Decoding the AGP for Personalized Diabetes Management

Utilizing readouts to inform clinical decisions
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AGP Report

Standardized glucose target levels

Set by an International Consensus Panel of diabetes experts, this graphic representation of glucose statistics and targets for Type 1 Diabetes (T1D) and Type 2 Diabetes (T2D) displays optimal goals for Time in Range (TIR) - green, Time Below Range (TBR) - two categories in light and dark red, and Time Above Range (TAR) - two categories in yellow and orange.1,4

Important

Separate targets have been recommended for women with T1D during pregnancy; women with gestational and T2D during pregnancy, and for people who are at higher risk of hypoglycemia because of age, duration of diabetes, duration of insulin therapy, or impaired awareness of hypoglycemia.4

Glucose target levels during pregnancy
AGP ReportGoals for Type 1 and Type 2 Diabetes highlightGoals for Type 1 and Type 2 Diabetes highlight

Clinical trial check-in

Recent research underscores the significance of TIR in diabetes management, revealing an inverse relationship between TIR 70–180 mg/dL and the occurrence of diabetes complications like retinopathy, peripheral neuropathy, and cardiovascular disease.6,9-12

Impact on A1C and TIR

Data showed that discontinuing CGM usage caused partial reversal of A1C reduction and TIR improvements in individuals with type 2 diabetes on basal insulin.15

Impact on hospitalizations

A retrospective database study of patients with type 2 diabetes who were treated with short- or rapid-acting insulin therapy demonstrated that CGM usage was associated with reductions in inpatient and emergency outpatient acute diabetes-related events (ADEs) and all-cause hospitalization (ACH) rates. Also, notable reductions in ADEs and ACH rates were seen within the first 45 days of CGM usage.16
AGP ReportGoals for Type 1 and Type 2 Diabetes highlightGoals for Type 1 and Type 2 Diabetes highlight

Personalized treatment tip

Standard glucose target recommendations are a starting point and ultimately should be individualized for each person with diabetes based on their risk for hypoglycemia, likelihood of benefit from intensive glycemic control, and treatment burden.4

Even though the AGP does not set A1C targets, there is a correlation between the A1C and Time in Range (TIR) that can be used to inform clinical decision-making.8

Patient and disease factors used to guide individualized glycemic targets are depicted in the figure below.17 Factors that are potentially modifiable and those that usually are not modifiable can influence risks and benefits of therapy.7 Therefore, it is vital for the clinical care team to determine patient-specific glycemic targets, reevaluating over time as patient factors change to balance the risks and benefits.
Personalized treatment tip

Assess blood glucose fluctuations beyond A1C

Glycemic variability

Because of the limitations of A1C, the search has continued for alternative ways to measure and assess blood glucose fluctuations. Glycemic variability (GV; the coefficient of variation [%CV] metric) is an indicator of hyperglycemia and hypoglycemia and is a measure of the fluctuations or oscillations of the glucose measurements throughout the day or days. GV takes into consideration both the amplitude of the excursion (how far out of range a blood glucose measurement is) and the time spent in the excursion (how long the blood glucose is out of range). The target for GV is <36%.13,18-20

The Importance of Glycemic Variability

Doctor with a tablet in his hands and patient looking at it
Reference 1,6,13,20-24

Glucose management indicator

The glucose management indicator (GMI) is a metric that indicates an estimated average A1C level by converting an individual’s mean glucose readings using a population-based formula. When it comes to the full assessment of glycemic control, discordance between laboratory A1C and GMI values in a real-world setting suggest that healthcare providers evaluate A1C and GMI as only individual pieces of a complete puzzle.25,26
AGP ReportGlucose Metrics highlightGlucose Metrics highlight

Identifying and addressing hypoglycemia

Hypoglycemia may occur in up to 50% of people with type 2 diabetes.27 Therefore, after checking data capture and confirming adequate data, the next step in a systematic Ambulatory Glucose Profile (AGP) review is to identify hypoglycemia or Time Below Range (TBR). Are blood glucose levels rising, falling, or staying the same? Healthcare providers (HCPs) should talk to their patients and ask them about any activities or actions that may have contributed to their pattern of low glucose.13

To address hypoglycemia, review medications (insulin or oral agents, such as sulfonylureas) that can cause hypoglycemia and need to be adjusted accordingly to reduce hypoglycemia when it occurs. Also, consider missed meals, unusual physical activity, and/or alcohol consumption as potential contributors.13

Knowing what the blood glucose level is, where it is headed, and how the patient feels – in the context of overall hypoglycemia awareness – is important for using CGM information to prevent hypoglycemia and increase TIR.13
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(a) Target glucose range

The target glucose range, which is shown as the range between two green parallel lines.1

(b) Median glucose line

The median line traces the midpoint glucose reading as a measure of average glucose at each point in the modal day, revealing oscillations and out-of-range values. This is different than the average (mean) glucose, which is simply an arithmetic average. The significance of the median glucose line is that if it remains flat and in the target range throughout the day, that is typically a good sign of glycemic control.1

