Cgm case studies

Current Trends in Professional
Continuous Glucose Monitoring
Guest Editor:

Bruce W. Bode, M.D
Atlanta Diabetes Associates
Atlanta, Georgia

Proceedings of ‘‘Current Trends in Professional Continuous Glucose Monitoring (CGM),’’ Keck School of Medicine, University of Southern
California, Los Angeles, California, Sponsored by Medtronic.

Current Trends in Professional Continuous Glucose
Monitoring has been compiled and produced from
funding solely provided by Medtronic MiniMed, Inc.
and Lifescan, Inc. Medtronic MiniMed, Inc.
or its affiliates provided support for some of the
studies reported in the other articles included in
this special supplement.

Current Trends in Professional Continuous
Glucose Monitoring
contents
4

Introduction
B.W. Bode, P. Phillips, B. Nardacci, K.C. Arnold, B.S. Horowitz, O. Odugbesan, S. Reddy

6

Case 1: A 62-Year-Old Woman with Complex Medical History and Hypoglycemia Unawareness
P. Phillips

9

Case 2: A 60-Year-Old Woman with Diabetes Secondary to Necrotizing Pancreatitis with
Highly Variable Blood Glucose Levels on Basal Bolus Therapy
E. Nardacci

12

Case 3: A 41-Year-Old Man with Type 1 Diabetes with Good Glucose Control
K.C. Arnold

14

Case 4: A 29-Year-Old Woman with Type 1 Diabetes, Pregnant with Triplets
K.C. Arnold

16

Case 5: A 61-Year-Old Man with Type 1 Diabetes
S. Reddy

18

Case 6: A Type 1 Diabetic College Student with a Crazy Lifestyle and Crazy Blood Sugars
B.S. Horowitz

20

Case 7: A 38-Year-Old Woman with Type 1 Diabetes
B.W. Bode

23

Case 8: A 69-Year-Old Woman with Type 2 Diabetes and Good Premeal Glucose, But a High A1c
B.S. Horowitz

26

Case 9: A 37-Year-Old Woman with Type 2 Diabetes at 20 Weeks of Gestation
K.C. Arnold

28

Case 10: A 41-Year-Old Woman with Type 2 Diabetes, High A1c
O. Odugbesan

31
37
41

Discussion Regarding Use of Professional Continuous Glucose Monitoring
Professional Continuous Glucose Monitoring (CGM) Progress Note
HIGHLIGHTS FROM DIABETES TECHNOLOGY & THERAPEUTICS
Continuous Glucose Monitoring in Non-Insulin-Using Individuals with Type 2 Diabetes: Acceptability,
Feasibility, and Teaching Opportunities
N.A. Allen, J.A. Fain, B. Braun, S.R. Chipkin

49

Sustained Efficacy of Continuous Subcutaneous Insulin Infusion in Type 1 Diabetes Subjects with
Recurrent Non-Severe and Severe Hypoglycemia and Hypoglycemia Unawareness: A Pilot Study
M. Gimenez, M. Lara, and I. Conget

54

Maximizing Reimbursement through Correct Coding Initiatives
E. Orzeck

Introduction
Bruce W. Bode, M.D.,1 Paula Phillips, M.D.,2
Elizabeth Nardacci, FNP-C,3 Kathleen C. Arnold, A.N.P.,4
Barry S. Horowitz, M.D.,5 Ola Odugbesan, M.D.,6
Sushma Reddy, M.D.7

case presentations, the role of professional CGM in the real world
was discussed.

1

Atlanta Diabetes Associates, Atlanta, Georgia.
Diabetes & Metabolism Specialists, San Antonio,
Texas.
3
Albany Medical Center, Albany, New York.
4
The Diabetes Center, PLLC, Ocean Springs, Mississippi.
5
Palm Beach Diabetes and Endocrine Specialists, PA, West Palm
Beach, Florida.
6
North Atlanta Endocrinology, Lawrenceville, Georgia.
7
Endocrinology & Diabetes Center, Fort Gratiot,
Michigan.
2

D

Abstract
A total of 10 patients were discussed during this meeting entitled ‘‘Current Trends in Professional Continuous Glucose Monitoring (CGM).’’ Seven patients had type 1 diabetes and faced
challenges with day-to-day glucose control, five with poor glucose
and two with normal A1c. Two patients switched to insulin pump
treatment after reviewing their progessional CGM data. Another
subject with type 2 diabetes on oral agents switched to CSII and
was able to achieve target A1c and deliver a healthy, normal-sized
baby. Two other patients had type 2 diabetes: one on MDI using
large amounts of insulin, and another on oral agents only. After

uring the ‘‘Current Trends in Professional Continuous
Glucose Monitoring (CGM)’’ symposium, held at the University of Southern California on November 20, 2009, seven
distinguished experts in the field of CGM from around
the country presented and discussed the use of professional CGM in
10 patients. After the case presentations, all seven faculty members
discussed which patients are appropriate candidates for professional CGM, and how physicians and nurse practitioners do professional CGM in the real world, using professional CGM outputs to
make appropriate therapy adjustments, and scheduling follow-up
evaluations.
Glucose monitoring has evolved from urine testing to selfmonitored blood glucose (SMBG) to CGM. The first continuous
glucose sensor was introduced in 1999 (Fig. 1). This early device
incorporated a sensor that measures interstitial glucose, continuously giving an average glucose reading of the interstitial fluid
every 5 min up to 188 tests per day over a 3-day period. The initial
data showed that the device significantly lowered HbA1c in people
with elevated A1c, and reduced severe hypoglycemia in patients
with normal A1c.
There are four commercially available CGMs, two from Medtronic MiniMed (one professional and retrospective, and the other
real-time), Freestyle Navigator and Dexcom SEVEN Plus (Fig. 2).
Professional CGM is a blinded evaluation by the healthcare provider, who places a sensor with a transmitter on the patient in the

Evolution of Diabetes Management Technologies

Insulin pump therapy
Urine glucose testing

Continuos
glucose sensor

Point-in-time
BG meters

Integrated systems:
Pumps/Meters/Software

Discovery of insulin
Artificial
Pancreas

1900s

1922

1977

1978

1999

2003

Fig. 1. Evolution of diabetes management technologies. The first
continuous glucose sensor was introduced in 1999. The first device
that integrated insulin pumps, glucose sensors, and software
was introduced in 2003.

4

CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING

Fig. 2. The two types of continuous glucose monitoring target different users: health care professionals and empowering individual
patients with diabetes.

ª 2010 Medtronic Minimed, Inc. All rights reserved.

INTRODUCTION

office. The provider instructs the patient to continue usual care and
keep a log of SMBG readings; time and dosage of whichever insulin
or oral agents being taken; meal times; and food intake, activity,
and symptoms of high and low blood sugar. Patients are blinded to
the glucose values, and return to the office after 3 days to download
the data. After reviewing the data from the professional CGM
device, the healthcare provider recommends necessary therapeutic
changes.
In contrast, personal CGM (also known as real-time CGM) devices
are worn by the patient for longer periods and enable the patient to
see real-time glucose values throughout the day, and make changes

on their insulin dose or adjust food intake to avoid extreme hypoand hyperglycemia.
Address correspondence to:
Bruce W. Bode, M.D.
Atlanta Diabetes Associates
77 Collier Road, Suite 2080
Atlanta, GA 30309
E-mail: bbode001@aol.com

CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 5

Case 1
A 62-Year-Old Woman with Complex Medical History
and Hypoglycemia Unawareness

Paula Phillips, M.D.
Diabetes & Metabolism Specialists, San Antonio, Texas.

Patient History
The first case is an obese 62-year-old woman with type 1 diabetes
(diagnosed at the age of 30 years) and hypoglycemia unawareness. On
initial presentation in March 2008, the patient had inadequate glucose
control with an A1c of 9.6%. She was on NPH 10 units in the morning,
Glargine 15 units at bedtime, and a sliding scale of rapid-acting insulin
analog before meals. She had wide glycemic excursions on four-timesa-day self-monitored blood glucose (SMBG) ranging from 37 to
542 mg=dL. Most of the hypoglycemic episodes (<50 mg=dL) were in
the morning, and thus she never used the sliding scale at breakfast. By
lunchtime, her blood glucose (BG) ranged between 300 and
350 mg=dL.

Comorbidities and Diabetic
Complications
The patient’s history is significant for anoxic brain injury that
occurred in June 2006 while wearing an insulin pump. Apparently,
she had very little training on the insulin pump, did not change it
every 3 days, and experienced infections at the site as a result. After
the hypoglycemic episode, she had to be in a nursing home for 4 years
before going home to her family.
Additional comorbidities include diabetic neuropathy and gastroparesis. She was on metoclopramide treatment but for her gastrointestinal complaints. She functions relatively well considering her
brain injury, with a minor tic, some speech difficulties, and poor
memory. She is very meticulous recording BG and everything she
eats. Her surgical history is significant for cholecystectomy and
hysterectomy.

Rationale for Initiating Professional CGM
After initial presentation, the provider changed the patient’s regimen to basal bolus insulin with Glargine at bedtime and premeal
insulin aspart with a supplemental scale. Subsequently, this was
adjusted to split basal dosing, but she continued to have wide glycemic excursions. Before her initial professional CGM study in
May 2009, her baseline A1c had improved by 1% to 8.6%. Her
treatment at that time had evolved to Detemir twice a day at 8:00 am
and 6:00 pm with a higher dose at bedtime if her BG level exceeded
250 mg=dL. She took insulin Aspart *6 units before meals on a
sliding scale.

6


On the basis of SMBG, she seemed to have relatively good BG
before lunch and dinner, but her morning BGs were very high. If her
bedtime BG was very elevated ([250 mg=dL), she tended to drop and
there was a big difference between her bedtime BG and the BG value
the next morning. If her BG was reasonably controlled at bedtime
(<150 mg=dL), then she would have very high fasting blood sugars
(400–500 mg=dL). Thus, the rationale for the initial professional CGM
was to try to distinguish if this pattern was due to snacking at bedtime
due to fear of hypoglycemia, or due to counter regulatory hormones
in response to nocturnal hypoglycemia.

Initial Professional CGM Results
The initial professional CGM revealed no evidence of overnight hypoglycemia. Her CGM glucose averaged 193 mg=dL, and
she is in the hyperglycemic range most of day as shown by the large
red segments in the pie chart of the Sensor Summary (Fig. 3). The
charts also had some blue segments, indicating minimal periods of
hypoglycemia. The Sensor Summary highlights a poor glucose
control.
The Sensor Modal Day tracings were highly variable, with an inconsistent pattern in the morning (including two brief periods of
hypoglycemia), and significant postmeal excursions both at breakfast and dinner, with a drop in BG late afternoon (Fig. 4).

