 h. During the closed loop, mean glucose was 129 mg/dL (135/121 mg/dL during the day/night), time within target range 70-180 mg/dL was 87% (82%/94% during the day/night), and time <60 mg/dL was 1.1% (2.0%/0.0% during the day/night).
Following this pilot trial, Control-IQ was deployed in several studies, including the large-scale National Institutes of Health International Diabetes Closed-Loop (iDCL) Trial.
The use of continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) systems has gained wide acceptance in diabetes care. These devices have been demonstrated to be ...clinically valuable, improving glycemic control and reducing risks of hypoglycemia in ambulatory patients with type 1 diabetes and type 2 diabetes. Approximately 30-40% of patients with type 1 diabetes and an increasing number of insulin-requiring patients with type 2 diabetes are using pump and sensor technology. As the popularity of these devices increases, it becomes very likely that hospital health care providers will face the need to manage the inpatient care of patients under insulin pump therapy and CGM. The American Diabetes Association advocates allowing patients who are physically and mentally able to continue to use their pumps when hospitalized. Health care institutions must have clear policies and procedures to allow the patient to continue to receive CSII treatment to maximize safety and to comply with existing regulations related to self-management of medication. Randomized controlled trials are needed to determine whether CSII therapy and CGM systems in the hospital are associated with improved clinical outcomes compared with intermittent monitoring and conventional insulin treatment or with a favorable cost-benefit ratio.
This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society ...and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.
•Users performed a mean of 16.3 glucose checks per day, well above guidelines for self-monitoring.•Estimated HbA1c reduced from 8.0% to 6.7% (64 to 50 mmol/mol) as scans increased from 4 to 48 per ...day.•Time below 3.9, 3.1 and 2.5 mmol/L decreased by 15%, 40% and 49% from lowest to highest scan groups.•Higher rates of scanning were linked to increased time in range and reduced time in hyperglycaemia.•Associations were consistent by country, but differences were found in hypoglycaemic exposure.
Randomised controlled trials demonstrate that using flash glucose monitoring improves glycaemic control but it is unclear whether this applies outside trial conditions. We investigated glucose testing patterns in users worldwide under real life settings to establish testing frequency and association with glycaemic parameters.
Glucose results were de-identified and uploaded onto a dedicated database once readers were connected to an internet-ready computer. Data between September 2014 and May 2016, comprising 50,831 readers and 279,446 sensors worldwide, were analysed. Scan rate per reader was determined and each reader was sorted into twenty equally-sized rank-ordered groups, categorised by scan frequency. Glucose parameters were calculated for each group, including estimated HbA1c, time above, below and within range identified as 3.9–10.0 mmol/L.
Users performed a mean of 16.3 scans/day median (IQR): 14 (10–20) with 86.4 million hours of readings and 63.8 million scans. Estimated HbA1c gradually reduced from 8.0% to 6.7% (64 to 50 mmol/mol) as scan rate increased from lowest to highest scan groups (4.4 and 48.1 scans/day, respectively; p < .001). Simultaneously, time below 3.9, 3.1 and 2.5 mmol/L decreased by 15%, 40% and 49%, respectively (all p < .001). Time above 10.0 mmol/L decreased from 10.4 to 5.7 h/day (44%, p < .001) while time in range increased from 12.0 to 16.8 h/day (40%, p < .001). These patterns were consistent across different countries.
In real-world conditions, flash glucose monitoring allows frequent glucose checks with higher rates of scanning linked to improved glycaemic markers, including increased time in range and reduced time in hyper and hypoglycaemia.
Automated insulin delivery is the new standard for type 1 diabetes, but exercise-related hypoglycemia remains a challenge. Our aim was to determine whether a dual-hormone closed-loop system using ...wearable sensors to detect exercise and adjust dosing to reduce exercise-related hypoglycemia would outperform other forms of closed-loop and open-loop therapy.
