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Accuracy and Precision of Four Value-Added Blood Glucose Meters: the Abbott Optium, the DDI Prodigy, the HDI True Track, and the HypoGuard Assure Pro

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This study compared the accuracy and precision of four value-added glucose meters. Finger stick glucose measurements in diabetes patients were performed using the Abbott Diabetes Care (Alameda, CA) Optium, Diagnostic Devices, Inc. (Miami, FL) DDI Prodigy, Home Diagnostics, Inc. (Fort Lauderdale, FL) HDI True Track Smart System, and Arkray, USA (Minneapolis, MN) HypoGuard Assure Pro. Finger glucose measurements were compared with laboratory reference results. Accuracy was assessed by a Clarke error grid analysis (EGA), a Parkes EGA, and within 5%, 10%, 15%, and 20% of the laboratory value criteria (chi2 analysis). Meter precision was determined by calculating absolute mean differences in glucose values between duplicate samples (Kruskal-Wallis test). Finger sticks were obtained from 125 diabetes patients, of which 90.4% were Caucasian, 51.2% were female, 83.2% had type 2 diabetes, and average age of 59 years (SD 14 years). Mean venipuncture blood glucose was 151 mg/dL (SD +/-65 mg/dL; range, 58-474 mg/dL). Clinical accuracy by Clarke EGA was demonstrated in 94% of Optium, 82% of Prodigy, 61% of True Track, and 77% of the Assure Pro samples (P < 0.05 for Optium and True Track compared to all others). By Parkes EGA, the True Track was significantly less accurate than the other meters. Within 5% accuracy was achieved in 34%, 24%, 29%, and 13%, respectively (P < 0.05 for Optium, Prodigy, and Assure Pro compared to True Track). Within 10% accuracy was significantly greater for the Optium, Prodigy, and Assure Pro compared to True Track. Significantly more Optium results demonstrated within 15% and 20% accuracy compared to the other meter systems. The HDI True Track was significantly less precise than the other meter systems. The Abbott Optium was significantly more accurate than the other meter systems, whereas the HDI True Track was significantly less accurate and less precise compared to the other meter systems.
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Accuracy and Precision of Four Value-Added Blood
Glucose Meters: the Abbott Optium, the DDI Prodigy,
the HDI True Track, and the HypoGuard Assure Pro
Catherine A. Sheffield, Pharm.D.,
1
Michael P. Kane, Pharm.D., F.C.C.P., B.C.P.S.,
2
Gary Bakst, M.D.,
3
Robert S. Busch, M.D., F.A.C.E.,
3
Jill M. Abelseth, M.D., F.A.C.E.,
3
and Robert A. Hamilton, Pharm.D.
2
Abstract
Purpose: This study compared the accuracy and precision of four value-added glucose meters.
Methods: Finger stick glucose measurements in diabetes patients were performed using the Abbott Diabetes
Care (Alameda, CA) Optium, Diagnostic Devices, Inc. ( Miami, FL) DDI Prodigy
, Home Diagnostics, Inc.
(Fort Lauderdale, FL) HDI True Track Smart System
, and Arkray, USA (Minneapolis, MN) HypoGuard
Assure
Pro. Finger glucose measurements were compared with laboratory reference results. Accuracy was
assessed by a Clarke error grid analysis (EGA), a Parke EGA, and within 5%, 10%, 15%, and 20% of the
laboratory value criteria (w
2
analysis). Meter precision was determined by calculating absolute mean differences
in glucose values between duplicate samples (Kruskal-Wallis test).
Results: Finger sticks were obtained from 125 diabetes patients, of which 90.4% were Caucasian, 51.2% were
female, 83.2% had type 2 diabetes, and average age of 59 years (SD 14 years). Mean venipuncture blood glucose
was 151 mg=dL (SD 65 mg=dL; range, 58–474mg=dL). Clinical accuracy by Clarke EGA was demonstrated in
94% of Optium, 82% of Prodigy, 61% of True Track, and 77% of the Assure Pro samples (P<0.05 for Optium and
True Track compared to all others). By Parke EGA, the True Track was significantly less accurate than the other
meters. Within 5% accuracy was achieved in 34%, 24%, 29%, and 13%, respectively (P<0.05 for Optium,
Prodigy, and Assure Pro compared to True Track). Within 10% accuracy was significantly greater for the
Optium, Prodigy, and Assure Pro compared to True Track. Significantly more Optium results demonstrated
within 15% and 20% accuracy compared to the other meter systems. The HDI True Track was significantly less
precise than the other meter systems.
Conclusions: The Abbott Optium was significantly more accurate than the other meter systems, whereas the
HDI True Track was significantly less accurate and less precise compared to the other meter systems.
Introduction
Self-monitoring of blood glucose (SMBG) is recog-
nized as an integral adjunctive tool for diabetes manage-
ment.
1
SMBG provides for real-time glucose measurements,
which better enable patients and clinicians to adjust diabetes
regimens and reach glycemic targets. Intensive treatment
of type 1 diabetes mellitus, with an emphasis on four-point
SMBG (e.g., preprandial and postprandial glucose monitor-
ing), was shown to significantly lower the risk of diabetes-
related microvascular complications by 50–76% in the
Diabetes Control and Complications Trial.
2
Several other
studies have also provided evidence that SMBG plays a
crucial role in glycemic control and subsequent glycosylated
hemoglobin (A1C) lowering.
3–5
A recent meta-analysis of
SMBG in type 2 diabetes concluded that its use is associated
with significant decreases in A1C for this population.
6
SMBG
complements the use of A1C testing and is endorsed by spe-
cialty organizations to optimize glycemic control.
7,8
Current
recommendations by the American Diabetes Association
(ADA) propose that SMBG be performed at least three times
daily for type 1 and gestational diabetes patients and as clin-
ically necessary for type 2 patients to reach glycemic goals.
7
A recent global consensus conference of diabetes experts
recently recommended that SMBG be used by all patients
with diabetes.
9
1
Department of Pharmacy Practice, Dayton Veterans Administration Medical Center, Dayton, Ohio.
2
Department of Pharmacy Practice, Albany College of Pharmacy and Health Sciences; and
3
The Endocrine Group, LLP, Albany, New York.
DIABETES TECHNOLOGY & THERAPEUTICS
Volume 11, Number 8, 2009
ªMary Ann Liebert, Inc.
DOI: 10.1089=dia.2008.0143
1
DIA-2008-0143-Kane_1P
Type: original-article
DIA-2008-0143-Kane_1P.3D 06/13/09 6:01pm Page 1
The cost of SMBG supplies is a significant barrier for some
patients. Value-added (generic or lower cost) meter blood
glucose testing systems are available to patients as a reduced-
cost alternative to popular name-brand meters and test strips.