Therapy Adjustments=Treatment Alterations
The provider adjusted the basal insulin to Detemir BID 7 units in
the morning and 10 units at night (11 units if BG [ 220 mg=dL at
night) due to high morning BG. Aspart was maintained at the same
dose. The patient saw the certified diabetes educator and nurse
practitioner every 1 to 3 weeks. Most of the patient’s meals and snacks
were low on protein, so she was instructed to have protein with each
meal and snack, but to limit snacks overall.

Follow-Up Professional CGM Results=
Response to Therapy Adjustments
On follow-up professional CGM, the BG pattern showed fewer
excursions after breakfast and lunch (Fig. 5). The patient continued to
have hyperglycemia after dinner that continued for up to 6 h, particularly after meals with high-fat content. On two out of the three
evenings, her BG monitor recorded over 449 mg=dL.
Examination of professional CGM outputs and the patient’s handwritten diary revealed that the patient was recording her BG levels in
her diary inaccurately. For example, if the SMBG meter reading was
95, the patient recorded it as 195, probably due to her brain injury.


Sensor Summary
7/20/2009

7/21/2009

7/22/2009

7/23/2009

Totals

# of Sensor Values

92

288

288

159

827

Average (mg/dL)

192

205

169

293

208

43-306

83-346

50-353

43-381

STDev (mg/dL)

99

58

74

181-381
63

# of Meter Values

2

4

4

2

12

Average (mg/dL)

191

157

149

283

181

66-315

177-192

56-235

196-369

56-369

Date

Sensor

Meter

Min - Max (mg/dL)

Min - Max (mg/dL)
Designation
Optimal Accuracy
Criteria

# of Paired Readings

X: Use Clinical
Judgment

83

X: Use Clinical
Judgment

2

4

4

2

12

Mean Abs. Diff. [MAD %]

19.3

17.7

6.1

5.5

12.1

Correlation Coeff. [R]

n/a

0.99

n/a

0.97

2

3

7

0

12

# of High Excursions*

1

3

6

0

10

# of Low Excursions*

1

0

1

0

2

Duration Above High Limit

04:30 (59%)

20:25 (85%)

14:30 (60%)

13:15 (100%)

52:40 (76%)

Duration Within Limits

02:05 (27%)

03:35 (15%)

07:15 (31%)

00:00 (0%)

12:55 (19%)

Duration Below Low Limit

01:05 (14%)

00:00 (0%)

02:15 (9%)

00:00 (0%)

03:20 (5%)

Glucose Area Above High
Limit (mg/dL*Day)

75

68

43

153

76

Glucose Area Below Low
Limit (mg/dL*Day)

Excursions
High > 140mg/dL
Low < 70mg/dL

n/a

# of Excursions*

3

0

1

0

1

Pie Chart
Red: Above Limits
Green: Within Limits
Blue: Below Limits

X: Please use your clinical judgment - this day does not satisfy the optimal accuracy criteria according to set thresholds:
N [¼ 3, R [¼ 0.79 and MAD <¼ 28% [or <¼ 18% if the range (Min-Max) of meter values is less than 100 mg=dL (5.6 mmol=L) - see
Criteria Note below].
C: This day does not have any paired sensor=meter data and no sensor plot is provided. As a result, ‘Meter Only’ data is available.
S: Please use your clinical judgment - this day does not have any meter data. As a result, ‘Sensor Only’ data is available.
Criteria Note: If the range (Min-Max) of Meter Values is less than 100 mg=dL (5.6 mmol=L) then ‘R’ will be reported as ‘N=A’.
In this case the optimal accuracy threshold set for MAD is <¼18%.
Excursion Note: Excursions are counted in the day that the excursion event started.

Fig. 3. The red segments of the Sensor Summary pie chart show that the patient is hyperglycemic most of day.

Fig. 4. The Sensor Modal Day report show two brief periods of hypoglycemia (shown in blue and
green), and significant postmeal
excursions.


PHILLIPS

Fig. 5. The Sensor Modal Time Report shows that the patient experienced hyperglycemia after dinner that continued for up to 6 h.

Given the patient’s generally poor dietary habits, she would have
benefited from a correction factor and a carbohydrate ratio instead of
sliding scale insulin. However, given her cognitive deficits, she would
likely be unable to master the calculations involved.

Conclusions
The follow-up professional CGM tracings revealed the need to
adjust insulin or diet (or both) at dinner and decrease the amount of
basal insulin at night. Because of her hypoglycemic unawareness and
marked excursions in her glycemic control, the patient would benefit

8 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING

from a personal CGM with an audible warning. She would also
benefit from insulin-pump therapy. Theoretically, given her gastroparesis and the way she responds to high-fat meals, the endocrinologist could prescribe square wave bolus or dual wave bolus, and
variable basal rates starting at 3:00 am or 4:00 am onward, but it would
be clinically challenging to pursue this option.

Disclosure Statement
Paula Phillips, M.D., is a speaker for Medtronic Diabetes.

Case 2
A 60-Year-Old Woman with Diabetes Secondary to Necrotizing Pancreatitis with
Highly Variable Blood Glucose Levels on Basal Bolus Therapy


Elizabeth Nardacci, FNP-C
Albany Medical Center, Albany, New York.

Patient History
This patient developed necrotizing pancreatitis and was found to
have diabetes in January 2008, about a year before the initial professional continuous glucose monitoring (CGM) evaluation. Despite
multiple visits with both the physician and the diabetes educators, the
patient had continued difficulty in dosing her insulin correctly. Her
baseline regimen was Aspart *4 to 6 units with meals. She would not
adjust her insulin dose more than 2 units at a time. She was also on
Glargine 14 units at bedtime, which occurred at very varied times.
Her initial A1c was 10.2%.

The average sensor value was 269 mg=dL, which corresponded
with A1c of 10.2%. Only 13% of her glucose readings were within the
target range (WTR 70–150 mg=dL), 2% below the target, and 85% of
readings were above the target (>150 mg=dL).
The Sensor Modal Day revealed no consistent BG pattern. BG
ranging from 200 to above 400 mg=dL. The provider examined the
diary with the patient, comparing it to the professional CGM tracings.
According to her diary, the patient was taking her glargine at varying
times, but admitted missing her injections. (Fig. 6).
The blue plus signs on the Sensor Modal Details indicate when the
patient does SMBG. The tracing indicated wide glucose excursions
that were not detected by SMBG (Fig. 7).


Rationale for Initiating Professional CGM
The patient was inexperienced with insulin dosing and really
wanted to do a better job, as she had wildly fluctuating blood glucose
(BGs). She felt hypoglycemic everyday, complained of feeling poorly,
and was having difficulty functioning, especially in caring for her
12-year-old grandson of whom she had custody. She checked her BG
up to six times daily because of concern about her symptoms. She
never missed appointments with our diabetes educators, whom she
saw frequently. The diabetes educators initiated the professional CGM.

After using the Professional CGM, the provider recommended an
insulin pump, and the patient agreed.

Follow-Up Professional CGM Results=Response
to Therapy Adjustments
Four months after initiating insulin pump therapy, the patient had
better BG control because of the continuous infusion of the basal
insulin. The patient said things were better generally, but she still felt
like she was experiencing hypoglycemia at lunchtime.

Fig. 6. The Sensor
Modal Day output
shows severe
hyperglycemia.



9

NARDACCI

Fig. 7. The Sensor Daily Details highlight peak blood glucose readings that were missed on self-monitoring of blood glucose.

Fig. 8. Sensor Modal Day indicates less blood glucose variability overall compared to the earlier evaluation.

10


CASE 2: WOMAN WITH DIABETES SECONDARY TO NECROTIZING PANCREATITIS

On follow-up professional CGM, the Sensor Modal Day was much
improved (Fig. 8). The tracings confirmed the patient’s perceptions:
she was overcorrecting and experiencing hypoglycemia in the afternoon. The mean sensor value dropped from 269 to 179 mg=dL, and
the standard deviation went from 101 to 79, indicating reduced
glucose excursions. The A1c declined from 10.2% initial, to 9.9% in
January 2009, and to 7.8% in July 2008.
The patient was able to maintain and improve control, experiencing brief periods of hyperglycemia during the day. Her postprandial BGs remained elevated. She was carbohydrate counting
well, according to the dietician, so the provider altered the pump
settings to increase the patient’s basal rates slightly at night, assuming that the patient probably experienced some hypoglycemia
unawareness. The insulin of carbohydrate ratio was also adjusted.
The patient was doing what the bolus wizard told her to do, but
since the setting was incorrect she was overcorrecting. The clinician adjusted the sensitivity number upward to give her less of a
correction.

This case illustrates three major issues that illustrate the use of
professional CGM to generate an ‘‘aha! moment.’’ (1) The process of
going through the professional CGM output and looking at the diary
often elucidates previously hidden behavior that plays a key role in
glycemic control. This patient would not have admitted missing
glargine doses without seeing the wide glucose excursions. (2) The
patient had been taking her evening dose of insulin at varying times.
The professional CGM tracings provided adequate information to accept
an insulin pump, because the patient could maintain BG control despite
bed times that could differ from night to night by 6–8 h. (3) Although
ordinarily a very anxious patient might not be an ideal pump therapy
candidate, this patient was highly motivated and able to do a good job
with a lot of education and support. Using the bolus wizard was very
critical in helping this patient become confident in making dosing
decisions, compared to her earlier hesitation in adjusting her injections
by only 2 units each time. These changes allowed to patient to lower and
maintain her A1c values and confirmed that she was making better
decisions.

Conclusions


Professional CGM identified multiple reasons for uncontrolled
diabetes in this patient. Although the patient is not at goal, she has
improved significantly.

Elizabeth Nardacci, F.N.P., BC-ADM, is a speaker for Eli Lilly and
Medtronic Diabetes. She is on the medical advisory board of Medtronic Diabetes.


11

Case 3
A 41-Year-Old Man with Type 1 Diabetes with Good Glucose Control

Kathleen C. Arnold, A.N.P.

Patient History
This patient is a 41-year-old man found to have type 1 diabetes in
February 2008. He had no other significant medical history or diabetes complications, and his A1c was 5.9%. He was managed with
Glargine, 15 units at bedtime, and Aspart with a correction formula
and a carbohydrate ratio, and he tested his blood glucose (BG) four to
five times daily. He was an avid bicyclist who took 1–4-h bike rides
3–5 days a week.

Rationale for Initiating Professional Continuous
Glucose Monitoring

Fig. 9. Sensor Modal Time tracing for an avid cyclist. Red arrows
indicate unrecognized hyperglycemia and hypoglycemia.

Both the patient and the healthcare provider wanted professional continuous glucose monitoring (CGM) to evaluate the BG
control on cycling days.

Fig. 10. Sensor Daily Details reveal most blood glucose values are within range, even on days that the patient takes long bike rides.

