Making the Most of Continuous Glucose Monitoring

Transcription

1 Making the Most of Continuous Glucose Monitoring Gary Scheiner MS, CDE Owner & Clinical Director Integrated Diabetes Services LLC Wynnewood, PA AADE 2014 Diabetes Educator of the Year (877)

2 FDA Approved CGM Options Medtronic 530G, 630G integrated pump w/enlite sensor DexCom G4 Platinum/Share Dexcom G5 Medtronic ipro, Dexcom G4 Professional Pending FDA Approval Freestyle Libre Medtronic 670G Dexcom G6

3 How They Work Glucose sensor is inserted in subcutaneous tissue and connected to a transmitter Glucose sensor sends values to the transmitter Transmitter then sends data wirelessly to a pump or handheld monitor every 5 minutes, where data can be viewed and acted upon in real-time SC Sensor Transmitter Pump or Handheld Monitor

4 Interstitial Fluid and Lag Time Plasma (V1) (V2) Capillary glucose must diffuse into the interstitial fluid (ISF) ISF glucose levels may lag capillary levels by 5 15 minutes When glucose levels are stable, ISF glucose levels and capillary blood glucose levels are similar Overall, the sensor glucose trends are more important than the absolute measurements Illustration adapted from Rebrin K, et al. Am J Physiol. 1992;277:E561 E571.

5 What Do We Get in Real Time? ü Numbers ü Alerts ü Trends

6 The Numbers: Ballpark Estimates +/- 20% if >80 (4.4) +/- 20 mg/dl if <80 (+/- 1 mmol/l if < 4.4)

7 The Numbers: The Ballpark Is Getting Smaller! MARD Compared to YSi (lab) Medtronic Sof-Sensor: 17-18% Dexcom 7: 15-16% Medtronic Enlite: 12-14% Freestyle Libre: 11-12% Dexcom G5: 9-10%

8 Can The Numbers Be Trusted? 81% of CGM Users openly admit to using CGM glucose values for determining insulin doses.* *T1D Exchange Research, 2015

9 Can The Numbers Be Trusted? YES*. but Not during first 1-2 sensor cycles Not during the first hrs after insertion Not when recovering from hypoglycemia Not in state of rapid rise or fall Not if recent calibration off >20% Not if acetaminopthen taken in past 4 hrs *Off-label recommendation

10 ï Alerts ð

11 Types of Alerts Hi/Low Alert: Cross specified high or low thresholds Predictive Alert: Anticipated crossing of high or low thresholds (Medtronic only) Rate of Change: Rapid rise or fall

12 Hi/Low Alert: þ must balance benefit vs nuisance þ low: at least 80 mg/dl þ high: very high (300?), titrate down Predictive Alert: þ potential for false positives þ set for short time interval Rate of Change: þ >3 mg/dl/min fall rate may be useful Low Suspend (Medtronic only) þ can reduce incidence of hypoglycemia þ false positives are common

13 The Value of Alerts: Minimizing the DURATION and MAGNITUDE of BG Excursions

14 CGM Turns Mountains into Molehills

15 CGM Alerts Are Like BLOOD SUGAR BUMPERS!

16 Timely, consistent response is Key! 1. Act on the highs - hydrate - exercise - bolus (less IOB) 2. Act on the lows - rapid carbs

17 Decision-Making Based on Trend Information Self-Care Choices o To snack? o To check again soon? o To exercise? o To adjust insulin? Key Situations o Driving o Sports o Tests o Bedtime

18 Bolus Adjustment Based on Trend Information BG Stable: Usual Bolus Dose BG Rising Gradually: é bolus slightly* BG Rising Sharply: é é bolus modestly** BG Dropping Gradually: ê bolus slightly* BG Dropping Sharply: ê ê bolus modestly** * Enough to offset 25 mg/dl (1.5 mmol/l) ** Enough to offset 50 mg/dl (3 mmol/l)

19 Hypo Treatment Based on Trend Information Predictive Hypo Alert or Hypo Alert & recovering: Subtle Treatment 50% of usual carbs Med-High G.I. food Hypo Alert & Dropping: Aggressive Treatment Full or increased carbs High G.I. food vs

20 Hyper Treatment: When the levee trend graph breaks Break within 2 hours of bolus: do not correct! No break within 2 hours of bolus: Correct!

21 What Can We Get From Analyzing CGM Data? (a retrospective journey)

22 Completely Overwhelmed!

23 Objectives-Based Analysis 1. Are bolus amounts appropriate? Meal doses Correction doses 2. How long do boluses work? 3. What is the magnitude of postprandial spikes? 4. Is basal insulin holding BG steady?

