Glycemic Targets: Standards of Medical Care in Diabetes

GOALS OF CARE

6. Glycemic Targets: Standards of Medical Care in Diabetes—2022

Diabetes Care 2022;45(Suppl. 1):S83–S96 | https://doi.org/10.2337/dc22-S006

American Diabetes Association Professional Practice Committee*

The American Diabetes Association (ADA) “Standards of Medical Care in Diabetes”

includes the ADA’s current clinical practice recommendations and is intended to pro-vide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Commit-tee, a multidisciplinary expert committee (http://doi.org/10.2337/dc22-SPPC), are responsible for updating the Standards of Care annually, or more frequently as war-ranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA’s clinical practice recommendations, please refer to the Standards of Care Introduction (http://doi.org/10.2337/dc22-SINT).

Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

ASSESSMENT OF GLYCEMIC CONTROL

Glycemic control is assessed by the A1C measurement, continuous glucose monitoring (CGM) using either time in range (TIR) and/or glucose management indicator (GMI), and blood glucose monitoring (BGM). A1C is the metric used to date in clinical trials demonstrating the beneﬁts of improved glycemic control. Individual glucose monitor-ing (discussed in detail in Section 7,“Diabetes Technology,” https://doi.org/10.2337/

dc22-S007) is a useful tool for diabetes self-management, which includes meals, exer-cise, and medication adjustment, particularly in individuals taking insulin. CGM serves an increasingly important role in the management of the effectiveness and safety of treatment in many patients with type 1 diabetes and in selected patients with type 2 diabetes. Individuals on a variety of insulin regimens can beneﬁt from CGM with improved glucose control, decreased hypoglycemia, and enhanced self-efﬁcacy (Section 7,“Diabetes Technology,” https://doi.org/10.2337/dc22-S007) (1).

Glycemic Assessment

Recommendations

6.1 Assess glycemic status (A1C or other glycemic measurement such as time in range or glucose management indicator) at least two times a year in patients who are meeting treatment goals (and who have stable glycemic control).E

6.2 Assess glycemic status at least quarterly and as needed in patients whose therapy has recently changed and/or who are not meeting glycemic goals.E

A1C reﬂects average glycemia over approximately 3 months. The performance of the test is generally excellent for National Glycohemoglobin Standardization Program (NGSP)-certiﬁed assays (see www.ngsp.org). The test is the primary tool for assessing

*A complete list of members of the American Diabetes Association Professional Practice Com-mittee can be found at http://doi.org/10.2337/

dc22-SPPC.

Suggested citation: American Diabetes Asso-ciation Professional Practice Committee. 6. Gly-cemic targets: Standards of Medical Care in Diabetes—2022. Diabetes Care 2022;45(Suppl.

1):S83–S96

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6.GLYCEMICTARGETS

Diabetes Care Volume 45, Supplement 1, January 2022 S83

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glycemic control and has a strong predic-tive value for diabetes complications (2– 4). Thus, A1C testing should be per-formed routinely in all patients with dia-betes at initial assessment and as part of continuing care. Measurement approxi-mately every 3 months determines whether patients’ glycemic targets have been reached and maintained. A 14-day CGM assessment of TIR and GMI can serve as a surrogate for A1C for use in clinical management (5–9). The fre-quency of A1C testing should depend on the clinical situation, the treatment regimen, and the clinician’s judgment.

The use of point-of-care A1C testing or CGM-derived TIR and GMI may pro-vide an opportunity for more timely treatment changes during encounters between patients and providers. People with type 2 diabetes with stable glyce-mia well within target may do well with A1C testing or other glucose assessment only twice per year. Unstable or inten-sively managed patients or people not at goal with treatment adjustments may require testing more frequently (every 3 months with interim assess-ments as needed for safety) (10). CGM parameters can be tracked in the clinic or via telemedicine to optimize diabe-tes management.

A1C Limitations

The A1C test is an indirect measure of average glycemia and, as such, is subject to limitations. As with any laboratory test, there is variability in the measure-ment of A1C. Although A1C variability is lower on an intraindividual basis than that of blood glucose measurements, clinicians should exercise judgment when using A1C as the sole basis for assessing glycemic control, particularly if the result is close to the threshold that might prompt a change in medication therapy.

For example, conditions that affect red blood cell turnover (hemolytic and other anemias, glucose-6-phosphate dehydro-genase deﬁciency, recent blood trans-fusion, use of drugs that stimulate eryth-ropoesis, end-stage kidney disease, and pregnancy) may result in discrepancies between the A1C result and the patient’s true mean glycemia. Hemoglobin var-iants must be considered, particularly when the A1C result does not correlate with the patient’s CGM or BGM levels.