12



CASE 3: MAN WITH DIABETES AND GOOD GLUCOSE CONTROL

The CGM tracings showed that the patient had overall good glycemic control, with the exception of hyperglycemia when he was
prepping for long rides. For long rides he ‘‘carbo loaded’’ to keep his BG
up when he is riding with a product called ‘‘goo,’’ which contains 80–
100 g of instant-acting carbohydrate. The Sensor Modal Day revealed
hypoglycemic and hyperglycemic excursions, of which the patient was
unaware.
The patient tried to ride almost every day during his professional
CGM evaluation, and he had no problems with sensor adherence while
riding. The Sensor Daily Details reveal which days the patient was
cycling by BG peaks (Fig. 9). He did have some unrecognized hyperglycemia during the night, and several episodes of unrecognized hypoglycemia.

Therapy Adjustments=Treatment
Alterations
The only therapy adjustment for this patient was to change the
way he carbohydrate loads before a ride. He now eats a longer-acting
carbohydrate bar that includes some protein. No change in his insulin
regimen was necessary.
The patient is considering an insulin pump. He practiced with a
smart pump with tubes, which was too bulky for his body type did not

adhere well to his skin during bike rides. He has applied for an insulin
pump with disposable components instead.

Follow-Up Professional CGM
Follow-up professional CGM revealed that most of his blood sugars
are within the range, with fewer episodes of hypoglycemia (Fig. 10). He
continues to ride but will take a break during the cold weather.

Conclusions
This case illustrates that even though the patient had good glucose
control, this apparent level of control masked swings in BG subsequent to carbohydrate loading with the simple carbohydrate gel.
Once he changed his preride carbohydrate source with protein, he
was able to normalize his BG, not only during the day, but also
overnight. Professional CGM also helped this patient to take the next
step for better glycemic management by highlighting the benefits
that an insulin pump would provide.

Kathleen C. Arnold, A.N.P., BC-ADM, is a speaker for Lilly, Medtronic Diabetes, NovoNordisk, and Sanofi Aventis.


Case 4
A 29-Year-Old Woman with Type 1 Diabetes, Pregnant with Triplets


Patient History
A 29-year-old patient with previously diagnosed type 1 diabetes
presented with a nonplanned pregnancy with triplets. Her A1c at 14
weeks of gestation was 7.3%.

Rationale for Initiating Professional
The provider usually manages pregnant women with type 1 diabetes
using an insulin pump because of the rapidly changing needs for
insulin during pregnancy. The patient had a hypoglycemic seizure due
to insulin stacking and was transported to the hospital by ambulance.
Her baseline treatment was a Medtronic Paradigm 722 pump, and she
tested her blood glucose (BG) six to eight times daily.

Initial Professional Continuous Glucose
Monitoring Results
Professional continuous glucose monitoring (CGM) revealed
multiple hyperglycemic and hypoglycemic episodes, of which the
patient was unaware of, because she did performed self-monitored
blood glucose (SMBG) at times other than when the peaks or lows
occurred (Fig. 11). Although the CGM device has 70 mg=dL as the default, the value should be changed to 60 for pregnancy. For pregnancy, target BG 2 hours postprandial is 120=mg=dL, and the patient
did not always achieve that.

Therapy Adjustments
She initiated her pump very early in the pregnancy, and her pump
downloads indicated hypoglycemia regularly. Premeal targets in
pregnancy are 60 to 80 mg=dL, and she was having readings in the
50 mg=dL range.
After looking at the professional CGM output and at the patient’s
A1c, the provider recommended personal CGM. The patient’s A1c
started out at 9.9% before pregnancy and then declined, first to 7.3%
and then to 5.6%, once on insulin pump therapy.

In early September, the patient had some complications. She underwent an intrauterine laser surgery to separate blood vessels of the
two identical twins within this triplet pregnancy that were sharing a
blood source; one of the fetuses was not growing. She subsequently
developed preeclampsia. She delivered via C-section at 22 weeks’
gestation. One male infant weighed 1 pound 4 ounces, and another
male 1 pound 3 ounces; the third infant died within 18 hours of birth.
Both live infants were placed on ventilators. The patient developed
postoperative pneumonia and Escherichia coli infection. While being
treated for the infections, she was taken off her pump and given
insulin infusions for a couple of days and then returned to the insulin
pump.

Conclusions
Professional CGM helped this pregnant woman with type 1 diabetes, to realize that she was experiencing hypoglycemic excursions
and hyperglycemia on a daily basis, and drove the decision to pre-

Fig. 11. The Sensor Daily Details identify exactly when multiple hyperglycemic and hypoglycemic episodes occur.

14



CASE 4: WOMAN WITH DIABETES, PREGNANT WITH TRIPLETS

scribe a personal sensor. The CGM technology enabled day by day
adjustments that resulted in a shift from an A1c of 9.9% to 5.6%.
As the pregnant abdomen expands, placement of sensors has to
change. Sometimes the patients may move the sensor from the abdominal area to the legs or buttocks.
This patient was compliant with her regimen after the hypoglycemic episode. The patient used her Bolus Wizard 100% of the time,
and performed SMBG four to five times daily.
Often times with pregnancy in women with type 1 diabetes, especially with triplets, you may not have the best outcome. Her preterm

labor was likely related either to the intervention they did at the
hospital or to her extremely poor control before conception, at which
time the patient was followed by a different provider. The two surviving babies are doing well.



Case 5
A 61-Year-Old Man with Type 1 Diabetes

Sushma Reddy, M.D.

four times a day, he still experienced unrecognized hyperglycemic
peaks that were missed with SMBG.

Endocrinology & Diabetes Center, Fort Gratiot, Michigan.

Patient History
This case is a 61-year-old man with type 1 diabetes who originally presented with type 2 diabetes in 1989, and was initially
treated with oral agents. In 1995, he was started on insulin. In 2001,
a C-peptide test confirmed that the patient had type 1 diabetes. He
was placed on basal-bolus therapy, and switched to an insulin
pump in 2004. His job involves physical labor and he had low
insulin requirements at breakfast and lunch. His major meal is
dinner and he is sedentary afterward. His insulin-to-carbohydrate
ratio at dinner was 1 unit for 8 grams of carbohydrate, in contrast to
1:12 at breakfast and lunch.

Comorbidities and Diabetic Complications
The patient had hypertension and hyperlipidemia, and was
euthyroid secondary to hyperthyroidism 20 years before. He
had diabetic retinopathy and peripheral neuropathy. Surgical
history included angioplasty for coronary artery disease 1.5 years
before.

Glucose Monitoring
He performed self-monitored blood glucose (SMBG) before dinner,
2 hours afterward, bedtime, and once in the middle of the night, at
which time he had hyperglycemia. He had a higher basal rate of 2 to
2.1 units between 8 pm and 8 am. However, in spite of that, his A1c
remained elevated at 9%.

Monitoring Results
Professional continuous glucose monitoring CGM revealed postprandial hyperglycemia, and nocturnal hyperglycemia between 8 pm
and 2 am, indicating that the patient sometimes forgot to bolus after a night-time snack. The sensor summary indicated that the patient’s glucose level was within normal range only 24% of his time
with a mean sensor glucose of 206 mg=dL (standard deviation,
81 mg=dL).
The patient recognized how serious the problem was when the
physician discussed each day’s tracings and discovered that on the
day the patient had no bedtime snack, his BG levels were fairly well
controlled (Fig. 12). Another tracing revealed that the patient was
taking his insulin after breakfast, and another that he was not bolusing appropriately at dinner time. Although he performed SMBG

16

The Sensor Modal Day report revealed a dawn phenomenon (Fig.
13), which was corrected by a higher basal rate. The provider also
adjusted the pump sensitivity and the insulin-to-carbohydrate ratio
for the patient’s bedtime snack. He also reinforced the message that
‘‘whenever your hand goes to your mouth, it needs to go to your
pump.’’ The patient also upgraded to a newer (model 722) insulin
pump.

The patient’s A1c improved to 8.3%. The patient now uses a personal real-time CGM to help keep his BG under control. Remembering
to bolus before his bedtime snack remains an ongoing challenge, and
he experiences nocturnal hyperglycemia between 9 pm and 1 am
about 2 days per week.

Conclusions
This case shows the typical evolution of type 1 diabetes in
adulthood. He had type 1 diabetes from onset, which unfortunately
went unrecognized. The professional CGM clearly demonstrated to
the patient just how brittle his diabetes was and inspired him to
improve his behavior, at least temporarily. Professional CGM is
particularly helpful in managing patients in whom the A1c remains
elevated despite multiple interventions. The professional CGM
tracings highlights hyperglycemia based on which provider can
recommend treatment changes to reduce hyperglycemia. In addition, professional CGM is particularly motivating for those patients
who bolus after a meal despite being trained to bolus beforehand,
because they are not sure what they are going to eat beforehand or
they forget.
A recent study sponsored by the Juvenile Diabetes Research
Foundation showed an improvement in glucose control with realtime CGM use. There is a learning curve for the physician and patient
to set a personal CGM device, so that the patient is not woken up too
often that they become noncompliant. That is what happened with
this patient, who routinely forgot to bolus with a bed time snack.
Unfortunately, at a subsequent visit, this patient’s A1c reverted to
8.2% (lowest A1c was 7.2%), and the patient revealed that he had
stopped using his personal CGM device. The patient immediately
recognized that when he used his personal CGM regularly and remembered to bolus appropriately, he would not be awakened by
alarms.



CASE 5: MAN WITH TYPE 1 DIABETES

Fig. 12. Sensor Daily Details reveal that blood glucose is above 300 mg=dL throughout the day and at bedtime, and nearly normal
on waking. Blood glucose peaks were not recognized with SMBG (shown as blue plus signs).

Fig. 13. Sensor Modal Day reveals a
dawn phenomenon between 3 am
and 6 am (shown in black).

Sushma Reddy, M.D., is a speaker for Eli Lilly, Medtronic Diabetes, Novo Nordisk, Sanofi-Aventis, Takeda, and Bristol Meyers
Squibb.


Case 6
A Type 1 Diabetic College Student with a Crazy Lifestyle
and Crazy Blood Sugars

Barry S. Horowitz, M.D.
Beach, Florida.

Patient History
This is the case of a college student with a crazy lifestyle with wide
glucose excursions. This 18-year-old woman was found to have type
1 diabetes 3 years ago. She attends a community college and admits
to a stressful life and poor dietary habits. Her baseline regimen was
Aspart before meals.
She was counting carbohydrates with a ratio of 0.5:3 at breakfast,
0.5:5 at lunch, and 12:9 at dinner. She was using a correction factor
of 50 and was taking an inadequate glargine dose at bedtime. She
checked her blood glucose (BG) inconsistently because of her
schedule (2–6 T=day). Her BG ranged from 50 to 300 mg=dL and she
was keeping poor records.

tinuous glucose monitoring (CGM) was ordered to clarify the patterns
and help the patient establish better control.

