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Current Trends in ProfessionalContinuous Glucose Monitoring
Guest Editor:
Bruce W. Bode, M.D
Atlanta Diabetes AssociatesAtlanta, 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 byMedtronicMiniMed, 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 IntroductionB.W. Bode, P. Phillips, B. Nardacci, K.C. Arnold, B.S. Horowitz, O. Odugbesan, S. Reddy
Case 1: A 62-Year-Old Woman with Complex Medical History and Hypoglycemia Unawareness6P. Phillips
Case 2: A 60-Year-Old Woman with Diabetes Secondary to Necrotizing Pancreatitis withHighly Variable Blood Glucose Levels on Basal Bolus Therapy
9
E. Nardacci
Case 3: A 41-Year-Old Man with Type 1 Diabetes with Good Glucose Control12K.C. Arnold
Case 4: A 29-Year-Old Woman with Type 1 Diabetes, Pregnant with Triplets14K.C. Arnold
Case 5: A 61-Year-Old Man with Type 1 Diabetes16S. Reddy
Case 6: A Type 1 Diabetic College Student with a Crazy Lifestyle and Crazy Blood Sugars18B.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
Case 9: A 37-Year-Old Woman with Type 2 Diabetes at 20 Weeks of Gestation26K.C. Arnold
Case 10: A 41-Year-Old Woman with Type 2 Diabetes, High A1c28O. Odugbesan
Discussion Regarding Use of Professional Continuous Glucose Monitoring31
Professional Continuous Glucose Monitoring (CGM) Progress Note37
HIGHLIGHTS FROM DIABETES TECHNOLOGY & THERAPEUTICS
Continuous Glucose Monitoring in Non-Insulin-Using Individuals with Type 2 Diabetes: Acceptability,Feasibility, and Teaching Opportunities
41
N.A. Allen, J.A. Fain, B. Braun, S.R. Chipkin
Sustained Efficacy of Continuous Subcutaneous Insulin Infusion in Type 1 Diabetes Subjects withRecurrent Non-Severe and Severe Hypoglycemia and Hypoglycemia Unawareness: A Pilot Study
49
M. Gimenez, M. Lara, and I. Conget
Maximizing Reimbursement through Correct Coding Initiatives54E. 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
1Atlanta Diabetes Associates, Atlanta, Georgia.2Diabetes & Metabolism Specialists, San Antonio,Texas.
3Albany Medical Center, Albany, New York.4The Diabetes Center, PLLC, Ocean Springs, Mississippi.5Palm Beach Diabetes and Endocrine Specialists, PA, West PalmBeach, Florida.
6North Atlanta Endocrinology, Lawrenceville, Georgia.7Endocrinology & Diabetes Center, Fort Gratiot,Michigan.
AbstractA total of 10 patients were discussed during this meeting en-
titled ‘‘Current Trends in Professional Continuous Glucose Mon-
itoring (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
case presentations, the role of professional CGM in the real world
was discussed.
During the ‘‘Current Trends in Professional Continuous
Glucose Monitoring (CGM)’’ symposium, held at the Uni-
versity 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 profes-
sional CGM, and how physicians and nurse practitioners do pro-
fessional 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 self-
monitored 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, continu-
ously 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 Med-
tronic 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 pro-
vider, who places a sensor with a transmitter on the patient in the
Fig. 2. The two types of continuous glucose monitoring target dif-ferent users: health care professionals and empowering individualpatients with diabetes.
Evolution of Diabetes Management Technologies
Insulin pump therapyContinuos
glucose sensor
Urine glucose testingPoint-in-timeBG meters
Discovery of insulin
Integrated systems:Pumps/Meters/Software
ArtificialPancreas
1900s 1922 1977 1978 1999 2003
Fig. 1. Evolution of diabetes management technologies. The firstcontinuous glucose sensor was introduced in 1999. The first devicethat integrated insulin pumps, glucose sensors, and softwarewas introduced in 2003.
4 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING ª 2010 Medtronic Minimed, Inc. All rights reserved.
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 hypo-
and 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
INTRODUCTION
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 5
Case 1A 62-Year-Old Woman with Complex Medical Historyand Hypoglycemia Unawareness
Paula Phillips, M.D.
Diabetes & Metabolism Specialists, San Antonio, Texas.
Patient HistoryThe 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-times-
a-day self-monitored blood glucose (SMBG) ranging from 37 to
542mg=dL. Most of the hypoglycemic episodes (<50mg=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
350mg=dL.
Comorbidities and DiabeticComplications
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 gastro-
paresis. She was on metoclopramide treatment but for her gastroin-
testinal 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 CGMAfter initial presentation, the provider changed the patient’s reg-
imen 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 gly-
cemic 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.
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 ResultsThe initial professional CGM revealed no evidence of over-
night 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 in-
consistent pattern in the morning (including two brief periods of
hypoglycemia), and significant postmeal excursions both at break-
fast and dinner, with a drop in BG late afternoon (Fig. 4).
Therapy Adjustments=Treatment AlterationsThe 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, par-
ticularly 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 hand-
written 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.
6 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING ª 2010 Medtronic Minimed, Inc. All rights reserved.
Sensor Summary
Date
Sensor
# of Sensor Values
7/20/2009 7/21/2009 7/22/2009 7/23/2009
159
293
181-381
63
2
283
196-369
2
5.5
n/a 0.97
0
0
0
288
169
50-353
74
4
149
56-235
4
288
205
83-346
58
4
157
177-192
4
17.7
n/a
3
3
0
20:25 (85%)
03:35 (15%)
00:00 (0%)
6.1
0.99
7
6
1
14:30 (60%) 13:15 (100%)
00:00 (0%)
00:00 (0%) 03:20 (5%)
12:55 (19%)
52:40 (76%)
2
10
12
12.1
12
56-369
181
12
83
43-381
208
827
Totals
153
0 1
76
07:15 (31%)
02:15 (9%)
68
0
43
1
92
192
43-306
99
2
191
66-315
2
19.3
n/a
2
1
1
04:30 (59%)
02:05 (27%)
01:05 (14%)
75
3
Average (mg/dL)
Min - Max (mg/dL)
STDev (mg/dL)
# of Meter Values
Average (mg/dL)
Min - Max (mg/dL)
Designation
# of Paired Readings
Mean Abs. Diff. [MAD %]
Correlation Coeff. [R]
# of Excursions*
# of High Excursions*
# of Low Excursions*
Duration Above High Limit
Duration Within Limits
Duration Below Low Limit
Pie ChartRed: Above LimitsGreen: Within LimitsBlue: Below Limits
Glucose Area Above HighLimit (mg/dL*Day)
Glucose Area Below LowLimit (mg/dL*Day)
Meter
Optimal AccuracyCriteria
ExcursionsHigh > 140mg/dLLow < 70mg/dL
X: Use ClinicalJudgment
X: Use ClinicalJudgment
X: Please use your clinical judgment - this day does not satisfy the optimal accuracy criteria according to set thresholds:N[¼ 3, R[¼0.79 and MAD<¼28% [or<¼ 18% if the range (Min-Max) of meter values is less than 100mg=dL (5.6mmol=L) - seeCriteria 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 100mg=dL (5.6mmol=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 re-port show two brief periods of hy-poglycemia (shown in blue andgreen), and significant postmealexcursions.
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 7
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.
ConclusionsThe 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
from a personal CGM with an audible warning. She would also
benefit from insulin-pump therapy. Theoretically, given her gastro-
paresis and the way she responds to high-fat meals, the endocrinol-
ogist 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 StatementPaula Phillips, M.D., is a speaker for Medtronic Diabetes.
Fig. 5. The Sensor Modal Time Report shows that the patient experienced hyperglycemia after dinner that continued for up to 6 h.
PHILLIPS
8 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING
Case 2A 60-Year-Old Woman with Diabetes Secondary to Necrotizing Pancreatitis withHighly Variable Blood Glucose Levels on Basal Bolus Therapy
Elizabeth Nardacci, FNP-C
Albany Medical Center, Albany, New York.
Patient HistoryThis patient developed necrotizing pancreatitis and was found to
have diabetes in January 2008, about a year before the initial pro-
fessional 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%.
Rationale for Initiating Professional CGMThe 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.
Initial Professional CGM ResultsThe 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).
Therapy Adjustments=Treatment AlterationsAfter using the Professional CGM, the provider recommended an
insulin pump, and the patient agreed.
Follow-Up Professional CGM Results=Responseto 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 SensorModal Day outputshows severehyperglycemia.
ª 2010 Medtronic Minimed, Inc. All rights reserved. CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 9
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.
NARDACCI
10 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING
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 af-
ternoon. 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, experi-
encing brief periods of hyperglycemia during the day. Her post-
prandial 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, as-
suming 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 clini-
cian adjusted the sensitivity number upward to give her less of a
correction.
ConclusionsProfessional CGM identified multiple reasons for uncontrolled
diabetes in this patient. Although the patient is not at goal, she has
improved significantly.
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 6–8h. (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.
Disclosure StatementElizabeth Nardacci, F.N.P., BC-ADM, is a speaker for Eli Lilly and
Medtronic Diabetes. She is on the medical advisory board of Med-
tronic Diabetes.
CASE 2: WOMAN WITH DIABETES SECONDARY TO NECROTIZING PANCREATITIS
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 11
Case 3A 41-Year-Old Man with Type 1 Diabetes with Good Glucose Control
Kathleen C. Arnold, A.N.P.
The Diabetes Center, PLLC, Ocean Springs, Mississippi.
Patient HistoryThis patient is a 41-year-old man found to have type 1 diabetes in
February 2008. He had no other significant medical history or dia-
betes 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 ContinuousGlucose Monitoring
Both the patient and the healthcare provider wanted profes-
sional continuous glucose monitoring (CGM) to evaluate the BG
control on cycling days.
Fig. 9. Sensor Modal Time tracing for an avid cyclist. Red arrowsindicate unrecognized hyperglycemia and hypoglycemia.
Fig. 10. Sensor Daily Details reveal most blood glucose values are within range, even on days that the patient takes long bike rides.
12 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING ª 2010 Medtronic Minimed, Inc. All rights reserved.
Initial Professional CGM ResultsThe CGM tracings showed that the patient had overall good gly-
cemic 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–
100g 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 hyper-
glycemia during the night, and several episodes of unrecognized hy-
poglycemia.
Therapy Adjustments=TreatmentAlterations
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 CGMFollow-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.
ConclusionsThis case illustrates that even though the patient had good glucose
control, this apparent level of control masked swings in BG subse-
quent 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.
Disclosure StatementKathleen C. Arnold, A.N.P., BC-ADM, is a speaker for Lilly, Med-
tronic Diabetes, NovoNordisk, and Sanofi Aventis.
CASE 3: MAN WITH DIABETES AND GOOD GLUCOSE CONTROL
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 13
Case 4A 29-Year-Old Woman with Type 1 Diabetes, Pregnant with Triplets
Kathleen C. Arnold, A.N.P.
The Diabetes Center, PLLC, Ocean Springs, Mississippi.
Patient HistoryA 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 ProfessionalContinuous Glucose Monitoring
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 GlucoseMonitoring 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 de-
fault, the value should be changed to 60 for pregnancy. For preg-
nancy, target BG 2 hours postprandial is 120=mg=dL, and the patient
did not always achieve that.