Participants underwent four arms in randomized order: dual-hormone, single-hormone, predictive low glucose suspend, and continuation of current care over 4 outpatient days. Each arm included three moderate-intensity aerobic exercise sessions. The two primary outcomes were percentage of time in hypoglycemia (<70 mg/dL) and in a target range (70-180 mg/dL) assessed across the entire study and from the start of the in-clinic exercise until the next meal.
The analysis included 20 adults with type 1 diabetes who completed all arms. The mean time (SD) in hypoglycemia was the lowest with dual-hormone during the exercise period: 3.4% (4.5) vs. 8.3% (12.6) single-hormone (
= 0.009) vs. 7.6% (8.0) predictive low glucose suspend (
< 0.001) vs. 4.3% (6.8) current care where pre-exercise insulin adjustments were allowed (
= 0.49). Time in hypoglycemia was also the lowest with dual-hormone during the entire 4-day study: 1.3% (1.0) vs. 2.8% (1.7) single-hormone (
< 0.001) vs. 2.0% (1.5) predictive low glucose suspend (
= 0.04) vs. 3.1% (3.2) current care (
= 0.007). Time in range during the entire study was the highest with single-hormone: 74.3% (8.0) vs. 72.0% (10.8) dual-hormone (
= 0.44).
The addition of glucagon delivery to a closed-loop system with automated exercise detection reduces hypoglycemia in physically active adults with type 1 diabetes.
Previous clinical trials showing the benefit of continuous glucose monitoring (CGM) in the management of type 1 diabetes predominantly have included adults using insulin pumps, even though the ...majority of adults with type 1 diabetes administer insulin by injection.
To determine the effectiveness of CGM in adults with type 1 diabetes treated with insulin injections.
Randomized clinical trial conducted between October 2014 and May 2016 at 24 endocrinology practices in the United States that included 158 adults with type 1 diabetes who were using multiple daily insulin injections and had hemoglobin A1c (HbA1c) levels of 7.5% to 9.9%.
Random assignment 2:1 to CGM (n = 105) or usual care (control group; n = 53).
Primary outcome measure was the difference in change in central-laboratory-measured HbA1c level from baseline to 24 weeks. There were 18 secondary or exploratory end points, of which 15 are reported in this article, including duration of hypoglycemia at less than 70 mg/dL, measured with CGM for 7 days at 12 and 24 weeks.
Among the 158 randomized participants (mean age, 48 years SD, 13; 44% women; mean baseline HbA1c level, 8.6% SD, 0.6%; and median diabetes duration, 19 years interquartile range, 10-31 years), 155 (98%) completed the study. In the CGM group, 93% used CGM 6 d/wk or more in month 6. Mean HbA1c reduction from baseline was 1.1% at 12 weeks and 1.0% at 24 weeks in the CGM group and 0.5% and 0.4%, respectively, in the control group (repeated-measures model P < .001). At 24 weeks, the adjusted treatment-group difference in mean change in HbA1c level from baseline was -0.6% (95% CI, -0.8% to -0.3%; P < .001). Median duration of hypoglycemia at less than <70 mg/dL was 43 min/d (IQR, 27-69) in the CGM group vs 80 min/d (IQR, 36-111) in the control group (P = .002). Severe hypoglycemia events occurred in 2 participants in each group.
Among adults with type 1 diabetes who used multiple daily insulin injections, the use of CGM compared with usual care resulted in a greater decrease in HbA1c level during 24 weeks. Further research is needed to assess longer-term effectiveness, as well as clinical outcomes and adverse effects.
clinicaltrials.gov Identifier: NCT02282397.
Adolescents and young adults with type 1 diabetes exhibit the worst glycemic control among individuals with type 1 diabetes across the lifespan. Although continuous glucose monitoring (CGM) has been ...shown to improve glycemic control in adults, its benefit in adolescents and young adults has not been demonstrated.