The sensor summary reveals that this patient is within her BG
target ranges about 47% of the time. The Sensor Modal Day tracing
showed a roller-coaster pattern of both highs and lows throughout
the day. Sensor Daily Details revealed that the patient was having
premeal hypoglycemia and postmeal hyperglycemia throughout the
evaluation period (Fig. 14). Sensor Modal Time analysis showed that
she was peaking in the middle of the night and then having hypoglycemia toward the morning.
Examining the diary in conjunction with the CGM outputs revealed
poor dietary habits, with meals that included very little protein and a
lot of simple carbohydrates (e.g., granola bars, graham crackers, and
popcorn), probably very typical for a college student. Her BGs often
increased significantly after eating these high-carbohydrate meals.
When she developed hypoglycemia she again consumed a lot of carbohydrates, which led to more hyperglycemia.



Her baseline A1c was 7.1%, which is almost at target, but the few
reported BG measurements were so variable that professional con-

We decreased her Glargine to 12 units because of the fasting hypoglycemia on awakening. The dietician recommended increasing

Fig. 14. Sensor Daily Details reveal several unrecognized episodes of nocturnal hypoglycemia and several hyperglycemic peaks
missed with self-monitored BG.

18



CASE 6: DIABETIC COLLEGE STUDENT WITH CRAZY LIFESTYLE

Fig. 15. The Sensor Modal Time tracings revealed elimination of the hyperglycemia peaks at 2 am and the hypoglycemia on
awakening seen in the previous professional CGM study.

protein consumption and decreasing simple carbohydrates, and
taught her how to avoid over treating the hypoglycemia. The certified
diabetes educator helped her calculate premeal insulin dosing. The
physician suggested that the patient go on an insulin pump to more
accurately dose her insulin. The patient now uses Aspart with a
Medtronic 522 pump with individualized basal rates, carbohydrate
ratios, sensitivities, and glucose targets.

A follow-up professional CGM was performed about 3 months
later. The patient’s BG was in normal ranges 77% of the time, compared with <50% of the time at the earlier evaluation. In contrast
to the roller-coaster pattern seen in the first one, the BG pattern
smoothed out, with very little hypoglycemia, and only occasional
hyperglycemia. The Sensor Modal Time report shows that the earlier
2 am peaks and the hypoglycemia episodes on awakening are gone
(Fig. 15). The preprandial hypoglycemia and postprandial hyperglycemias were essentially eliminated.
The diary indicated improved dietary habits. The patient still has
occasional excursions on the Sensor Daily Detail report, probably as a

result of reverting to poor food habits. The patient’s glycemic control
improved markedly, with her A1c improved from 7.1% to 5.7% at her
most recent visit, and no accompanying hypoglycemic episodes.

Conclusions
The major take-home message from this case is that CGM reveals
behavior patterns that inhibit good glycemic control. BG excursions
that do not appear with routine monitoring become obvious often
times when we do professional CGM. These results motivated the
patient to consider a pump. Ultimately, this patient progressed to
better control because of the professional CGM technology.

Barry S. Horowitz, M.D., is a speaker for Abbott Pharmaceuticals,
Amylin Pharmaceuticals, Astra-Zeneca Pharmaceuticals, Bristol
Myers Squibb, Eli Lilly Pharmaceuticals, Merck & Co, Inc., Medtronic
Diabetes, Novo Nordisk, Pfizer Pharmaceuticals, Sanofi-Aventis
Pharmaceuticals, and Takeda Pharmaceuticals.


Case 7
A 38-Year-Old Woman with Type 1 Diabetes

Bruce W. Bode, M.D.
Atlanta Diabetes Associates, Atlanta, Georgia.

Patient History

Yes, there was 1 day when her BG was consistently in the 150 to
200 mg=dL range.
The patient was instructed not to change her usual patterns during
the professional continuous glucose monitoring (CGM) evaluation,
but she obviously did because her average BG was 150 mg=dL on her
Sensor Summary (Fig. 17), and it does not correspond with an A1c of
9.2%. Clearly, the patient bolused and monitored more often than
usual. Even so, the BG patterns are still erratic. Either she is eating at
night to protect against lows overnight, or she needed an increased
basal insulin dose.

This is the case of a 38-year-old woman with type 1 diabetes
diagnosed in 1988. The baseline regimen was insulin Aspart via
insulin pump. The baseline A1c was 9.2%, although her A1c values
were in the range during two prior pregnancies. The patient is generally not compliant: she has used the same insulin dose for years,
forgets to bolus regularly, does not bring her blood glucose (BG)
logbook to office visits, and rarely monitors herself (zero to two
times daily). She claims to be too busy to monitor her BG, although
she did so during pregnancy. The patient is concerned about weight
gain, and about hypoglycemia if she attempts to improve her glycemic control.

Initially, the provider increased the basal rate, followed by a second increase several weeks later. The patient finally agreed to a pump
after seeing the reports that she would not go low. However, she
would not agree to use the Bolus Wizard, nor would she reinstate her
antidepression medication out of fear of weight gain.



The patient shows signs of preproliferative retinopathy. She also
has a history of depression, but does not take antidepressants because
she gained weight when on treatment in the past. Thus, her fear of
potential weight gain prevents her from treating both her depression
and her diabetes.

The patient’s last A1c did not change much (9.1%), but at least
she is monitoring twice a day. She usually boluses five times daily,
which is an improvement. She has also applied for personal CGM
coverage.


Conclusions
The patient is on an insulin pump and manually boluses approximately five times a day with 2 to 7 units. She will purposely under
bolus if she feels she might go low. The patient denies snacking after
9:00 pm but has very high glucose levels in the morning. Taking the
patient at her word, the appropriate therapeutic choice would be to
increase her basal insulin. The provider wished to know whether the
patient experienced a rise in BG in the dawn phase.

Professional CGM revealed previously unrecognized problems
with this patient’s BG patterns overnight. This patient may benefit
most from personal CGM, but she has to become much more accepting of her diabetes to take that proactive approach.
Professional CGM may not give an accurate picture of each patient’s diabetes control, because patients may change their diabetesrelated behavior during the professional CGM evaluation, despite
being told to maintain their usual routine.
The following steps will improve the likelihood that patients will
not change their behavior while on professional CGM.
.

Monitoring Results
The Sensor Daily Detail report revealed a clear dawn rise starting
earlier than what was previously recognized (Fig. 16). She often has
normal BG at bedtime, but at *1 am her BG will start to rise from
150 to 300 mg=dL by the time she wakes up. If her BG at bedtime is
around 120 mg=dL, it will rise to 280 mg=dL or so upon awakening.
If her bed time BG is 100 mg=dL, it may rise to 180 mg=dL on
awakening. She denies eating despite apparent evidence to the
contrary. During the day, her BG rarely dips below 70 mg=dL, but
she has many hyperglycemic excursions, some up to 346 mg=dL.

20

.

Before insertion, explain that the reason we are doing the study
is to see actual day-to-day diabetic control and stress not to
change anything for the first couple of days.
Specifically mention that you are not going to judge the patient.
Acknowledge that it may be difficult for the patient to do everything as usual because he or she knows that the healthcare
professional is going to see what the patient is actually doing,
but that is why it is so important.

According to a recent study, the second best predictor of success
with CGM (after age >25 years) is frequency of BG self-monitoring.
To be successful using a personal CGM, the patient must monitor



Fig. 16. Sensor Daily
Details reveals a dawn
phenomenon earlier than
expected, and blood
glucose peaks that are
not recognized
with SMBG.

Sensor Summary
6/26/2009

6/27/2009

6/28/2009

6/29/2009

6/30/2009

7/1/2009

# of Sensor Values

102

288

288

288

288

217

Average (mg/dL)

133

188

209

155

164

150

47-197

87-307

86-346

57-286

69-226

STDev (mg/dL)

33

66

65

56-331
72

66

33

# of Meter Values

3

5

4

4

6

5

Average (mg/dL)

108

172

157

92

124

160

96-116

77-270

72-242

46-141

49-262

118-232

Date

Sensor

Meter

Min - Max (mg/dL)

Min - Max (mg/dL)
Designation
Optimal Accuracy
Criteria

X: Use Clinical
Judgment
3

5

4

4

6

4


28.1

11.5

12.9

11.7

7.1

5.5



0.99

0.99

n/a

1.00

0.95

4

3

1

5

6

3


3

3

1

3

4

2


1

0

0

2

2

1


02:25 (28%)

14:25 (60%)

19:05 (80%)

10:25 (43%)

11:30 (48%)

08:30 (47%)


05:50 (69%)

09:35 (40%)

04:55 (20%)

13:10 (55%)

11:35 (48%)

09:30 (53%)


00:15 (3%)

00:00 (0%)

00.00 (0%)

00:25 (2%)

00:55 (4%)

00:05 (0%)

Limit (mg/dL*Day)

5

48

67

29

33

12

Limit (mg/dL*Day)

Excursions
High > 150mg/dL
Low < 70mg/dL

n/a

# of Excursions*

1

0

0

0

0

0

Pie Chart
Red: Above Limits
Blue: Below Limits

X: Please use your clinical judgment - this day does not satisfy the optimal accuracy criteria according to set thresholds:
N >¼ 3, R >¼ 0.79 and MAD <¼ 28% [or <¼ 18% if the range (Min-Max) of meter values is less than 100 mg=dL (5.6 mmol=L) - see Criteria
Note below].
Criteria Note: If the range (Min-Max) of Meter Values is less than 100 mg=dL (5.6 mmol=L) then ‘R’ will be reported as ‘N=A’.
In this case the optimal accuracy threshold set for MAD is <¼ 18%.

Fig. 17. Sensor Summary reveals an average BG of 150 mg=dL. Patient experiences hyperglycemia from 28% to 80% of the day.


BODE

at least four times daily. Because this patient routinely does not selfmonitor as recommended, and is likely to hear multiple alarms
because of her extreme glucose excursions, she might not be very
successful on a personal CGM. On the other hand, since she changed her
self-monitored blood glucose (SMBG) behavior during the professional
CGM evaluation as well as during her previous pregnancies, she might
be motivated enough to develop better control on personal CGM.
Some patients use personal CGM data exclusively to make changes
in insulin dosing instead of SMBG. This may be particularly important when treating adolescents who may be out of control. It is

possible, however, that personal CGM may help teens moderate BG
swings even if performing SMBG less often than recommended. Some
adolescents use personal CGM successfully, especially when driving
privileges may be withheld if they don’t.

Bruce W. Bode, M.D., received fees for research grants, advisory
boards, and consultant activities, and is on the speaker’s bureau for
Johnson & Johnson, Medtronic Diabetes, Novo Nordisk, and SanofiAventis.


Case 8
A 69-Year-Old Woman with Type 2 Diabetes
and Good Premeal Glucose, But a High A1c


Barry S. Horowitz, M.D.
Beach, Florida.