Therapy AdjustmentsShe 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.
Response to Therapy AdjustmentsIn early September, the patient had some complications. She un-
derwent 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.
ConclusionsProfessional CGM helped this pregnant woman with type 1 dia-
betes, 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 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING ª 2010 Medtronic Minimed, Inc. All rights reserved.
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 ab-
dominal area to the legs or buttocks.
This patient was compliant with her regimen after the hypogly-
cemic 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, espe-
cially 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 sur-
viving babies are doing well.
Disclosure StatementKathleen C. Arnold, A.N.P., BC-ADM, is a speaker for Lilly, Med-
tronic Diabetes, NovoNordisk, and Sanofi Aventis.
CASE 4: WOMAN WITH DIABETES, PREGNANT WITH TRIPLETS
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 15
Case 5A 61-Year-Old Man with Type 1 Diabetes
Sushma Reddy, M.D.
Endocrinology & Diabetes Center, Fort Gratiot, Michigan.
Patient HistoryThis case is a 61-year-old man with type 1 diabetes who origi-
nally 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 ComplicationsThe 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.
Rationale for Initiating Professional ContinuousGlucose 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%.
Initial Professional Continuous GlucoseMonitoring Results
Professional continuous glucose monitoring CGM revealed post-
prandial hyperglycemia, and nocturnal hyperglycemia between 8 pm
and 2 am, indicating that the patient sometimes forgot to bolus af-
ter a night-time snack. The sensor summary indicated that the pa-
tient’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 bo-
lusing appropriately at dinner time. Although he performed SMBG
four times a day, he still experienced unrecognized hyperglycemic
peaks that were missed with SMBG.
Therapy Adjustments=Treatment AlterationsThe 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.
Follow-Up Professional CGM Results=Responseto Therapy Adjustments
The patient’s A1c improved to 8.3%. The patient now uses a per-
sonal 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.
ConclusionsThis 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 addi-
tion, 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 real-
time 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 re-
membered to bolus appropriately, he would not be awakened by
alarms.
16 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING ª 2010 Medtronic Minimed, Inc. All rights reserved.
Disclosure StatementSushma Reddy, M.D., is a speaker for Eli Lilly, Medtronic Dia-
betes, Novo Nordisk, Sanofi-Aventis, Takeda, and Bristol Meyers
Squibb.
Fig. 12. Sensor Daily Details reveal that blood glucose is above 300mg=dL throughout the day and at bedtime, and nearly normalon waking. Blood glucose peaks were not recognized with SMBG (shown as blue plus signs).
Fig. 13. Sensor Modal Day reveals adawn phenomenon between 3 amand 6 am (shown in black).
CASE 5: MAN WITH TYPE 1 DIABETES
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 17
Case 6A Type 1 Diabetic College Student with a Crazy Lifestyleand Crazy Blood Sugars
Barry S. Horowitz, M.D.
Palm Beach Diabetes and Endocrine Specialists, PA, West PalmBeach, Florida.
Patient HistoryThis 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.
Rationale for Initiating ProfessionalContinuous Glucose Monitoring
Her baseline A1c was 7.1%, which is almost at target, but the few
reported BG measurements were so variable that professional con-
tinuous glucose monitoring (CGM) was ordered to clarify the patterns
and help the patient establish better control.
Initial Professional CGM ResultsThe 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 hypo-
glycemia 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 car-
bohydrates, which led to more hyperglycemia.
Therapy Adjustments=Treatment AlterationsWe decreased her Glargine to 12 units because of the fasting hy-
poglycemia on awakening. The dietician recommended increasing
Fig. 14. Sensor Daily Details reveal several unrecognized episodes of nocturnal hypoglycemia and several hyperglycemic peaksmissed with self-monitored BG.
18 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING ª 2010 Medtronic Minimed, Inc. All rights reserved.
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.
Follow-Up Professional CGM Results=Responseto Therapy Adjustments
A follow-up professional CGM was performed about 3 months
later. The patient’s BG was in normal ranges 77% of the time, com-
pared 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 hyper-
glycemias 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.
ConclusionsThe 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.
Disclosure StatementBarry 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.
Fig. 15. The Sensor Modal Time tracings revealed elimination of the hyperglycemia peaks at 2 am and the hypoglycemia onawakening seen in the previous professional CGM study.
CASE 6: DIABETIC COLLEGE STUDENT WITH CRAZY LIFESTYLE
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 19
Case 7A 38-Year-Old Woman with Type 1 Diabetes
Bruce W. Bode, M.D.
Atlanta Diabetes Associates, Atlanta, Georgia.
Patient HistoryThis 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 gen-
erally 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 gly-
cemic control.
Comorbidities and Diabetic ComplicationsThe 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.
Rationale for Initiating ProfessionalContinuous Glucose Monitoring
The patient is on an insulin pump and manually boluses approx-
imately 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.
Initial Professional Continuous GlucoseMonitoring 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.
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.
Therapy Adjustments=Treatment AlterationsInitially, the provider increased the basal rate, followed by a sec-
ond 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.
Response to Therapy AdjustmentsThe 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.
ConclusionsProfessional 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 ac-
cepting of her diabetes to take that proactive approach.
Professional CGM may not give an accurate picture of each pa-
tient’s diabetes control, because patients may change their diabetes-
related 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.
. 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 ev-
erything 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
20 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING ª 2010 Medtronic Minimed, Inc. All rights reserved.
Fig. 16. Sensor DailyDetails reveals a dawnphenomenon earlier thanexpected, and bloodglucose peaks that arenot recognizedwith SMBG.
Sensor Summary
Date
Sensor
# of Sensor Values
6/26/2009 6/27/2009 6/28/2009 6/29/2009
288
155
56-331
72
4
92
46-141
4
11.7
n/a 1.00
5
3
2
288
209
86-346
65
4
157
72-242
4
288
188
87-307
66
5
172
77-270
5
11.5
0.99
3
3
0
14:25 (60%)
09:35 (40%)
00:00 (0%)
12.9
0.99
1
1
0
19:05 (80%) 10:25 (43%)
13:10 (55%)
00:25 (2%) 00:55 (4%)
11:35 (48%)
11:30 (48%)
2
4
6
7.1
6
49-262
124
6
66
57-286
164
288
6/30/2009
29
0 0 0
33 12
04:55 (20%)
00.00 (0%)
48
0
67
0
102
133
47-197
33
3
108
96-116
3
28.1
n/a
4
3
1
02:25 (28%)
05:50 (69%)
00:15 (3%)
5
1
X: Use ClinicalJudgment
Average (mg/dL)
Min - Max (mg/dL)
STDev (mg/dL)
# of Meter Values
Average (mg/dL)
Min - Max (mg/dL)
Designation
# of Paired Readings
Mean Abs. Diff. [MAD %]
Correlation Coeff. [R]
# of Excursions*
# of High Excursions*
# of Low Excursions*
Duration Above High Limit
Duration Within Limits
Duration Below Low Limit
Pie ChartRed: Above LimitsGreen: Within LimitsBlue: Below Limits
Glucose Area Above HighLimit (mg/dL*Day)
Glucose Area Below LowLimit (mg/dL*Day)
Meter
Optimal AccuracyCriteria
ExcursionsHigh > 150mg/dLLow < 70mg/dL
0.95
00:05 (0%)
09:30 (53%)
08:30 (47%)
1
2
3
5.5
4
118-232
160
5
33
69-226
150
217
7/1/2009
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<¼28% [or<¼ 18% if the range (Min-Max) of meter values is less than 100mg=dL (5.6mmol=L) - see CriteriaNote 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 100mg=dL (5.6mmol=L) then ‘R’ will be reported as ‘N=A’.
In this case the optimal accuracy threshold set for MAD is<¼ 18%.Excursion Note: Excursions are counted in the day that the excursion event started.
Fig. 17. Sensor Summary reveals an average BG of 150mg=dL. Patient experiences hyperglycemia from 28% to 80% of the day.
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 21
at least four times daily. Because this patient routinely does not self-
monitor 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 impor-
tant 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.
Disclosure StatementBruce 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 Sanofi-
Aventis.
BODE
22 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING
Case 8A 69-Year-Old Woman with Type 2 Diabetesand Good Premeal Glucose, But a High A1c
Barry S. Horowitz, M.D.
Palm Beach Diabetes and Endocrine Specialists, PA, West PalmBeach, Florida.
Patient HistoryThis 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 dif-
ferent 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.
Comorbidities and Diabetic ComplicationsHer comorbid conditions include cardiomyopathy, hyper-
tension, and hyperlipidemia, for all of which she was taking
medication.
Rationale for Initiating ProfessionalContinuous Glucose Monitoring
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 self-
monitored 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.
Initial Professional CGM ResultsThe Sensor Summary from her first professional CGM showed
that her CGM glucose values equally distributed in within, be-
low, and above target range. The patient was completely un-
aware 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.
Therapy Adjustments=Treatment AlterationsThe patient’s diary revealed that she did not take premeal insulin
when her premeal blood sugar was normal. She had had a miscon-
ception 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.
Response to Therapy AdjustmentsThe 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 CGMThis follow-up CGM showed improved and more consistent gly-
cemic control. The Sensor Summary revealed that the hypoglyce-
mia 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%.
ConclusionsThis subject with type 2 diabetes denied experiencing hypo-
glycemia, but she was low a third of the time during the first
ª 2010 Medtronic Minimed, Inc. All rights reserved. CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 23
professional CGM evaluation. Many researchers think that the
increased mortality may be associated with unrecognized hypo-
glycemia with tight glycemic control in patients with type 2 di-
abetes 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.
Fig. 18. The Sensor Modal Dayshowed blood glucose droppingthroughout the night and morningand postprandial hyperglycemia.
Fig. 19. The Sensor Daily Detail report showed that the patient was still often under dosing her mealtime insulin, but at least wasnot skipping doses.
HOROWITZ
24 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING
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. Realisti-
cally, 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.
Disclosure StatementBarry Horowitz, M.D., is a speaker for Abbott Pharmaceuticals,
Amylin Pharmaceuticals, Astra-Zeneca Pharmaceuticals, Bristol
Myers Squibb, Eli Lilly Pharmaceuticals, Merck & Co, Inc., Medtro-
nic Diabetes, Novo Nordisk, Pfizer Pharmaceuticals, Sanofi-Aventis
Pharmaceuticals, and Takeda Pharmaceuticals.
CASE 8: DIABETIC WOMAN WITH GOOD PREMEAL GLUCOSE, BUT HIGH A1C
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 25
Case 9A 37-Year-Old Woman with Type 2 Diabetes at 20 Weeks of Gestation
Kathleen C. Arnold, A.N.P.
The Diabetes Center, PLLC, Ocean Springs, Mississippi.
Patient History
This 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.
Rationale for Initiating Professional ContinuousGlucose Monitoring
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.
Initial Professional Continuous GlucoseMonitoring Results
The Sensor Daily Detail revealed high postprandial BG values,
some as high as 200 mg=dL, starting at breakfast and usually wors-
ening at lunch and dinner (Fig. 20).
Therapy Adjustments=Treatment AlterationsThe clinician reviewed her dietary log and discussed the rela-
tionships 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.
