At last week's Diabetes Technology Society Meeting in Bethesda, MD, Dexcom's VP of Science & Technology Tom Peyser presented a brand new metric for glycemic variability based on CGM data that may be much more useful and easier to understand than Standard Deviation.
"Glycemic variability" is of course a fancy name for how out-of-control your blood sugar levels are. Swinging between severe ups and downs all the time (high variability) puts you at risk for severe lows, may contribute to complications long-term, and sure as heck has a negative impact on your mood and quality of life.
"All are difficult to calculate. None are easy to understand. And all fail to differentiate between basic cases. A simple, easily understood, easily calculated glycemic variability metric is needed," Peyser stated in his DTS presentation.
Endocrine Society Annual Meeting Happening Now
Follow #ENDO2015 for updates on research & treatments.
FDA Approves New Basal Insulin
Sanofi's Troujeo has 'flatter profile' of action that helps to avoid lows.
Daytona Win for Racecar Driver with Diabetes!
Type 1 driver Ryan Reed wins first NASCAR series race at Daytona on Feb. 21.
His new concept is simple: look at the CGM data graph below. Instead of concentrating on how high or low the line is fluctuating, think about the LENGTH of that line if it were a piece of string and you stretched it out; the more ups and downs the line shows, the longer it would stretch out, of course, because the line would actually be longer.
Based on this "length of line"(or distance traveled) concept, Peyser says Dexcom has developed a new, "intuitive topological measure" they're calling the Glycemic Variability Index, or GVI. It can be easily calculated in Excel, using this "easy" trigonometry:
Then, calculated for a given length of time, the values are easily understood:
GVI = 1.0 to 1.2 means low variability (non-diabetic)
GVI = 1.2-1.5 means modest variability
GVI = >1.5 means high glycemic variability
Peyser says he's spent the past months working on this concept and running it by glycemic variability experts like Dr. Irl Hirsch, "and they all felt it had merit," he says.
To validate the concept, they've run comparisons to both the Standard Deviation and the commonly used MAGE measure, which he says is particularly complex to understand and calculate.
"Our results were comparable to both MAGE and Standard Deviation!" Peyser says.
But they didn't stop there.
They wanted to develop something whereby a patient's "full glycemic state can be characterized by a single number."
What they came up with is something called the Patient Glycemic Status (PGS) measurement. It combines calculations of your GVI + mean glucose + percentage of time in range, using this formula:
They even did a study of diabetic and non-diabetic subjects to validate these values:
PGS â‰¤35 excellent glycemic status (non-diabetic)
PGS 35-100 good glycemic status (diabetic)
PGS 100-150 poor glycemic status (diabetic)
PGS >150 very poor glycemic status (diabetic)
"Both GVI and PGS can be used to 'flag' problems in glycemic control and help clinicians direct resources to patients who need further help," Peyser asserted.
Don't forget that Peyser works for Dexcom, a CGM company. And the successful use of CGM is defined as reduced glycemic variability. They're all about ways to make better use of CGM data — and I think we can all get behind that as well!
I have no doubt we'll be hearing more about the new GVI and PGS markers in the coming year.
In the meantime, next time you're viewing your own CGM data, go get some string and scissors to measure your "line." Then, if you're not so hot at trigonometry, at least you can compare today's string to the one you'll cut out next time. Here's to achieving a shorter line!