Patient History
This patient is a 69-year-old woman who was found to have type 2
diabetes about 6 years ago when she developed cardiomyopathy. Her
current treatment regimen includes Aspart before meals with different units and Glargine at bedtime. She did not follow a 50:50 ratio
of basal and bolus therapy, but her regimen presumably worked for
her at the time.

Her comorbid conditions include cardiomyopathy, hypertension, and hyperlipidemia, for all of which she was taking
medication.



The patient was checking her blood glucose (BG) four times
daily. She stated that her blood sugars were in the low 100s
premeals and at bedtime, but she routinely forgot her logbook.
When she did bring her logbook, her premeal BG looked
pretty good, but she was very noncompliant postprandial selfmonitored BG, despite multiple requests to do so. Her baseline
A1c was 7.5%.
The provider ordered professional continuous glucose monitoring
(CGM) because he suspected that the patient was having some
postprandial hyperglycemia.

The Sensor Summary from her first professional CGM showed
that her CGM glucose values equally distributed in within, below, and above target range. The patient was completely unaware of hypoglycemia, although she experienced substantial
nocturnal hypoglycemia everyday. The Sensor Modal Day
showed that she was having some postprandial hyperglycemia
and variability in her glycemic control in the evening (Fig. 18).
The Sensor Daily Detail and Sensor Modal Time confirmed that
her BG dropped throughout the night, leading to hypoglycemia
toward the early morning. She also experienced postprandial
hyperglycemia.


The patient’s diary revealed that she did not take premeal insulin
when her premeal blood sugar was normal. She had had a misconception that if she had normal BG before meals, she did not need to
take insulin. She also had subsequent postprandial hyperglycemia
that was not captured with self-monitored BG.
This patient is Hispanic and eats traditional, high-carbohydrate
meals with lots of rice and beans. Comparing her diary entries to
professional CGM outputs revealed that she took her usual dose of
premeal insulin, even on days when she ate high-carbohydrate meals,
and consequently developed postmeal hyperglycemia.
The provider lowered her glargine dose at bedtime to reduce
nocturnal hypoglycemia and provided additional education from a
nutritionist and a diabetes educator. We again emphasized that she
should dose her Aspart before meals regardless of what her blood
sugars were. We also taught her how to count carbohydrates and use
that along with the correction factor so she could be taking more
insulin when she ate higher-carbohydrate meals and have better
postprandial results.

The patient began checking postmeal BG after seeing the postmeal
hyperglycemia on the professional CGM report. She began counting
carbohydrates with the correction factor for meals, which lead to
better and less variable BG throughout the day.

Follow-Up Professional CGM
This follow-up CGM showed improved and more consistent glycemic control. The Sensor Summary revealed that the hypoglycemia was almost eliminated, with most BG values within the normal
range and some hyperglycemia. The Sensor Modal Day report also
shows some hypoglycemia overnight but not in the ranges that she
was having before. The Sensor Modal Time report also revealed BG
dips from 4 to 8 am, and some high BG after breakfast and dinner that
was better than before. The Sensor Daily Detail report and diary
showed that the patient was still often under dosing the mealtime
insulin, but this was better compared to before when she was skipping
doses entirely (Fig. 19). She was given some further counseling about
her diet, and we cut back a little bit more on her glargine dose. Her
most recent A1c had improved from 7.5% to 6.5%.

Conclusions
This subject with type 2 diabetes denied experiencing hypoglycemia, but she was low a third of the time during the first


23

HOROWITZ

Fig. 18. The Sensor Modal Day
showed blood glucose dropping
throughout the night and morning
and postprandial hyperglycemia.

Fig. 19. The Sensor Daily Detail report showed that the patient was still often under dosing her mealtime insulin, but at least was
not skipping doses.

professional CGM evaluation. Many researchers think that the
increased mortality may be associated with unrecognized hypoglycemia with tight glycemic control in patients with type 2 diabetes as has been hypothesized in the ACCORD trial. Many
patients are unwilling or unable to check BG at the most the

clinically informative times (e.g., postprandially). The professional
CGM showed this patient how her behavior patterns influenced her
BG patterns. In this patient, the professional CGM resulted in
behavior changes, leading to improvement in A1c from 7.5% to
6.5% with no associated hypoglycemia.


CASE 8: DIABETIC WOMAN WITH GOOD PREMEAL GLUCOSE, BUT HIGH A1C

One panelist suggested that Dr. Horowitz might want to consider
splitting the glargine into two doses, given the trend toward higher
BG in the evening, but the postprandial hyperglycemia at dinner was
not high enough. This patient was assigned a ratio of 3:1. Realistically, this patient was not going to abandon her traditional Hispanic
diet, so she needed that ratio, and the professional CGM tracings
reinforced that therapeutic decision.

Barry Horowitz, M.D., is a speaker for Abbott Pharmaceuticals,
Amylin Pharmaceuticals, Astra-Zeneca Pharmaceuticals, Bristol
Myers Squibb, Eli Lilly Pharmaceuticals, Merck & Co, Inc., Medtronic Diabetes, Novo Nordisk, Pfizer Pharmaceuticals, Sanofi-Aventis
Pharmaceuticals, and Takeda Pharmaceuticals.


Case 9
A 37-Year-Old Woman with Type 2 Diabetes at 20 Weeks of Gestation


Monitoring Results


The Sensor Daily Detail revealed high postprandial BG values,
some as high as 200 mg=dL, starting at breakfast and usually worsening at lunch and dinner (Fig. 20).

T

Patient History
his is a case of a 37-year-old woman with type 2 diabetes
associated with pregnancy. She had no known diabetes
complications and her baseline A1c was 5.7%. She tests her
blood glucose (BG) six to eight times daily. Her baseline
treatment was NPH twice a day (14 units in the morning and 20 units
at night), and Lispro. The BG target is lower for pregnancy, 80 divided
by 40 and carbohydrates divided by 10.

The clinician reviewed her dietary log and discussed the relationships between her high-carbohydrate and high-fat intake and her
high postprandial BG readings. The dietician recommended dietary
changes and her carbohydrate ratio was adjusted to carbohydrates
divided by eight.

Glucose Monitoring

Follow-Up Professional Continuous Glucose
Monitoring Results=Response to Therapy
Adjustments

The healthcare professional wanted to ensure that the patient was
doing well day to day, in light of the challenges posed by BG control
during pregnancy for patients with type 1 or type 2 diabetes.

Before a follow-up professional continuous glucose monitoring
to re-verify the ratio was scheduled, the patient was induced, and she
delivered a healthy 6-pound boy at 38 weeks.

Fig. 20. Sensor Daily Details revealed unrecognized postprandial hyperglycemia.

26



CASE 9: WOMAN WITH DIABETES AT 20 WEEKS OF GESTATION

Conclusions
This case emphasizes that an A1c in the 5.6%–5.7% range through
the entire pregnancy may mask underlying postprandial BG excursions, even in a patient who checked her BG six to eight times daily,
including 2 h after meals.
Although this patient had a healthy outcome (a normal-sized
infant), diabetic women with decent A1cs may still deliver a macrosomic infant. A high A1c during pregnancy is a major risk factor
for macrosomia, which is also thought to be related to obesity and
insulin-resistant syndrome later in life. There’s a trend toward lowering the target A1c to <5% in pregnancy. The American Diabetes

Association fasting target is now 95 mg=dL (ADA 2008). The
guidelines may be revised to 80 mg=dL to try to get better glucose
control.
With this patient, early intervention contributed to a healthy
outcome. To prevent macrosomia, ideally a clinician should intervene preconception, but failing that, one should intervene no later
than early in the second trimester.



Case 10
A 41-Year-Old Woman with Type 2 Diabetes, High A1c

Ola Odugbesan, M.D.


North Atlanta Endocrinology, Lawrenceville, Georgia.

The patient is on prednisone therapy for asthma and has irritable
bowel syndrome. She developed profound hyperglycemia that required insulin therapy.

A

Patient History
41-year-old woman was initially found to have gestational diabetes during pregnancy and type 2 diabetes in
2003 after she miscarried. Her A1c measured 8.4% in early
summer 2009. She is one of the clinical diabetes managers
within the presenter’s practice, but her own diabetes was being
managed by her internist.

Glucose Monitoring
At the time she agreed to be followed within the practice where she
worked, she was on pioglitazone and metformin, but she was probably not compliant with this regimen, because of gastrointestinal side
effects from metformin.

Sensor Summary
Date

5/29/2009

Totals

288

169

577

Average (mg/dL)

234

252

282

257

106-299

182-297

234-323

39

24

20

106-323
32

# of Meter Values
Meter

5/28/2009

120

STDev (mg/dL)

Sensor

5/27/2009
# of Sensor Values

4

5

2

11

Average (mg/dL)

227

259

290

253

173-306

239-268

271-308

173-308

Min - Max (mg/dL)

Min - Max (mg/dL)

X: Use Clinical
Judgment

Designation
Optimal Accuracy
Criteria

3

5

2

10


7.0

3.3

7.5

5.3



n/a

n/a

0.84

2

0

0

2


2

0

0

2


0

0

0

0


09:15 (92%)

24:00 (100%)

14:05 (100%)

47:20 (98%)


00:45 (8%)

00:00 (0%)

00:00 (0%)

00:45 (2%)


00:00 (0%)

00:00 (0%)

00.00 (0%)

00:00 (0%)

Limit (mg/dL*Day)

57

72

102

78

Limit (mg/dL*Day)

Excursions
High > 180mg/dL
Low < 70mg/dL

0.94

# of Excursions*

0

0

0

0

Pie Chart
Red: Above Limits
Blue: Below Limits

Fig. 21. The Sensor
Summary revealed that the
patient was hyperglycemic
all day long.

X: Please use your clinical judgment - this day does not satisfy the optimal accuracy criteria according to set
thresholds:
N >¼ 3, R >¼ 0.79 and MAD <¼ 28% [or <¼ 18% if the range (Min-Max) of meter values is less than 100 mg=dL
(5.6 mmol=L) - see Criteria Note below].
C: This day does not have any paired sensor=meter data and no sensor plot is provided. As a result, ‘Meter
Only’ data is available.
S: Please use your clinical judgment - this day does not have any meter data. As a result, ‘Sensor Only’ data
is available.
Criteria Note: If the range (Min-Max) of Meter Values is less than 100 mg=dL (5.6 mmol=L) then ‘R’ will be
reported as ‘N=A’.
In this case the optimal accuracy threshold set for MAD is <¼ 18%.

