Interindividual variability in average glucose-glycated haemoglobin relationship in type 1 diabetes and implications for clinical practice

Is It Time to Move Beyond TIR to TITR? Real-World Data from Over 20,000 Users of Continuous Glucose Monitoring in Patients with Type 1 and Type 2 Diabetes

The growing use of continuous glucose monitoring (CGM) has been supported by expert consensus and clinical guidelines on glycemic management in diabetes with time in range (TIR 70-180 mg/dL) representing a key CGM-derived glucose metric. Time in tight range (TITR) has also been proposed for clinical use, spanning largely normal glucose levels of 70-140 mg/dL. However, keeping such narrow glucose ranges can be challenging, and understanding the factors modulating TITR can help achieve these tight glycemic targets. Our real-life study aimed to evaluate the relationship between average glucose (AG) and TIR/TITR in a large cohort (n = 22,006) of CGM users, divided into four groups: self-identified as having type 1 diabetes (T1D) treated with insulin using multiple daily injections (MDI) or pumps; type 2 diabetes (T2D) on MDI or insulin pumps; T2D on basal insulin only; and T2D not on insulin treatment. The T2D groups, regardless of treatment type, displayed the highest TIR and TITR values, associated with lowest glycemic variability measured as glucose coefficient of variation (CV; 23-30%). The T1D group showed the lowest TIR and TITR, associated with the highest CVs (36-38%). Overall, higher CV was associated with lower TIR and TITR for AG values below 180 and 140 mg/dL, respectively, with the reverse holding true for AG values above these thresholds. The discordance between AG and TIR/TITR was less pronounced in T2D compared with T1D, attributed to lower CV in the former group. It was also observed that TITR has advantages over TIR for assessing glycemia status and progress toward more stringent A1C, particularly when approaching normal glucose levels. The data detail how CV affects the AG relationship with TIR/TITR, which has implications for CGM interpretation. In many instances TITR, rather than TIR, may be preferable to employ once AG falls below 140 mg/dL and near-normal glucose levels are required clinically.

Diet and Glycemic Index in Children with Type 1 Diabetes

In children with type 1 diabetes, a healthy lifestyle is important to control postprandial glycemia and to avoid hyperglycemic peaks that worsen the inflammatory state of vessels and tissues. Glycemic index and glycemic load are two important indexes which assess the quality and quantity of foods consumed during meals. The main macronutrients of the diet have a different effect on postprandial blood glucose levels, so it is important that diabetic children consume foods which determine a slower and steadier glycemic peak. In this review, we present the results of the most recent studies carried out in the pediatric population with T1D, whose aim was to analyze the effects of low-glycemic-index foods on glycemic control. The results are promising and demonstrate that diets promoting low-glycemic-index foods guarantee a greater glycemic stability with a reduction in postprandial hyperglycemic peaks. However, one of the main limitations is represented by the poor adherence of children to a healthy diet. In order to obtain satisfactory results, a possibility might be to ensure a balanced intake of low-, moderate- and high-glycemic-index foods, preferring those with a low glycemic index and limiting the consumption of the high- and moderate-glycemic-index types.

Temporal changes in bio-behavioral and glycemic outcomes following a produce prescription program among predominantly Hispanic/Latino adults with or at risk of type 2 diabetes

In the United States (U.S.), consumption of fresh vegetables and fruits is below recommended levels. Enhancing access to nutritious food through food prescriptions has been recognized as a promising approach to combat diet-related illnesses. However, the effectiveness of this strategy at a large scale remains untested, particularly in marginalized communities where food insecurity rates and the prevalence of health conditions such as type 2 diabetes (T2D) are higher compared to the background population. This study evaluated the impact of a produce prescription program for predominantly Hispanic/Latino adults living with or at risk of T2D. A total of 303 participants enrolled in a 3-month observational cohort received 21 medically prescribed portions/week of fresh produce. A subgroup of 189 participants used continuous glucose monitoring (CGM) to assess the relationship between CGM profile changes and HbA1c level changes. For 247 participants completing the study (76% female, 84% Hispanic/Latino, 32% with T2D, age 56·6 ± 11·9 years), there was a reduction in weight (-1·1 [-1·6 to -0·6] lbs., p < 0.001), waist circumference (-0·4 [-1·0 to 0·6] cm, p = 0·007) and systolic blood pressure (SBP) for participants with baseline SBP >120 mmHg (-4·2 [-6·8 to -1·8] mmHg, p = 0·001). For participants with an HbA1c ≥ 7·0% at baseline, HbA1c fell significantly (-0·5 [-0·9 to -0·1] %, p = 0·01). There were also improvements in food security (p < 0·0001), self-reported ratings of sleep, mood, pain (all p < 0·001), and measures of depression (p < 0·0001), anxiety (p = 0·045), and stress (p = 0·002) (DASS-21). There was significant correlation (r = 0·8, p = 0·001) between HbA1c change and the change in average glucose for participants with worsening HbA1c, but not for participants with an improvement in HbA1c. In conclusion, medical prescription of fresh produce is associated with significant improvements in cardio-metabolic and psycho-social risk factors for Hispanic/Latino adults with or at risk of T2D.

