5/4/2009. Traditional Self Blood Glucose Monitoring. Continuous Glucose Monitoring: A New Tool for Optimizing Diabetes Management.

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1 Continuous Glucose Monitoring: A New Tool for Optimizing Diabetes Management Lynne Lyons, MPH, RD, CDE Clinical Science Manager Abbott Diabetes Care, Scientific Affairs Glucose (m mg/dl) Traditional Self Blood Glucose Monitoring Average of 136 mg/dl Standard Deviation of 62% 84% within target range 5 9: 11: 13: 15: 17: 19: 21: 23: 1: 3: 5: 7: 9: Time 2of 42 Glucose (m mg/dl) Where we are now View with Continuous Glucose Monitoring (CGM) Average of 152 mg/dl Standard Deviation of 85% 62% within target range Glycemic Characteristics in Continuously Monitored Patients with Diabetes N=11 (6 type 1, 41 type 2) 287 hrs of CGM masked 9 BG checks per day <7 mg/dl 8% of the time (1.9 hrs/d) 7-18 mg/dl 63% of the time 9-13 mg/dl ~28% of the time >18 mg/dl 29% of the time (7 hrs/d) Duration of hypoglycemia (hrs/day) Type hrs Type 2-1. hr 9: 11: 13: 15: 17: 19: 21: 23: 1: 3: 5: 7: 9: Time 3of 42 4of 42 Bode et al. Diabetes Care 28: ,25 1

2 Potential Benefits of CGM Reduce glycemic variability 1 Improve A1Cs 2,3 Without increasing risk of hypoglycemia Reduce incidence of serious hypo- and hyperglycemic events 4 Identify unrecognized hypoglycemia 5 What studies support the use of CGM? 5of Garg, et al. Diabetes Care 29:44-5,26 2. Deiss D, et al. Diabetes Care 29:273-32,26 3. JDRF CGM Study Group. NE Jrnl Med 359: ,28 4. Bode. Managed Care, Aug Chico et al. Diabetes Care 26: , 23 as % Hypoglycemia 1 75 CGM* Detects Unrecognized Hypoglycemia Percentage of patients with type 1 and type 2 diabetes with asymptomatic hypoglycemia detected by CGM % 47% All Patients T1 T2 N=7 Use of CGM* to Reduce Hypoglycemia Number of hypoglycemic episodes per day in masked vs unmasked CGM in Type 1 patients odes L) Mean # of Hypo Epis per Day (<7 mg/d Masked Data.8 Unmasked Data N=137 27% P= <.1 7of 42 *CGMS Chico et al. Diabetes Care 26: , 23 8of 42 *FreeStyle Navigator Bode, et al. Managed Care Aug/28 2

3 Effect of CGM* on A1C Effect of CGM on A1C A1C (%) Change in A1C in type 1 children and adults with A1Cs >8.1% N=162 Control group Biweekly group Continuous group Study: Continuous Glucose Monitoring and Intensive Treatment of Type 1 Diabetes The Juvenile Diabetes Research Foundation Continuous glucose Monitoring Study Group New England Journal of Medicine 359: , 28 Purpose: To evaluate the efficacy and safety of CGM in adults and children with type 1 diabetes 8 P =.8 P =.3 Baseline 1 Month 3 Months Time (months) 9of 42 *Guardian RT Deiss D, et al. Diabetes Care 29:273-32,26 1 of 42 Study Design N= 322 ENROLLMENT 165 CGM 157 Control Run In Phase 5:5 randomization RANDOMIZATION Real Time CGM Self Blood Glucose Monitoring 6 month outcome Real Time CGM Real Time CGM 12 month outcome Effect of CGM on A1C JDRF CGM Study Continuous vs non-continuous use Ability to lower A1C without severe hypoglycemia A1C Change Patient Group CGM SMBG P value 25+ years -.53%.2% < years -.18% -.21% years -.37% -.22% of of 42 JDRF CGM Study Group. NE Jrnl Med 359: ,28 3

4 A1C Improvement by Sensor Utilization Glycemic Variability Patient A: A1C =8.% 4 Percentage of subjects c Approx Change in A1c (%age points) 5% % CGM Use Age 25 Age Age 8-14 Change in A1c (%) A1C drop in all age groups, but dependent on CGM utilization <4. days/week 4.-<6. days/week 6. days/week Blood Glucose (mg/dl) Blood Glucose (mg/dl) Patient B: A1C = 8.% 13 of 42 JDRF CGM Study Group. NE Jrnl Med 359: ,28 5 Time (days) Used with permission from Clarke, Wm of hr CGM Profile with Similar A1Cs Use of CGM* to Identify and Reduce Glycemic Variability BG mg/dl BG mg/dl 3 Patient A A1C 6.9% : AM 2: AM 4: AM 6: AM 8: AM 1: AM 12: PM 2: PM 4: PM 6: PM 8: PM 1: PM 12: AM 3 Patient B A1C 6.7% : AM 2: AM 4: AM 6: AM 8: AM 1: AM 12: PM 2: PM 4: PM 6: PM 8: PM 1: PM 12: AM Mazze RM, Strock E, et al. Late-breaking abstract, American Diabetes Association Scientific Sessions, of 42 Adapted with permission, International Diabetes Center Time Sp pent (hours/d day) of 42*DexCom STS 21% 26% < Glucose range (mg/dl) 23% N=91 p=<.1 Control Display Garg, et al. Diabetes Care 29:44-5,26 4