28



CASE 10: WOMAN WITH DIABETES AND HIGH A1C

Sensor Summary
Date

9/17/2009

9/18/2009

Totals

288

288

159

773

Average (mg/dL)

145

138

149

139

143

137-165

63-181

88-193

63-193

6

21

20

98-165
12

# of Meter Values
Meter

9/16/2009

38

STDev (mg/dL)

Sensor

9/15/2009
# of Sensor Values

1

4

4

1

10

Average (mg/dL)

172

144

159

155

154

172-172

133-160

125-190

155-155

125-190

X: Use Clinical
Judgment

X: Use Clinical
Judgment

Min - Max (mg/dL)

Min - Max (mg/dL)
Designation
Optimal Accuracy
Criteria

X: Use Clinical
Judgment

19

1

4

4

1

10


17.0

6.3

23.2

13.4

14.8



n/a

n/a

n/a

n/a

n/a

# of Excursions*

0

2

2

0

4


0

1

2

0

3


0

1

0

0

1

00:00 (0%)

00:15 (1%)

01.55 (8%)

00:00 (0%)

02:10 (3%)

03:10 (100%)

23:10 (97%)

22.05 (92%)

13:15 (100%)

61:40 (96%)

00:00 (0%)

00:35 (2%)

00.00 (0%)

00:00 (0%)

00:35 (0%)

Limit (mg/dL*Day)

0

0

0

0

0

Limit (mg/dL*Day)

0

0

0

0

0

Excursions
High > 180mg/dL
Low < 70mg/dL

Pie Chart
Red: Above Limits
Blue: Below Limits

X: Please use your clinical judgment - this day does not satisfy the optimal accuracy criteria according to set thresholds: N > ¼ 3, R > ¼ 0.79
and MAD <¼ 28% [or <¼ 18% if the range (Min-Max) of meter values is less than 100 mg=dL (5.6 mmol=L) - see Criteria Note below].
Criteria Note: If the range (Min-Max) of Meter Values is less than 100 mg=dL (5.6 mmol=L) then ‘R’ will be reported
as ‘N=A’.In this case the optimal accuracy threshold set for MAD is <¼ 18%.

Fig. 22. Sensor Summary pie charts show the patient within targets 95%–100% of the time.

She was also supposed to be taking Lispro PRN for episodes of hyperglycemia. She was supposed to be checking her blood glucose (BG)
three to four times daily, but was apparently noncompliant with that
also. While she was on vacation, she developed profound hyperglycemia, felt weak and diaphoretic, and may have exacerbated her asthma
exacerbation, and also developed foot ulcers that took a little while to
heal. She ended up in the hospital. She is the nurse who counsels the
patients who come in for professional continuous glucose monitoring
(CGM), and is actually the one who places and removes the devices.

As a nurse specializing in diabetes care, the patient saw the Sensor
Summary and immediately recognized the implications (Fig. 21). In
fact, she described herself as a ‘‘rolling ball of sugar.’’ The pie charts
show that she is hyperglycemic all day long, with the rare episode of
normoglycemia. There were no meal markers because she essentially
grazed all day long.

The physician maintained the patient’s pioglitazone prescription,
because she does have profound insulin resistance, but metformin
was discontinued because of the gastrointestinal side effects. She was
switched to exenatide only, 5 mcg twice daily. Given her previous
poor dietary habits, she still wanted to have Lispro on hand if she ate a
very high carbohydrate meal. The patient saw the dietitian, and decided that she was going to be more active and try to achieve better
diabetes control.

Follow-up professional CGM showed that the patient was more
compliant with her treatment regimen and her BG was within target
95% of the time, with very little hyperglycemia, and virtually no
hypoglycemia (Fig. 22 and 23). She did not have gastrointestinal side
effects and so complied with her therapy. She lost about 20 pounds


ODUGBESAN

Fig. 23. Sensor Daily Details show blood glucose within range except for two episode of mild hyperglycemia (circled).

over a 4-month period because of improved diet, increased exercise,
and perhaps to some extent exenatide therapy. She feels better and
has had a much better quality of life.
The very rare episodes of hyperglycemia may reflect the days that
the pharmaceutical company sales representatives brought lunch for
the staff. Her latest A1c is within the normal range. This is a dramatic
difference from where she was before having the therapy.

vinces other patients of the value of professional CGM because she
knows firsthand how it improved her glycemic control.
The provider attributed the patient’s weight loss primarily to a
combination of diet and increased levels of physical activity, rather
than to the medication change, because the exenatide dose (5 mcg)
was so small.

Conclusions
This patient was not managing herself at all and truly ignoring her
diabetes. Her average BG was 257 and her A1c was 8.4%.
Use of professional CGM demonstrated that she does not need to
eat all day long and live in perpetual hyperglycemia. She now con-

Ola Odugbesan, M.D., is a speaker for Abbott, Amylin, Astra
Zeneca, Bristol-Myers Squibb, Glaxo SmithKline, Lilly, Medtronic
Diabetes, Merck, Novo Nordis, Satauru, and Takeda.


Discussion Regarding Use of Professional

T

he key points for optimizing patient management with
professional continuous glucose monitoring (CGM) reached
by consensus of the roundtable participants included
CGM Terminology, the Consensus Statement, Selection
Criteria for Professional CGM, Implementation of Professional
CGM in a Practice Setting, Interpreting Professional CGM Outputs,
Therapy Adjustments Guided by Professional CGM, and the Future of
CGM.

Consensus on CGM Terminology
Professional CGM is the term used most often to describe CGM
characterized by the following:
. The aim of professional CGM is to assess the patient’s realworld behavior and how it influences glucose patterns and to
determine the glucose patterns that are not visible when the
patient performs self-monitored blood glucose (SMBG) only
four to six times per day. The ultimate goal of professional CGM
is to enable the healthcare professional make appropriate adjustments in diet, physical activity, and adjustments in the
dosages of insulin and other medications.
. The device is owned by the individual healthcare provider, the
practice, or the hospital center.
. The CGM device is put in place by a professional licensed person.
. The patient is blinded to the readings and there are no audible
alarms to alert patients to hypo- or hyperglycemia.
. The device stays in place for 72 h.
. Professional CGM is more of a diagnostic tool.
. Upon downloading, the provider sees and interprets the readings retrospectively and discuss appropriate therapy adjustments with the patient.
Other terms used to describe professional CGM include blinded
CGM, blinded retrospective CGM, historical CGM, clinic CGM, CGM
for physicians, 72-h CGM, and CGM system.
Professional CGM is particularly useful for type 1 patients who
take multiple insulin injections or are on pumps to fine-tune their
dosage. In a patient with type 2 diabetes with an unexplained elevated
A1c, professional CGM can pinpoint needed changes in treatment that
would bring their A1c down. Professional CGM is particularly useful
for those patients who might be considering personal CGM, those
considering a change from MDI Insulin to pump therapy or from oral
agents to insulin.
Real-time CGM is the term used most often to describe CGM characterized by the following:
. The device is owned by the individual patient.
. The CGM device is put in place by a professional licensed
person.


.

The patient is not blinded to the readings and audible alarms
alert the patient to hypo- or hyperglycemia.
. Personal CGM is both a diagnostic and therapeutic tool.
. Patients must be trained to make their own therapy adjustments.
Data are displayed either on the pump or for patient not on a
pump on the CGM device itself.
Patients see and interpret the CGM data these in real time and
make their own therapeutic decisions.
. The device remains in place permanently (sensor changed every
3 days). According to data from the JDRF trials the best benefit
accrues to patients who use the personal CGM device 6 days a
week on an ongoing basis.
. When the physician sees the data, they are interpreted retrospectively; the patient has already acted upon the data.
Other terms used to describe personal CGM include real-time CGM,
home-use CGM, patient CGM, and consumer CGM.
Personal CGM is especially useful for patients who already monitor with SMBG frequently that are not at goal. It takes a lot more
training and follow-up with personal CGM than it does with professional CGM to ensure that the patients interpret the real-time
readings. If a patient is a candidate for personal CGM, the professional CGM evaluation is useful to document hypoglycemia, if the
condition has not been adequately documented using SMBG alone.
Some insurance carriers now require professional CGM as part of
the authorization for a personal CGM device. There are patients who,
even if their plan would authorize it, do not want a personal CGM
device but would agree to wear a professional CGM device for 3 days
to optimize therapy.
Roundtable participants agreed that providers must use consistent
terminology when distinguishing professional CGM from personal
CGM for the following reasons:
. When the term ‘‘professional’’ is attached to the term ‘‘CGM,’’
patients understand that it is the healthcare provider who collects data that are going to help manage their diabetes.
. When the adjective ‘‘personal’’ is attached to the term CGM,
patients understand that it is the patient who is most active in
the process; in addition, patients may not understand what the
term ‘‘real time’’ means.
. Insurers do not necessarily understand the distinction between
professional and personal CGM and may reimburse for something that was not requested.
*

*

Consensus on Definition of Professional CGM
Professional CGM is a diagnostic and therapeutic=management
tool used by the healthcare professional that allows the collection of


DISCUSSION REGARDING USE OF PROFESSIONAL CGM

retrospective glucose data in patients with diabetes. It is indicated to
optimize safe and effective glycemic control in patients in whom selfmonitoring of BG is inadequate.

Consensus on Selection Criteria for
Professional CGM
The overarching reason to use professional CGM is to better understand a patient’s glycemic control when self-monitoring of BG proves
inadequate to do so. A typical driver for consideration of professional
CGM is a patient who does not maintain their BG within targeted ranges,
or is not at their A1c goal, or both. The healthcare provider will need to
determine patterns that undermine safe and effective therapy, and make
appropriate therapeutic changes to get the patient to goal.
The rationales for professional CGM for the 10 cases presented at
this Roundtable are summarized in Table 1.
Cases 1, 2, 5, and 7 were all patients with type 1 diabetes and an
A1c that was too high. Two cases with type 1 diabetes had normal
A1cs, but each patient faced challenges with day-to-day glycemic
control—one because of intense athletic activities, and the other because of a demanding college schedule. In two cases (the college
student and the women with type 1 pregnant with triplets), the
professional CGM data influenced patients to switch to an insulin
pump, resulting in A1c values that declined to 5.7% and 5.6%, respectively, without any hypoglycemia. Case 9, the type 2 diabetic
woman on oral agents, switched to insulin therapy using a pump and
was able to get to goal, and deliver a healthy child no evidence of
macrosomia. Two cases had type 2 diabetes: case 8 was on multiple
daily injections with large amounts of insulin, with BG unawareness
at both extremes. Just by altering the regimen, she eliminated all
hypoglycemia and achieved an A1c of 6.5%. Case 10 was on oral
agents only and hyperglycemic 100% of the time. As a diabetes
specialist nurse, she recognized the implications of her tracings, and
she was finally motivated enough to change her diet and activity and
thus achieved normal BG levels.
Participants agreed that the goal of professional CGM should be to
open a patient’s eyes to what is going on with their diabetes, to get
that ‘‘aha!’’ moment when the patients realize why they need to do the
things they know that they should be doing, but that they are not.
Data from professional CGM may also be a trigger than can convince
patients to switch from MDI to pump therapy, if that is what the
physician has been recommending, or from pump therapy alone to
pump therapy with personal CGM.
One participant always recommends professional CGM for patients
who experience any severe hypoglycemic event requiring assistance
of another person. Another rationale for professional CGM is for
patients whose A1c is not at goal in spite of frequent glucose monitoring, or if their A1c is at goal with a high variability in their BG
meter download.
Patients who do not comply with recommendations for routine
glucose monitoring frequency may be willing to do SMBG four times
daily for 3 days, even if they generally come to physician visits with
no fingerstick data. The clinician needs to make sure that patient is
safe, and professional CGM can motivate them to do better.

