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Making the Most of Continuous Glucose Monitoring Gary Scheiner MS, CDE Owner & Clinical Director Integrated Diabetes Services LLC Wynnewood, PA Dean Type-1.

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Presentation on theme: "Making the Most of Continuous Glucose Monitoring Gary Scheiner MS, CDE Owner & Clinical Director Integrated Diabetes Services LLC Wynnewood, PA Dean Type-1."— Presentation transcript:

1 Making the Most of Continuous Glucose Monitoring Gary Scheiner MS, CDE Owner & Clinical Director Integrated Diabetes Services LLC Wynnewood, PA Dean Type-1 University

2 Making the Most of Continuous Glucose Monitoring 1.What Information Is Available 2.How to Use Immediate Data 3.How to Use Intermediate Data 4.What Can Be Learned from Retrospective Analysis 5.Optimizing CGM System Performance

3 Sensor Daily Overlay Report Options: Medtronic Carelink Personal Sensor Overlay By Meal 3

4 Sensor tracing & BG entries Basal & bolus delivery Carbohydrate, exercise & logbook entries Daily Summary Layered Report: Report Options: Medtronic Carelink Personal 4

5 Avg, SD, Hi/Low # Hi/Low Excursions, AUC % Time above, below, within target range Statistical Summary Report Options: Medtronic Carelink Personal 5

6 Hourly Stats w/data table for each hour Glucose Trend Includes event entries Report Options: DexCom DM3* 6 * Dexcom 7+ System not FDA approved for use in children under age 18 in the U.S.

7 BG Distribution % high, low, normal for each segment of the day Modal Day Customizable date range Report Options: DexCom DM3 7

8 Success Report Report Options: DexCom DM3 16 Jan - 15 Apr 1016 Apr - 15 Jul 10Change A1c %0.0 % N/A Mean Glucose % Standard Deviation % % in Hypoglycemia (39-55 mg/dL)01N/A % in Low (55-70 mg/dL)13200 % % in Target ( mg/dL) % % in High ( mg/dL) % % in Hyperglycemia ( mg/dL) % Days Sensor Used % 12 am1 am2 am3 am4 am5 am6 am7 am8 am9 am10 am11 am 16 Jan - 15 Apr Apr - 15 Jul Changes in control: week-to-week, month-to-month, or quarter-to-quarter Breakdown by hour, with averages 8

9 Report Options: Freestyle Navigator/Copilot Modal Day Report Customizable by date range, day of week Glucose Line Report Stats Report Broken down by phase of the day 9

10 Report Options: Freestyle Navigator/Copilot Logbook Report (Sensor BG q10 minutes) 10

11 What Do We Get in Real Time? Trends Alerts Numbers

12 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

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

14 Immediate Info: Hypoglycemia Alerts 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

15 Types of Alerts Hi/Low Alert: Cross specified high or low thresholds Predictive Alert: Anticipated crossing of high or low thresholds Rate of Change: Rapid rise or fall

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

17 CGM Turns Mountains into Molehills

18 Uniform Response is Key! 1.Fingerstick 2.Act on the Fingerstick

19 Setting Alerts Hi/Low alert thresholds are not BG target ranges Balance need for alerts against nuisance factor Predictive alerts lose value the further the advance warning (keep below 10 min) Rate of FALL alerts helpful for long-term hypo prevention (>3 mg/dl/min) (.17)

20 LOW:80 mg/dl (4.5 mmol) (90/5+ if hypo unaware) HIGH:300 mg/dL (18 mmol) (lower progressively toward 180/10) NOT RECOMMENDED: Low 70 (4) NOT RECOMMENDED: High 140 (8) Initial Hi/Low Alert Settings

21 Special Alert Settings Young children (higher, wider range) Hypoglycemia unawareness, high- risk professions (higher hypo setting) Pregnancy (lower, narrower range) HbA1c of 11.0% (higher initially)

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

23 Can The Numbers Be Trusted? Not during first 1-2 cycles of using the system Not during the first hrs after sensor insertion If BG Stable If Recent calibrations in-line If No recent alarms

24 Specific Insights to Derive (a purely retrospective journey)

25 CGM Data Analysis Tools Hardware/Software Medtronic: –Internet Access to Carelink –Carelink USB Adapter Dexcom*: –PC, DM3 Software –Connector Cable Color Printer * Dexcom 7+ System not FDA approved for use in children under age 18 in the U.S.

26 Before You Analyze, Qualify. Were sufficient calibrations performed? Did the calibrations match the CGM data reasonably well? Was the data mostly continuous? Was the time/date set correctly? 26

27 Before You Analyze, Qualify. MAD = 28% Abnormal Artifact gaps & inaccuracy 27

28 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? Objectives-Based Analysis

29 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? Objectives-Based Analysis

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

31 Reports to Focus on Summary Statistics Modal Day / Overlay Graphs Individual Day Details 31

32 These Are a Few of My Favorite Stats… qMean (avg) glucose q% Of Time Above, Below, Within Target Range qStandard Deviation q# Of High & Low Excursions Per Week 32

