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VA RESEARCH ON INSULIN DOSAGE AND MISCODED
GLUCOSE
METERS -- Study shows significant errors in
insulin dose can
result when blood glucose meters are miscoded.
Story here...
http://www.medicalnewstoday.com/medicalnews.php?newsid=56017
Story below:
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Significant Errors In Insulin Dose Can Result When Blood Glucose Meters
Are Miscoded According To New Clinical Study
When persons with diabetes use miscoded blood glucose meters to
determine how much insulin to take, significant errors in insulin dose
can result that may potentially lead to short- and long-term health
complications, according to findings of a new study presented at the
Sixth Annual Diabetes Technology Meeting in Atlanta, Georgia.
The American Diabetes Association estimates that there are 14.6 million
children and adults diagnosed with diabetes in the United States(1), of
which an estimated 4.4 million, or 30%, require insulin to manage their
disease(2). Those who require insulin must closely monitor their blood
sugar with a blood glucose meter to plan their meals, exercise regimens
and insulin dosage.
In this study, for certain miscoded meters, the probability of insulin
error of plus or minus 2 units of insulin was 50% as compared to 8% for
correctly, manually coded meters. The probability of insulin dose error
of plus or minus 3 units of insulin was 23% for the miscoded meters but
only 0.5% for the manually correctly coded meters.
Coding is the process by which a blood glucose meter is matched to each
new box of test strips being used. This is done either by inserting a
code strip or code chip into the meter, or by entering a code number
into the meter. If this step is not performed, the meter may give
inaccurate results leading to wrong therapy. For example, relying on a
miscoded blood glucose meter to determine how much insulin to take can
result in a potentially harmful overdose. Insulin overdose may cause
dangerously low blood sugar (hypoglycemia) leading to behavioral
changes, confusion, loss of consciousness and, if untreated, seizure,
coma and even death. Chronic under-dosing of insulin may contribute to
the long-term health problems associated with high blood sugar including
kidney disease, nerve disease, eye problems, and heart disease.
"When dealing with patients with diabetes we've observed that many
either do not understand what proper coding is, or do not realize its
importance. Patients sometimes use expired test strips and/or fail to
properly code their blood glucose meters to the lot of test strips they
are using," said Dr. Steven Edelman, an author on the study and
Professor of Medicine, division of Endocrinology and Metabolism,
University of California, San Diego, and the Veterans Affairs Medical
Center and founder of TAKING CONTROL OF YOUR DIABETES (
http://www.tcoyd.org ).
The study findings also showed that auto-coded meters (meters that
automatically set the correct code anytime a test strip is inserted)
gave more accurate blood glucose values than meters that had been
correctly coded manually. This also translated into a lower probability
of insulin dose error. For auto-coded meters, the probability of plus or
minus 1 unit and plus or minus 2 units of insulin could be as high as
35.4% and 1.4% respectively. However, with the auto-coded meters, there
were no calculated insulin dose errors above plus or minus 2 units.
"These findings are significant because studies have shown that
approximately 16% - or one out of six - persons failed to properly
manually code their blood glucose meters to the lot of test strips being
used(3). Understanding the potentially serious consequences of relying
on a meter that is not properly coded - is essential for every person
with diabetes, especially those who need to take insulin," said Linda
Schrock, a nurse and certified diabetes educator, who was also an
investigator on the study, at Elkhart General Hospital, Elkhart,
Indiana.
The study authors concluded that to avoid insulin dosing errors, people
should be carefully instructed how to correctly code their meters or be
advised to use an auto-coded meter.
Study Design
The study involved 116 patients at three clinical centers. The blood
glucose values for patients in this study ranged from 52 - 498 mg/dL.
After fasting, the patients were given a two-hour meal tolerance test.
At zero, 60 and 120 minutes the study subjects' fingerstick blood was
tested on five different popular blood glucose meters (two were
auto-coded meters). Some of the meters were purposely miscoded to the
lot of test strips. The auto-coded meters were always properly coded due
to their inherent design. The values from all the meters were compared
with blood glucose values measured on a laboratory glucose analyzer to
determine how accurate (inaccurate) the meters were.