Professional CGM can be justified in all diabetic patients who take
medications that can lead to hypoglycemia, even if they have A1c
values in a healthy range. Thus, all type 1 patients, and those type 2s
on insulin or oral agents that cause hypoglycemia (e.g., sulfonylureas) are candidates for professional CGM.
For patients with type 2 diabetes who are not on insulin and
whose A1c is not at goal, professional CGM is useful to determine
whether to offer the patient an alternative oral or switch to insulin.
For type 2 diabetic patients on basal insulin only, professional CGM
can help identify whether the patient may need to add rapid-acting
insulin for a meal, or to titrate multiple insulin doses as needed.
Insulin-requiring patients who have had type 2 diabetes for a long
time may have brittle disease that is very similar to type 1 characteristics.
One important take-home message is that patients may have A1c
values that are nominally at goal, but may actually have poor glycemic control. The A1c is an average value and, as such, may mask
widely fluctuating BG, especially at the extremes. If the SMBG record
indicates wide variations, the patient would be an excellent candidate
for professional CGM.
Roundtable participants emphasized that the terms ‘‘controlled’’ or
‘‘uncontrolled’’ diabetes should not be determined solely by the A1c,
particularly in type 1 diabetes. If a patient’s A1c is 6.5% but their BG
ranges between 40 and 400, then their diabetes in uncontrolled, and
it should be coded that way. This designation is particularly important
during pregnancy because of the risk of unrecognized postprandial
hyperglycemia, especially in type 1 diabetics that are near normal.
There is a correlation between postprandial glycemia control and
complications in gestational diabetes (HAPO 2008 N Engl J Med).
Patients still experience significant morbidity from hypoglycemia up
to and including the possibility of death. Unfortunately, there was no
professional CGM component in the large cardiovascular outcome
trials in type 2 diabetes, specifically Action to Control Cardiovascular
Risk in Diabetes trial (Gerstein 2008 NEJM).
After thorough discussion of the cases that were presented,
roundtable participants discussed the types of patients for whom
professional CGM is indicated to optimize glycemic control. Characteristics of patients who are good candidates for professional CGM
are listed in Table 2.

Consensus on Implementation of Professional
CGM in the Private Practice Setting
The Value of Retrospective Data with
Professional CGM
When considering whether to implement professional CGM in
their practices, healthcare professionals should be aware of the advantages of establishing such procedures as part of their service offerings. These advantages are summarized in Table 3.

Staff
One of the key components of initiating a professional CGM
component to a provider’s practice is having a dedicated staff. Particularly helpful is to have either a licensed professional in your



Table 1. Rationales for Initiating Professional Continuous Glucose Monitoring for Cases Presented
PRESENTER

BASELINE
TREATMENT

RATIONALE FOR
PROFESSIONAL CGM

DIABETES TYPE

GENDER

A1c AT BASELINE

Phillips

1

F

9.6%

NPH 10 U qam
Glargine 15 U qhs
R insulin SSI premeal

Hypoglycemia unawareness;
gastroparesis

Nardacci

2

F

10.2%

Aspart 4–6 U w=meals
Glargine 14 U qhs

Highly variable BG on basal
bolus therapy

Arnold

1

M

5.9%

Glargine 15 U qhs
Aspart BS-100

Avid cyclist considering pump

Arnold

2

F

5.7%

NPH 14–20 U
Lispro BS-80

Pregnant; 20 weeks gestation

Arnold

1

F

7.3%

MDT Pardigm 722 pump

Pregnant with triplets;
hypoglycemic seizure secondary
to insulin stacking

Horowitz

2

F

7.5%

Aspart pre meals
Glargine 50 U qhs

Good premeal sugars but high
A1c. Postprandial hyperglycemia

Horowitz

1

F

7.1%

Aspart pre meals
Glargine 15 U qam

18-year-old college student
with variable BG

Odugbesan

2

F

8.4%

Pioglitazone 30 mg qd
Exenatide 5 mg bid
Lispro PRN

Nonadherence

Reddy

1 and 2

M

9.0%

Insulin pump

High A1c

Bode

1

F

9.2%

Aspart via CSII

Hyperglycemia 24=7
Dawn phenomenon

BG, blood glucose; CGM, continuous glucose monitoring.

practice who is enthusiastic enough to champion the technology, a
medical assistant willing to be in charge of this program, or a motivated, well-educated patient who is willing to volunteer with patients who might be candidates for professional CGM.
Ideally, at least two staff members, including medical assistants,
should be cross-trained to insert and remove the professional CGM
devices. Then, if the champion or team leader is absent, there is
continuity.

Space
Space is a big issue in most practices. If a dedicated room is not
available, then a rolling cart to hold the computer and related
equipment is one option.
In one participant’s practice, the professional CGM devices are set
up with the hospital, and all patients are referred there, where the
devices are inserted in a dedicated room.

Scheduling
A schedule needs to be established to ensure getting the
equipment back and cleaned so that it can be used by the next
patient. In some practices, all professional CGM insertions are

done on Thursday with return of the devices on Monday or
Tuesday. Most participants indicated that the patient physically
returns the CGM device at the end of the 72-h evaluation period,
with the possible exception of some pediatric patients who mail
the devices back because they live far away and do not want to
miss school.
Other practices, particularly those with a higher volume of diabetic
patients on insulin pumps, do professional CGM insertions on
Monday mornings with return on Thursday morning, followed by
new patient insertions on Thursday afternoon with removals on
Monday morning.

Relaying Information to the Patient
The ideal scenario is to share professional CGM results with the
patient face to face. Some practices insist that patients come in for
interpretation, because getting the patient to see the professional
CGM data is very motivating and empowering. In these practices,
physicians may interpret and relay the information to the patient
directly. In other practices, the physician interprets the professional
CGM output and relays the information about suggested therapeutic
changes to the nurse practitioner or diabetes educator to communicate to the patient. Then, the patient comes back a few weeks after



Table 2. Professional Continuous Glucose Monitoring
Candidates

Table 3. The Value of Retrospective Data with Professional

Diabetic patients unable to achieve an optimal, safe, and effective glycemic
goal with self-monitoring of blood glucose

Minimal time required for training and patient start-up
No user interface allows for added simplicity of use

Diabetic patients with hemoglobin A1c within target range, but with highly
variable blood glucose

Unaltered glucose patterns without intervention or alerts affecting the
glucose levels

Patients with repeated episodes of hypoglycemia or hypoglycemic unawareness

Levels help guide appropriate therapy adjustments

Insulin-requiring patients

Observe the impact of patient’s diet, exercise, behavior, and medications on
their glucose levels

Diabetes in pregnancy

Direct attachment to the body can reduce the possibility of missed data
Not all patients are ready to understand and respond to real-time glucose
data

those changes are implemented. At that visit, the physician shows the
patient the professional CGM output and explains the rationale for
the changes. Time slots for relaying professional CGM results should
be kept open on the schedule so that patients can get their results in a
timely manner.
In another practice, 90% of the interpretation is done by a certified
diabetes educator (who is a licensed nurse practitioner) who goes over
the results and the recommended changes directly with the patients,
with physician oversight after the fact.
In reality, given both patients’ schedules, insurance plans with very
high copays for office visits, and how far in advance one’s practice is
booked with new patient visits, it can be difficult to arrange face-toface follow-up visits on a rapid basis after the professional CGM
evaluation. In some practices, a licensed staff member calls the patient
to relay the initial results, and then actually gives the patient a copy of
the data at the next visit.

.

.

*

.

Equipment
The practice should have available enough equipment for the
patient load and some backup devices in case a patient is late for their
appointment for the download when another patient is awaiting an
installation.
Roundtable participants agreed that, on average, it takes 10–
15 min to set up each patient with professional CGM device. All
participants also emphasize that each patient keeps a diary that records what and when they are eating, taking medications, and participating in physical activities.
For the patients who are on pumps, plan to download the pump
data simultaneously with the professional CGM device.
One panelist described a colleague who insists on using a personal
CGM device as a professional CGM device, and I have had multiple
discussions with him. This physician gives as his rationale for doing
this that the personal CGM is approved for a 7-day use, and you need
7 days to see what is going on with the patient’s glycemic control
during the week compared with weekends.
General consensus is that it is inappropriate to use a personal CGM
device as a substitute for a professional CGM evaluation for the
following reasons:

The use of personal CGM device eliminates the blinded nature of a
professional CGM, which is key to developing those ‘‘aha!’’ moments
with the patient when going over the professional CGM results.
When scheduled appropriately, 3 days of data are adequate for
evaluating glucose control over time.
For patients who have markedly different schedules for
weekends and weekdays, the provider can start the patient
with the professional CGM device on a Thursday and thus
catch both a weekday and a weekend day during the evaluation period
A personal CGM device requires more training for the patient to
be able to use it safely. The patient must perform SMBG before
making a therapeutic decision and then you have to teach them
also how to calibrate and that you got to calibrate it appropriately.
To get a complete picture of glycemic patterns within a 3-day
period, the provider may train the patient to perform overnight
basal rate testing the first day only, because the overnight
testing is a lot to ask day in and day out. On subsequent 2 days,
the patient might skip breakfast 1 day, and skip lunch or dinner
another day.

.

