Those who have been using continuous glucose monitoring (CGM) technology, like a Dexcom, for some time, are probably used to seeing the estimated A1c (eA1c) metric when reviewing their data trends. Discussions about how this metric correlates with the actual HbA1c level, as determined by a laboratory blood draw, have been ongoing in the diabetes community for some time. While for some patients, the eA1c as predicted via CGM data is in close agreement with their actual A1c values, for others, it may be quite discrepant from the laboratory value.
Experts explain that:
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.
As such, the U.S. Food and Drug Administration (FDA) recently called for a change to the name of the eA1c metric. Experts believe that renaming the eA1c metric would help to reduce patient and provider confusion, as for many individuals the prediction does not closely agree with the actual test result. Furthermore, researchers worked to develop a new formula that would better predict the expected A1c based on the most recently-available and accurate CGM data from numerous clinical trials.
In This Section
Glucose Management Indicator (GMI): A New Metric
Here is the breakdown of how the GMI metric differs from the previously-used eA1c in CGM data analysis:
The CGM-derived mean glucose would be entered into a standardized formula as before (although there is a slight modiﬁcation of the current eA1C formula), ) to generate a value similar to the previous eA1C value (and expressed in the same units [%]), but the name of the metric will be changed. The term GMI is intended to convey that this is a measure derived from glucose values and can provide an indication of the current state of a person’s glucose management. GMI is calculated from a formula derived from the regression line computed from a plot of mean glucose concentration points on the x-axis and contemporaneously measured A1C values on the y-axis. The studies used to generate the GMI equation [are all based on Dexcom data, but it is] expected that the formula would be similar irrespective of sensor accuracy, assuming that the sensor measurements are not directionally biased.
In summary, the GMI metric is similar to the eA1c metric, but was renamed to avoid confusion due to discrepancies from laboratory measurements, and is calculated with a very similar but slightly different formula that is based on more recent CGM trials.
How to Interpret the GMI Metric
Experts underscore that it is still very important to patients to get regular A1c labs, regardless of wearing a CGM, as “formulating an individualized A1c target is [an important] component of an effective glucose management plan.” The table below shows how the GMI metric can be interpreted by patients and providers:
Also, experts explain that individuals are likely to have the same kind of relationship between their GMI values and their A1c over time:
The literature available to date indicates that the difference in laboratory A1C and GMI remains relatively stable for each individual over time. If an individual has a lower GMI than expected from the measured A1C (lower average glucose than expected), then the GMI will usually continue to be lower than the laboratory A1C on repeated comparisons over time. Such an individual likely has a longer red blood cell (RBC) life span (slower RBC turnover rate) than average, a higher RBC glycation rate than average, or a variation in another, as yet undeﬁned biologic or genetic factor.
Essentially, the new GMI metric is very similar to the previously used eA1c metric, as it is an estimate of blood glucose control as reflected by what A1c level might be expected based on the patient’s particular data. However, the metric was renamed to not include the term “A1c” so as to avoid confusion if the predicted value does not closely agree with the laboratory A1c value. Also, the GMI formula was altered slightly, based on the most recently-available CGM studies.
To learn more, talk to your healthcare provider about how to best interpret your CGM data and what your A1c targets should be.