Three commonly used value meter systems are the HDI True
Track Smart System
(Home Diagnostics, Inc., Fort Lauder-
dale, FL), the HypoGuard Assure
Pro (Arkray, USA, Min-
neapolis, MN), and the DDI Prodigy
Autocode (Diagnostic
Devices, Inc., Miami, FL). The Abbott Optium(Abbott
Diabetes Care, Alameda, CA) is a newer value meter blood
glucose testing system. To date no direct comparisons of these
meters have been published.
The primary purpose of this study was to compare the
accuracy and precision of finger stick blood glucose mea-
surements obtained with the Abbott Optium, the DDI Prod-
igy Autocode, the HDI True Track, and the HypoGuard
Assure Pro to one another and to a laboratory reference value
obtained via venous puncture. A secondary objective was to
evaluate the relationship of any variation between finger
glucose measurements (compared to venous results) with
regard to time of the patient’s previous meal or insulin ad-
ministration.
Research Design and Methods
Design and methods
Laboratory sheets of adult patients presenting to the phle-
botomy area of this ambulatory care endocrinology practice
were reviewed for identification of patients scheduled for
venipuncture for glucose measurement. After explanation of
the study’s purpose and testing procedure, patient demo-
graphic information (age, gender, and type of diabetes), in-
formation regarding patient use of insulin, and time elapsed
since the patient’s most recently ingested meal was obtained
from consenting adults. The study was approved by the Al-
bany College of Pharmacy (Albany, NY) Institutional Review
Board prior to its initiation, and written informed consent was
obtained prior to each patient’s participation. Pregnant
women and children (individuals under 18 years of age) were
excluded from the study. According to results of previous
brand-name glucose meter accuracy and precision studies,
attainment of zone A results (meter results within 20% of the
standard) using an error grid analysis (EGA) has varied from
67% to 97%.
10
Based upon these data and the fact that Inter-
national Organization for Standardization requirements
mandate a meter accuracy rate of 95% of meter results falling
within 20% of the standard measurement (e.g., venipuncture
results) for glucose concentrations 75 mg=dL,
11
a sample
size of 100 patients would be required to detect a statistical
difference of zone A results of 97% and 85%. A total of 125
diabetes patients were recruited for this study. A nominal
honorarium was offered to assist in patient recruitment.
Consenting adults underwent venipuncture as well as
finger glucose testing. All venipuncture samples were
centrifuged within 15 min of being drawn and were analyzed
for glucose within 2 h of collection. A control solution check
was performed on each meter prior to patient sampling each
day of testing, according to the manufacturers’ instructions.
Within 5 min following venipuncture, duplicate finger blood
glucose measurements were taken from each of four fingers
(in order: pinkie, ring, middle, and index fingers) ipsilateral to
the venipuncture site. Blood samples from the same lance
were used for each set of duplicate tests. Meter sequence was
randomly assigned, and the same investigator (C.A.S.) per-
formed all measurements, according to the manufacturers’
instructions. All finger blood samples were obtained using a
single-use capillary blood sampling device (Unistik
2,
Owen-Mumford, Oxford, UK). Test strips with identical lot
numbers (Abbott Optium, 99135-36 40894; DDI Prodigy,
TD06J223-C22(13); HDI True Track, RG1922; HypoGuard
Assure Pro, 04267B) were used for the study. Results of finger
glucose measurements were compared with the laboratory
reference value obtained via venipuncture (hexokinase=and
glucose-6-phosphate dehydrogenase method [Cobas Integra,
Roche Diagnostics, Indianapolis, IN]). Study meters and
supplies were donated by the manufacturer (Abbott Optium)
or were purchased at a local pharmacy (DDI Prodigy, HDI
True Track, and the HypoGuard Assure Pro).
Clinical and statistical analysis
Accuracy was assessed by comparing the glucose results of
the first finger stick obtained with each meter to the laboratory
reference value. The following methods were used for this
analysis: (1) a Clarke EGA of meter results compared with
venipuncture results, (2) a Parkes EGA of meter results com-
pared with venipuncture results, and (3) a comparison of the
percentage of results obtained with each meter falling within
5%, 10%, 15%, or 20% of the laboratory value (w
2
analysis).
10,12
Meter precision was determined by calculating the absolute
mean percentage differences in glucose values between the
first and second finger test results. Differences in precision
between the meters were assessed by comparing these abso-
lute differences using the Kruskal-Wallis test.
The potential effect of time since the patient’s most recent
meal on meter accuracy and the effect of time since the pa-
tient’s most recent use of insulin on meter accuracy were as-
sessed by comparing the average differences in blood sugar
results obtained between finger results with the laboratory
values at predetermined time intervals (analysis of variance).
The predetermined time intervals were: 0–2, 2.1–4, 4.1–6, and
>6 h since the previous meal.
Results
Blood samples were obtained from 125 patients during 4
days of testing. Patient demographic information is provided
in bT1
Table 1. The study population consisted primarily of el-
derly, Caucasian, type 2 diabetes patients. Mean venipunc-
ture blood glucose was 151 mg=dL (SD 65 mg=dL; range,
58–474 mg=dL). Insulin use was reported by 66 of the
Table 1. Patient Demographics
Characteristic
Number of patients 125
Age (years) 59 14
a
Gender (% female) 64 (51.2%)
Ethnicity (% white) 113 (90.4%)
Type 2 diabetes mellitus (%) 104 (83.2%)
Insulin use (%) 66 (52.8%)
a
Mean SD value.
2 SHEFFIELD ET AL.
DIA-2008-0143-Kane_1P.3D 06/13/09 6:01pm Page 2
125 patients (52.8%), including 52 patients (41.6%) who re-
ported using premeal insulin. Finger stick blood samples for
glucose testing were obtained in duplicate in 124 of the 125
patients. Despite three attempts for a second reading, error
messages occurred in one patient during testing with the HDI
True Track.
T2 cTable 2 lists the percentage of glucose results in
each of the glucose ranges according to the ISO 15197 proto-
col.
11
No test results were below 50 mg=dL glucose.
Table 3 lists
T3 cthe results of the Clarke EGA accuracy analysis.
Clinically acceptable results (zones A and B) were similar
among the four meters; however, clinical accuracy (zone A
results) was significantly greater with the Abbott Optium
(94%), compared to the DDI Prodigy (82%), HDI True Track
(61%), and the HypoGuard Assure Pro (77%) (P<0.05). Using
these criteria, the HDI True Track was significantly less ac-
curate than all of the other meters.
