1. Understanding the Ups and Downs of Blood Glucose
Irl B. Hirsch, M.D.
University of Washington

2. Why are the risks of PDR different?
Question
Who has the greatest risk of proliferative diabetic retinopathy (PDR) over the next 10 years
A 55 y/o man with type 2 diabetes for 5 years, on oral agents, A1c = 9.0%
An 18 y/o man with 5 years of type 1 diabetes, on BID NPH/R, A1c = 9.0%
An 18 y/o man with 5 years of type 1 diabetes, on CSII, A1c = 9.0%
Why are the risks of PDR different?

3. Don’t forget about the “ups” and “downs”!
Postprandial hyperglycemia ≠ glycemic variability
Don’t forget about the “ups” and “downs”!

4. “Oxidative Stress” What Should You Know?
Oxygen is critical for life: respiration and energy
Oxygen is also implicated in many disease processes, ranging from arthritis, cancer, Lou Gehrig’s disease as well as aging
This dangerous form of oxygen is from the formation of “free radicals” or “reactive oxygen species”, or pro-oxidants
Normally, pro-oxidants are neutralized by anti-oxidants

5. “Oxidative Stress”: What You Should Know
Imbalance between pro-oxidants (free radicals, reactive oxygen species) and anti-oxidants

6. Oxidative Stress: Why is it Important?
Free radicals (reactive oxygen species) are known to fuel diabetic vascular complications

7. OK, What Turns On Oxidative Stress, Free Radicals, and Reactive Oxygen Species
High blood glucose
Science is confirmed on this point
Variability in blood glucose
Science is highly suggestive on this point

8. How Does One Measure…? Oxidative Stress Glycemic variability
Urinary isoprostanes: best marker of oxidative stress in total body
“HbA1c of oxidative stress”
Glycemic variability
Mean Amplitude of Glycemic Excursions (MAGE)
Standard deviation on SMBG meter download
I Hirsch

9. Urinary 8-SO-PGF2 alpha Excretion Rates
Correlation Between Urinary 8-iso-PGF2 alpha and MAGE in T2DM
1200
1000
800
600
400
200
Urinary 8-SO-PGF2 alpha Excretion Rates
(pg/mg creatinine)
MAGE (mg glucose/dL)
R=0.86, p<0.0001
JAMA 295: , 2006
I. Hirsch

10. Why This Study is So Important
Oxidative stress not related to A1c, fasting glucose, fasting insulin, mean blood glucose
Stronger correlation of oxidative stress to MAGE than to postprandial glucose levels!
MAGE = both the UPS and the DOWNS of blood glucose
I. Hirsch

11. So What Is The Significance of the Understanding of GV?
“…it suggests that different therapeutic strategies now in use should be evaluated for their potential to minimize glycemic excursion, as well as their ability to lower A1c.”
“…wider use of real-time continuous glucose monitoring in clinical practice would provide the required monitoring tool to minimize glycemic variability and superoxide overproduction.”
Brownlee M, Hirsch IB: JAMA: 295:1707, 2006
I. Hirsch

12. What About Long-Term Glycemic Variability?
Pittsburgh Epidemiology of Diabetes Complications
16-year follow-up of childhood T1DM, N=408
Results:
Risks of coronary disease over time related to A1c and variability of A1c!
Diabetes 55 (Supp 1): A1, 2006

13. What We KNOW Risk of complications are related to
Glycemic exposure as measured as A1c over time
Proven
Genetic risks
Clearly true, but little understanding
Glycemic variability
Supported by most but not all studies

14. Conclusion 1
Glycemic variability may be an important mechanism increasing oxidative stress and vascular complications
So how do we best measure glycemic variability in our patients with diabetes?
I. Hirsch

15. What’s a better way to assess glycemic variability?
Meter Downloads!
I. Hirsch

16. Which Patient Has More Variable Fasting Glucose Data?
Joe: HbA1c = 6.5%; on CSII with insulin aspart 60 54
148
146 70
203
165
132
110 79
185 68
210
138
144
252 75 77
Mary: HbA1c = 6.5%; on HS glargine and prandial lispro
Mean = 123 mg% Mean = 123 mg%
SD = SD = 63
I. Hirsch

17. Standard Deviation A measurement of glycemic variability
Can determine both overall and time specific SD
Need sufficient data points
Minimum 5 but prefer 10
I. Hirsch

18. Calculation To Determine SD Target
SD X 2 < MEAN
Ideally SD X 3 < mean, but extremely difficult with type 1 patients
I. Hirsch

19. Significance of a High SD
Insulin deficiency (especially good with fasting blood glucose)
Poor matching of calories (especially carbohydrates) with insulin
Gastroparesis
Giving mealtime insulin late (or missing shots completely)
Erratic snacking
Poor matching of basal insulin, need for CSII?
I. Hirsch

20. Other Significance of a High SD
Increased Oxidative Stress!
I. Hirsch

21. Caveats of the SD Need sufficient SMBG data
Low or high averages makes the 2XSD<mean rule irrelevant
I. Hirsch

22. Caveats of the SD: Low Mean56 85 98
106
110
113 46 60 59
128
Mean = 81; SD = 29
I. Hirsch

23. Caveats of SD: High Mean
210
249
294
112 77
302
288
259
321
193
Mean = 217; SD = 82
I. Hirsch

24. Putting it all together
Typical new patient visit to UW DCC
27 y/o woman on CSII for 5 years
Testing 4 to 5 times daily, A1c=6.4%
Major problems with hypoglycemia unawareness
Poor understanding of basic concepts of insulin use despite seen by specialists for 20 years (last appointment with endocrinologist was no more than 12 min for her “new patient appointment”)

25. After thinking about glycemic variability and oxidative stress
Question
After thinking about glycemic variability and oxidative stress
Who has the greatest risk of PDR over the next 10 years?
A 55 y/o man with T2DM for 5 years, on oral agents, A1c = 9.0%; Mean/SD = 210/50;
An 18 y/o man with 5 years of T1DM, on BID N/R, A1c = 9%; Mean/SD = 210/100;
An 18 y/o man with 5 years of T1DM, on CSII, A1c = 9% Mean/SD = 210/75;

26. The Future of Glycemic Variability: Measurements For the Future
SD: used with SMBG for over a decade with meter downloads; underutilized
Interquartile ratio: the range where the middle 50% of the values in a distribution falls, calculated by subtracting the 25th from the 75th percentile
Compared to SD, IQR not influenced by outliers
MAGE: gold standard (?) but requires continuous glucose sensing. May be more useful as we move into the CGM era
I. Hirsch

27. Data comparing these tools to markers of oxidative stress!
What We Need
Data comparing these tools to markers of oxidative stress!
I. Hirsch

28. Conclusions
Although there is no definitive proof from a randomized controlled trial, the data suggests that glycemic variability is a risk factor for microvascular complications
We have the opportunity to quantitate GV now with meter downloads
I. Hirsch

29. What You Should Take Away From This Discussion
A1c is not the only factor contributing to the complications of diabetes