Follow-Up Professional Continuous GlucoseMonitoring Results=Response to TherapyAdjustments
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 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING ª 2010 Medtronic Minimed, Inc. All rights reserved.
ConclusionsThis case emphasizes that an A1c in the 5.6%–5.7% range through
the entire pregnancy may mask underlying postprandial BG excur-
sions, 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 mac-
rosomic 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 low-
ering 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 inter-
vene preconception, but failing that, one should intervene no later
than early in the second trimester.
Disclosure StatementKathleen C. Arnold, A.N.P., BC-ADM, is a speaker for Lilly, Med-
tronic Diabetes, NovoNordisk, and Sanofi Aventis.
CASE 9: WOMAN WITH DIABETES AT 20 WEEKS OF GESTATION
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 27
Case 10A 41-Year-Old Woman with Type 2 Diabetes, High A1c
Ola Odugbesan, M.D.
North Atlanta Endocrinology, Lawrenceville, Georgia.
Patient History
A41-year-old woman was initially found to have gesta-
tional 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.
Comorbidities and Diabetic ComplicationsThe patient is on prednisone therapy for asthma and has irritable
bowel syndrome. She developed profound hyperglycemia that re-
quired insulin therapy.
Rationale for Initiating Professional ContinuousGlucose Monitoring
At the time she agreed to be followed within the practice where she
worked, she was on pioglitazone and metformin, but she was prob-
ably not compliant with this regimen, because of gastrointestinal side
effects from metformin.
Sensor Summary
Date
Sensor
# of Sensor Values
5/27/2009 5/28/2009 5/29/2009 Totals
577
257
106-323
32
11
253
173-308
10
5.3
0.84
2
2
0
169
282
234-323
20
2
290
271-308
2
288
252
182-297
24
5
259
239-268
5
3.3
n/a
0
0
0
24:00 (100%)
00:00 (0%)
00:00 (0%)
7.5
n/a
0
0
0
14:05 (100%) 47:20 (98%)
00:45 (2%)
00:00 (0%)
78
0
00:00 (0%)
00.00 (0%)
72
0
102
0
120
234
106-299
39
4
227
173-306
3
7.0
0.94
2
2
0
09:15 (92%)
00:45 (8%)
00:00 (0%)
57
0
X: Use ClinicalJudgment
Average (mg/dL)
Min - Max (mg/dL)
STDev (mg/dL)
# of Meter Values
Average (mg/dL)
Min - Max (mg/dL)
Designation
# of Paired Readings
Mean Abs. Diff. [MAD %]
Correlation Coeff. [R]
# of Excursions*
# of High Excursions*
# of Low Excursions*
Duration Above High Limit
Duration Within Limits
Duration Below Low Limit
Pie ChartRed: Above LimitsGreen: Within LimitsBlue: Below Limits
Glucose Area Above HighLimit (mg/dL*Day)
Glucose Area Below LowLimit (mg/dL*Day)
Meter
Optimal AccuracyCriteria
ExcursionsHigh > 180mg/dLLow < 70mg/dL
X: Please use your clinical judgment - this day does not satisfy the optimal accuracy criteria according to set
thresholds:
N>¼ 3, R>¼0.79 and MAD<¼28% [or<¼ 18% if the range (Min-Max) of meter values is less than 100mg=dL
(5.6mmol=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 100mg=dL (5.6mmol=L) then ‘R’ will be
reported as ‘N=A’.
In this case the optimal accuracy threshold set for MAD is<¼ 18%.
Excursion Note: Excursions are counted in the day that the excursion event started.
Fig. 21. The SensorSummary revealed that thepatient was hyperglycemicall day long.
28 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING ª 2010 Medtronic Minimed, Inc. All rights reserved.
She was also supposed to be taking Lispro PRN for episodes of hy-
perglycemia. 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 hyperglyce-
mia, 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.
Initial Professional CGM ResultsAs 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.
Therapy Adjustments=Treatment AlterationsThe 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 de-
cided that she was going to be more active and try to achieve better
diabetes control.
Follow-Up Professional CGM Results=Responseto Therapy Adjustments
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
Sensor Summary
Date
Sensor
# of Sensor Values
9/15/2009 9/16/2009 9/17/2009 9/18/2009
159
139
98-165
12
1
155
155-155125-190
1
13.4
n/a n/a
0
0
0
288
149
88-193
20
4
159
4
288
138
63-181
21
4
144
133-160
4
6.3
n/a
2
1
1
00:15 (1%)
23:10 (97%)
00:35 (2%)
23.2
n/a
2
2
0
01.55 (8%) 00:00 (0%)
13:15 (100%)
00:00 (0%) 00:35 (0%)
61:40 (96%)
02:10 (3%)
1
3
4
14.8
10
125-190
154
10
19
63-193
143
773
Totals
0
0 0
0
22.05 (92%)
00.00 (0%)
0
0
0
0
38
145
137-165
6
1
172
172-172
1
17.0
n/a
0
0
0
00:00 (0%)
03:10 (100%)
00:00 (0%)
0
0
Average (mg/dL)
Min - Max (mg/dL)
STDev (mg/dL)
# of Meter Values
Average (mg/dL)
Min - Max (mg/dL)
Designation
# of Paired Readings
Mean Abs. Diff. [MAD %]
Correlation Coeff. [R]
# of Excursions*
# of High Excursions*
# of Low Excursions*
Duration Above High Limit
Duration Within Limits
Duration Below Low Limit
Pie ChartRed: Above LimitsGreen: Within LimitsBlue: Below Limits
Glucose Area Above HighLimit (mg/dL*Day)
Glucose Area Below LowLimit (mg/dL*Day)
Meter
Optimal AccuracyCriteria
ExcursionsHigh > 180mg/dLLow < 70mg/dL
X: Use ClinicalJudgment
X: Use ClinicalJudgment
X: Use ClinicalJudgment
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 100mg=dL (5.6mmol=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 100mg=dL (5.6mmol=L) then ‘R’ will be reported
as ‘N=A’.In this case the optimal accuracy threshold set for MAD is<¼ 18%.
Excursion Note: Excursions are counted in the day that the excursion event started.
Fig. 22. Sensor Summary pie charts show the patient within targets 95%–100% of the time.
CASE 10: WOMAN WITH DIABETES AND HIGH A1C
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 29
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.
ConclusionsThis 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-
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.
Disclosure StatementOla 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.
Fig. 23. Sensor Daily Details show blood glucose within range except for two episode of mild hyperglycemia (circled).
ODUGBESAN
30 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING
Discussion Regarding Use of ProfessionalContinuous Glucose Monitoring
The 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 TerminologyProfessional 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 real-
world 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 ad-
justments 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 read-
ings retrospectively and discuss appropriate therapy adjust-
ments 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 char-
acterized 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 adjust-
ments.* 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 retro-
spectively; 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 mon-
itor with SMBG frequently that are not at goal. It takes a lot more
training and follow-up with personal CGM than it does with pro-
fessional CGM to ensure that the patients interpret the real-time
readings. If a patient is a candidate for personal CGM, the profes-
sional 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 col-
lects 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 some-
thing that was not requested.
Consensus on Definition of Professional CGMProfessional CGM is a diagnostic and therapeutic=management
tool used by the healthcare professional that allows the collection of
ª 2010 Medtronic Minimed, Inc. All rights reserved. CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 31
retrospective glucose data in patients with diabetes. It is indicated to
optimize safe and effective glycemic control in patients in whom self-
monitoring of BG is inadequate.
Consensus on Selection Criteria forProfessional CGM
The overarching reason to use professional CGM is to better under-
stand 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 be-
cause 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%, re-
spectively, 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 mon-
itoring, 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., sulfonyl-
ureas) 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 char-
acteristics.
One important take-home message is that patients may have A1c
values that are nominally at goal, but may actually have poor gly-
cemic 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. Char-
acteristics of patients who are good candidates for professional CGM
are listed in Table 2.
Consensus on Implementation of ProfessionalCGM in the Private Practice SettingThe Value of Retrospective Data withProfessional CGM
When considering whether to implement professional CGM in
their practices, healthcare professionals should be aware of the ad-
vantages of establishing such procedures as part of their service of-
ferings. These advantages are summarized in Table 3.
StaffOne of the key components of initiating a professional CGM
component to a provider’s practice is having a dedicated staff. Par-
ticularly helpful is to have either a licensed professional in your
DISCUSSION REGARDING USE OF PROFESSIONAL CGM
32 CURRENT TRENDS IN PROFESSIONAL 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 mo-
tivated, well-educated patient who is willing to volunteer with pa-
tients 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.
SpaceSpace 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.
SchedulingA 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 PatientThe 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 communi-
cate to the patient. Then, the patient comes back a few weeks after
Table 1. Rationales for Initiating Professional Continuous Glucose Monitoring for Cases Presented
PRESENTER DIABETES TYPE GENDER A1c AT BASELINEBASELINETREATMENT
RATIONALE FORPROFESSIONAL CGM
Phillips 1 F 9.6% NPH 10U 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 14–20U
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 30mg 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.
DISCUSSION REGARDING USE OF PROFESSIONAL CGM
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 33
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-to-
face 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.
EquipmentThe 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 re-
cords what and when they are eating, taking medications, and par-
ticipating 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 evalu-
ation 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 appro-
priately.. 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 ReimbursementReimbursement policies must be established before initiating the
professional CGM evaluation, to ensure that the procedure will be
reimbursed. Medicare reimburses professional CGM for insulin-
requiring diabetic patients. In some cases, Medicare will also reim-
burse 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
Table 2. Professional Continuous Glucose MonitoringCandidates
Diabetic patients unable to achieve an optimal, safe, and effective glycemic
goal with self-monitoring of blood glucose
Diabetic patients with hemoglobin A1c within target range, but with highly
variable blood glucose
Patients with repeated episodes of hypoglycemia or hypoglycemic unawareness
Insulin-requiring patients
Diabetes in pregnancy
Table 3. The Value of Retrospective Data with ProfessionalContinuous Glucose Monitoring
Minimal time required for training and patient start-up
No user interface allows for added simplicity of use
Unaltered glucose patterns without intervention or alerts affecting the
glucose levels
Levels help guide appropriate therapy adjustments
Observe the impact of patient’s diet, exercise, behavior, and medications on
their glucose levels
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
DISCUSSION REGARDING USE OF PROFESSIONAL CGM
34 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING
companies are familiar with requests for professional CGM, and
rationales for performing the procedure must be filled out as re-
quired. 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 ProfessionalCGM 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 profes-
sional 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 in-
sulin. 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 evalu-
ation 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 ProfessionalCGM 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 inter-
pretation 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 Guidedby 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 car-
bohydrate 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.
DISCUSSION REGARDING USE OF PROFESSIONAL CGM
CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING 35
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 Futureof 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 finger-
stick. 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 bat-
tery 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 one-
or 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.
ConclusionsThe 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.