Table 4 lists the
T4 cresults of the Parkes EGA accuracy analy-
sis. Using these criteria, the Abbott Optium and DDI Prodigy
Autocode showed greater accuracy compared to the other
two meters, whereas the HDI True Track was significantly
less accurate than the other three meters.
Figure 1 illustrates
F1 cthe results of the within 20%, 15%, 10%,
and 5% accuracy analyses. Accuracy rates based on meter
values falling within 5% of the laboratory reference values
were 42% (Abbott Optium), 24% (DDI Prodigy Autocode),
29% (HypoGuard Assure Pro), and 13% (HDI TrueTrack),
respectively (P<0.05 for the HDI True Track compared to the
other meters). Accuracy rates based on meter values falling
within 10% of the laboratory reference values were 59%
(Abbott Optium), 54% (DDI Prodigy Autocode), 43% (Hy-
poGuard Assure Pro), and 30% (HDI TrueTrack), respectively
(P<0.05 for the HDI True Track compared to other meters
and for the HypoGuard Assure Pro compared to the Optium).
Significantly more results with the Abbott Optium met the
within 15% and 20% accuracy criteria compared to the other
meters. The HDI True Track was associated with significantly
less accuracy compared to the other meters.
The HDI True Track was significantly less precise than the
other meters. There were no significant differences in preci-
sion among the remaining three meters ( bT5
Table 5). Glucose
results varied 9–15 mg=dL (approximately 6–10%), on aver-
age, between the first and second finger test results.
An analysis of the effect of time since the patient’s most
recent meal (analysis of variance) found no appreciable effect
on meter accuracy. There was no greater variability of finger
glucose results compared to venipuncture glucose results
when results were compared according to the predetermined
time intervals of 0–2 (n¼20), 2.1–4 (n¼55), 4.1–6 (n¼22), and
>6h (n¼28) since the previous meal. In addition, there was
no greater variability of finger glucose results compared to
venipuncture glucose results in patients using premeal insulin
(absolute difference ¼19.9 mg=dL, n¼52) versus those not
using premeal insulin (18.1 mg=dL, n¼73).
Discussion
The beneficial impact of tight glycemic control on micro- and
macrovascular complications of diabetes is well established
based on the results of the Diabetes Control and Complications
Trial,
2
the Epidemiology of Diabetes Interventions and Com-
plications Trial,
13
and the United Kingdom Prospective Dia-
betes Study.
14
In concordance with these data, current practice
guidelines from the ADA
7
and American Association of Clin-
ical Endocrinologists (AACE)
8
recommend glycosylated he-
moglobin goals of <7% and <6.5%, respectively.
Despite data supporting intensive therapy and the avail-
ability of agents with multiple glucose-lowering mechanisms,
overall glycemic control in the United States is poor. According
to 1999–2002 National Health and Nutrition Examination Sur-
vey data,
15
only 49.8% of adult Americans with diabetes mel-
litus achieved the ADA A1C goal of <7%. The 2003–2004 data
indicate that only one-thirdof patients with type 2 diabetes met
the AACE’s more stringent A1C goal of <6.5%.
16
SMBG is an integral part of diabetes management, en-
dorsed by the ADA, American Association of Clinical En-
docrinologists, and a consensus global panel of diabetes
experts.
1,7,8,9
It allows a patient to appreciate the effects of
adjustments in diet, exercise, and medication therapy on
blood glucose levels and helps them to make treatment de-
cisions. SMBG may help patients gain better overall glycemic
control, ultimately helping to reduce the risk of complications.
Daily four-point SMBG has been associated with a significant
50–76% reduction in microvascular complications when used
in conjunction with intensive insulin therapy in patients with
type 1 diabetes.
2
Table 2. ISO 15197 Protocol Glucose Standards
Glucose level
(mg=dL)
ISO standard
(%)
Study
results (%)
<50 5 0
51–80 15 4
81–120 20 32
121–200 30 47.2
201–300 15 12.8
301–400 10 3.2
>400 5 0.8
Table 3. Meter Accuracy: Clarke EGA
Zone
Meter A B C D E
Abbott Optium 118
a
70 0 0
DDI Prodigy Autocode 103 19 0 3 0
HDI True Track 76
a
44 3 2 0
HypoGuard Assure Pro 96 28 1 0 0
a
P<0.05 versus all others (w
2
analysis).
Table 4. Meter Accuracy: Parke EGA
Zone
Meter A B C D E
Abbott Optium 119 6 0 0 0
DDI Prodigy Autocode 111 14 0 0 0
HDI True Track 94
ab
30 1 0 0
HypoGuard Assure Pro 106
a
19 0 0 0
a
P<0.05 versus Optium (w
2
analysis).
b
P<0.05 versus Prodigy (w
2
analysis).
FOUR VALUE-ADDED GLUCOSE METERS 3
DIA-2008-0143-Kane_1P.3D 06/13/09 6:01pm Page 3
The utility of SMBG for patients using insulin is widely
accepted; however, its role in the management of type 2 dia-
betes patients treated with oral medication is more contro-
versial. Recent data indicate that SMBG can help lower A1C in
this population in a cost-effective manner. Care plans for type
2 diabetes patients that include SMBG are associated with
greater A1C reductions than plans that do not.
3–5
A recent
meta-analysis concluded that the use of SMBG by patients
with type 2 diabetes is associated with a significant A1C re-
duction of 0.39%.
6
A computer modeling study based on in-
formation from a large managed care database indicated that
SMBG is cost-effective for type 2 diabetes patients on oral
medications. Although SMBG was associated with an in-
crease in direct costs, these were offset by reductions in
complications and complication-associated costs, along with a
slight increase in quality-adjusted life years.
17
Multiple barriers to SMBG exist, however. A survey by
Karter et al.
18
indicated that nonadherence with SMBG may
be independently predicted by several factors, including
longer time since diagnosis, less intensive therapy, male sex,
increased age, smoking, excessive alcohol consumption, and
higher out-of-pocket test strip costs. Vincze et al.
19
reported
that a diagnosis of type 2 diabetes (as opposed to type 1) and
environmental barriers, such as lifestyle interference, incon-
venience, painfulness, and cost, impact SMBG adherence.
Generic or ‘‘value added’’ blood glucose strips are a potential
solution to the financial burden of testing, but data evaluating
the degree of accuracy or precision of value added products
are not available.
Patients using SMBG data to make self-care decisions work
under the assumption that meter results accurately reflect
their capillary blood glucose level. Several methods are cur-
rently used to assess meter accuracy. Two error grids, the
Clarke Error Grid
10
and the Parkes Error Grid,
12
have been
developed to take into account the differences between ref-
erence and meter glucose values as well as the clinical sig-
nificance of a treatment decision based on the SMBG result.