5 Nocturnal Glycemic Variability Nocturnal Glycemic Ranges Time Spent (hours/ /night) % 33% < % p=< Control Display CGM Systems Glucose value (mg/dl) 17 of 42 Garg, et al. Diabetes Care 29:44-5,26 Evolution of CGM Systems Early 199s Today Retrospective/Intermittent Provider makes decisions based on glucose patterns retrospectively No real-time assessment of glycemia by patient (glucose trends, alarms) Identification of hypoglycemia unawareness Prospective/Continuous Real-time Allows patient to respond to glucose changes Immediate identification and treatment of hypo/hyper events following confirmatory blood glucose check Used in clinical arena Interstitial Fluid (ISF) Glucose Measurements Glucose Testing Timeline s 2+ Interstitial Fluid Testing 19 of 42 2 of 42 5

6 Continuous Glucose Monitoring FreeStyle Navigator Continuous Glucose Monitoring System* Characteristics of Prospective, Real-time CGM Systems Provides Continuous Glucose Readings DexCom Seven Continuous Glucose Monitoring System, and DexCom Seven Plus Continuous Glucose Monitoring System Measures Interstitial Fluid Glucose CGM Calibrated with Blood Glucose 21 of 42 MiniMed Paradigm REAL-Time System Insulin Pump and Continuous Glucose Monitoring System and Guardian REAL Time Continuous Glucose Monitoring System 22 of 42 Alarms to Warn of Hypo- and Hyperglycemia Trend Arrows indicate Glucose Rate and Direction Potential Candidates for CGM Getting Started with CGM Patients with type 1 or type 2 diabetes who are not reaching treatment goals despite adequate SMBG A1C/ glycemic variability Intentional hyperglycemia due to fear of hypoglycemia Frequent hypoglycemia or hypoglycemia unawareness Gastroparesis 24 of 42 6

7 Considerations for Patient Selection Ability to interpret and respond to the data appropriately Motivated to take diabetes meds and perform SMBG as indicated Getting Started with CGM Technology User expectations What are users expectations of CGM system? Goals in using CGM Scope and limitations of CGM How will he/she use the information in decision making? User readiness to utilize CGM information Is additional help needed for success in user s daily life? 25 of of 42 Managing Expectations Continuous glucose monitors are monitoring devices CGM systems are not a cure for diabetes CGM systems do not replace the need for fingersticks To improve diabetes control, users of CGM devices must: wear the CGM device look at the display frequently work with HCP to make decisions based on the data after confirmatory blood glucose tests Education Considerations Diabetes basics review Insulin action and duration Role of food choices Safe self-management practices i.e. checking blood glucose before driving CGM education Sensor basics Interstitial fluid (ISF) glucose and lag Data interpretation 27 of of 42 7

8 Capillary vs. Interstitial Fluid (ISF) Glucose CGM systems measure ISF glucose and are calibrated to plasma glucose ISF and capillary glucose levels similar when glucose levels stable Glucose diffusion between capillary and ISF accounts for a lag of ~14 minutes on average during periods of rapid glucose change Setting Glucose Alarms Find a balance between useful glucose information and excessive alarms Prevent alarm burnout Consider setting alarms widely during training period Low alarms lower and high alarms higher Caution patients not to rely entirely on glucose alarms to manage their diabetes 29 of 42 Adapted from Koschinsky, 21 3 of 42 Setting Low Glucose Alarms Setting High Glucose Alarms Setting at lower glucose level will minimize excessive alarms, but not capture all hypoglycemic events Users at low risk of hypo events Setting at higher glucose level will result in more false alarms, but will capture more hypo events Hypoglycemic unawareness Setting at higher glucose level will minimize excessive alarms, but not capture all hyper events Setting at lower glucose level will capture more hyper events, but will also increase the risk of false alarms Can be used to alert user of missed meal bolus 31 of of 42 8

9 Utilizing the Data Assess overall glycemic goals Address safety: severe hypoglycemia/hypoglycemia unawareness and hyperglycemic events Identify glycemic trends and patterns Utilizing Real-time Data on Receiver Where you are Adjustment of therapy in response to current glucose readings and high and low glucose alarms Where you re going Prediction of hypo- and hyperglycemic events by trends and rates of change (trend arrows and graphs, projected alarms) What preceded the event Feedback about glucose response to food, exercise, illness, medication (line graph) 33 of of of 42 Utilizing Real-time Data on the Receiver Scenario: Patient is getting ready to go to a restaurant for lunch and has the following information on his CGM receiver What would his likely response be? 11:45 A 3 hour 78 Learnings from the Line Graph Insulin Timing of 42 8a Yesterday 1a Insulin bolus: 7:3 AM Breakfast: 7:3 AM a Today 1a Insulin bolus: 7: AM Breakfast: 7:3 AM 9

10 Learnings from the Line Graph Effect of Food Learnings from the Line Graph Effect of Exercise Yesterday Today a 1a 8a 1a 2p 4p Bagel Breakfast Oatmeal breakfast Bike ride 2 minutes 37 of of 42 Retrospective Data Navigating the Future with CGM Review overall glycemic control Evaluate repeated glycemic patterns and day-to-day differences Optimize care by analyzing statistics, pie charts, and other retrospective ti data, as individualized id d for clinician and user Increase our knowledge Augment current therapies Develop new treatment options Enhance quality of life 39 of 42 4 of 42 1