However, most assays in use in the U.S.

are accurate in individuals who are het-erozygous for the most common variants (see www.ngsp.org/interf.asp). Other measures of average glycemia such as fructosamine and 1,5-anhydroglucitol are available, but their translation into aver-age glucose levels and their prognostic signiﬁcance are not as clear as for A1C and CGM. Though some variability in the relationship between average glucose levels and A1C exists among different individuals, in general the association between mean glucose and A1C within an individual correlates over time (11).

A1C does not provide a measure of glycemic variability or hypoglycemia.

For patients prone to glycemic variabil-ity, especially patients with type 1 dia-betes or type 2 diadia-betes with severe insulin deﬁciency, glycemic control is best evaluated by the combination of results from BGM/CGM and A1C. Dis-cordant results between BGM/CGM and A1C can be the result of the conditions outlined above or glycemic variability, with BGM missing the extremes.

Correlation Between BGM and A1C Table 6.1 shows the correlation between A1C levels and mean glucose levels based on the international A1C-Derived Average Glucose (ADAG) study, which assessed the correlation between A1C and frequent BGM and CGM in 507 adults (83% non-Hispanic White) with type 1, type 2, and no diabetes (12), and an empirical study of the average blood glucose levels at premeal, postmeal, and bedtime associated with speciﬁed A1C levels using data from the ADAG trial (13). The American Diabetes Association (ADA) and the American Association for Clinical Chemistry have determined that the correlation (r5 0.92) in the ADAG trial is strong enough to justify reporting both the A1C result and the estimated average glucose (eAG) result when a cli-nician orders the A1C test. Clicli-nicians should note that the mean plasma glu-cose numbers inTable 6.1 are based on

2,700 readings per A1C in the ADAG trial. In a recent report, mean glucose measured with CGM versus central labo-ratory–measured A1C in 387 participants in three randomized trials demonstrated that A1C may underestimate or overesti-mate mean glucose in individuals (11).

Thus, as suggested, a patient’s BGM or CGM proﬁle has considerable potential

for optimizing his or her glycemic man-agement (12).

A1C Differences in Ethnic Populations and Children

In the ADAG study, there were no signi ﬁ-cant differences among racial and ethnic groups in the regression lines between A1C and mean glucose, although the study was underpowered to detect a dif-ference and there was a trend toward a difference between the African and Afri-can AmeriAfri-can and the non-Hispanic White cohorts, with higher A1C values observed in Africans and African Ameri-cans compared with non-Hispanic Whites for a given mean glucose. Other studies have also demonstrated higher A1C lev-els in African Americans than in Whites at a given mean glucose concentration (14,15). In contrast, a recent report in Afro-Caribbeans found lower A1C rela-tive to glucose values (16). Taken together, A1C and glucose parameters are essential for the optimal assessment of glycemic status.

A1C assays are available that do not demonstrate a statistically signiﬁcant difference in individuals with hemo-globin variants. Other assays have sta-tistically signiﬁcant interference, but the difference is not clinically signi ﬁ-cant. Use of an assay with such

Table 6.1—Estimated average glucose (eAG)

A1C (%) mg/dL* mmol/L

5 97 (76–120) 5.4 (4.2–6.7) 6 126 (100–152) 7.0 (5.5–8.5) 7 154 (123–185) 8.6 (6.8–10.3) 8 183 (147–217) 10.2 (8.1–12.1) 9 212 (170–249) 11.8 (9.4–13.9) 10 240 (193–282) 13.4 (10.7–15.7) 11 269 (217–314) 14.9 (12.0–17.5) 12 298 (240–347) 16.5 (13.3–19.3) Data in parentheses are 95% CI. A calcula-tor for converting A1C results into eAG, in either mg/dL or mmol/L, is available at professional.diabetes.org/eAG. *These esti-mates are based on ADAG data of2,700 glucose measurements over 3 months per A1C measurement in 507 adults with type 1, type 2, or no diabetes. The correlation between A1C and average glucose was 0.92 (12,13). Adapted from Nathan et al.

(12).

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statistically signiﬁcant interference may explain a report that for any level of mean glycemia, African Americans heterozygous for the common hemo-globin variant HbS had lower A1C by about 0.3 percentage points when compared with those without the trait (17,18). Another genetic variant, X-linked glucose-6-phosphate dehydro-genase G202A, carried by 11% of Afri-can AmeriAfri-cans, was associated with a decrease in A1C of about 0.8% in hemizygous men and 0.7% in homozy-gous women compared with those without the trait (19).

A small study comparing A1C to CGM data in children with type 1 dia-betes found a highly statistically signi ﬁ-cant correlation between A1C and mean blood glucose, although the cor-relation (r 5 0.7) was signiﬁcantly lower than in the ADAG trial (20).

