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
gary@integrateddiabetes.com
(877) 735-3648
CGM Options
FDA Approved
• Medtronic 530G integrated pump w/Enlite
sensor
• Medtronic Guardian® REAL-Time System
• DexCom G4 Platinum/Share
• Medtronic iPro, Dexcom G4 Professional
Pending FDA Approval
• Freestyle Libre
• Medtronic 640G
• Dexcom G5
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
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.
What Do We Get in Real Time?
 Numbers
 Alerts
 Trends
The Numbers:
Ballpark Estimates
+/- 20% if >80 (4.4)
+/- 20 mg/dl if <80 (+/- 1 mmol/l if < 4.4)
The Numbers:
The Ballpark Is Getting Closer!
Compared to YSi (lab)
Medtronic Sof-Sensor: +/- 17-18%
Dexcom 7+: +/- 15-16%
Medtronic Enlite: +/- 12-14%
Freestyle Navigator (n/a): +/- 12-13%
Dexcom G4: +/- 9-10%
Can The Numbers Be Trusted?
• Not during first 1-2 cycles of using the
system
• Not during the first 12-24 hrs after sensor
insertion
• If BG Reasonably Stable
• If Recent calibrations in-line
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
The Value of Alerts:
Minimizing the DURATION and
MAGNITUDE of BG Excursions
CGM Turns Mountains into Molehills
CGM Alerts Are Like
BLOOD SUGAR BUMPERS!
Response is Key
1. Fingerstick
(if nec.)
2. Act on the
glucose value
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)
Decision-Making
Based on Trend Information
• Self-Care Choices
o
o
o
o
To snack?
To check again soon?
To exercise?
To adjust insulin?
• Key Situations
o
o
o
o
Driving
Sports
Tests
Bedtime
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)
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
What Can We Get From
Analyzing CGM Data?
(a retrospective journey)
Completely
Overwhelmed!
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?
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?
Objectives-Based Analysis
8. How do various lifestyle events
affect BG?
–
–
–
–
–
–
–
Hi-Fat meals
Unusual foods
Stress
Illness
Work/School
Sex
Alcohol
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 23
Case Study 1a:
Fine-Tuning Meal/Correction Boluses
•
34-y.o. pump user
Glucose (mg/dL)
400
300
200
100
0
3 AM
Breakfast and
lunch doses
may be too low
6 AM
9 AM
12 PM
3 PM
Dinner dose
appears OK
6 PM
9 PM
Night-snack
dose clearly
insufficient
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.
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.
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
Case Study 2a:
Postprandial Analysis
Young adult on MDI.
HbA1c are higher than expected based on SMBG
Tired and lethargic after meals
400
Glucose (mg/dL)
•
•
•
300
Meal
200
100
Meal
Meal
Meal
Significant postprandial spikes (300s).
Consider pramlintide before meals.
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.
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.
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.
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)
•
•
•
300
200
100
0
3 AM
6 AM
9 AM
12 PM
3 PM
6 PM
9 PM
Basal dose is likely too high. Consider reducing.
Case Study 4:
Determination of Insulin Action Curve
12am
3-Hour
Duration
3am
6am
4-Hour
Duration
5-Hour
Duration
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.
Case Study 6:
Effectiveness of Amylin/GLP-1
•
15 mcg pramlintide
•
60 mcg pramlintide
Case Study 7:
Response Curve to Different Food Types
Cereal
Oatmeal
Yogurt
Postprandial peak:
cereal > oatmeal > yogurt
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!!
400
300
Glucose (mg/dL)
•
200
100
0
9 AM 12 PM 3 PM 6 PM
9 PM
STRESS CAN RAISE BLOOD GLUCOSE… A LOT!!!
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.
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.
Ingredients For Success
• Have the right expectations
• Wear the CGM at least 90% of the time
• Look at the monitor 10-20 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
Questions?