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Understanding the Ups and Downs of Blood Glucose

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

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Understanding the Ups and Downs of Blood Glucose

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

  2. 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. 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 Oxidative Stress = 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 • 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. Correlation Between Urinary 8-iso-PGF2 alpha and MAGE in T2DM 1200 1000 800 600 400 200 0 R=0.86, p<0.0001 Urinary 8-SO-PGF2 alpha Excretion Rates (pg/mg creatinine) 0 20 40 60 80 100 120 140 160 MAGE (mg glucose/dL) JAMA 295:1688-97, 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 Mary: HbA1c = 6.5%; on HS glargine and prandial lispro Mean = 123 mg% Mean = 123 mg% SD = 51 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 Mean Mean = 81; SD = 29 I. Hirsch

  23. Caveats of SD: High Mean 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. 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. 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

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