This study evaluated the association of time in range (TIR) of 70-180 mg/dL (3.9-10 mmol/L) with the development or progression of retinopathy and development of microalbuminuria using the Diabetes ...Control and Complications Trial (DCCT) data set in order to validate the use of TIR as an outcome measure for clinical trials.
In the DCCT, blood glucose concentrations were measured at a central laboratory from seven fingerstick samples (seven-point testing: pre- and 90-min postmeals and at bedtime) collected during 1 day every 3 months. Retinopathy progression was assessed every 6 months and urinary microalbuminuria development every 12 months. Proportional hazards models were used to assess the association of TIR and other glycemic metrics, computed from the seven-point fingerstick data, with the rate of development of microvascular complications.
Mean TIR of seven-point profiles for the 1,440 participants was 41 ± 16%. The hazard rate of development of retinopathy progression was increased by 64% (95% CI 51-78), and development of the microalbuminuria outcome was increased by 40% (95% CI 25-56), for each 10 percentage points lower TIR (
< 0.001 for each). Results were similar for mean glucose and hyperglycemia metrics.
Based on these results, a compelling case can be made that TIR is strongly associated with the risk of microvascular complications and should be an acceptable end point for clinical trials. Although hemoglobin A
remains a valuable outcome metric in clinical trials, TIR and other glycemic metrics-especially when measured with continuous glucose monitoring-add value as outcome measures in many studies.
Continuous glucose monitoring (CGM) improves glycemic control, but data are inconclusive about its influence on quality of life (QOL). We investigated the impact of 24 weeks of CGM use on QOL in ...adults with type 1 diabetes (T1D) who use multiple daily insulin injections.
DIAMOND (Multiple Daily Injections and Continuous Glucose Monitoring in Diabetes) was a prospective randomized trial that assessed CGM versus self-monitoring of blood glucose (SMBG) only in 158 adults with poorly controlled T1D. At baseline and study end, participants completed QOL measures that assessed overall well-being (WHO-5), health status (EQ-5D-5L), diabetes distress (DDS), hypoglycemic fear (worry subscale of the HFS-II), and hypoglycemic confidence (HCS). At study end, CGM participants completed the CGM Satisfaction Survey. Linear regression analyses compared treatment group changes in QOL outcomes over time. Associations between CGM satisfaction and change in QOL outcomes and in glycemic control indices were assessed.
The CGM group demonstrated a greater increase in hypoglycemic confidence (
= 0.01) and a greater decrease in diabetes distress (
= 0.01) than the SMBG group. No significant group differences in well-being, health status, or hypoglycemic fear were observed. CGM satisfaction was not significantly associated with glycemic changes but was associated with reductions in diabetes distress (
< 0.001) and hypoglycemic fear (
= 0.02) and increases in hypoglycemic confidence (
< 0.001) and well-being (
= 0.01).
CGM contributes to significant improvement in diabetes-specific QOL (i.e., diabetes distress, hypoglycemic confidence) in adults with T1D, but not with QOL measures not specific to diabetes (i.e., well-being, health status). CGM satisfaction was associated with most of the QOL outcomes but not with glycemic outcomes.
To examine the overall state of metabolic control and current use of advanced diabetes technologies in the U.S., we report recent data collected on individuals with type 1 diabetes participating in ...the T1D Exchange clinic registry. Data from 16,061 participants updated between 1 September 2013 and 1 December 2014 were compared with registry enrollment data collected from 1 September 2010 to 1 August 2012. Mean hemoglobin A1c (HbA1c) was assessed by year of age from <4 to >75 years. The overall average HbA1c was 8.2% (66 mmol/mol) at enrollment and 8.4% (68 mmol/mol) at the most recent update. During childhood, mean HbA1c decreased from 8.3% (67 mmol/mol) in 2-4-year-olds to 8.1% (65 mmol/mol) at 7 years of age, followed by an increase to 9.2% (77 mmol/mol) in 19-year-olds. Subsequently, mean HbA1c values decline gradually until ∼30 years of age, plateauing at 7.5-7.8% (58-62 mmol/mol) beyond age 30 until a modest drop in HbA1c below 7.5% (58 mmol/mol) in those 65 years of age. Severe hypoglycemia (SH) and diabetic ketoacidosis (DKA) remain all too common complications of treatment, especially in older (SH) and younger patients (DKA). Insulin pump use increased slightly from enrollment (58-62%), and use of continuous glucose monitoring (CGM) did not change (7%). Although the T1D Exchange registry findings are not population based and could be biased, it is clear that there remains considerable room for improving outcomes of treatment of type 1 diabetes across all age-groups. Barriers to more effective use of current treatments need to be addressed and new therapies are needed to achieve optimal metabolic control in people with type 1 diabetes.
A closed-loop system (also called an artificial pancreas) may improve glycemic outcomes in children with type 1 diabetes. In this 16-week trial, the glucose level was in the target range for a ...greater percentage of time with a closed-loop system than with a sensor-augmented insulin pump.
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.