These error grids were developed using expert opinion. The
International Organization for Standardization criteria assess
whether or not a glucose meter is capable of producing 95% of
its results within 5, 10, and 15 mg=dL of reference glucose
values <75 mg=dL and within 5, 10, 15, and 20% of the ref-
erence value if the glucose value is 75 mg=dL.
11
Food and
Drug Administration blood glucose meter approval is based
on the International Organization for Standardization criteria,
mandating that manufacturers demonstrate that 95% of meter
readings fall within 20% of actual blood glucose values.
10,20
This accepted standard still allows for substantial variation in
glucose readings, a variation that is arguably too great in light
of modern intense diabetes management regimens as hypo-
glycemia could result in the overcorrection of an otherwise
normal glucose value.
According to the Clarke EGA in this study, the Abbott
Optium was the most accurate of the meters studied, with
94% (P<0.05) of results falling in zone A (representing less
than a 20% deviation from the true blood glucose), whereas
the HDI True Track was the least accurate, with only 61% of
results falling in zone A. There were no significant differences
in clinically acceptable results, defined as the summation of
zone A and zone B (the deviation from true blood glucose is
>20% but leads to no treatment or benign treatment) results,
among the meters.
FIG. 1. Meter accuracy: glucose measurements falling within 5%, 10%, 15%, or 20% of venipuncture results. *P<0.05 versus
all others (w
2
analysis);
{
P<0.05 versus Abbott Optium (w
2
analysis). Color images available online at www.liebertonline
.com=dia.
Table 5. Precision Analysis
Mean SD precision
Relative
(%)
Absolute
(mg=dL)
95% CI
(mg=dL)
Abbott Optium 6 5910 8–11
DDI Prodigy Autocode 8 61110 10–13
HDI True Track 10 13
a
15 18
b
12–19
HypoGuard Assure Pro 7 71116 8–14
a
P<0.05, Kruskal-Wallis test, compared to Abbott Optium and
HypoGuard Assure Pro.
b
P<0.05, Kruskal-Wallis test, compared to all.
4 SHEFFIELD ET AL.
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The Parkes Error Grid analysis was developed as the result
of a consensus of 100 endocrine clinicians in the attempt to
construct an unbiased tool to analyze the clinical significance
of SMBG measurement errors. Zone A results are defined as
results causing no effect on clinical action, whereas zone B
results are defined as results resulting in altered clinical action
or having little or no effect on clinical outcome. Using the
Parkes Error Grid analysis, the Abbot Optium and DDI
Prodigy Autocode were found to be significantly more clini-
cally accurate (zone A results) than the HDI True Track. The
Abbott Optium was also more accurate than the HypoGuard
Assure Pro (P<0.05). There were no significant differences
among the meters regarding clinically acceptable glucose re-
sults (summation of zone A and B results).
Using the stricter International Organization for Standar-
dization accuracy criteria, the Abbott Optium continued to
perform significantly better than the other meters, with 85% of
its readings falling within 15% of the reference values. The
Abbott Optium and DDI Prodigy Autocode had significantly
more results falling within 10% of the reference values than
the HypoGuard Assure Pro and the HDI True Track, and the
Abbott Optium, DDI Prodigy Autocode, and the DDI Prodigy
Autocode had significantly more results falling within 5% of
the reference values than the HDI True Track (Fig. 1). The HDI
True Track was significantly less accurate compared to all
other meters using the more strict accuracy criteria. The HDI
True Track was also significantly less precise compared to the
other meters.
Because there are currently no data to confirm whether
greater meter accuracy (i.e., more glucose readings falling
within 5%, 10%, 15%, or 20% of the reference values) is as-
sociated with better patient outcomes, prospective studies to
evaluate this topic are needed. Until such data are available,
however, it seems reasonable to surmise that better meter
accuracy could potentially lead to better treatment decisions
by patients, especially if it means patients feel more secure
and confident in their self-care decisions because of their
perception of greater meter accuracy.
Meter accuracy, while extremely important, is not the sole
criterion for meter selection. Factors such as blood sample
size, software capabilities, ease of use, pain associated with
testing, size of the numerical display, frequency of error
messages requiring a retest, and insurance coverage=out-of-
pocket cost also impact this decision. These variables were not
evaluated for the meters in this study and should be taken into
account by the clinician when deciding on a glucose meter for
an individual patient.
Another ‘‘real world’’ clinical consideration with all four
meters in this study is the fact that control solution is not
readily provided with purchase of the meter (unlike most
brand-name meters) but must be ordered separately from the
manufacturer or ordered and purchased at a pharmacy. Thus,
unless patients make the extra effort to obtain the control
solution, they will not be able to properly conduct control tests
on their meters.
Our study had several potential limitations. For each value-
added testing system, only one meter and one test strip lot
was used. This provided standardization to the study, but it
may have introduced a potential source of error. While most
of the study supplies were purchased at a local pharmacy, the
fact that the Abbott supplies for this study were donated by
the manufacturer is a potential source of bias. All finger stick
testing was done by one of the authors (C.A.S.), according to
manufacturers’ instructions. This increased the internal va-
lidity of the study, but it also potentially limits its external
validity as the results may not necessarily be applicable to real
world practice, because some patients do not use control so-
lution or follow all of the manufacturer’s instructions for
SMBG when testing.
A limited number of patients had glucose results in the
extremes of hypoglycemic and hyperglemic ranges according
to ISO 15197 protocol criteria. An assessment of meter accu-
racy and precision in these extremes of glucose ranges were
therefore based on a limited number of results.
Two potential criticisms of this study include the fact that
glucose testing was performed on different blood samples
(venipuncture and four different fingersticks) and on different
types of blood (venous and capillary), differences that re-
portedly may be exacerbated in the nonfasting state.
21
How-
ever, we believe that our methods can be justified on the basis
that (1) although patients test capillary whole blood, most
professionals assess meter accuracy using a laboratory refer-
ence of venous blood glucose values and (2) an analysis of the
effect of time since the patient’s most recent meal and use of
premeal insulin found no additional appreciable effect on
meter accuracy (e.g., no additional differences between ve-
nous and capillary glucose levels were found in these sub-
groups).
Finally, no popular brand-name meters were included in the
present study; therefore the value-added results cannot be di-
rectly compared to results obtained in studies using the popular
brand-name meter systems. Although a direct comparison
across studies is not possible, it is interesting to note that the
accuracy of the best of the value-added meters appear to have
performed at a level comparable to that of the best performing
popular name-brand meters.
22,23
Prospective studies to directly
compare the accuracy and precision of popular brand-name
and value-added meter systems are needed.
