What continuous glucose monitoring (CGM) metrics measure glycemic control and who would benefit most from monitoring these metrics?


Accurate glucose measurements are vital in the management of diabetes mellitus (DM).1 The American Diabetes Association (ADA) and the American Association of Clinical Endocrinology (AACE) guidelines consider glycated hemoglobin (A1C) a standardized measure of glycemic control in patients with DM.2,3 The ADA guidelines recommend an A1C goal of <7%, and AACE recommends ≤ 6.5% for most patients. Target A1C may be individualized based on a patient’s disease duration, comorbidities, hypoglycemia risk, adverse drug effect risk, life expectancy, established vascular complications, patient preference, and patient resources.1-3 However, using A1C alone to assess glycemic control has its limitations; A1C only measures average glycemia over approximately the last 3 months.3 It does not provide information regarding glucose trends leading to acute hypo- and hyperglycemic events, which have been associated with the development of microvascular and macrovascular complications.1 Measuring A1C alone does not provide adequate data to assess glycemic control, especially in patients with frequent glycemic variability (GV).1,3 Additionally, A1C measurements may be unreliable in patients with anemia, hemoglobinopathies, iron deficiencies, glucose-6-phosphate dehydrogenase deficiency, end-stage renal disease, and pregnancy. Blood glucose monitoring (BGM) captures a snapshot of the current glucose level and may also improve glucose control.1 However, like A1C, BGM is limited by its inability to alert for impending hypoglycemia or hyperglycemia.

Continuous glucose monitoring (CGM) addresses some of the limitations of A1C testing and BGM.4 Real-time CGM (rtCGM) measures interstitial glucose concentrations, which lag slightly behind blood glucose readings, providing near real-time glucose data. Intermittently-scanned CGM (isCGM) displays glucose readings retrospectively upon scanning. CGM systems provide data regarding blood glucose trends. Depending on the system, CGMs may have alarms to alert the patient of hypoglycemia or hyperglycemia. Alarms are especially advantageous for patients with hypoglycemia unawareness.3 Identifying glucose trends and maintaining blood glucose levels within a target range may improve outcomes. Guidelines recommend CGM use in certain populations including:4,5

  • adults, children, and pregnant women with type 1 or type 2 DM treated with intensive insulin therapy consisting of multiple daily insulin injections or a continuous subcutaneous insulin infusion
  • patients with hypoglycemia unawareness, frequent and severe hypoglycemic events, or nocturnal hypoglycemia
  • women with gestational DM (GDM) regardless of insulin therapy
  • patients with type 2 DM treated with basal insulin therapy

Because optimal CGM use requires initial and ongoing diabetes education, training, and support, it is critical to individualize use and CGM type according to the patient or caregiver’s technology literacy, their desire to learn, and the availability of CGM devices.4

Although there have been improvements in sensor accuracy, ease of use, and reimbursement for CGM technology, successful clinical practice utilization has lagged behind adoption.6 To address this problem, the Advanced Technologies & Treatments for Diabetes (ATTD) group identified clinical CGM targets to supplement the consensus CGM metric standards developed in 2017.1,6

What are the priority CGM metrics?

The key to the accurate evaluation of glycemic control is the collection of adequate CGM glucose data.1,5,6 CGM use for at least 70% of the prior 14 days corresponds robustly with 3 months of mean glucose (estimated A1C), time in ranges, and hyperglycemia. Hypoglycemic variability may require 4 weeks of CGM data collection to assess.5,6 Of the 14 key metrics initially defined in 2017, the 2019 ATTD Congress selected 10 metrics that may be most useful in clinical practice.6 Five of these are priority metrics: glucose management indicator (GMI), glycemic variability (GV), time in range (TIR), time below range (TBR), and time above range (TAR).5,6

The GMI approximates A1C based on the average glucose values from CGM readings for 14 days or greater (GMI [%] = 3:31 + 0.023923 X [mean glucose in mg/dL]).7 Therefore, the GMI may be higher, similar to, or lower than the laboratory A1C because it reflects differences in the patient’s red blood cell life span, how glucose binds to hemoglobin, or recent changes in glycemic control. The A1C and GMI will differ by 0.3% in 51% of patients and by 0.5% or more in 28%, but will be the same in 19% of patients. If A1C and GMI measurements are discordant, the literature indicates that the difference between the two values will remain stable for an individual patient over time.

GV measures the fluctuation of blood glucose levels (the amplitude, frequency, and duration) and strongly correlates with hypoglycemia and mortality.1 The percent coefficient of variation [%CV] is a metric used to measure GV. Higher fluctuations occur more frequently in patients with type 1 DM than those with type 2.5 If the %CV >36%, it is indicative of “unstable” blood glucose levels and the patient is at higher risk of severe hypoglycemia.

Time in ranges is the percentage of CGM readings and time during the day which glucose values fall within a specified range.6 Time in range is defined as the time spent in the target range between 70 and 180 mg/dL.3 Time below range is defined as the time spent below 70 mg/dL, and TAR refers to the time spent above 180 mg/dL.  Continuous glucose monitoring metrics, GMI and TIR, can be used as an alternate to A1C to assess glycemic control in therapeutic decision-making. Table 1 provides percent TIR and corresponding estimated average glucose over 3 months and A1C values.8,9 Table 2 provides percent GMI and corresponding CGM-derived average glucose values.10

Table 1. Glycated Hemoglobin A1C and Estimated Average Glucose with Corresponding TIR Decile

CGM Table 1.png

Data adapted from 8,9
A1C = glycated hemoglobin; eAG = estimated average glucose; TIR = time in range

Table 2. GMI with Corresponding CGM-derived Average Glucosea

CGM Table 2.png

Data adapted from 10
GMI = glucose management indicator; CGM = continuous glucose monitoring
a CGM-derived Average Glucose is derived from at least 14 days of CGM data

Who would most benefit from monitoring time in ranges (TIR, TBR, and TAR), GMI, and GV?