IMPORTANCE: 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. OBJECTIVE: To determine the effectiveness of CGM in adults with type 1 diabetes treated with insulin injections. DESIGN, SETTING, AND PARTICIPANTS: 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%. INTERVENTIONS: Random assignment 2:1 to CGM (n = 105) or usual care (control group; n = 53). MAIN OUTCOMES AND MEASURES: 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. RESULTS: 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. CONCLUSIONS AND RELEVANCE: 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. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT02282397
Technological advances have had a major effect on the management of type 1 diabetes. In addition to blood glucose meters, devices used by people with type 1 diabetes include insulin pumps, continuous ...glucose monitors, and, most recently, systems that combine both a pump and a monitor for algorithm-driven automation of insulin delivery. In the next 5 years, as many advances are expected in technology for the management of diabetes as there have been in the past 5 years, with improvements in continuous glucose monitoring and more available choices of systems that automate insulin delivery. Expansion of the use of technology will be needed beyond endocrinology practices to primary-care settings and broader populations of patients. Tools to support decision making will also need to be developed to help patients and health-care providers to use the output of these devices to optimise diabetes management.
Background:
As the use of continuous glucose monitoring (CGM) increases, there is a need to better understand key metrics of time in range 70-180 mg/dL (TIR70-180) and hyperglycemia and how they ...relate to hemoglobin A1c (A1C).
Methods:
Analyses were conducted utilizing datasets from four randomized trials encompassing 545 adults with type 1 diabetes (T1D) who had central-laboratory measurements of A1C. CGM metrics were calculated and compared with each other and A1C cross-sectionally and longitudinally.
Results:
Correlations among CGM metrics (TIR70-180, time >180 mg/dL, time >250 mg/dL, mean glucose, area under the curve above 180 mg/dL, high blood glucose index, and time in range 70-140 mg/dL) were typically 0.90 or greater. Correlations of each metric with A1C were lower (absolute values 0.66-0.71 at baseline and 0.73-0.78 at month 6). For a given TIR70-180 percentage, there was a wide range of possible A1C levels that could be associated with that TIR70-180 level. On average, a TIR70-180 of 70% and 50% corresponded with an A1C of approximately 7% and 8%, respectively. There also was considerable spread of change in A1C for a given change in TIR70-180, and vice versa. An increase in TIR70-180 of 10% (2.4 hours per day) corresponded to a decrease in A1C of 0.6%, on average.
Conclusions:
In T1D, CGM measures reflecting hyperglycemia (including TIR and mean glucose) are highly correlated with each other but only moderately correlated with A1C. For a given TIR or change in TIR there is a wide range of possible corresponding A1C values.
Continuous glucose monitoring (CGM), which studies have shown is beneficial for adults with type 1 diabetes, has not been well-evaluated in those with type 2 diabetes receiving insulin.
To determine ...the effectiveness of CGM in adults with type 2 diabetes receiving multiple daily injections of insulin.
Randomized clinical trial. (The protocol also included a type 1 diabetes cohort in a parallel trial and subsequent second trial.) (ClinicalTrials.gov: NCT02282397).
25 endocrinology practices in North America.
158 adults who had had type 2 diabetes for a median of 17 years (interquartile range, 11 to 23 years). Participants were aged 35 to 79 years (mean, 60 years SD, 10), were receiving multiple daily injections of insulin, and had hemoglobin A1c (HbA1c) levels of 7.5% to 9.9% (mean, 8.5%).
Random assignment to CGM (n = 79) or usual care (control group, n = 79).
The primary outcome was HbA1c reduction at 24 weeks.
Mean HbA1c levels decreased to 7.7% in the CGM group and 8.0% in the control group at 24 weeks (adjusted difference in mean change, -0.3% 95% CI, -0.5% to 0.0%; P = 0.022). The groups did not differ meaningfully in CGM-measured hypoglycemia or quality-of-life outcomes. The CGM group averaged 6.7 days (SD, 0.9) of CGM use per week.
6-month follow-up.
A high percentage of adults who received multiple daily insulin injections for type 2 diabetes used CGM on a daily or near-daily basis for 24 weeks and had improved glycemic control. Because few insulin-treated patients with type 2 diabetes currently use CGM, these results support an additional management method that may benefit these patients.
Dexcom.
HbA1c is a valuable metric for comparing treatment groups in a randomized trial, for assessing glycemic trends in a population over time, or for cross-sectional comparisons of glycemic control in ...different populations. However, what is not widely appreciated is that HbA1c may not be a good indicator of an individual patient’s glycemic control because of the wide range of mean glucose concentrations and glucose profiles that can be associated with a given HbA1c level. To illustrate this point, we plotted mean glucose measured with continuous glucose monitoring (CGM) versus central laboratory–measured HbA1c in 387 participants in three randomized trials, showing that not infrequently HbA1c may underestimate or overestimate mean glucose, sometimes substantially. Thus, if HbA1c is to be used to assess glycemic control, it is imperative to know the patient’s actual mean glucose to understand how well HbA1c is an indicator of the patient’s glycemic control. With knowledge of the mean glucose, an estimated HbA1c (eA1C) can be calculated with the formula provided in this article to compare with the measured HbA1c. Estimating glycemic control from HbA1c alone is in essence applying a population average to an individual, which can be misleading. Thus, a patient’s CGM glucose profile has considerable value for optimizing his or her diabetes management. In this era of personalized, precision medicine, there are few better examples with respect to the fallacy of applying a population average to a specific patient rather than using specific information about the patient to determine the optimal approach to treatment.
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