Discordance Between Glucose Management Indicator and Glycated Hemoglobin in People Without Diabetes

Background: In recent years, continuous glucose monitor (CGM) use is increasing in people without diabetes to promote healthy lifestyle. CGM metrics such as glucose management indicator (GMI), a statistical formula to estimate glycated hemoglobin (HbA1c) from sensor glucose, is commonly used to approximate HbA1c. This study was aimed to evaluate discordance between GMI and HbA1c in people without diabetes. Methods: Children and nonpregnant adults (age ≥6 years) without diabetes (laboratory HbA1c <5.7% and negative islet antibodies) were invited to participate in a multicenter prospective study aimed to evaluate glycemic profiles in nondiabetic individuals. Each participant wore a blinded Dexcom G6 for up to 10 days. GMI was calculated from mean sensor glucose and discordance between GMI and HbA1c was analyzed. Results: Of 201 screened participants, 153 participants (mean age 31.2 ± 21.0 years, 66.0% female, HbA1c 5.1% ± 0.3%) were included in the analysis. Mean GMI was 0.59% higher than laboratory HbA1c in participants without diabetes. The discordance between GMI and HbA1c of 0.4% or greater was 71% in participants without diabetes compared with 39% in the original GMI development cohort. Conclusion: GMI does not accurately estimate HbA1c in healthy people without diabetes. Clinical trial registration number is: NCT00717977.

A Comparison of Continuous Glucose Monitoring Estimated Hemoglobin A1c in Adults with Type 1 or Type 2 Diabetes

Background: The relationship of mean glucose measured with continuous glucose monitoring (CGM) and hemoglobin A1c (HbA1c) shows considerable variability between individuals with diabetes and may be influenced by race-related factors. Whether the relationship of mean glucose with HbA1c varies according to type 1 diabetes (T1D) or type 2 diabetes (T2D) has not been well evaluated. Methods: Data from 343 participants in four clinical trials (191 with T1D and 152 with T2D) were analyzed. Least squares linear regression models were fit with HbA1c as the dependent variable and mean glucose as the independent variable. Results: Mean age was 57 ± 15 years in the T1D cohort and 58 ± 10 years in the T2D cohort. The T1D cohort was 89% White non-Hispanic, 5% African American, 3% Hispanic, and 3% other or mixed race compared with 52%, 16%, 22%, and 9%, respectively, in the T2D cohort. The relationship between CGM-measured mean glucose and laboratory-measured HbA1c significantly differed between T1D and T2D cohorts, with HbA1c on average being higher with T2D than T1D for the same mean glucose (P = 0.002). However, this difference was largely attributable to the difference in the proportion of African Americans between T1D and T2D; and after stratifying by race, the mean glucose-HbA1c relationship showed only a small difference between T1D non-African Americans and T2D non-African Americans. The mean glucose-HbA1c relationship appeared similar for White non-Hispanic and Hispanic individuals. Conclusion: HbA1c on average was higher in T2D than T1D for a given mean glucose, but after accounting for race, there was no meaningful difference in the mean glucose-HbA1c relationship comparing T1D and T2D. The mean glucose-HbA1c relationship differs in African American compared with White individuals, but does not appear to differ comparing White non-Hispanic to Hispanic individuals. The published glucose management indicator formula appears to be suitable for both T1D and T2D.

Evaluation of continuous glucose monitoring-derived person-specific HbA1c in the presence and absence of complications in type 1 diabetes

AIM

To evaluate the accuracy of a novel kinetic model at predicting HbA1c in a real-world setting and to understand and explore the role of diabetes complications in altering the glucose-HbA1c relationship and the mechanisms involved.

MATERIALS AND METHODS

Deidentified HbA1c and continuous glucose monitoring values were collected from 93 individuals with type 1 diabetes. Person-specific kinetic variables were used, including red blood cell (RBC) glucose uptake and lifespan, to characterize the relationship between glucose levels and HbA1c. The resulting calculated HbA1c (cHbA1c) was compared with glucose management indicator (GMI) for prospective agreement with laboratory HbA1c.

RESULTS

The cohort (42 men and 51 women) had a median age (IQR) of 61 (43, 72) years and a diabetes duration of 21 (10, 33) years. A total of 24 459 days of continuous glucose monitoring (CGM) data were available and 357 laboratory HbA1c were used to assess the average glucose-HbA1c relationship. cHbA1c had a superior correlation with laboratory HbA1c compared with GMI with a mean absolute deviation of 1.7 and 6.7 mmol/mol, r²  = 0.85 and 0.44, respectively. The fraction within 10% of absolute relative deviation from laboratory HbA1c was 93% for cHbA1c and 63% for GMI. Macrovascular disease had no effect on the model's accuracy, whereas microvascular complications resulted in a trend towards higher HbA1c, secondary to increased RBC glucose uptake.

CONCLUSIONS

cHbA1c, which takes into account RBC glucose uptake and lifespan, accurately reflects laboratory HbA1c in a real-world setting and can aid in the management of individuals with diabetes.