Conclusions
The Abbott Optium was significantly more accurate than the
other studied meters, whereas the HDI True Track was signif-
icantly less accurate. The HDI True Track was significantly less
precise compared to the other meters. Further studies are nee-
ded to compare the relative accuracy of the most accurate val-
ue-added meters with that of brand-name meters.
Acknowledgments
This study was supported by an investigator-initiated re-
search grant from Abbott Diabetes Care.
Author Disclosure Statement
No competing financial interests exist.
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Address correspondence to:
Michael P. Kane, Pharm.D., F.C.C.P., B.C.P.S.
Department of Pharmacy Practice
Albany College of Pharmacy and Health Sciences
106 New Scotland Avenue
Albany, NY 12208
E-mail: michael.kane@acphs.edu
6 SHEFFIELD ET AL.
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... 6,7 Several studies have evaluated the comparative accuracy and precision of many different BGMSs currently used for self-monitoring of blood glucose, but none have included the EZ BGMS. [8][9][10][11][12][13] The primary objective of this study was to evaluate differences in accuracy between the EZ and four other BGMSs across a wide glucose range. The secondary objective was to examine differences in accuracy between the EZ and the other BGMSs in the low glucose range (<70 mg/dl). ...
... Previous studies have evaluated the comparative accuracy and precision of the other BGMSs used in this study (ACAP, FFL, OTU2, and TT), and in some cases, the FFL and the OTU2 performed better in these previous studies than in the current study, [8][9][10]12,13 while the performance of the TT was similarly poorer compared with other BGMSs evaluated. 11 However, none of these studies included the EZ meter. Study design differences could account for the apparent discordant results reported in these studies compared with the current analysis. ...
Article
This study evaluated differences in accuracy between the CONTOUR® NEXT EZ (EZ) blood glucose monitoring system (BGMS) and four other BGMSs [ACCU-CHEK® Aviva (ACAP), FreeStyle Freedom Lite® (FFL), ONE TOUCH® Ultra®2 (OTU2), and TRUEtrack® (TT)]. Up to three capillary blood samples (N = 393) were collected from 146 subjects with and without diabetes. One sample per subject was tested with fresh (natural) blood; the other samples were glycolyzed to lower blood glucose to <70 mg/dl. Meter results were compared with results from plasma from the same sample tested on a Yellow Springs Instruments (YSI) 2300 STAT PlusTM glucose analyzer. Blood glucose monitoring system accuracy was compared using mean absolute relative difference (MARD; from laboratory reference method results) and other analyses. Separate analyses on fresh (natural) samples only were conducted to determine potential effects of glycolysis on MARD values of systems utilizing glucose-oxidase-based test strip chemistry. Across the tested glucose range, the EZ had the lowest MARD of 4.7%; the ACAP, FFL, OTU2, and TT had MARD values of 6.3%, 18.3%, 23.4%, and 26.2%, respectively. For samples with glucose concentrations <70 mg/dl, the EZ had the lowest MARD (0.65%), compared with the ACAP (2.5%), FFL (18.3%), OTU2 (22.4%), and TT (33.2%) systems. The EZ had the lowest MARD across the tested glucose ranges when compared with four other BGMSs when all samples were analyzed as well as when natural samples only were analyzed.
... This experiment contained samples with the following glucose concentrations shown in Table 1. The glucose concentrations in the blood were measured twice per a sample using Abbott Freestyle Optium [26] glucometer. This instrument shows concentration in values of mmol/l standard, which can be converted to mg/dl by multiplication by 18. ...
... Despite the prerequisite of demonstrating compliance with ISO 15197 before market approval of a new BG system, the performance of currently available BG systems (= after market approval) has been fiercely debated after reports 668373D STXXX10.1177/1932296816668373Journal of Diabetes Science and TechnologyZijlstra et al research-article2016 1 Profil, Neuss, Germany about BG systems on the market failing ISO evaluations. [3][4][5][6][7] Urgent action calls have been published by the European Association for the Study of Diabetes (EASD) and the Diabetes Technology Society (DTS) advocating the need for postmarketing surveillance programs and development of test protocols to assess BG system performance. ...
Article
Background: The objective was to evaluate the performance (in terms of accuracy, precision, and trueness) of 5 CE-certified and commercially available blood glucose (BG) systems (meters plus test strips) using an innovative clinical-experimental study design with a 3-step glucose clamp approach and frequent capillary BG measurements. Methods: Sixteen subjects with type 1 diabetes participated in this open label, single center trial. BG was clamped at 3 levels for 60 minutes each: 60-100-200 mg/dL. Medical staff performed regular finger pricks (up to 10 per BG level) to obtain capillary blood samples for paired BG measurements with the 5 BG systems and a laboratory method as comparison. Results: Three BG systems displayed significantly lower mean absolute relative deviations (MARD) (ACCU-Chek® Aviva Nano [5.4%], BGStar® [5.1%], iBGStar® [5.3%]) than 2 others (FreeStyle InsuLinx® [7.7%], OneTouch Verio®IQ [10.3%]). The measurement precision of all BG systems was comparable, but relative bias was also lower for the 3 systems with lower MARD (ACCU-Chek [1.3%], BGStar [-0.9%], iBGStar [1.0%]) compared with the 2 others (FreeStyle [-7.2%], OneTouch [8.9%]). Conclusions: This 3 range glucose clamp approach enables a systematic performance evaluation of BG systems under controlled and reproducible conditions. The random error of the tested BG systems was comparable, but some showed a lower systematic error than others. These BG systems allow an accurate glucose measurement at low, normal and high BG levels.
... [57,74] Although the ADA and ISO guidelines have been published for over a decade, few POCGMDs meet these accuracy standards. Two examples of evaluations include [1] Sheffield and colleagues [75] studied four commercially available POCGMDs and reported that only two devices met ISO standard requirements and [2] Florkowski and colleagues [76] evaluated two POCGMDs, and although both passed ISO requirements, they failed to meet ADA 1996 recommendations. One specific concern with POCGMDs is errors in the hypoglycemic range and the potential impact on clinical decisionmaking. ...