(c) Interquartile range

The darker shaded band between the 25th and 75th percentiles, known as the interquartile range (IQR), illustrates the 50% of glucose readings closest to the median line. It depicts the variability or oscillations in these readings from day to day, providing insight into daily trends in glucose levels. Additionally, it highlights the impact of medication and mealtimes on glucose control.1

(d) Outlier glucose ranges

The outer border areas mark the cutoffs for the 5th and 95th percentile ranges (lowest and highest 5%, respectively), indicative of less common glucose readings. Variability in glucose levels occurs intermittently, offering insights into how behavior and lifestyle factors can influence glucose control. Importantly, the highest and lowest glucose readings (outside of the 5th–95th percentile range) are not included in the AGP. These infrequent values are omitted as they have minimal impact on clinical judgment and decision-making.1

Graphic components of the AGP

The “modal” day of the Ambulatory AGP report displays all the glucose readings over a single 24-hour period, allowing clinicians to easily identify suboptimal glucose patterns. The overall trend of the glucose readings is just as important as the actual glucose value and can provide objective criteria to conduct a systematic approach for a more personalized diabetes management plan.1,7
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Daily glucose profiles

Daily glucose profiles show the glucose trace for each day of the 14-day AGP. Clinicians can interpret glucose variability within the context of different daily activities and identify on-off events that may have been missed in the overall summary. These on-off events are important calls for contingency planning and education, particularly for illness, busy or stressful days, and other life events.1

Alternative CGM reports

Another CGM report, the Glucose Pattern Insights Report (GPIR), is similar to the AGP report but offers a guided interpretation of CGM data. The GPIR highlights areas necessitating clinical attention, offering therapy recommendations and key discussion points on medication and lifestyle considerations to go over with patients. The GPIR is frequently more comprehensible for patients and their care partners but is only offered on certain CGM devices.28
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Make sure you don’t miss this!

Standard glucose target recommendations are a starting point and ultimately should be individualized for each person.4

A generalized interpretation plan of an AGP report should be conducted stepwise:13,29,30
  1. Evaluate data adequacy
  2. Identify and address Time Below Range (TBR)
  3. Identify and address high Glycemic Variability (GV)
  4. Identify and address Time Above Range (TAR)
  5. Improve Time in Range (TIR)
Another CGM report, GPIR, is similar to the AGP report but offers a guided interpretation of CGM data.28