To determine the effect of CGM on glycemic control in adolescents and young adults with type 1 diabetes.
Randomized clinical trial conducted between January 2018 and May 2019 at 14 endocrinology practices in the US including 153 individuals aged 14 to 24 years with type 1 diabetes and screening hemoglobin A1c (HbA1c) of 7.5% to 10.9%.
Participants were randomized 1:1 to undergo CGM (CGM group; n = 74) or usual care using a blood glucose meter for glucose monitoring (blood glucose monitoring BGM group; n = 79).
The primary outcome was change in HbA1c from baseline to 26 weeks. There were 20 secondary outcomes, including additional HbA1c outcomes, CGM glucose metrics, and patient-reported outcomes with adjustment for multiple comparisons to control for the false discovery rate.
Among the 153 participants (mean SD age, 17 3 years; 76 50% were female; mean SD diabetes duration, 9 5 years), 142 (93%) completed the study. In the CGM group, 68% of participants used CGM at least 5 days per week in month 6. Mean HbA1c was 8.9% at baseline and 8.5% at 26 weeks in the CGM group and 8.9% at both baseline and 26 weeks in the BGM group (adjusted between-group difference, -0.37% 95% CI, -0.66% to -0.08%; P = .01). Of 20 prespecified secondary outcomes, there were statistically significant differences in 3 of 7 binary HbA1c outcomes, 8 of 9 CGM metrics, and 1 of 4 patient-reported outcomes. The most commonly reported adverse events in the CGM and BGM groups were severe hypoglycemia (3 participants with an event in the CGM group and 2 in the BGM group), hyperglycemia/ketosis (1 participant with an event in CGM group and 4 in the BGM group), and diabetic ketoacidosis (3 participants with an event in the CGM group and 1 in the BGM group).
Among adolescents and young adults with type 1 diabetes, continuous glucose monitoring compared with standard blood glucose monitoring resulted in a small but statistically significant improvement in glycemic control over 26 weeks. Further research is needed to understand the clinical importance of the findings.
ClinicalTrials.gov Identifier: NCT03263494.
A major obstacle in optimizing the performance of closed-loop automated insulin delivery systems has been the delay in insulin absorption and action that results from the subcutaneous (SC) route of ...insulin delivery leading to exaggerated postmeal hyperglycemic excursions. We aimed to investigate the effect of Afrezza inhaled insulin with ultrafast-in and -out action profile on improving postprandial blood glucose control during hybrid closed-loop (HCL) treatment in young adults with type 1 diabetes.
We conducted an inpatient, three-way, randomized crossover standardized meal study to assess the efficacy and safety of Afrezza at a low (A
) and a high (A
) dose as compared with a standard SC rapid-acting insulin (aspart) premeal bolus during Diabetes Assistant (DiAs) HCL treatment. Participants received two sequential meals on three study days, and premeal insulin bolus was determined based on home insulin-to-carbohydrate ratio for each meal (rounded up to the closest available Afrezza cartridge dose for A
and down for A
). The primary efficacy outcome was the peak postprandial plasma glucose (PPG) level calculated by pooling data for up to 4 h after the start of each meal. Secondary outcomes included hyperglycemic, hypoglycemic, and euglycemic venous glucose metrics.
The mean ± SD PPG for the rapid-acting insulin control arm and A
was similar (185 ± 50 mg/dL vs. 195 ± 46 mg/dL, respectively;
= 0.45), while it was higher for meals using A
(208 ± 54 mg/dL,
= 0.04). The A
achieved significantly lower early PPG level than the control arm (30 min;
< 0.001), and improvement in PPG waned at later time points (120 and 180 min;
= 0.02) coinciding with the end of Afrezza glucodynamic action.
Afrezza (A
) premeal bolus reduced the early glycemic excursion and improved PPG during HCL compared with aspart premeal bolus. The improvement in PPG was not sustained after the end of Afrezza glucodynamic action at 120 min.
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