33 Case Examples (the retrospective journey)

34 Case Study 1: The Dark Side of the Moon Type 2; using glargine and metformin Fasting readings OK; HbA1c elevated BG rising & staying high after meals. Consider meglitinide, exenatide, mealtime bolus insulin BG rising & staying high after meals. Consider meglitinide, exenatide, mealtime bolus insulin 3 AM 6 AM Glucose (mg/dL) AM 12 PM 3 PM 6 PM 9 PM

35 Case Study 2a: Fine-Tuning Meal/Correction Boluses Breakfast and lunch doses may be too low Dinner dose appears OK Glucose (mg/dL) AM 6 AM 9 AM 12 PM 3 PM 6 PM 9 PM Night-snack dose clearly insufficient 34-y.o. pump user

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

37 Case Study 2c: Fine-Tuning Meal/Correction Boluses BG Rising 9pm-1am. Consider structured night snacks with increased bolus amount. BG Rising 9pm-1am. Consider structured night snacks with increased bolus amount. Teenager on a pump; stays up late.

38 Case Study 2d: Fine-Tuning Meal/Correction Boluses Pumper, dropping low after correcting for highs during the night Corr. Bolus Consider increasing nighttime correction factor / insulin sensitivity

39 Case Study 3a: Postprandial Analysis Young adult on MDI. HbA1c are higher than expected based on SMBG Tired and lethargic after meals Significant postprandial spikes (300s). Consider pramlintide before meals. Significant postprandial spikes (300s). Consider pramlintide before meals. Glucose (mg/dL) Meal

40 Case Study 3b: 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. Spiking primarily after dinner. Consider lower g.i. food or pre-bolusing.

41 Case Study 3c: 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. Spiking primarily after breakfast. Consider splitting breakfast or walking post-bkfst.

42 Case Study 4a: 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. BG rising 1am-6am. Consider raising basal insulin 12am-5am.

43 Case Study 4b: Basal Insulin Regulation Glucose (mg/dL) AM 6 AM 9 AM 12 PM 3 PM 6 PM 9 PM Basal dose is likely too high. Consider reducing. Type 1 diabetes; using insulin glargine & MDI History of morning lows Snacking at night and not covering w/bolus

44 Case Study 4c: Basal Insulin Regulation Glucose (mg/dL) BG dropping after bolus action completed. Consider reducing basal rates early morning & late afternoon. Pump user, frequent lows before breakfast and dinner.

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

46 Case Study 6: 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. Dropping & rebounding during the night. Consider decreasing basal in early part of night.

47 Case Study 7: Effectiveness of Pramlintide/Exenatide 15 mcg pramlintide 60 mcg pramlintide

48 Case Study 8: Response Curve to Different Food Types Postprandial peak: cereal > oatmeal > yogurt Postprandial peak: cereal > oatmeal > yogurt Cereal Oatmeal Yogurt

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

50 Case Study 10a: Delayed Effects Experiencing delayed-onset hypoglycemia from heavy workouts. Consider temp basal reduction. Pump user Basal rates confirmed overnight yellow night: light cardio workout prior evening Red night: Lifting & cardio workout prior evening

51 Case Study 10b: Delayed Effects Delayed rise from high-fat meals. Consider using temp basal increase. Delayed rise from high-fat meals. Consider using temp basal increase. Saturday Nights, Dinner Out Pump user Normal fasting readings during the week, but high on weekends

52 Your Turn! What conclusions might you draw? What recommendations would you give?

53 Your Turn! What conclusions might you draw? What recommendations would you give?

54 Optimizing CGM System Performance Calibration Sensor & Site Care Signal reception Ingredients for success

55 Calibrate at times when blood glucose (BG) is stable (fasting, pre-meals)* Avoid calibrations during times of rapid glucose change* –Post meal –UP or DOWN arrows are displayed –In the period following a correction with food or insulin –During exercise * Not required w/Dexcom system Optimal Calibration

56 Calibrate before bedtime to avoid alarms during the night Use good SMBG technique –Proper coding –Clean hands –Sufficient blood sample –Fresh strips USE FINGERSTICKS Enter the calibration immediately after the fingerstick (Dexcom, Medtronic systems) Calibration

57 The Sensors Storage –Refrigeration preferred (but not required) –OK to use 1-2 months past expiration Site Selection –Fleshy areas –At least 2 Away from insulin infusion –Avoid tight clothing areas, scars, bruises, lipoatrophy –Rotate sites

58 The Sensors Timing –Allow adequate wetting time (Medtronic) –Put sensor in the night before connecting the transmitter (Medtronic) Bleeding/Irritation –Slight bleeding OK –Profuse bleeding: remove –Remove introducer needle at proper angle

59 The Sensors Adhesive –Completely cover the Transmitter & Sensor (Navigator & Medtronic systems) –Check sensor daily for loose tape –Apply extra tape over sensor & transmitter if tape patch begins to curl around edges Site Irritation –Watch for redness, swelling, tenderness –Remove sensor with prolonged irritation (>1 hour)

60 Signal Reception Heed transmitter ranges –Medtronic: 6 ft. –Dexcom: 5 ft. –Navigator: 10 ft. Signals do not travel well through water –Wear receiver on same side of body as sensor Keep receiver very close while charging (Dexcom) Charge transmitter fully every 6 days (Medtronic)

61 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

62 Questions?


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