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References

  1. Doupis J, Horton ES. Utilizing the New Glucometrics: A Practical Guide to Ambulatory Glucose Profile Interpretation. touchREV Endocrinol. 2022;18(1):20-26. doi:10.17925/EE.2022.18.1.202.
  2. ElSayed NA, Aleppo G, Aroda VR, et al. 7. Diabetes technology: standards of care in diabetes–2023. Diabetes Care. 2023;46(Suppl 1):S111-S127. doi:10.2337/dc23-S0073
  3. Riddlesworth TD, Beck RW, Gal RL, et al. Optimal sampling duration for continuous glucose monitoring to determine long-term glycemic control. Diabetes Technol Ther. 2018;20(4):314-316. doi: 10.1089/dia.2017.0455
  4. Battelino T, Danne T, Bergenstal RM, et al. Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range. Diabetes Care.2019;42(8):1593-1603. doi: 10.2337/dci19-0028
  5. Emral R, Pathan F, Cortés CA, et al. Self-reported hypoglycemia in insulin-treated patients with diabetes: Results from an international survey on 7289 patients from nine countries. Diabetes Res Clin Pract. 2017;134:17-28. doi:10.1016/j.diabres.2017.07.031
  6. Vigersky RA, McMahon C. The relationship of hemoglobin A1C to time-in-range in patients with diabetes. Diabetes Technol Ther. 2019;21(2):81-85. doi:10.1089/dia.2018.0310
  7. ElSayed NA, Aleppo G, Aroda VR, et al. 6. Glycemic Targets: Standards of Care in Diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S97-S110. doi:10.2337/dc23-S006
  8. Beck RW, Bergenstal RM, Cheng P, et al. The relationships between time in range, hyperglycemia metrics, and HbA1c. J Diabetes Sci Technol. 2019;13(4):614-626. doi:10.1177/1932296818822496
  9. Lu J, Ma X, Zhou J, et al. Association of time in range, as assessed by continuous glucose monitoring, with diabetic retinopathy in type 2 diabetes. Diabetes Care. 2018;41(11):2370-2376. doi: 10.2337/dc18-1131
  10. Li F, Zhang Y, Li H, et al. TIR generated by continuous glucose monitoring is associated with peripheral nerve function in type 2 diabetes. Diabetes Res Clin Pract. 2020;166:108289.
  11. Yang J, Yang X, Zhao D, et al. Association of time in range, as assessed by continuous glucose monitoring, with painful diabetic polyneuropathy. J Diabetes Invest. 2021;12:828-836. doi: 10.1016/j.diabres.2020.108289
  12. Lu J, Ma X, Shen Y, et al. Time in range is associated with carotid intima-media thickness in type 2 diabetes. Diabetes Technol Ther. 2020;22(2):72-78. doi: 10.1089/dia.2019.0251
  13. Wright EE, Morgan K, Fu DK, Wilkins N, Guffey WJ. Time in range: how to measure it, how to report it, and its practical application in clinical decision-making. Clin Diabetes. 2020;38(5):439-448. doi: 10.2337/cd20-0042
  14. Czupryniak L, Dzida G, Fichna P, et al. Ambulatory glucose profile (AGP) report in daily care of patients with diabetes: practical tips and recommendations. Diabetes Ther. 2022;13(4):811-821. doi:10.1007/s13300-022-01229-9
  15. Aleppo G, Beck RW, Bailey R, et al. The effect of discontinuing continuous glucose monitoring in adults with type 2 diabetes treated with basal insulin. Diabetes Care. 2021;44(12):2729-2737. doi:10.2337/dc21-1304
  16. Bergenstal RM, Kerr MSD, Roberts GJ, Souto D, Nabutovsky Y, Hirsch IB. Flash CGM is associated with reduced diabetes events and hospitalizations in insulin-treated type 2 diabetes. J Endocr Soc. 2021;5(4):bvab013. doi:10.1210/jendso/bvab013
  17. Inzucchi SE, Bergenstal RM, Buse JB, et al. Management of hyperglycemia in type 2 diabetes, 2015: a patient-centered approach: update to a position statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care. 2015;38(1):140-149. doi:10.2337/dc14-2441
  18. Kovatchev BP. Metrics for glycemic control: from HbA1c to continuous glucose monitoring. Nat Rev Endocrinol. 2017;13(7):425-436. doi: 10.1038/nrendo.2017.3
  19. Kovatchev B. Glycemic variability: risk factors, assessment, and control. J Diabetes Sci Technol. 2019;13(4):627-635. doi:10.1177/1932296819826111
  20. Rodbard D. Glucose variability: a review of clinical applications and research developments. Diabetes Technol Ther. 2018;20(S2):S25-S215. doi: 10.1089/dia.2018.0092
  21. Papachristoforou E, Lambadiari V, Maratou E, Makrilakis K. Association of glycemic indices (hyperglycemia, glucose variability, and hypoglycemia) with oxidative stress and diabetic complications. J Diabetes Res. 2020:7489795. doi: 10.1155/2020/7489795
  22. Zhang Z-Y, Miao L-F, Qian L-L, et al. Molecular mechanisms of glucose fluctuations on diabetic complications. Front Endocrinol (Lausanne). 2019;10:640. doi:10.3389/fendo.2019.00640
  23. Shi R, Feng L, Liu Y-M, et al. Glycemic dispersion: a new index for screening high glycemic variability. Diabetol Metab Syndr. 2023;15(1):95. doi:10.1186/s13098-023-01077-y
  24. Valente T, Arbex AK. Glycemic variability, oxidative stress, and impact on complications related to type 2 diabetes mellitus. Curr Diabetes Rev. 2021;17(7):e071620183816. doi: 10.2174/1573399816666200716201550.
  25. Bergenstal RM, Beck RW, Close KL, et al. Glucose management indicator (GMI): a new term for estimating A1C from continuous glucose monitoring. Diabetes Care.2018;41(11):2275-2280. doi: 10.2337/dc18-1581
  26. Fang M, Wang D, Rooney MR, et al. Performance of the glucose management indicator (GMI) in type 2 diabetes. Clin Chem. 2023;69(4):422-428. doi:10.1093/clinchem/hvac210
  27. Edridge CL, Dunkley AJ, Bodicoat DH, et al. Prevalence and incidence of hypoglycaemia in 532,542 people with type 2 diabetes on oral therapies and insulin: a systematic review and meta-analysis of population based studies. PLoS One. 2015;10(6):e0126427. doi:10.1371/journal.pone.0126427
  28. Wright EE, Novak MT, Hayter GA, et al. The effects of glucose reporting tools on therapeutic decision making: a comparative reading study with primary care providers. Poster presented at ADA 82nd Scientific Sessions; June 5, 2022; New Orleans, LA.
  29. Evans M, Cranston I, Bailey CJ. Ambulatory glucose profile (AGP): utility in UK clinical practice. Br J Diabetes. 2017;17(1):26. doi:10.15277/bjd.2017.121
  30. Johnson ML, Martens TW, Criego AB, Carlson AL, Simonson GD, Bergenstal RM. Utilizing the ambulatory glucose profile to standardize and implement continuous glucose monitoring in clinical practice. Diabetes Technol Ther. 2019;21(S2):S217-S225. doi:10.1089/dia.2019.0034