Glucose values obtained from some of the miscoded meters used for this
study showed an average error ranging between plus 29% and minus 37%.
A Monte Carlo simulation, (a statistical method that uses existing data
sets to forecast performance in the field) was conducted on the data
from the clinical trial to generate 'ideal' and 'simulated-meter'
glucose values, and subsequent insulin doses. This simulation was based
on various assumptions such as, one unit (1U) of insulin covers 50mg/dL
blood glucose.* From these calculations, the probability of insulin dose
errors for the three types of blood glucose meters (miscoded, manually
correctly coded and autocoded) were determined.
The probability for an error of plus or minus one unit of insulin was
44.6% for correctly coded meters compared to 49.6% for incorrectly coded
meters. The probability for an error with a miscoded meter of plus or
minus four units of insulin was 2.8% and for plus or minus five units of
insulin was 0.06%. There was no instance of a plus or minus four or five
unit error with correctly, manually coded meters. For auto-coded meters
there were no calculated insulin dose errors above plus or minus two
units.
Bayer HealthCare, Diabetes Care
Bayer HealthCare, Diabetes Care is a worldwide leader in diabetes,
supporting customers in 100 countries. Since the introduction of
CLINITEST(R) reagent tablets in 1941, Bayer has led the way in diabetes
care product innovation. The company changed the face of diabetes care
in 1969 when it introduced the first portable blood glucose meter and
test strips. Bayer HealthCare further innovated diabetes management by
being the first company to introduce a suite of blood glucose monitors
that do not require coding. The BREEZE(R) and CONTOUR(R) blood glucose
monitoring systems offer people with diabetes an unparalleled choice in
diabetes management systems. Recently, the Arthritis Foundation in the
United States and the Arthritis Society of Canada each granted Ease-of
Use Commendation to the BREEZE meter, representing the first time a
blood glucose meter has been recognized as easy to use for arthritis
sufferers.
In July 2006, Bayer Diabetes Care acquired Metrika Inc., maker and
manufacturer of A1CNow+(R), a meter-based diabetes monitoring system for
measurement of HbA1c (glycated hemoglobin) an important indicator of
long term blood sugar control.
Bayer HealthCare, Diabetes Care global headquarters is located in
Tarrytown, New York, in the United States and operates as part of Bayer
HealthCare LLC, a member of the worldwide Bayer HealthCare group.
Bayer HealthCare AG
Bayer HealthCare, a subsidiary of Bayer AG, is one of the world's
leading, innovative companies in the health care and medical products
industry based in Leverkusen/Germany. In 2005, the Bayer HealthCare
subgroup generated sales amounting to some 9.4 billion Euro. Bayer
HealthCare employed 33,800 people worldwide in 2005.
The company combines the global activities of the divisions Animal
Health, Consumer Care, Diabetes Care, Diagnostics and Pharmaceuticals.
Since January 1, 2006 the new Pharmaceutical Division consists of the
former Biological Products and Pharmaceutical Division and now comprises
three business units: Hematology/Cardiology, Oncology and Primary Care.
Bayer HealthCare's aim is to discover and manufacture products that will
improve human and animal health worldwide. The products enhance
well-being and quality of life by diagnosing, preventing and treating
diseases.
Small variations may occur due to the nature of Monte Carlo simulation.
(1) American Diabetes Association:
http://www.diabetes.org/diabetes-statistics.jsp
(2) Roper 2005 U.S. Diabetes Patient Marker Study, April 19, 2006
(3) Raine, C.H. Endo Prac 9: pg 137, 2003
This news release contains forward-looking statements based on current
assumptions and forecasts made by Bayer Group management. Various known
and unknown risks, uncertainties and other factors could lead to
material differences between the actual future results, financial
situation, development or performance of the company and the estimates
given here. These factors include those discussed in our public reports
filed with the Frankfurt Stock Exchange and with the U.S. Securities and
Exchange Commission (including our Form 20-F). The company assumes no
liability whatsoever to update these forward-looking statements or to
conform them to future events or developments.
Bayer Diabetes Care
http://www.bayerdiag.com
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Larry Scott