24 Objectives-Based Analysis 5. Are asymptomatic lows occurring? Are there rebounds from lows? Are lows being over/under treated? 6. How does exercise affect BG? Immediate Delayed effects 7. Is amylin/glp-1 doing the job?

25 Objectives-Based Analysis 8. How do various lifestyle events affect BG? Hi-Fat meals Unusual foods Stress Illness Work/School Sex Alcohol

26 These Are a Few of My Favorite Stats q Mean (avg) glucose q % Of Time Above, Below, Within Target Range q Standard Deviation q # Of High & Low Excursions Per Week 26

27 Case Study 1a: Fine-Tuning Meal/Correction Boluses 34-y.o. pump user 400 Glucose (mg/dl) AM 6 AM 9 AM 12 PM 3 PM 6 PM 9 PM Breakfast and lunch doses may be too low Dinner dose appears OK Night-snack dose clearly insufficient

28 Case Study 1b: Fine-Tuning Meal/Correction Boluses 5-year-old on MDI; levemir BID. Dropping low 2-3 hours after dinner. Consider decreasing dinner bolus.

29 Case Study 1c: Fine-Tuning Meal/Correction Boluses Teenager on a pump; stays up late. BG Rising 9pm-1am. Consider structured night snacks with increased bolus amount.

30 Case Study 1d: Fine-Tuning Meal/Correction Boluses Pumper, dropping low after correcting for highs during the night Corr. Bolus Consider increasing nighttime correction factor / insulin sensitivity

31 Young adult on MDI. Case Study 2a: Postprandial Analysis HbA1c are higher than expected based on SMBG Tired and lethargic after meals 400 Glucose (mg/dl) Meal Meal Meal Meal Significant postprandial spikes (300s). Consider pramlintide before meals.

32 Case Study 2b: Postprandial Analysis Pump user, usually bolusing right before eating. Potatoes w/dinner most nights. Spiking primarily after dinner. Consider lower g.i. food or pre-bolusing.

33 Case Study 2c: Postprandial Analysis Pump user, 6 months pregnant Pre-bolusing (15-20 min) at most meals. Spiking primarily after breakfast. Consider splitting breakfast or walking post-bkfst.

34 Case Study 3a: Basal Insulin Regulation Pump user, 6 months pregnant Generally not eating (or bolusing) after 8pm. BG rising 1am-6am. Consider raising basal insulin 12am-5am.

35 Case Study 3b: Basal Insulin Regulation Type 1 diabetes; using insulin glargine & MDI History of morning lows Snacking at night and not covering w/bolus 400 Glucose (mg/dl) AM 6 AM 9 AM 12 PM 3 PM 6 PM 9 PM Basal dose is likely too high. Consider reducing.

36 Case Study 4: Determination of Insulin Action Curve 12am 3am 6am 3-Hour Duration 4-Hour Duration 5-Hour Duration

37 Case Study 5: Detection of Silent Hypoglycemia Type1 college student; on pump Frequent fasting highs (9-10 AM). Wanted to raise overnight basal rates. Dropping & rebounding during the night. Consider decreasing basal in early part of night.

38 Case Study 6: Effectiveness of Amylin/GLP-1 15 mcg pramlintide 60 mcg pramlintide

39 Case Study 7: Response Curve to Different Food Types Cereal Oatmeal Yogurt Postprandial peak: cereal > oatmeal > yogurt

40 Case Study 8a: Responses to Lifestyle Events (stress) Type 1 diabetes; pump user 40 years old; athletic Handsome, excellent speaker Late for meeting Gets flat tire; eats 15g carbs to prepare for tire change Spare is flat too!! Glucose (mg/dl) AM 12 PM 3 PM 6 PM 9 PM STRESS CAN RAISE BLOOD GLUCOSE A LOT!!!

41 Case Study 8b: Responses to Lifestyle Events (exercise) Pump user Basal rates confirmed overnight yellow night: light cardio workout prior evening Red night: Lifting & cardio workout prior evening Experiencing delayed-onset hypoglycemia from heavy workouts. Consider temp basal reduction.

42 Case Study 8c: Responses to Lifestyle Events (dining out) Pump user Normal fasting readings during the week, but high on weekends Saturday Nights, Dinner Out Delayed rise from high-fat meals. Consider using temp basal increase.

43 Ingredients For Success Have the right expectations Wear the CGM at least 90% of the time Look at the monitor times per day Do not over-react to the data; take IOB into account Adjust your therapy based on trends/patterns Calibrate appropriately Minimize nuisance alarms

44 Questions?