DISCUSSION REGARDING USE OF PROFESSIONAL CGM
36 CURRENT TRENDS IN PROFESSIONAL CONTINUOUS GLUCOSE MONITORING
Continuous Glucose Monitoring in Non–Insulin-UsingIndividuals with Type 2 Diabetes: Acceptability,
Feasibility, and Teaching Opportunities
Nancy A. Allen, Ph.D.,1 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 in-terventions targeting non–insulin-using, sedentary individuals with type 2 diabetes mellitus (T2DM). The aimsof this study were to describe CGM in terms of (1) feasibility and acceptability and (2) dietary- and exercise-teaching events.Methods: Cross-sectional data were analyzed from 27 non–insulin-using adults with T2DM who wore CGMfor 72 h as part of a larger study on using CGM for exercise counseling in this population. Feasibility data in-cluded accuracy of entering daily self-monitored blood glucose (SMBG) readings and events (e.g., meals, ex-ercise), sensor failures, alarms, optimal accuracy of glucose data, and download failures. Acceptability dataincluded CGM satisfaction and wearing difficulties. Dietary- and exercise-teaching events were identified fromCGM 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 paperlog of events. Insufficient SMBG entries resulted in 32CGM graphs with ‘‘use clinical judgment’’ warnings.Eighty-three percent of missed SMBG entries were from 18 participants 55–77 years old. Missing correlationcoefficients resulted from glucose concentrations varying <100mg=dL. A majority of participants (n¼ 19) werewilling 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.
Introduction
Continuous glucose monitoring (CGM) technologyhas the potential to change approaches to educating in-
dividuals with diabetes. Since the first CGM device was ap-proved by the U.S. Food and Drug Administration in 1999,1
other models have been developed and distributed,2,3 withimproved accuracy of glucose sensors.4 These devices providedifferent types of CGM data, retrospective and real-time, forcounseling individuals with diabetes.5–9 The increasing im-portance of CGM technology in diabetes health care is re-flected by the term ‘‘continuous glucose monitoring’’ as thetopic of 26 research presentations and three symposia at the2007 American Diabetes Association’s 67th Scientific Sessionand by this search term in Medline retrieving an increasingnumber of articles (10 articles in 1998–1999, 146 articles in
2006–2007). However, few studies have addressed how cli-nicians can use this technology to counsel non–insulin-usingindividuals with type 2 diabetes mellitus (T2DM) to changebehaviors and to improve diabetes self-management skills.
Although technology-related interventions might changebehaviors and improve health-related outcomes, feasibilitystudies are necessary before advancing to costly clinical trials.To determine the feasibility of using CGM in a larger, ran-domized control pilot study to change lifestyle behaviors inindividuals with T2DM,10 we first conducted a preliminaryfocus group study with nine non–insulin-using individualswith T2DM who wore CGM.11 The results of that study wereused to develop the feasibility and acceptability measures forthis cross-sectional pilot study with 27 sedentary, non–insu-lin-using individuals with T2DM.10 Data from those 27 indi-viduals were examined in the present study to determine (1)
1Yale University, New Haven, Connecticut.2University of Massachusetts Dartmouth, Dartmouth, Massachusetts.3University of Massachusetts Amherst, Amherst, Massachusetts.
DIABETES TECHNOLOGY & THERAPEUTICSVolume 11, Number 3, 2009ª Mary Ann Liebert, Inc.DOI: 10.1089=dia.2008.0053
41
feasibility and acceptability of CGM and (2) uses of CGMdatato provide dietary and exercise education to non–insulin-us-ing individuals with T2DM.
Research Design and Methods
This study examined cross-sectional data from non–insu-lin-using individuals with T2DMwhowore CGM (MedtronicMiniMed, Northridge, CA) for 72 h as part of a larger pilotstudy (n¼ 52).10 Twenty-five participants in the larger studywere part of a control group that did not wear CGM. Therewere no significant differences between the groups at baseline.
Sample and setting
Participants were recruited from two health systems inWestern Massachusetts. Inclusion criteria were (1) knownhistory of T2DM, (2) >18 years old, (3) not exercising morethan 2 days per week, (4) hemoglobin A1c >7.5%, (5) notreceiving insulin, and (6) able to read and speak English.Exclusion criteria were (1) inability to walk 0.25 miles in10min, (2) taking glucocorticoids, and (3) failing prescreeningevaluation (e.g., ischemic heart disease, systolic blood pres-sure >200mm Hg, diastolic blood pressure >110mm Hg,dyspnea on exertion).
Written informed consent was obtained from participantsin accordance with study protocols and institutional reviewboards at study sites.10 Study data were obtained from 27participants who wore CGM in the intervention group of alarger study (n¼ 52).10
Demographic information
Demographic data included gender, race, ethnicity, maritalstatus, education, age, and duration of diabetes. Participantsalso provided information on current diabetes medicationsand smoking history.
Glucose levels
Glucose levels were monitored two ways: (1) continuouslyfor 72 h by the Medtronic CGM device and (2) at least threetimes per day by self-monitored blood glucose (SMBG)readings. The CGM device has four components: pager-sizedglucose monitor, disposable subcutaneous glucose-sensingdevice with an external electrical connector, connecting cable,and communication device to download data from the mon-itor to a personal computer.12 Signals from the sensor are sentevery 10 s to a glucose monitor, where they are averaged andstored every 5min. The monitor calibrates sensor readingsagainst the wearer’s three or four daily required SMBGreadings entered into the CGM device. Information from theCGM device is not available to the wearer but must bedownloaded at the end of 72 h by a clinician to a personalcomputer. CGM software produces daily glucose trend plots,a summary table of average glucose levels, glucose ranges,and standard deviations. Daily and modal color graphs arealso produced with glucose values and markers for meals,exercise, and medication events, visually showing the inter-action among these parameters. Participants were instructedto keep awritten log of events (e.g., SMBG,meals, exercise) ona standardized worksheet. Glucose values obtained withCGM correlate with plasma glucose concentrations measuredin the laboratory13 and at home.12
Physical activity
The amount and intensity of physical activity were objec-tively measured by an ActiGraph (Pensacola, FL) accelerom-eter. This small (5.1-�3.8-�1.5-cm) device was secured by anelastic strap at each participant’s right waist. Monitors wereprogrammed to collect data every minute over 7 days. Thesedata were downloaded into ActiGraph software (DOSRIU256K.EXE, version 2.27) for analysis. The cut points ofFreedson et al.14 were used to determine sedentary (<499counts), light activity (500–1,951 counts), moderate activity(1,952–5,724 counts), and vigorous activity (�5,725 counts).
Feasibility measures
The variables used to assess CGM feasibility, as developedin a preliminary focus group study,11 were (1) accuracy ofparticipant’s CGM input, (2) sensor failures (i.e., signal<10 or>200; initialization signal varies randomly), (3) alarm data, (4)optimal accuracy of glucose data, and (5) data downloadfailures (e.g., lost data, gaps in graphs). Accuracy of CGMinput refers to participant-entered meals, exercise, and med-ication. Missed meal entries were identified by a rise in glu-cose levels without an event marked on the CGM graph andwere recognized by participants as a meal on the paper log orduring review of CGM data with the researcher. Missed ex-ercise entries were identified by a decrease in glucose levelwithout an event marker following increased activity mea-sured by activity monitors or acknowledged by participantsduring review with the researcher. Missed medication entrieswere identified by reviewing CGM graphs for medicationentries and comparing to participants’ medication list.
Acceptability measures
Acceptability was assessed by six questions developedfrom a preliminary focus group study.11 Four of these ques-tions addressed issues related towearing the CGM sensor andmonitor, one addressed participant satisfaction with theCGM, and one addressed understandability of the CGMgraphs (Table 1).
Dietary- and exercise-teaching events
A dietary-teaching event was defined as a glucose excur-sion (a peak change in glucose level of >20mg=dL) in re-sponse to ameal and=or twomeals with glucose excursions ofdiffering magnitudes (in mg=dL). Similarly, an exercise-teaching event was defined as a decline in glucose levels fol-lowing a bout of self-reported exercise or an exercise eventmarked on the CGM graph. An exercise-teaching event alsoincluded increases in glucose levels following sedentary be-havior. CGM graphs were reviewed for teachable dietary andexercise events based on participants’ meals and exercise fromentered CGM meter events, written log, participants’ reportduring counseling, and=or comparison to activity monitordata. For each participant, the number of teaching events wascounted for each day the CGM device was worn.
Body mass index
Body mass index was calculated as weight (kg)=height(m2). Weight was measured to the nearest 0.1 kg using adesignated standing scale in each clinic. participants were
42 ALLEN ET AL.
asked to wear light indoor clothing and to remove shoes be-fore being weighed. Height was measured to the nearest0.5 cm.
Hemoglobin A1c levels
Hemoglobin A1c levels were drawn and assayed byhigh-pressure liquid chromatography (Variant instrument,Bio-Rad, Hercules, CA) according to standard clinical meth-ods.
Procedures
After participants provided consent, they were assessed atbaseline for (1) demographic data, (2) medication history, (3)hemoglobin A1c, and (4) body mass index. Participants werenext instructed on wearing the CGM device, entering data,entering events, and using a log to record SMBG data, meals,exercise, and other events. The CGM device was inserted and
worn for 72 h. Participants removed the CGM device at homeand brought it to the clinic the following week. Data weredownloaded at that appointment and reviewed individuallywith each participant. The activity monitor was simulta-neously worn during the same 72h and for an additional 4days after removing the CGM. Data from activity monitorswere not reviewedwith participants but were used to identifyamounts and duration of exercise in relation to glucose ex-cursions.
Statistical analysis
Frequency distributions and appropriate summary statis-tics for central tendency and variability were used to describedemographic and clinical data using SPSS version 15 (SPSS,Chicago, IL). Descriptive statistics were used to analyze CGMfeasibility data, acceptability data, and teachable events (di-etary- and exercise-related glucose changes).
Table 1. CGM Acceptability Data
CGM evaluation question Frequency (%) (n¼ 21)
1. What issues, if any, did you have with the CGM?a. Skin irritation 4 (19)b. Pain at sensor site day 1 1 (4.8)c. Pain at sensor site continuously 0d. Discomfort at sensor site day 1 2 (9.5)e. Discomfort at sensor site continuously 2 (9.5)f. Discomfort with sensor location 0g. Discomfort due to monitor location 0h. Infection at sensor site 0i. Limited my activities 2 (9.5)j. Remembering to enter blood sugars, meals, exercise
into the monitor11 (52.4)
l. Alarms 6 (28.6)m. Difficulty understanding direction 2 (9.5)
2. How much difficulty did you experience whenshowering with the CGM?a. None 11 (55)b. Small 4 (20)c. Moderate 3 (15)d. Large 2 (10)
3. How much difficulty did you experience whensleeping with the CGM?a. None 17 (81)b. Small 2 (9.5)c. Moderate 2 (9.5)d. Large 0
4. How much difficulty did you experience whilewearing the CGM during the daytime?a. None 20 (95.2)b. Small 1 (4.8)c. Moderate 0d. Large 0
5. Would you wear the CGM again?a. Yes 18 (85.7)b. No 2 (9.5)c. Don’t know 1. (4.8)
6. Did you experience difficulty in understanding theCGM graph?a. Yes 0b. No 21 (100)c. Don’t know 0
CGM ACCEPTABILITY, FEASIBILITY, AND USES 43
Results
Participants
Most participants were female, white, and obese, with amean age of 57 years, and spent the majority of their timeengaging in light-intensity activity (Table 2). On average,participants had an 8-year history of diabetes, partial collegeeducation, and suboptimal glycemic control. The majority ofparticipants were taking a sulfonylurea (n¼ 18) and metfor-min (n¼ 17), while only six participants were taking a glita-zone. No participants were taking an alpha-glucosidaseinhibitor or meglitinide analog.