Article
Point of care testing is also referred to as near patient, bedside, or extra laboratory testing. It helps in bringing the test immediately to the patient via convenient handheld, portable, or transportable devices. POCT devices facilitate ways to improve the quality and outcomes of care while decreasing cost and length of stay especially for critical care practitioners. One of the oldest applications POCT is for self-monitoring of blood glucose (SMBG) devices They were originally designed for home self-monitoring of blood glucose (SMBG) for diabetic patients to improve glucose control during regular life activities. However, ease of use of a POCGMD and its rapid reporting of BG information led to its utilization in the inpatient setting. POCGMD represents the largest commercial market for POCT. The newer POCT devices have an advanced level of connectivity with laboratory information system (LIS). They electronically capture and transmit results to a central management point (a central data station and/or a clinical or laboratory information system), ensuring that post-analytical errors are minimized. QC is an immediate check on the integrity of the POCT device. There should be regular review of QC and EQA results as part of quality improvement. The global POCT field is in need of whole-blood standards, harmonization among methods, and improved QC. Granting these 3 wishes will facilitate common sense consistency among measurement procedures performed at the point of care and, in our opinion, will ultimately improve diagnoses, treatment decisions, and patient outcomes. EQA is both desirable and required for POCT devices. Abstract Point of care testing is also referred to as near patient, bedside, or extra laboratory testing. It helps in bringing the test immediately to the patient via convenient handheld, portable, or transportable devices. POCT devices facilitate ways to improve the quality and outcomes of care while decreasing cost and length of stay especially for critical care practitioners. One of the oldest applications POCT is for self-monitoring of blood glucose (SMBG) devices They were originally designed for home self-monitoring of blood glucose (SMBG) for diabetic patients to improve glucose control during regular life activities. However, ease of use of a POCGMD and its rapid reporting of BG information led to its utilization in the inpatient setting. POCGMD represents the largest commercial market for POCT. The newer POCT devices have an advanced level of connectivity with laboratory information system (LIS). They electronically capture and transmit results to a central management point (a central data station and/or a clinical or laboratory information system), ensuring that post-analytical errors are minimized. QC is an immediate check on the integrity of the POCT device. There should be regular review of QC and EQA results as part of quality improvement. The global POCT field is in need of whole-blood standards, harmonization among methods, and improved QC. Granting these 3 wishes will facilitate common sense consistency among measurement procedures performed at the point of care and, in our opinion, will ultimately improve diagnoses, treatment decisions, and patient outcomes. EQA is both desirable and required for POCT devices.
... Accurate measurements only result in data points within the A and B zone of the grid. 43 Five separate in vivo transcutaneous SESORS glucose experiments are presented on Clarke error grids in Figure 1. Measurements were taken from multiple spots of the implanted sensor due to movement of body of the rat as it breathed. ...
Article
This paper presents the latest progress on quantitative, in vivo, transcutaneous glucose sensing using surface enhanced spatially offset Raman spectroscopy (SESORS). Silver film over nanosphere (AgFON) surfaces were functionalized with a mixed self-assembled monolayer (SAM) and implanted subcutaneously in Sprague-Dawley rats. The glucose concentration was monitored in the interstitial fluid of six separate rats. The results demonstrated excellent accuracy and consistency. Remarkably, the root-mean-square error of calibration (RMSEC) (3.6 mg/dL) and the root-mean-square error of prediction (RMSEP) (13.7 mg/dL) for low glucose concentration (<80 mg/dL) is lower than the current International Organization Standard (ISO/DIS 15197) requirements. Additionally, our sensor demonstrated functionality up 17 days after implantation, including 12 days under the laser safety level for human skin exposure with only one time calibration. Therefore, our SERS based sensor shows promise for the challenge of reliable continuous glucose sensing systems for optimal glycemic control.
Article
Glycemia is an important indicator of the metabolic state of the body, so the alteration of their normal values is a imminent warning of possible metabolic failure, health professionals are not exempt from this, however even with the knowledge acquired in their training can be equally affected by a person of any other profession. We sought the frequency of alterations in blood glucose levels of doctors. Performing 100 surveys conducted by pollster of ENMyH (Escuela Nacional de Medicina y Homeopatía) engaged in teachers activities, administrative and / or medical practice accompanied by a rapid testing being used two glucometers, a brand Accu-sensor and the other mark Sheck Optium. We found a rate of 22% of glycemic alterations and 50% of the population are factors that favor the emergence of glycemic alterations, as the association between the amount of intake and glycemia (r = 0.15), 78% of the studied population normoglycemic values, being so far the highest compared to other countries where it was studied, the alterations were associated with working life style and food. It also made findings that associate control habits, lifestyle and monitoring with blood glucose values by doctors.
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Control of blood glucose (BG) in an acceptable range is a major therapy target for diabetes patients in both the hospital and outpatient environments. This review focuses on the state of point-of-care (POC) glucose monitoring and the accuracy of the measurement devices. The accuracy of the POC glucose monitor depends on device methodology and other factors, including sample source and collection and patient characteristics. Patient parameters capable of influencing measurements include variations in pH, blood oxygen, hematocrit, changes in microcirculation, and vasopressor therapy. These elements alone or when combined can significantly impact BG measurement accuracy with POC glucose monitoring devices (POCGMDs). In general, currently available POCGMDs exhibit the greatest accuracy within the range of physiological glucose levels but become less reliable at the lower and higher ranges of BG levels. This issue raises serious safety concerns and the importance of understanding the limitations of POCGMDs. This review will discuss potential interferences and shortcomings of the current POCGMDs and stress when these may impact the reliability of POCGMDs for clinical decision-making.
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Diabetes mellitus has a major impact on costs for healthcare and society. The estimation for 2010 is that investment in diabetes will reach 11.6% of public healthcare expenses worldwide. The expected rise in the prevalence of diabetes over the coming decades may create problems for the sustainability of healthcare systems, such as those in Spain. The rise in direct costs is the main issue in diabetes, especially the treatment of acute and chronic complications that often need hospital care. Severe hypoglycemia (SH) is the most frequent acute complication. In Spain, the incidence of SH is estimated at two episodes per patient per year for Type 1 diabetes and one to two episodes for advanced Type 2 diabetes requiring insulin treatment. Although results vary, Spanish national data provide an estimated cost of approximately €3500 per SH episode. It also has a major influence on indirect costs, mainly related to reduced productivity, absenteeism and occasionally early retirement, and affects direct health, such as quality of life. As a result of SH, patients acquire a fear of new hypoglycemic episodes, which makes them modify their behavior and habits and, in the long term, has the potential to negatively impact metabolic control. Educational programs for healthcare professionals and patients with diabetes, increased involvement of patients in the management of their illness and regular self-measurement of blood glucose are all strategies aimed at minimizing the social and economic effects of severe hypoglycemia.
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This letter presents the first quantitative, in vivo, transcutaneous glucose measurements using surface enhanced Raman spectroscopy (SERS). Silver film over nanosphere (AgFON) surfaces were functionalized with a mixed self-assembled monolayer (SAM) and implanted subcutaneously in a Sprague-Dawley rat. The glucose concentration was monitored in the interstitial fluid. SER spectra were collected from the sensor chip through the skin using spatially offset Raman spectroscopy (SORS). The combination of SERS and SORS is a powerful new approach to the challenging problem of in vivo metabolite and drug sensing.