Billing and Reimbursement
Reimbursement policies must be established before initiating the
professional CGM evaluation, to ensure that the procedure will be
reimbursed. Medicare reimburses professional CGM for insulinrequiring diabetic patients. In some cases, Medicare will also reimburse for patients who are not on insulin if you can demonstrate that
they are not in control. Non-Medicare health plans have differing
policies governing professional CGM reimbursement. In addition,
Medicare and some private insurers will reimburse for two to four
yearly professional CGM evaluations.
The lead staff member in charge of professional CGM must contact
the local insurance providers and obtain their procedures and referral
forms for professional CGM authorization. Not all insurance



companies are familiar with requests for professional CGM, and
rationales for performing the procedure must be filled out as required. The forms must document exactly how the patient meets the
criteria established by each insurer’s plan. In particular, diagnoses of
uncontrolled diabetes or other rationales must be coded accurately.
The device’s manufacturer may provide a resource guide for practices
that want to utilize the technology.
There was general agreement about coding for reimbursement for
professional CGM. Pre-CGM evaluation can be billed using codes
99212–99215. The procedure itself, including placement of the
sensor, removal of the sensor, and downloading the data, is coded as
professional CGM 95250. The initial visit during which the device is
inserted is just a visit and not a charge. The 90250 charge is done at
the time of the download.
The interpretation of both personal CGM and professional CGM is
coded as 95251, billed on the day that you interpret it. This latter
charge is billable whether the interpretation is shared with the patient
by telephone or in person, so long as the interpretation of the
download with recommendation of therapeutic adjustments is done
by a licensed practitioner (e.g., Medical Doctor, Doctor of Osteopathy,
Nurse Practitioner, or Physician Assistant).
Within the practice, a system of checks and balances are needed to
ensure that all patients who were scheduled for professional CGM
received the equipment and returned it, and that all services provided
are billed for at the end of every week. In one practice, the billing
department meets quarterly with the healthcare provider to discuss
the implementation of the professional CGM service.

Consensus on Follow-Up Professional
CGM Recommendations
Participants agreed that repeating a professional CGM evaluation
is important for two main reasons: (1) the patient and healthcare
provider get to evaluate the success of therapeutic changes guided by
the first evaluation; (2) glycemic control is an evolving story for
many diabetics, and regular evaluations are necessary to ensure that
patients continue to integrate data into their behaviors that govern
glycemic control over time.
Several participants indicated that, although follow-up professional CGM evaluation is clinically important, and is covered by
Medicare, in reality, repeat professional CGM is underutilized. One
participant’s practice is just starting to incorporate follow-up CGM
evaluations within 3 or 6 months to ensure that the therapeutic
changes that have been made actually improved the BG pattern
overall, and not just the A1c.
The roundtable moderator just finished participating in a trial in
which eligible subjects had type 2 diabetes treated with basal insulin. Subjects were placed on an insulin pump and professional
CGM was used to optimally titrate their basal and bolus insulin so
they had no hypoglycemia. Subjects came back weekly for evaluation of the sensor data, with alteration to the basal and bolus
insulin as needed to get everyone to goal. Every subject’s A1c
dropped an average of 1.5–2.0 points no matter what regimen they
were on.

Consensus on Interpreting Professional
CGM Outputs
Participants described the systematic ways in which they interpret
output from the professional CGM device. The basic concept is to go
from a big picture to a small picture and stop at the level at which you
have enough information.
One participant starts with the pie charts of the Sensor Summary,
and the average glucose on the meter as well as the sensor, to make
sure it is an adequate study. Second, he checks the Sensor Modal Day
output for trends in highs and lows. Then, the Sensor Modal Time
chart gives a clear sense of what happened overnight, and before and
after meals. Then, he compares the Sensor Modal Day output with the
diary listings day by day, and adds handwritten notes. Thus, he might
observe an uptrend in BG on a day that the patient ate rice and
beans and did not bolus enough. With practice, this level of interpretation can take as little as 5 minutes. He summarizes the data on a
preprinted sheet to indicate that if it is an adequate study, if there is
any hyperglycemia or hypoglycemia overnight or at meals, what
changes need to be made, and a place to sign off. The sheet goes to the
nurse, who calls the patient and relays the recommendations for
changes.
Another practitioner also writes notes on the output and gives
patients a copy. The original goes in the chart in a section clearly
labeled sensor downloads so that it can be retrieved easily as
needed.
Whether the discussion of professional CGM results is done by the
physician or another licensed member of the team, it should include
showing the patient what certain foods, activities, or medication
dosing do to the BG pattern. This discussion will help the patient
understand how the clinician can identify instances of overtreating,
or fear of hypoglycemia and the defensive behavior in eating patients
engage in to prevent hypoglycemia overnight.

Consensus on Therapy Adjustments Guided
by Professional CGM
Overall, participants agreed that the three main adjustments that
might be triggered by professional CGM results are the basal insulin
dose, dosing before meals, and dosing after meals. Patients may see
how underutilizing insulin for meals, and improper use of the carbohydrate ratio really affect their BG.
If the patient does not wake up with a normal fasting glucose, the
clinician needs to optimize the basal insulin delivery. The most
common changes are more meal-related changes. Some patients need
changes in insulin dose to cover meals better because the basal dose is
too high. They are having hypoglycemia before the next meal. Some
patients go to bed high and then wake up normal and do a lot of
defensive eating at night.
Another important interpretation is to identify when during
the night a patient becomes hypoglycemic, to adjust the insulin dosage
to prevent further episodes of nocturnal hypoglycemia. The glucose
patterns after a meal will govern establishment of the appropriate
doses of preprandial insulin to cover the carbohydrate load for meals.



For type 2 patients with elevated A1cs, one participant may
change a patient’s oral agent or change their insulin regimen when
she finds hyperglycemia where she least expects it based on output
from professional CGM.
It is important to be cautious about making too many dietary or
medication changes at one visit to ensure that you can identify what
change made the difference. If several changes are appropriate, one
participant recommended choosing the change the patient is willing
to do first.

Expert Recommendations on the Future
of Professional CGM
During this discussion, roundtable participants brainstormed
about how professional CGM might improve over time. The ideal
system would not require the patient to test glucose with a fingerstick. Second, when the CGM sensor detects hypoglycemia, a device
that shuts the pump off when the patient does not respond to the
alarm need to be approved in the United States. Such a device is
already approved in Europe.
One of the problems with miniaturizing components is that there
is a tradeoff based on physics—to get things really small, the battery life will be shorter. One participant was frustrated because
his professional CGM equipment failed after only 14 months.
He suggested that if a longer or unlimited battery life cannot be
built, then the battery needs to be rechargeable, because primary
care doctors and endocrinologists will not embrace the technology
if they feel like they have to replace expensive devices every
2 years.

Ideally, professional CGM would evolve into a handheld device
into which the patient could input insulin dosing that would collect
and display meal markers to replace the handwritten diary. Perhaps
the device could even take and upload pictures of the food being
eaten. Ideally, this future device would use artificial intelligence to
analyze some of those patterns and highlight them—sort of like an
EKG interpretation. The system would allow the clinician to agree or
disagree with the automatically generated interpretation, and the
output would display the diary overlaid on the BG tracings in a oneor two-page format and permit the clinician to make therapeutic
changes as appropriate.
The devices need to be connected to (1) the patients’ significant
others, (2) the doctor’s office, or (3) a central monitoring station. This
would be particularly useful for those elderly patients who live alone
and value their independence. The device would predict BG trends
and notify patients of severe hypoglycemia and hyperglycemia
before they happen.
The ultimate improvement, of course, will be the closed loop
system with a sensor and pump working together.

Conclusions
The 10 varied cases presented at this roundtable discussion provided
an excellent tutorial in how to interpret data generated by professional
CGM evaluations. This technology can benefit a wide range of diabetic
patients. Healthcare providers must educate third-party payers that
there is more to glucose control than just an A1C value. Professional
and personal CGM both have an important role in guiding therapy
adjustments to optimize our patient’s overall BG control.


DIABETES TECHNOLOGY & THERAPEUTICS
Volume 11, Number 3, 2009
ª Mary Ann Liebert, Inc.
DOI: 10.1089=dia.2008.0053

Continuous Glucose Monitoring in Non–Insulin-Using
Individuals with Type 2 Diabetes: Acceptability,
Feasibility, and Teaching Opportunities
1
Nancy A. Allen, Ph.D., James A. Fain, Ph.D.,2 Barry Braun, Ph.D.,3 and Stuart R. Chipkin, M.D.3

Abstract

Background: Continuous glucose monitoring (CGM) has the potential to provide useful data for behavioral interventions targeting non–insulin-using, sedentary individuals with type 2 diabetes mellitus (T2DM). The aims
of this study were to describe CGM in terms of (1) feasibility and acceptability and (2) dietary- and exerciseteaching events.
Methods: Cross-sectional data were analyzed from 27 non–insulin-using adults with T2DM who wore CGM
for 72 h as part of a larger study on using CGM for exercise counseling in this population. Feasibility data included accuracy of entering daily self-monitored blood glucose (SMBG) readings and events (e.g., meals, exercise), sensor failures, alarms, optimal accuracy of glucose data, and download failures. Acceptability data
included CGM satisfaction and wearing difficulties. Dietary- and exercise-teaching events were identified from
CGM and activity monitor data.
Results: CGM graphs showed 141 dietary- and 71 exercise-teaching events. About half the participants (52%)
reported difficulty remembering to enter events into CGM monitors, but most (82%) kept an accurate paper
log of events. Insufficient SMBG entries resulted in 32 CGM graphs with ‘‘use clinical judgment’’ warnings.
Eighty-three percent of missed SMBG entries were from 18 participants 55–77 years old. Missing correlation
coefficients resulted from glucose concentrations varying <100 mg=dL. A majority of participants (n ¼ 19) were
willing to wear CGM again despite reporting minor discomfort at sensor site and with wearing the monitor.
Conclusions: CGM data provided several teaching opportunities in non–insulin-using adults with T2DM.
Overall, CGM was acceptable and feasible. Some identified problems may be eliminated by newer technology.

2006–2007). However, few studies have addressed how clinicians can use this technology to counsel non–insulin-using
individuals with type 2 diabetes mellitus (T2DM) to change
behaviors and to improve diabetes self-management skills.
Although technology-related interventions might change
behaviors and improve health-related outcomes, feasibility
studies are necessary before advancing to costly clinical trials.
To determine the feasibility of using CGM in a larger, randomized control pilot study to change lifestyle behaviors in
individuals with T2DM,10 we first conducted a preliminary
focus group study with nine non–insulin-using individuals
with T2DM who wore CGM.11 The results of that study were
used to develop the feasibility and acceptability measures for
this cross-sectional pilot study with 27 sedentary, non–insulin-using individuals with T2DM.10 Data from those 27 individuals were examined in the present study to determine (1)

Introduction

C

ontinuous glucose monitoring (CGM) technology
has the potential to change approaches to educating individuals with diabetes. Since the first CGM device was approved by the U.S. Food and Drug Administration in 1999,1
other models have been developed and distributed,2,3 with
improved accuracy of glucose sensors.4 These devices provide
different types of CGM data, retrospective and real-time, for
counseling individuals with diabetes.5–9 The increasing importance of CGM technology in diabetes health care is reflected by the term ‘‘continuous glucose monitoring’’ as the
topic of 26 research presentations and three symposia at the
2007 American Diabetes Association’s 67th Scientific Session
and by this search term in Medline retrieving an increasing
number of articles (10 articles in 1998–1999, 146 articles in
1

Yale University, New Haven, Connecticut.
University of Massachusetts Dartmouth, Dartmouth, Massachusetts.
University of Massachusetts Amherst, Amherst, Massachusetts.

2
3

41

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