Feasibility
Events were most accurately entered on the first and lastdays of wearing the CGM device (Table 3). On these days, theevents most accurately entered, in decreasing order, wereexercise (70–82%), medications (56–68%), and meals (42–58%). The CGM device was worn for the shortest times on thefirst and last days. Of all events entered on days 2 and 3, mealswere enteredwith the lowest accuracy (26–33%),with exercise(52–59%) and medications (46–58%) generally entered withmoderate accuracy. These data support those from the ac-ceptability follow-up questionnaire showing that 52% ofparticipants had difficulty remembering to enter CGM events.Despite many participants using the event monitor with onlymoderate accuracy, most (81.5%) kept an accurate paper logof events. No sensors failed, but one CGM cable failed.
The CGM has five possible alarms: (1) disconnect, (2) ISIG(initialization signal) out of range, (3) memory full, (4) cali-bration error, and (5) noise. Of the 27CGM files reviewed,
three hadCGM-disconnect alarms. Of these three, two sensorshad been disconnected. One sensor was disconnected becauseof a CGM cable caught on a door, and another for an un-known reason. The third monitor was turned off for an un-known reason. No ISIG out-of-range or memory-full alarmsoccurred. The five calibration-error alarms were caused bymeter glucose readings falling outside the acceptable limitsused to calibrate sensor glucose values. For example, oneparticipant entered three values (245, 229, 209mg=dL) thatrapidly decreased over 15min, causing a calibration alarm.Lastly, two participants had sensor-noise alarms related torapidly rising glucose levels (>400mg=dL).
Optimal accuracy of CGM glucose data was calculated byCGM software from two sources, glucose sensor and glucosemeter data, for each day the sensor was worn.15 Optimal ac-curacy depended on two criteria: (1) correlation betweensensor and meter readings of at least 0.79 and (2) mean ab-solute difference �28%.15 When data from the CGM devicewere downloaded, correlation coefficients were calculatedbetween glucose meter readings and sensor glucose values(paired data) for each day. These paired data were used tocalculate the mean absolute difference, i.e., the difference be-tween the meter and sensor glucose values, divided by themeter value, and averaged across meter–sensor pairs=day.When optimal accuracy criteria were not met or if fewer thanthree meter–sensor pairs were available (required to calculatecorrelation coefficients), a message appeared (‘‘use clinicaljudgment’’) (Table 4).
About half the participants (51.8%) did not enter more thantwo glucose meter readings on days 1 and 4 (Table 4). Thisomission may be partly attributable to the shorter wear timeson those days. In contrast, most participants entered three ormore glucose meter readings on days 2 (85.2%) and 3 (80.7%).Of the 59 missed glucose meter readings, 49 (83%) were from
Table 2. Participant Demographics (n¼ 27)
Characteristic n¼ 27
Age (years) mean� SD 57.0� 15Diabetes’ duration (years) (mean� SD) 8.3� 6Body mass index (kg=m2) (mean� SD) 36.05� 7Hemoglobin A1c (mean� SD) 8.3� 1Activity (min=day)Light=sedentary 1,427� 12Moderate activity 13� 11
Gender (n [%])Female 15 (56)Male 12 (44)
Race (n [%])White 25 (93)African American 2 (7)
Ethnicity (n [%])Not Hispanic or Latino 25 (93)Hispanic or Latino 2 (7)
Marital status (n [%])Single 8 (30)Married 14 (52)Divorced 4 (15)Widowed 1 (4)
Education (n [%])Graduate or professional training 5 (19)College or university graduate 4 (15)Partial college education 10 (37)High school graduate 7 (26)Partial high school education 1 (4)
Table 3. Accuracy of Participant-Entered
Events on the CGM Device
n (%) on day wearing CGM deviceNumber of missedevents identified onCGM tracingsa 1 2 3 4
Meals0 15 (57.7) 7 (25.9) 9 (33.3) 11 (42.3)1 6 (23.1) 6 (22.2) 5 (18.5) 8 (30.8)�2 5 (19.2) 14 (51.8) 13 (48.1) 7 (26.8)
Exercise0 22 (81.5) 16 (59.3) 14 (51.9) 18 (69.2)1 4 (14.8) 9 (33.3) 10 (37) 8 (30.8)2 1 (3.7) 2 (7.4) 3 (11.1)
Medications0 18 (67.7) 15 (57.7) 12 (46.2) 14 (56)1 8 (29.6) 5 (19.2) 7 (26.9) 8 (32)�2 1 (3.7) 6 (23) 7 (26.9) 3 (12)
aMissed meal entries were identified by a rise in glucose levelswithout an event marked on the CGM graph and were recognized asa meal by participants as a meal on the paper log or during review ofCGM data. Missed exercise entries were identified by a decrease inglucose level without an event marker following increased activitymeasured by activity monitors or acknowledged by participantsduring a review. Missed medication entries were identified byreviewing CGM graphs for medication entries and comparing toparticipants’ medication list.
44 ALLEN ET AL.
18 participants 55–77 years old, and only 17% were from nineparticipants 19–54 years old.
Of the 21CGM reports with calculated correlation coeffi-cients, three failed to meet the criterion of�0.79 (two on day 1and one on day 2) (Table 4). Most participants had missingcorrelation coefficients because their daily glucose levelsvaried <100mg=dL, below the range needed to calculatethese coefficients (Table 3). The mean absolute differencecould not be calculated for two participants on days 1–3 andfor seven participants on day 4 because of insufficient pairedglucose readings. Several CGM graphs (n¼ 32) had ‘‘useclinical judgment’’ messages on days 1 (n¼ 19) and 4 (n¼ 13)because participants did not enter at least three SMBG read-ings. Overall, optimal accuracy criteria were not met by amajority of participants on days 1–4 because their glucoselevels varied �100mg=dL, and they did not enter enoughglucose meter readings on days 1 and 3 (Table 4). Five CGMdaily graphs had gaps due to participants failing to correctlyenter SMBG data or having unpaired meter readings (meterand sensor readings disagreed or monitor was turned off ).
Acceptability
Participants reported minor CGM difficulties: skin irrita-tion (n¼ 4), pain (n¼ 1), or discomfort at sensor site (n¼ 2)and activity limitations (n¼ 2). No infections were observedor reported at CGM sensor sites. Participants reported small(n¼ 5), moderate (n¼ 3), and large (n¼ 2) amounts of diffi-culty with the CGM device while showering. Similarly, par-ticipants reported small (n¼ 3) andmoderate (n¼ 2) difficultysleeping with the monitor. However, the majority reported nodifficulty wearing the CGM (n¼ 20) and answered ‘‘yes’’when asked if they would wear the monitor again (n¼ 19).Only two participants reported difficulty understandingCGM directions, but 11 participants reported difficulty en-tering events such as meals, exercise, and SMBG data. Noparticipants reported difficulty understanding the CGMgraphs.
Dietary- and exercise-teaching events
Over the 72-h CGM period, 77 exercise- and 141 dietary-teaching events occurred (Table 5 and Figs. 1 and 2). Mostexercise-teaching opportunities (66–70%) occurred on days 2and 3, but the majority of participants had dietary-teachableopportunities on all 4 days.
Discussion
Overall, the CGM was reliable, acceptable, and providedmany teaching opportunities. CGM has most frequently beenused to adjust insulin levels in people with type 1 diabetes,16–18 T2DM,19 and during pregnancy.20 However, this study
Table 4. Optimal Accuracy of CGM Sensor Data
n (%) on day wearing CGM device
Optimal accuracy criteriona 1 2 3 4
Paired sensor–meter readings�2 14 (51.8) 4 (14.8) 4 (19.1) 14 (51.9)3 9 (33.3) 6 (22.2) 10 (38.5) 6 (22.2)�4 4 (14.8) 17 (63) 11 (42.2) 7 (25.9)Missing 1
Correlation coefficient<0.79 2 (50) 1 (11.1) 0 0�0.79 2 (50) 8 (88.9) 6 (100) 2 (100)Missing 23 18 21 25
Mean absolute difference�28 24 (96) 24 (96) 25 (100) 20 (100)�29 1 94) 1 (4)Missing 2 2 2 7
Use clinical judgment 19 (70.4) 5 (18.5) 6 (22.2) 13 (48.1)
aThe CGM software calculates the paired sensor-meter readings, correlation coefficient, and meanabsolute difference data. The above categories are displayed on the CGM sensor report for each day thesensor is worn.
Table 5. CGM Teaching Events
n (%) on day wearing CGM deviceNumber of teachingevents on CGMgraphs per daya 1 2 3 4
Exercise0 18 (66.7) 8 (29.6) 9 (33.3) 14 (51.9)1 7 (25.9) 13 (48.1) 13 (48.1) 12 (44.4)2 2 (7.4) 4 (14.8) 4 (14.8) 1 (3.7)3 1 (3.7) 1 (3.7)4 1 (3.7)
Diet0 10 (37) 2 (7.4) 5 (18.5) 8 (29.6)1 15 (55.6) 6 (22.2) 6 (22.2) 12 (44.4)2 1 (3.7) 14 (51.9) 10 (37) 6 (22.2)3 1 (3.7) 5 (18.5) 6 (22.2)4 1 (3.7)
aA dietary-teaching event was defined as a glucose excursion (apeak change in glucose level of> 20mg=dL) in response to a mealand=or two meals with glucose excursions of differing magnitudes(in mg=dL). An exercise-teaching event was defined as (1) a declinein glucose levels following a bout of self-reported exercise or anexercise event marked on the CGM graph or (2) increases in glucoselevels following sedentary behavior.
CGM ACCEPTABILITY, FEASIBILITY, AND USES 45
identified many opportunities for teaching non–insulin-usingindividuals with T2DM about the influence of diet and exer-cise on glucose levels. Although these participants weregenerally sedentary, several CGM graphs showed decreasedglucose levels after exercise. These observations are consistentwith reports that moderate exercise significantly reducesblood glucose concentration in individuals with T2DM.21,22
One study showed that a single bout of moderate exerciseimproved glycemic levels for at least 24 h in obese individualswith T2DM.22 These data further support using CGM to de-tect changes in glucose levels in response to exercise, thusproviding opportunities for counseling.
Participants’ CGM graphs also showed glucose levelchanges in response to meals, particularly after breakfast orsupper. Similarly, in another study dietary glycemic excur-sions were observed after meals on CGM graphs of individ-uals with T2DM.23 Glucose levels in that study wereexamined 4h after meals (postprandial) and at all other times(interprandial) before and after an 18-day calorie-restricteddiet. Caloric restriction significantly improved interprandialhyperglycemia but did not affect postprandial glucose ex-cursions after breakfast.23 CGM data may provide opportu-nities for developing individualized treatment plans,including the content and timing ofmeals and exercise. Futurestudies are needed to determine if behavior change followingcounseling is evident on a repeat CGM study. Moreover,CGM tracings may reveal that behavior changes are insuffi-cient to control glucose levels, and further research is neededto determine whether CGM studies might be used to counselindividuals with T2DM on the necessity of initiating insulintherapy. Lastly, CGM devices with non-blinded, real-timedisplays might bemore effective in changing diet and exercise
behavior because individuals can immediately see the resultsof their behaviors andmake instantaneous changes. To date, itis unknown whether individual real-time decision-makingversus retrospective counseling is more effective at changingdiet and exercise behaviors in non–insulin-using individualswith T2DM.