The ATTD group recommends individualized glycemic targets based on DM type, age, risk for complications, and pregnancy.6 The primary goal for safe and effective glucose control is to reduce TBR to target levels and then address individualized TIR or TAR targets (see Table 3). Achieving individualized TIR can reduce the risk of long-term microvascular complications in patients with type 1 or type 2 DM. Every 10% reduction in TIR correlates with a 64% increased risk for retinopathy progression and 40% increased risk for microalbuminuria. The AACE guidelines recommend individualizing mean glucose and GMI targets for all people with DM (Table 3) and maintaining a GV target (%CV) ≤ 36%.5

Patients with type 1 or type 2 DM on intensive insulin therapy, who require tight glycemic control, will benefit the most from monitoring time in ranges, particularly pregnant patients with type 1 DM.6 A 5% to 7% higher TIR reading while in the second and third trimesters is correlated with a decreased risk for increased size for gestational age, macrosomia, neonatal hypoglycemia, shoulder dystocia, and neonatal intensive care admissions. Pregnant patients with type 2 DM and patients with GDM experience one-third less time in hyperglycemia than pregnant women with type 1 DM. Clear CGM targets are currently not defined in pregnant patients with type 2 DM due to lack of data.6,11 Lastly, monitoring time in ranges can be a useful tool to reduce the likelihood of severe hypoglycemia in patients at greater risk due to age, duration of DM, length of insulin therapy, or hypoglycemic unawareness.6 Patients with comorbidities such as renal disease, osteoporosis, cognitive deficits, and cardiovascular disease may also be at higher risk for hypoglycemic complications.

Table 3. ADA and AACE consensus recommendations for glycemic targets (percentage of CGM readings with corresponding target glucose range (mg/dL))

CGM table 3.png

Adapted from3-6,11
a For patients aged <25 years, the TIR target is approximately 60% if the A1C goal is 7.5%
b Information taken from the AACE recommendation only
c No current recommendation due to lack of evidence regarding CGM for pregnant women with type 2 DM and/or gestational DM

ADA = American Diabetes Association; AACE= American Association of Clinical Endocrinology; GDM= gestational diabetes mellitus; TAR = time above range; TBR = time below range; TIR = time in range


The use of CGM enables patients to obtain current glucose levels and trends so they can appropriately adjust insulin dosing and mitigate acute glycemic changes. GV, time in ranges (TIR, TBR, and TAR), and GMI are useful clinical targets to enhance CGM data analysis and therapeutic decision-making for improved outcomes.

For more in-depth information about current recommendations regarding glucose monitoring, insulin delivery, hybrid systems, and developing individualized treatment plans, please refer to the Technologies in Diabetes Care Continuing Education module.


  1. Danne T, Nimri R, Battelino T, et al. International consensus on use of continuous glucose monitoring. Diabetes Care. 2017;40(12):1631-1640. doi: 10.2337/dc17-1600
  2. Garber AJ, Handelsman Y, Grunberger G, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the comprehensive type 2 diabetes management algorithm – 2020 executive summary. Endocr Pract. 2020;26(1):107-139. doi: 10.4158/CS-2019-0472
  3. American Diabetes Association. 6. Glycemic Targets: Standards of Medical Care in Diabetes-2022. Diabetes Care. 2022. 45(Supp 1):S83-S96. doi: 10.2337/dc22-S006
  4. American Diabetes Association. 7. Diabetes technology: Standards of medical care in diabetes-2022. Diabetes Care. 2022; 45(Suppl 1); S97-S112. doi: 10.2337/dc22-S007
  5. Grunberger G, Sherr J, Allende M, et al. American Association of Clinical Endocrinology Clinical Practice Guideline: The use of advanced technology in the management of persons with diabetes mellitus. Endocrine Practice. 2021;27(6):505-537. doi:10.1016/j.eprac.2021.04.008
  6. 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
  7. 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
  8. 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
  9. eAG/A1C conversion calculator. American Diabetes Association-DiabetesPro. Accessed April 14, 2022. https://professional.diabetes.org/diapro/glucose_calc
  10. GMI/mean glucose conversion calculator. JAEB Center for Health Research. Accessed April 14, 2022. https://www.jaeb.org/gmi/
  11. American Diabetes Association. 15. Management of diabetes in pregnancy: standards of medical care in diabetes-2022. 45(Supp 1): S232-243. doi: 10.2337/dc22-S015

Prepared by:

Janelle Panganiban, PharmD
Clinical Pharmacist, Academic Detailer
University of Illinois College of Pharmacy

Lori Uildriks, PharmD, BCPS, BCGP
Assistant Director Medicaid Programs-Operations
University of Illinois College of Pharmacy

The information presented is current as of June 6, 2022. This information is intended as an educational piece and should not be used as the sole source for clinical decision-making.