Whether there are clinically meaningful differences in how A1C relates to aver-age glucose in children or in different ethnicities is an area for further study (14,21,22). Until further evidence is available, it seems prudent to establish A1C goals in these populations with consideration of individualized CGM, BGM, and A1C results. Limitations in perfect alignment between glycemic measurements do not interfere with the usefulness of BGM/CGM for insulin dose adjustments.

Glucose Assessment by Continuous Glucose Monitoring

Recommendations

6.3 Standardized, single-page glu-cose reports from continuous glucose monitoring (CGM) devi-ces with visual cues, such as the ambulatory glucose proﬁle, should be considered as a standard sum-mary for all CGM devices.E 6.4 Time in range is associated with

the risk of microvascular compli-cations and can be used for assessment of glycemic control.

Additionally, time below target and time above target are useful parameters for the evaluation of the treatment regimen (Table 6.2).C

CGM is rapidly improving diabetes man-agement. As stated in the recommenda-tions, time in range (TIR) is a useful metric of glycemic control and glucose patterns, and it correlates well with A1C in most studies (23–28). New data sup-port the premise that increased TIR cor-relates with the risk of complications.

The studies supporting this assertion are reviewed in more detail in Section 7,

“Diabetes Technology” (http://doi.org/

10.2337/dc22-S007); they include cross-sectional data and cohort studies (29– 31) demonstrating TIR as an acceptable end point for clinical trials moving

forward and that it can be used for assessment of glycemic control. Addition-ally, time below target (<70 and <54 mg/dL [3.9 and 3.0 mmol/L]) and time above target (>180 mg/dL [10.0 mmol/

L]) are useful parameters for insulin dose adjustments and reevaluation of the treatment regimen.

For many people with diabetes, glu-cose monitoring is key for achieving gly-cemic targets. Major clinical trials of insulin-treated patients have included BGM as part of multifactorial interven-tions to demonstrate the beneﬁt of intensive glycemic control on diabetes complications (32). BGM is thus an inte-gral component of effective therapy of patients taking insulin. In recent years, CGM is now a standard method for glu-cose monitoring for most adults with type 1 diabetes (33). Both approaches to glucose monitoring allow patients to evaluate individual responses to therapy and assess whether glycemic targets are being safely achieved. The international consensus on TIR provides guidance on standardized CGM metrics (see Table 6.2) and considerations for clinical inter-pretation and care (34). To make these metrics more actionable, standardized reports with visual cues, such as the ambulatory glucose proﬁle (see Fig. 6.1), are recommended (34) and may help the patient and the provider better inter-pret the data to guide treatment deci-sions (23,26). BGM and CGM can be useful to guide medical nutrition therapy and physical activity, prevent hypoglyce-mia, and aid medication management.

While A1C is currently the primary mea-sure to guide glucose management and a valuable risk marker for developing diabe-tes complications, the CGM metrics TIR (with time below range and time above range) and GMI provide the insights for a more personalized diabetes management plan. The incorporation of these metrics into clinical practice is in evolution, and remote access to these data can be critical for telemedicine. A rapid optimization and harmonization of CGM terminology and remote access is occurring to meet patient and provider needs (35–37). The patient’s speciﬁc needs and goals should dictate BGM frequency and timing and consideration of CGM use. Please refer to Section 7,“Diabetes Technology” (http://

doi.org/10.2337/dc22-SPPC), for a more complete discussion of the use of BGM and CGM.

Table 6.2—Standardized CGM metrics for clinical care 1. Number of days CGM device is worn (recommend 14 days) 2. Percentage of time CGM device is active (recommend 70% of

data from 14 days) 3. Mean glucose

4. Glucose management indicator 5. Glycemic variability (%CV) target#36%*

6. TAR: % of readings and time>250 mg/dL (>13.9 mmol/L) Level 2 hyperglycemia 7. TAR: % of readings and time 181–250 mg/dL

(10.1–13.9 mmol/L)

Level 1 hyperglycemia

8. TIR: % of readings and time 70–180 mg/dL (3.9–10.0 mmol/L) In range

9. TBR: % of readings and time 54–69 mg/dL (3.0–3.8 mmol/L) Level 1 hypoglycemia 10. TBR: % of readings and time<54 mg/dL (<3.0 mmol/L) Level 2 hypoglycemia CGM, continuous glucose monitoring; CV, coefﬁcient of variation; TAR, time above range;

TBR, time below range; TIR, time in range. *Some studies suggest that lower %CV targets (<33%) provide additional protection against hypoglycemia for those receiving insulin or sulfonylureas. Adapted from Battelino et al. (34).

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