Using CGM in older individuals with T2DM raised atechnology-related consideration not found in younger indi-viduals with T2DM. Older participants had difficulty re-membering to enter events such as meals and exercise into theCGM device. However, most participants kept an accuratepaper log of these events, which were easily transferred to theCGM graphs for teaching purposes. To date, the accuracy ofpaper logs versus the accuracy of entering events into theCGM device has not been reported in this population. Mostimportantly, however, all participants reported understand-ing the CGM graphs regardless of their age.
The optimal accuracy of glucose data on CGM reports re-vealed two common problems in participants with T2DM:narrow range of glucose concentrations and insufficientSMBG values entered. Non–insulin-using individuals withT2DM, unlike those with type 1 diabetes, may not have glu-cose levels that vary more than 100mg=dL, as needed to cal-culate correlation coefficients between interstitial and bloodglucose concentrations. Therefore, researchers and clinicianscan expect to see a majority of CGM reports with ‘‘N=A’’ nextto correlation coefficients. Another problem was participantsentering fewer than three SMBG readings into CGM devices,which occurred most frequently on the first and last weardays, resulting in a ‘‘use clinical judgment’’ warning. Olderindividuals with T2DM entered fewer SMBG readings thanyounger participants. A similar problem was reported in an-
7070
140140
0
Time of Day
Meal and long-actingmedication
Glucose levels elevateafter breakfast
3:00 AM 6:00 AM 9:00 AM 12:00 PM 3:00 PM 6:00 PM 9:00 PM
100
200
Glu
cose
- m
g/dL
300
400
Glucose levels decreaseafter physical activity
Meal following activity haslower glucose elevation
Meal and exerciseExercise
70
140
Paired Meter ValueUnpaired Meter Value
Sensor ValueMeal
InsulinExercise
OtherTime Change (From)
Time Change (To)Legend
FIG. 1. CGM teaching events. Day 2 of CGM depicts glucose level decrease following physical activity in a 58-year-oldwhite man: physical activity=exercise ( ), meal (^), long-acting medication ( ), and SMBG ( ).
46 ALLEN ET AL.
other study of individuals with type 1 and type 2 diabetes butwas resolved by educating participants to enter more dailyglucose values.24 However, older participants were not re-ported to have more difficulty using the CGM device.24 Si-milarly, older adults (66� 6 years) with T2DM experiencemore technological difficulties learning continuous insulininfusion therapy25 than middle-age adults (55� 10 years).26
Interpretability of CGM graphs in the present study was notcompromised, but future studies might consider follow-upphone calls on day 1 to reinforce written instructions anddecrease the number of ‘‘use clinical judgment’’ warnings onthe CGM accuracy report.
Most participants were willing to wear the CGM deviceagain and overall tolerated the procedure well. However,some reported minor skin irritation and discomfort, and onereported pain at the sensor site. This finding echoes a reportthat eight of 70 patients experienced discomfort at CGMsensor sites.25 Although participants should be prepared forpossible discomfort at sensor sites, they can be reassured thatsuch discomfort has generally been transitory and insufficientto deter individuals’ willingness to wear the CGM deviceagain.
Some problems identified in this study will be eliminated bynewer technology, such as the CGMS� iPro (Medtronic). Thisnewer technology uses the same sensor, which is attached to aquarter-sized recorder instead of the cumbersome cable andmonitor of the original CGM. Therefore, many wearing issuesidentified in this study (i.e., showering and sleeping with themonitor) will be eliminated. Furthermore, there are no alarmsfor wearers to manage. At least three or four SMBG readingsper day must still be obtained, but this information is enteredinto software by clinicians=researchers along with events on
the log sheet when the unit is downloaded. Although this newtechnology eliminates someproblems associatedwith the olderCGMdevice, our findings suggest emphasizing towearers thatthey must enter at least three SMBG values every day thesensor is worn and to avoid entering SMBG values when glu-cose levels are rapidly changing. Furthermore, individualswith T2DM and=or a limited range of glucose concentrationwill likely show ‘‘N=A’’ correlation coefficients, which will notaffect interpretability of data.
CGM technology offers many opportunities to counsel in-dividualswith T2DMon strategies to lower glucose levels andimprove self-management behaviors. Such technology offersT2DM patients personalized visual data that may be effectiveat communicating the need to change life-style behaviors.
Acknowledgments
This study was supported by grants F31 NR008818-01A1and T32NR008346-05 from the National Institutes of Health.Medtronic Minimed provided a small equipment grant, andBio-Rad Laboratories provided all A1c assays.We are gratefulto Claire Baldwin for her editorial assistance.
Author Disclosure Statement
No competing financial interests exist.
References
1. Food and Drug Administration: Food and Drug Adminis-tration Summary of Safety and Effectiveness Data for Con-tinuous Glucose Monitoring System (CGMS). http:==fda.gov=cdc (accessed January 11, 2003).
7070
140140
70
140
0
Time of Day
Paired Meter Value
Middle of the night snack-sandwich and muffin
Unpaired Meter Value
3:00 AM 6:00 AM 9:00 AM 12:00 PM 3:00 PM 6:00 PM 9:00 PM
100
200
Glu
cose
- m
g/dL
300
400
Sensor ValueMeal
InsulinExercise
OtherTime Change (From)
Time Change (To)Legend
Highest glucose levelsof the day from highcarbohydrate snack
Glucose levels decreaseafter physical activity
Breakfastand tennis
Candy andfast food
Spaghettiand bread
Glucose levels rise fromhigh carbohydrate
FIG. 2. CGM teaching events: dietary. Day 3 of CGM depicts glucose level increases with high carbohydrate meals andsome lowering of glucose levels following physical activity in a 47-year-old African American woman: physical activi-ty=exercise ( ), meal (^), long-acting medication ( ), and SMBG ( ).
CGM ACCEPTABILITY, FEASIBILITY, AND USES 47
2. Garg S, Zisser H, Schwartz S, Bailey T, Kaplan R, EllisS, Jovanovic L: Improvement in glycemic excursionswith a transcutaneous, real-time continuous glucose sen-sor: a randomized controlled trial. Diabetes Care 2006;29:44–50.
3. Weinstein RL, Schwartz SL, Brazg RL, Bugler JR, Peyser TA,McGarraugh GV: Accuracy of the 5-day FreeStyle Navigatorcontinuous glucose monitoring system: comparison withfrequent laboratory reference measurements. Diabetes Care2007;30:1125–1130.
4. Weinzimer SA, DeLucia MC, Boland EA, Steffen A, Tam-borlane WV: Analysis of continuous glucose monitoringdata from non-diabetic and diabetic children: a tale of twoalgorithms. Diabetes Technol Ther 2003;5:375–380.
5. Bode B, Gross K, Rikalo N, Schwartz S, Wahl T, Page C,Gross T, Mastrototaro J: Alarms based on real-time sensorglucose values alert patients to hypo- and hyperglycemia:the Guardian continuous monitoring system. DiabetesTechnol Ther 2004;6:105–113.
6. Feldman B, Brazg R, Schwartz S, Weinstein R: A continuousglucose sensor based on wired enzyme technology—resultsfrom a 3-day trial in patients with type 1 diabetes. DiabetesTechnol Ther 2003;5:769–779.
7. Gross TM, Bode BW, Einhorn D, Kayne DM, Reed JH, WhiteNH, Mastrototaro JJ: Performance evaluation of the Mini-Med continuous glucose monitoring system during patienthome use. Diabetes Technol Ther 2000;2:49–56.
8. Maran A, Crepaldi C, Tiengo A, Grassi G, Vitali E, PaganoG, Bistoni S, Calabrese G, Santeusanio F, Leonetti F, RibaudoM, Di Mario U, Annuzzi G, Genovese S, Riccardi G, PrevitiM, Cucinotta D, Giorgino F, Bellomo A, Giorgino R, PosciaA, Varalli M: Continuous subcutaneous glucose monitoringin diabetic patients: a multicenter analysis. Diabetes Care2002;25:347–352.
9. Potts RO, Tamada JA, Tierney MJ: Glucose monitoring byreverse iontophoresis. Diabetes Metab Res Rev 2002;18(Suppl 1):S49–S53.
10. Allen NA, Fain JA, Braun B, Chipkin SR: Continuous glu-cose monitoring improves physical activity behaviors of in-dividuals with with type 2 diabetes: a randomized clinicaltrial. Diabetes Res Clin Pract 2008;80:371–379.
11. Allen NA, Fain JA, Braun B, Chipkin SR: Feasibility andacceptability of continuous glucose monitoring and acceler-ometer technology in exercising individuals with type 2 di-abetes. J Clin Nurs 2009;18:373–383.
12. Gross TM, Mastrototaro JJ: Efficacy and reliability of theContinuous Glucose Monitoring System. Diabetes TechnolTher 2000;2(Suppl 1):S19–S26.
13. Rebrin K, Steil GM, Van Antwerp WP, Mastrototaro JJ:Subcutaneous glucose predicts plasma glucose independentof insulin: implications for continuous monitoring. Am JPhysiol 1999;277:E561-E571.
14. Freedson PS, Melanson E, Sirard J: Calibration of the Com-puter Science and Applications, Inc. accelerometer. Med SciSports Exerc 1998;30:777–781.
15. Mastrototaro JJ: The MiniMed Continuous Glucose Mon-itoring System. Diabetes Technol Ther 2000;2(Suppl 1):S13–S18.
16. Bode BW, Gross TM, Thornton KR, Mastrototoro JM: Con-tinuous glucose monitoring used to adjust diabetes therapy
improves glycosylated hemoglobin: a pilot study. DiabetesRes Clin Pract 1999;46:183–190.
17. Deiss D, Kordonouri O, Hartmann R, Hopfenmuller W,Lupke K, Danne T: Treatment with insulin glargine reducesasymptomatic hypoglycemia detected by continuous sub-cutaneous glucose monitoring in children and adolescentswith type 1 diabetes. Pediatr Diabetes 2007;8:157–162.
18. Kaufman FR, Gibson LC, Halvorson M, Carpenter S, FisherLK, Pitukcheewanont P: A pilot study of the continuousglucose monitoring system: clinical decisions and glycemiccontrol after its use in pediatric type 1 diabetic subjects.Diabetes Care 2001;24:2030–2034.
19. Zick R, Petersen B, Richter M, Haug C, Group SS: Com-parison of continuous blood glucose measurement withconventional documentation of hypoglycemia in patientswith type 2 diabetes on multiple daily insulin injectiontherapy. Diabetes Technol Ther 2007;9:483–492.
20. Murphy HR, Rayman G, Duffield K, Lewis KS, Kelly S, JohalB, Fowler D, Temple RC: Changes in the glycemic profiles ofwomen with type 1 and type 2 diabetes during pregnancy.Diabetes Care 2007;30:2785–2791.