Article
Full-text available
Background Improved blood-glucose control decreases the progression of diabetic microvascular disease, but the effect on macrovascular complications is unknown. There is concern that sulphonylureas may increase cardiovascular mortality in patients with type 2 diabetes and that high insulin concentrations may enhance atheroma formation. We compared the effects of intensive blood-glucose control with either sulphonylurea or insulin and conventional treatment on the risk of microvascular and macrovascular complications in patients with type 2 diabetes in a randomised controlled trial. Methods 3867 newly diagnosed patients with type 2 diabetes, median age 54 years (IQR 48-60 years), who after 3 months' diet treatment had a mean of two fasting plasma glucose (FPG) concentrations of 6.1-15.0 mmol/L were randomly assigned intensive policy with a sulphonylurea (chlorpropamide, glibenclamide, or. glipizide) or with insulin, or conventional policy with diet. The aim in the intensive group was FPG less than 6 mmol/L. in the conventional group, the aim was the best achievable FPG with diet atone; drugs were added only if there were hyperglycaemic symptoms or FPG greater than 15 mmol/L. Three aggregate endpoints were used to assess differences between conventional and intensive treatment: any diabetes-related endpoint (sudden death, death from hyperglycaemia or hypoglycaemia, fatal or non-fatal myocardial infarction, angina, heart failure, stroke, renal failure, amputation [of at least one digit], vitreous haemorrhage, retinopathy requiring photocoagulation, blindness in one eye,or cataract extraction); diabetes-related death (death from myocardial infarction, stroke, peripheral vascular disease, renal disease, hyperglycaemia or hypoglycaemia, and sudden death); all-cause mortality. Single clinical endpoints and surrogate subclinical endpoints were also assessed. All analyses were by intention to treat and frequency of hypoglycaemia was also analysed by actual therapy. Findings Over 10 years, haemoglobin A(1c) (HbA(1c)) was 7.0% (6.2-8.2) in the intensive group compared with 7.9% (6.9-8.8) in the conventional group-an 11% reduction. There was no difference in HbA(1c) among agents in the intensive group. Compared with the conventional group, the risk in the intensive group was 12% lower (95% CI 1-21, p=0.029) for any diabetes-related endpoint; 10% lower (-11 to 27, p=0.34) for any diabetes-related death; and 6% lower (-10 to 20, p=0.44) for all-cause mortality. Most of the risk reduction in the any diabetes-related aggregate endpoint was due to a 25% risk reduction (7-40, p=0.0099) in microvascular endpoints, including the need for retinal photocoagulation. There was no difference for any of the three aggregate endpoints the three intensive agents (chlorpropamide, glibenclamide, or insulin). Patients in the intensive group had more hypoglycaemic episodes than those in the conventional group on both types of analysis (both p<0.0001). The rates of major hypoglycaemic episodes per year were 0.7% with conventional treatment, 1.0% with chlorpropamide, 1.4% with glibenclamide, and 1.8% with insulin. Weight gain was significantly higher in the intensive group (mean 2.9 kg) than in the conventional group (p<0.001), and patients assigned insulin had a greater gain in weight (4.0 kg) than those assigned chlorpropamide (2.6 kg) or glibenclamide (1.7 kg). Interpretation Intensive blood-glucose control by either sulphonylureas or insulin substantially decreases the risk of microvascular complications, but not macrovascular disease, in patients with type 2 diabetes. None of the individual drugs had an adverse effect on cardiovascular outcomes. All intensive treatment increased the risk of hypoglycaemia.
Article
Full-text available
To compare the abilities and associated hypoglycemia risks of insulin glargine and human NPH insulin added to oral therapy of type 2 diabetes to achieve 7% HbA(1c). In a randomized, open-label, parallel, 24-week multicenter trial, 756 overweight men and women with inadequate glycemic control (HbA(1c) >7.5%) on one or two oral agents continued prestudy oral agents and received bedtime glargine or NPH once daily, titrated using a simple algorithm seeking a target fasting plasma glucose (FPG) <or=100 mg/dl (5.5 mmol/l). Outcome measures were FPG, HbA(1c), hypoglycemia, and percentage of patients reaching HbA(1c) <or=7% without documented nocturnal hypoglycemia. Mean FPG at end point was similar with glargine and NPH (117 vs. 120 mg/dl [6.5 vs. 6.7 mmol/l]), as was HbA(1c) (6.96 vs. 6.97%). A majority of patients ( approximately 60%) attained HbA(1c) <or=7% with each insulin type. However, nearly 25% more patients attained this without documented nocturnal hypoglycemia (<or=72 mg/dl [4.0 mmol/l]) with glargine (33.2 vs. 26.7%, P < 0.05). Moreover, rates of other categories of symptomatic hypoglycemia were 21-48% lower with glargine. Systematically titrating bedtime basal insulin added to oral therapy can safely achieve 7% HbA(1c) in a majority of overweight patients with type 2 diabetes with HbA(1c) between 7.5 and 10.0% on oral agents alone. In doing this, glargine causes significantly less nocturnal hypoglycemia than NPH, thus reducing a leading barrier to initiating insulin. This simple regimen may facilitate earlier and effective insulin use in routine medical practice, improving achievement of recommended standards of diabetes care.
Article
Full-text available
The American Association of Clinical Endocrinologists/American College of Endocrinology Medical Guidelines for Clinical Practice are systematically developed statements to assist healthcare professionals in medical decision making for specific clinical conditions. Most of the content herein is based on literature reviews. In areas of uncertainty, professional judgment was applied. These guidelines are a working document that reflects the state of the field at the time of publication. Because rapid changes in this area are expected, periodic revisions are inevitable. We encourage medical professionals to use this information in conjunction with their best clinical judgment. The presented recommendations may not be appropriate in all situations. Any decision by practitioners to apply these guidelines must be made in light of local resources and individual patient circumstances.
Article
Full-text available
Although the scientific literature contains numerous reports of the statistical accuracy of systems for self-monitoring of blood glucose (SMBG), most of these studies determine accuracy in ways that may not be clinically useful. We have developed an error grid analysis (EGA), which describes the clinical accuracy of SMBG systems over the entire range of blood glucose values, taking into account 1) the absolute value of the system-generated glucose value, 2) the absolute value of the reference blood glucose value, 3) the relative difference between these two values, and 4) the clinical significance of this difference. The EGA of accuracy of five different reflectance meters (Eyetone, Dextrometer, Glucometer I, Glucometer II, Memory Glucometer II), a visually interpretable glucose reagent strip (Glucostix), and filter-paper spot glucose determinations is presented. In addition, reanalyses of a laboratory comparison of three reflectance meters (Accucheck II, Glucometer II, Glucoscan 9000) and of two previously published studies comparing the accuracy of five different reflectance meters with EGA is described. EGA provides the practitioner and the researcher with a clinically meaningful method for evaluating the accuracy of blood glucose values generated with various monitoring systems and for analyzing the clinical implications of previously published data.