21. Kang J, Kelley DE, Robertson RJ, Goss FL, Suminski RR,Utter AC, Dasilva SG: Substrate utilization and glucoseturnover during exercise of varying intensities in individualswith NIDDM. Med Sci Sports Exerc 1999;31:82–89.
22. MacDonald AL, Philp A, Harrison M, Bone AJ, Watt PW:Monitoring exercise-induced changes in glycemic control intype 2 diabetes. Med Sci Sports Exerc 2006;38:201–207.
23. Colette C, Ginet C, Boegner C, Benichou M, Pham TC,Cristol JP, Monnier L: Dichotomous responses of inter andpostprandial hyperglycaemia to short-term calorie restric-tion in patients with type 2 diabetes. Eur J Clin Investig2005;35:259–264.
24. Chico A, Vidal-Rios P, Subira M, Novials A: The ContinuousGlucose Monitoring System is useful for detecting unrec-ognized hypoglycemias in patients with type 1 and type 2diabetes but is not better than frequent capillary glucosemeasurements for improving metabolic control. DiabetesCare 2003;26:1153–1157.
25. Raskin P, Bode BW, Marks JB, Hirsch IB, Weinstein RL,McGill JB, Peterson GE, Mudaliar SR, Reinhardt RR: Con-tinuous subcutaneous insulin infusion and multiple dailyinjection therapy are equally effective in type 2 diabetes: arandomized, parallel-group, 24-week study. Diabetes Care2003;26:2598–2603.
26. Herman WH, Ilag LL, Johnson SL, Martin CL, Sinding J, AlHarthi A, Plunkett CD, LaPorte FB, Burke R, Brown MB,Halter JB, Raskin P: A clinical trial of continuous subcuta-neous insulin infusion versus multiple daily injections inolder adults with type 2 diabetes. Diabetes Care 2005;28:1568–1573.
Address reprint requests to:Nancy A. Allen, Ph.D.
Yale University100 Church Street South
P.O. Box 9740New Haven, CT 06536-0740
E-mail: nancy.a.allen@yale.edu
48 ALLEN ET AL.
Sustained Efficacy of Continuous Subcutaneous InsulinInfusion in Type 1 Diabetes Subjects with Recurrent
Non-Severe and Severe Hypoglycemia and HypoglycemiaUnawareness: A Pilot Study
Marga Gimenez, M.D., Merce Lara, B.N., and Ignacio Conget, M.D., Ph.D.
Abstract
Background: This study evaluated the effect of CSII on hypoglycemia awareness and on glucose profile in type 1diabetes (T1D) subjects with repeated non-severe or severe hypoglycemia (NS or SH, respectively).Methods: We included subjects (1) older than 18 years, (2) with T1D duration of >5 years, (3) on multiple dosesof insulin, and (4) without micro- or macrovascular complications and more than four NS events per week (in thelast 8 weeks) and more than two SH events (in the last 2 years). NS/SH episodes and hypoglycemia awarenesswere evaluated. A 72-h continuous glucose monitoring (CGM) was performed before continuous subcutaneousinsulin infusion (CSII). A hypoglycemia-induced test was used to evaluate each patient’s symptoms ineuglycemia/hypoglycemia. Quality of life (QoL) was also evaluated. After 6, 12, and 24 months, all the subjectswere reevaluated.Results: Twenty subjects were included (34.0� 7.5 years old, 12 women, A1c 6.7� 1.1%, 16.2� 6.6 years ofdiabetes’ duration). At baseline, 19 out of 20 subjects displayed hypoglycemia unawareness, which diminishedsignificantly during the follow-up (3 out of 20). NH episodes per week diminished from 5.40� 2.09 at baseline to2.75� 1.74 at the end of the follow-up (P< 0.001). SH episodes fell from 1.25� 0.44 per subject-year to 0.05� 0.22after 24 months (P< 0.001). Hemoglobin A1c remained unaltered. With CGM, the percentage of values within70–180mg/dL increased (53.2� 11.0% to 60.3� 17.1%, P¼ 0.13), and the percentage of values <70mg/dL de-creased (13.7� 9.4% to 9.1� 5.2%, P¼ 0.07), after 24 months. Mean amplitude of glycemic excursions diminishedafter 24 months of CSII (136� 28mg/dL to 115� 19mg/dL; P< 0.02). An improvement in all the aspects of QoLwas observed. The basal alteration in symptom response to an induced hypoglycemia improved after 24 monthsof initiating CSII leading to a response indistiguishable from that observed in a control group of subjects withT1D without repeated NH and SH.Conclusions: CSII prevents hypoglycemic episodes, improves hypoglycemia awareness, and ameliorates gly-cemic profile in T1D subjects with repeated NS/SH. Its use is also associated with an improvement in diabetesQoL.
Introduction
Intensive insulin therapy significantly reduces the risk ofcomplications in subjects with type 1 diabetes (T1D) and
represents the standard treatment from the onset of the dis-ease.1 However, this therapy is unfailingly associated with ahigher risk of non-severe and severe hypoglycemia (NS andSH, respectively) episodes.2 Iatrogenic hypoglycemia causesrecurrent morbidity in most people with T1D. Likewise, it isan obstacle to the maintenance of euglycemia over a lifetime
using intensive insulin therapy and thus precludeseuglycemia’s long-term benefits.3,4
Frequent and repeated episodes of hypoglycemia in sub-jects with T1D almost invariably result in a reduced ability/failure to recognize hypoglycemia symptoms and signs atthe physiological normal threshold (*55mg/dL). This syn-drome of hypoglycemia unawareness frequently occurs inT1D, and the lack of warning symptoms puts patients at ahigh risk for SH because they are unable to take measures toprevent it.5
Endocrinology and Diabetes Unit, Institute of Biomedical Investigations August Pi i Sunyer; CIBER of Diabetes and Associated MetabolicDiseases; and Hospital Clınic i Universitari, Barcelona, Spain.
DIABETES TECHNOLOGY & THERAPEUTICSVolume 12, Number 7, 2010ª Mary Ann Liebert, Inc.DOI: 10.1089/dia.2010.0028
49
In the same way a history of hypoglycemia induces un-awareness, meticulous prevention of it can reverse hypogly-cemia unawareness. Thus, it is essential that intensive insulintherapy for T1D is designed not only to maintain near-normoglycemia, but also to prevent and minimize the burdenof hypoglycemia.6–9 Although such a goal is feasible, andeven including a proper blood glucose monitoring, the use ofindividualized blood glucose targets, and the implementationof specific education programs, there is no consensus onwhich is the best rational plan of insulin therapy.10–12 A veryrecent meta-analysis including recent randomized clinicaltrials found that the use of continuous subcutaneous insulininfusion (CSII) is not associatedwith a significant difference inhypoglycemia risk.13
In this context, the use of continuous glucose monitoring(CGM) systems and the evaluation of hypoglycemia aware-ness could help us to identify these subjects and to decide on asafe approach to optimize the metabolic control for them.14
The aim of our study was to evaluate the effect of CSII onthe frequency of hypoglycemia, hypoglycemia unawareness,and continuous glucose profile characteristics in a group ofT1D subjects with repeated NS and SH.
Patients and Methods
We conducted a prospective study including patientsconsecutively with the following criteria: (1)>18 years old, (2)T1D duration >5 years, (3) on conventional insulin treatmentusing multiple doses of insulin (MDI) including rapid-actinganalogs (lispro or aspart) as prandial insulins and glargine asbasal insulin, and (4) with an absence of micro- or macro-vascular complications and presenting more than four NSevents per week (in the last 8 weeks) and more than two SHevents (in the last 2 years). Absence of microalbuminuria wasassured bymeasuring the 24-h urinary albumin excretion rate(last three samples <20 mg/min). The presence of cardiovas-cular disease was ruled out considering the following: nohistory of cardiovascular disease events, no electrocardio-gram alterations, normal stress echocardiography, and anankle-brachial index >0.9. The initiation of CSII treatmentwas proposed to all subjects following the indications andcriteria of reimbursement from the Catalan National HealthService authorities. Contraindications for CSII were ruled outin all subjects, mainly including inability to perform self-management of an intensive insulin therapy program, evi-dence of poor treatment compliance and failure to attendoutpatient clinics, and evidence of a disabling psychiatricdisorder.15 The study was approved by the Hospital Clınic iUniversitari (Barcelona, Spain) Ethics Committee, andinformed consent was obtained from all the patients. Thestudy has been performed in accordance with the ethicalstandards laid out in an appropriate version of the Declara-tion of Helsinki.
Within 1 month before initiation of CSII, data on age,gender, duration of the disease, body mass index, renalfunction, and hemoglobin A1c (HbA1c) (Menarini Diag-nostici, Florence, Italy) (normal range, 3.5–5.5%; where3.5%¼ 20.2mmol/mol International Federation of ClinicalChemistry¼ 4.0% Diabetes Control and Complications Trialand 5.5%¼ 42.1mmol/mol International Federation of Clin-ical Chemistry¼ 6.0% Diabetes Control and ComplicationsTrial) were recorded. Patients were questioned regarding the
number of hypoglycemic episodes they presented. NS andSH were defined following the American Diabetes Associa-tion criteria.16 SH events were defined as those associatedwith neuroglycopenia severe enough to require treatmentfrom a third party. The questionnaire of Clarke et al.17 wasused to evaluate hypoglycemia awareness. CGM for 72 husing the CGMS� System Gold� from Medtronic Minimed(Northridge, CA, USA) was recorded within 2 weeks beforeinitiation of CSII in order to describe the glucose profile.Glucose variability was evaluated calculating mean ampli-tude of glucose excursions (MAGE) designed by Serviceet al.18 from continuous sensor readings. MAGE over 24 his the mean of the absolute differences between glucosepeak and nadir values in excess of at least 1 SD of the meanglucose.
Before initiation of CSII a hypoglycemia-induced test wasperformed as described previously.19 Patients answered theHypoglycemia Symptoms Score Questionnaire first after30min of euglycemia (80–120mg/dL) and then after 30min ofbeing in hypoglycemia (45–55mg/dL).20 The test scores be-tween the two states were compared, and the variation wasexpressed in a percentage. The same experimental protocolwas performed in a control group of 20 subjects with T1D andsimilar characteristics (age, gender, disease duration, treat-ment, and absence of micro- or macrovascular complications)but with fewer than four NS events per week (in the last8weeks) and no SH episodes in order to compare the responseto hypoglycemia.
Quality of life (QoL) assessment was performed using twodifferent questionnaires: the Diabetes Quality-of-Life (DQoL)questionnaire, in which higher scores relate to deterioration inQoL, and the SF-12 health survey questionnaire.
All the subjects included in our study received our specifictherapeutic education program for patients beginning CSII.They received a diet adjusted to their age and body massindex, and insulin doses were adjusted to maintain fastingand preprandial glucose levels between 90 and 130mg/dL,postprandial below 180mg/dL, and at bedtime between 100and 180mg/dL, based on four to six daily capillary blooddeterminations. Glucose targets and capillary glucose deter-minations were comparable to those used with MDI. Patientswere encouraged to avoid values<70mg/dL. The same teamsaw patients as required during the therapeutic educationprogram and every 2–3 months thereafter until 24 months offollow-up. Patients were instructed on glucose goals andself-monitoring glucose control when necessary. All patientswere using pumps with preprogrammable variable basalrates. After 6, 12, and 24 months of follow-up, all the subjectswere evaluated for the number of hypoglycemic episodes(NS and SH) and with the questionnaire of Clarke et al.17 Atthe end of the study, results obtained after 72 h of CGM, theHypoglycemia Symptoms Score questionnaire during thehypoglycemia-induced test, and results of the DQoL andSF-12 questionnaires were again obtained.