Article
Full-text available
The objectives of this study were 1) to construct new error grids (EGs) for blood glucose (BG) self-monitoring by using the expertise of a large panel of clinicians and 2) to use the new EGs to evaluate the accuracy of BG measurements made by patients. To construct new EGs for type 1 and type 2 diabetic patients, a total of 100 experts of diabetes were asked to assign any error in BG measurement to 1 of 5 risk categories. We used these EGs to evaluate the accuracy of self-monitoring of blood glucose (SMBG) levels in 152 diabetic patients. The SMBG data were used to compare the new type 1 diabetes EG with a traditional EG. Both the type 1 and type 2 diabetes EGs divide the risk plane into 8 concentric zones with no discontinuities. The new EGs are similar to each other, but they differ from the traditional EG in several significant ways. When used to evaluate a data set of measurements made by a sample of patients experienced in SMBG, the new type 1 diabetes EG rated 98.6% of their measurements as clinically acceptable, compared with 95% for the traditional EG. The consensus EGs furnish a new tool for evaluating errors in the measurement of BG for patients with type 1 and type 2 diabetes.
Article
The Diabetes Control and Complications Trial has demonstrated that intensive diabetes treatment delays the onset and slows the progression of diabetic complications in subjects with insulin-dependent diabetes mellitus from 13 to 39 years of age. We examined whether the effects of such treatment also occurred in the subset of young diabetic subjects (13 to 17 years of age at entry) in the Diabetes Control and Complications Trial. One hundred twenty-five adolescent subjects with insulin-dependent diabetes mellitus but with no retinopathy at baseline (primary prevention cohort) and 70 adolescent subjects with mild retinopathy (secondary intervention cohort) were randomly assigned to receive either (1) intensive therapy with an external insulin pump or at least three daily insulin injections, together with frequent daily blood-glucose monitoring, or (2) conventional therapy with one or two daily insulin injections and once-daily monitoring. Subjects were followed for a mean of 7.4 years (4 to 9 years). In the primary prevention cohort, intensive therapy decreased the risk of having retinopathy by 53% (95% confidence interval: 1% to 78%; p = 0.048) in comparison with conventional therapy. In the secondary intervention cohort, intensive therapy decreased the risk of retinopathy progression by 70% (95% confidence interval: 25% to 88%; p = 0.010) and the occurrence of microalbuminuria by 55% (95% confidence interval: 3% to 79%; p = 0.042). Motor and sensory nerve conduction velocities were faster in intensively treated subjects. The major adverse event with intensive therapy was a nearly threefold increase of severe hypoglycemia. We conclude that intensive therapy effectively delays the onset and slows the progression of diabetic retinopathy and nephropathy when initiated in adolescent subjects; the benefits outweigh the increased risk of hypoglycemia that accompanies such treatment. (J PEDIATR 1994;125:177-88)
: The diagnosis and management of diabetes in primary care has increased immensely over the past several years. The focus of this article is on the latest substantive revisions in the diagnosis, treatment, and management of diabetes, which was presented in the January 2014 issue of the ADA's journal Diabetes Care.
Article
background Intensive diabetes therapy aimed at achieving near normoglycemia reduces the risk of microvascular and neurologic complications of type 1 diabetes. We studied whether the use of intensive therapy as compared with conventional therapy during the Diabetes Control and Complications Trial (DCCT) affected the long-term inci- dence of cardiovascular disease. methods The DCCT randomly assigned 1441 patients with type 1 diabetes to intensive or conventional therapy, treating them for a mean of 6.5 years between 1983 and 1993. Ninety-three percent were subsequently followed until February 1, 2005, during the observational Epidemiology of Diabetes Interventions and Complications study. Cardiovascular disease (defined as nonfatal myocardial infarction, stroke, death from cardiovascular disease, confirmed angina, or the need for coronary-artery revascularization) was assessed with standardized measures and classified by an in- dependent committee. results During the mean 17 years of follow-up, 46 cardiovascular disease events occurred in 31 patients who had received intensive treatment in the DCCT, as compared with 98 events in 52 patients who had received conventional treatment. Intensive treat- ment reduced the risk of any cardiovascular disease event by 42 percent (95 percent confidence interval, 9 to 63 percent; P = 0.02) and the risk of nonfatal myocardial infarction, stroke, or death from cardiovascular disease by 57 percent (95 percent confidence interval, 12 to 79 percent; P = 0.02). The decrease in glycosylated hemo- globin values during the DCCT was significantly associated with most of the posi- tive effects of intensive treatment on the risk of cardiovascular disease. Microalbu- minuria and albuminuria were associated with a significant increase in the risk of cardiovascular disease, but differences between treatment groups remained signifi- cant (P≤0.05) after adjusting for these factors. conclusions Intensive diabetes therapy has long-term beneficial effects on the risk of cardiovas- cular disease in patients with type 1 diabetes.
Article
Self-monitoring of blood glucose (SMBG) is a cornerstone of diabetes care, but little is known about barriers to this self-care practice. This cross-sectional study examines SMBG practice patterns and barriers in 44,181 adults with pharmacologically treated diabetes from the Kaiser Permanente Northern California Region who responded to a health survey (83% response rate). The primary outcome is self-reported frequency of SMBG. Although most patients reported some level of SMBG monitoring, 60% of those with type 1 diabetes and 67% of those with type 2 diabetes reported practicing SMBG less frequently than recommended by the American Diabetes Association (three to four times daily for type 1 diabetes, and once daily for type 2 diabetes treated pharmacologically). Significant independent predictors of nonadherent practice of SMBG included longer time since diagnosis, less intensive therapy, male sex, age, belonging to an ethnic minority, having a lower education and neighborhood income, difficulty communicating in English, higher out-of-pocket costs for glucometer strips (especially for subjects with lower incomes), smoking, and excessive alcohol consumption. Considerable gaps persist between actual and recommended SMBG practices in this large managed care organization. A somewhat reduced SMBG frequency in subjects with linguistic barriers, some ethnic minorities, and subjects with lower education levels suggests the potential for targeted, culturally sensitive, multilingual health education. The somewhat lower frequency of SMBG among subjects paying higher out-of-pocket expenditures for strips suggests that removal of financial barriers by providing more comprehensive coverage for these costs may enhance adherence to recommendations for SMBG.