Results are presented as mean� SD values. Comparisonswere performed using a paired Student’s t test or an analysisof variance for repeated measurements. Comparisons be-tween proportions were made with a w2 test. A value ofP< 0.05 was considered statistically significant. All statisticalcalculations were performed by the Statistical Package forSocial Science (version 14.0) for personal computers (SPSS,Inc., Chicago, IL).
50 GIMENEZ ET AL.
Results
A total of 20 subjects with NS and SH were included in thestudy, and their clinical and metabolic characteristics atbaseline are shown in Table 1.
At the time of the inclusion in the study, 19 subjects (onewas non-classified) were shown to have hypoglycemia un-awareness according to the Clarke test (score: �4¼unawareness, 3¼non-classified, �2¼ awareness), scoring onaverage 5.45� 1.19. Progressively, we observed a decrease inthe Clarke test score: 3.70� 1.65, 2.74� 1.06, and 1.6� 2.03after 6, 12, and 24 months of follow-up, indicating an im-provement in the hypoglycemia unawareness towards nor-mal awareness (P< 0.001 for baseline vs. 24 months). At theend of the follow-up, only three of the 20 subjects were clas-sified as having hypoglycemia unawareness. In absoluteterms, the evolution of hypoglycemia awareness categories isshown in Figure 1.
The mean number of episodes of NH per week progres-sively diminished from 5.40� 2.09 at baseline to 4.60� 2.33,3.07� 1.39, and 2.75� 1.74 after 6, 12, and 24 months, re-spectively (P< 0.001 for baseline vs. 24 months). When thenumber of SH episodes were analyzed, they fell from
1.25� 0.44 per subject year at baseline to 0.05� 0.22 at the endof the follow-up (P< 0.001). Additionally, HbA1c remainedunaltered during the follow-up: 6.6� 1.0%, 6.7� 0.9%,6.7� 0.8%, and 6.3� 0.9% for baseline, 6, 12 and 24 months,respectively.
Considering data obtained from the CGMS, after the 24-month follow-up, the percentage of valueswithin target levels(70–180mg/dL) increased (53.2� 11.0% to 60.3� 17.1%,P¼ 0.13), and the percentage of values below 70mg/dLdecreased (13.7� 9.4% to 9.1� 5.2%, P¼ 0.07); however, thesetendencies did not reach statistical significance. MAGEdiminished after 24 months of CSII from 136� 28 to115� 19mg/dL at 24 months of follow-up (P< 0.02).
At baseline, subjects with NS and SH scored 31.6� 16.4 onthe Hypoglycemia Symptoms Score Questionnaire duringhypoglycemia, representing a rise of 52% in comparison toeuglycemia (21.0� 3.15). At 24 months after initiating CSII,the score was 62.3� 23.6 (P< 0.001, in comparison to base-line), an increase of 196% (P< 0.001, in comparison to base-line) with respect to euglycemia (21.05� 3.15). These resultswere compared with those obtained in the control group(33.5� 8.7 years old; 12women; 14.0� 6.5 years of duration ofthe disease; all of them on MDI; HbA1c¼ 6.7� 0.7%; differ-ence not significant) under the same conditions of glycemialevels in the euglycemia and hypoglycemia periods. The scoreon the Hypoglycemia Symptoms Score questionnaire was54.5.6� 18.4 during hypoglycemia, representing a rise of163% in comparison to euglycemia (20.5� 1.9). This responsewas not different from that observed in T1D subjects with NSand SH after 24 months of treatment with CSII.
Regarding QoL outcomes, a significant improvement in allthe aspects evaluated by DQoL test was observed. This wasalso the case for the results obtained by the SF-12 health sur-vey questionnaire (Table 2).
Discussion
Our study shows that the use of CSII in T1D subjects with ahistory of recurrent hypoglycemia and SH leads to a persistent
Table 1. Baseline Characteristics of the Study Group
Characteristic Value
Number of subjects 20Age (year) 34.0� 7.5Gender (M/W) 8/12Duration of diabetes (years) 16.2� 6.6BMI (kg/m2) 24.3� 3.1On MDI treatment (%) 100HbA1c (%) 6.7� 1.1Creatinine (mg/dL) 0.8� 0.1UAE (mg/24 h) 6.5� 2.5
Data are mean� SD values. BMI, body mass index; HbA1c,hemoglobin A1c; MDI, multiple daily injections; M/W, men/women; UAE, urinary albumin excretion.
0
5
10
15
20
25
0 6 12 24
Months
No
of
sub
ject
s in
eac
h c
ateg
ory
Unawareness
Non-classified
Awareness
FIG. 1. Number of subjects in each category of the Clarke test during the follow-up.
CSII EFFICACY IN REPEATED-HYPOGLYCEMIA T1D 51
diminution in number of hypoglycemic episodes, aswell as to asustained improvement in hypoglycemia awareness, eventhough there were no change in HbA1c, and the percentageof glycemic values within target levels and below 70mg/dLremained without significant change.
Hypoglycemia in T1D is the consequence of the non-physiological replacement of insulin even when using thetheoretically physiological basal-bolus approach. Since theDiabetes Control and Complications Trial results, there is nodoubt that intensive insulin therapy effectively delays theonset and slows the progression of diabetic retinopathy, ne-phropathy, and neuropathy in patients with T1D.1,2 However,the price to pay is an increase in NH and SH episodes (two- tothreefold). Mild hypoglycemia, if recurrent, induces un-awareness of hypoglycemia, which impairs glucose counter-regulation and predisposes to SH. A very recent survey of alarge hospital-based population confirmed that there is stilla significant proportion of people with T1D (around 20%)who suffer from hypoglycemia unawareness.21 Thus, despitemodern patient education and improvements in thestrengthening of insulin therapy, hypoglycemia and hypo-glycemia unawareness are still far from solved in T1D.
In patients with repeated hypoglycemia and hypoglycemiaunawareness, the meticulous prevention of hypoglycemicepisodes can reverse the physiological abnormalities associ-ated with this condition.22–24 In order to create more suc-cessful clinical management of T1D, the implementation of amore physiological pattern of insulin replacement therapy,including the use of real-time CGM, as has been demonstratedin some long-term studies, is necessary.25–30 However, there isno consensus on which, if any, should be the preferable,suitable, and efficient approach.
In our study, probably by effectively diminishing thenumber of hypoglycemic episodes, the use of CSII was asso-ciatedwith a shift from abnormal perception of hypoglycemiato a normal awareness. This is true, not only in experimentalconditions of a controlled-induced hypoglycemia but also inclinical assessment using specific tools. It should be under-lined that these results were obtained without a deteriorationof glycemic control in terms of HbA1c. Furthermore, the re-sults provided from CGM are in agreement with these find-ings showing a tendency to a diminishing of values ofglycemia <70mg/dL, an increase in the percentage of valueswithin target levels, and a significant improvement in thevariability in glucose profile. In addition to this, it should benoted that all these beneficial effects of CSII come not with a
detrimental effect but with an improvement in all aspects ofquality of life.
Fatourechi et al.13 in a very recent systematic review andmeta-analysis commissioned by the Hypoglycemia TaskForce of The Endocrine Society examined the best availableevidence about the use of CSII and MDI as intensive insulinreplacement therapies and the risk of hypoglycemia. Includ-ing 15 recent randomized control trials the authors concludedthat CSII was associated with a slightly lower HbA1c withouta significant difference in terms of hypoglycemia. Never-theless, the investigators recognized that these results camefrom patients at a low risk of hypoglycemia and that thereforethey cannot be fully extrapolated in patients with recurrentSH or hypoglycemia unawareness.
In absolute terms, and acknowledging the differencesbetween both studies, the magnitude of restoration ofhypoglycemia awareness achieved in our study using CSII isquite similar to that observed by Leitao et al.31 using islettransplantation. However, it does not seem clear to us if theimprovement observed in hypoglycemia awareness in thatstudy is really due to a diminishing of number of hypogly-cemic episodes as data on that subject are not described intheir article.
We are well aware of the limitations of our study. Mainly,there is no control group, and it includes a relatively smallnumber of high-risk subjects for hypoglycemia in whom thebeneficial effect of CSII option could be exacerbated. How-ever, prior to the initiation of CSII, all of our patients had beenincluded in our specific diabetes education program for pa-tients receiving conventional intensive insulin treatment andpoor metabolic control with no benefit with regard to hypo-glycemia. Considering the very disabling and labile profile ofour patients and in light of the indications and criteria fromthe Catalan National Health Service authorities and guide-lines, we did not consider maintaining MDI therapy to anyfurther extent. In this topic, very recently the new guidancefrom the National Institute for Health and Clinical Excellenceon CSII for the treatment of diabetes mellitus recommendedthis type of therapy as a treatment option in T1D subjects whoattempt to achieve target HbA1c values with intensive insulintherapy but experience repeated and unpredictable occur-rences of hypoglycemia (www.nice.org/uk/TA57).
In summary, CSII may persistently prevent hypoglycemicepisodes, improve hypoglycemia awareness, and amelioratethe glycemic profile in T1D subjects with repeated SH.Moreover, its use is associated with an improvement in dia-betes QoL aspects.
Acknowledgments
We are indebted to all of those involved at any time in thespecific therapeutic education program for patients beginningCSII at the Endocrinology and Diabetes Unit of the HospitalClınic i Universitari of Barcelona (colloquially called ‘‘Pro-grama Bombas’’). M.G. is the recipient of a grant from theHospital Clınic i Universitari of Barcelona. This work wassupported in part by a grant (PI060250) from the ‘‘Ministeriode Sanidad y Consumo’’ of Spain. Medtronic Iberica spon-sored this work, in part.
Author Disclosure Statement
No competing financial interests exist.
Table 2. Quality of Life Outcomes After 24 Months
of Using Continuous Subcutaneous Insulin Infusion:
Scores at Baseline and After 24 Months of Follow-Up
Baseline 24 months P
DQoL questionnaireSatisfaction 36.0� 6.4 28.8� 5.5 <0.001Impact of treatment 33.6� 7.5 27.4� 6.0 <0.002Social/vocational worrying 13.3� 4.1 11.5� 3.8 <0.05Diabetes-related issuesworrying
10.1� 2.6 8.0� 1.9 <0.01
SF-12 health surveyquestionnaire
34.1� 3.9 37.0� 2.9 <0.01
DQoL, Diabetes Quality of Life.
52 GIMENEZ ET AL.
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Address correspondence to:Ignacio Conget, M.D., Ph.D.
Endocrinology and Diabetes UnitInstitute of Biomedical Investigations August Pi i Sunyer
Villarroel 17008036 Barcelona, Spain
E-mail: iconget@clinic.ub.es
CSII EFFICACY IN REPEATED-HYPOGLYCEMIA T1D 53
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