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1Running head: CONTINUOUS GLUCOSE MONITORING, BETTER CONTROL

Continuous Glucose Monitoring:

Diabetes Patients Gain Better Control

Nina Jo Hibbard

Auburn University/ Auburn Montgomery


Abstract

Background

The long term effect of patients with Type 1 and Type 2 diabetes are decreased when using a

continuous glucose monitor (CGM) as compared to checking blood sugars two to four times

daily. The Evidence Based Practice (EBP) evaluation in this paper is to investigate the outcomes

as it relates to changes in the hemoglobin A1C (A1C) and GlycoMark (GM) lab tests in the short

term and in complications in the long term.

Method

The method used for this project will be a retrospective study of 20-50 type 1 or type 2 diabetes

patients who have worn a CGM for seven days. A1C and GM lab values will be evaluated prior

to and post wearing the device. Known evidence will be taken to make this determination. The

ACE Star Model will be the approach to evaluating the basis for possible evidence change. The

potential project possibilities regarding implementation would be to encourage more patients to

wear GGM devices for better glucose control. The evaluation methods would include a small

test of change with current patients who have worn the device temporarily.

Results

The result of the study show 56 patients had improved GM and A1C lab values after wearing the

CGM.


Conclusion

The outcome as it related to changes in the A1C and GM lab tests in the short term were proven

to be beneficial to the patient as evidence by lab value improvements. Long term outcomes need

further evaluation.


Continuous Glucose Monitoring: Diabetes Patients Gain Better Control

Diabetes has been identified as one of the top 20 priority areas for national action

according to the Institute of Medicine (IOM, 2003). The prevalence of diabetes has risen more

than ever in 2010. According to the American Diabetes Association (ADA), new statistics reveal

that there are a total of 25.8 million children and adults in the United States which is 8.3% of the

population that have diabetes. There are 18.8 million diagnosed and 7.0 million undiagnosed

people with diabetes. What is even more profound is that 79 million people have prediabetes.

There have been 1.9 million new cases of diabetes which are diagnosed in people aged 20 years

and older. In contrast to the 2007 National Diabetes Fact Sheet, which used fasting glucose data

to estimate undiagnosed diabetes and prediabetes, the 2011 National Diabetes Fact Sheet uses

both fasting glucose and A1C levels to derive estimates for undiagnosed diabetes and

prediabetes. These tests were chosen because they are most frequently used in clinical practice.

Complications

Diabetes complications are also wide range and consist of multiple areas of concern. Heart

disease and stroke are 4 times more likely with a diagnosis of diabetes. In 2004, heart disease

was noted on 68% of diabetes-related death certificates among people aged 65 years or older. In

2004, stroke was noted on 16% of diabetes-related death certificates among people aged 65 years

or older. Adults with diabetes have heart disease death rates about 2 to 4 times higher than

adults without diabetes. In addition, the risk for stroke is 2 to 4 times higher among people with

diabetes. Another complication is high blood pressure. In 2005-2008, of adults aged 20 years or

older with self-reported diabetes, 67% had blood pressure greater than or equal to 140/90 mmHg


or used prescription medications for hypertension. Blindness is a large concern as well for

individuals. Diabetes is the leading cause of new cases of blindness among adults aged 20–74

years. Diabetes is the leading cause of kidney failure, accounting for 44% of new cases in 2008.

In 2008, 48,374 people with diabetes began treatment for end-stage kidney disease in the United

States. In 2008, a total of 202,290 people with end-stage kidney disease due to diabetes were

living on chronic dialysis or with a kidney transplant in the United States. Neuropathy is another

complication patients face when dealing with diabetes. About 60% to 70% of people with

diabetes have mild to severe forms of nervous system damage. Further, more than 60% of

nontraumatic lower-limb amputations occur in people with diabetes. In 2006, about 65,700

nontraumatic lower-limb amputations were performed in people with diabetes.

Cost of Diabetes

The total cost of diagnosed diabetes in the United States in 2007 was $174 billion dollars.

$116 billion was for direct medical costs and$58 billion for indirect costs such as disability, work

loss and premature mortality. After adjusting for population age and sex differences, average

medical expenditures among people with diagnosed diabetes were 2.3 times higher than what

expenditures would be in the absence of diabetes. Factoring in the additional costs of

undiagnosed diabetes, prediabetes, and gestational diabetes brings the total cost of diabetes in the

United States in 2007 to $218 billion (American Diabetes Association, 2011).

Control of the Disease

Diabetes can be controlled in numerous ways. Type 1 diabetes is controlled by insulin

100% of the time. Type 2 diabetes patients can be controlled in a variety of ways. Some


patients can monitor their diet and exercise, while others sometimes need to add an oral

medication for added control. If these regimens fail, insulin can be added, from one injection per

day for basal control up to intensive multiple injections including basal bolus therapy. Another

alternative is Continuous Insulin Infusion (CSII). This mechanism of control is used for Type 1

and Type 2 diabetes patients. There is another vital part of controlling diabetes which is by

checking blood sugars several times per day. A patient with diabetes must maintain optimal

blood sugar control by testing several times a day. This is referred to as self-monitoring blood

glucose (SMBG). Good times to check blood sugars are fasting, before meals, two hours after

meals, bedtime and 2-3am. Other times necessary are before driving, before exercise or during a

sickness. A recent survey of Medicare patients shared they check two to four times a day. This

is due partly to inconvenience of remembering all the different times. It is also due to guidelines

regarding the number of testing strips per month allowed by insurance providers (Medicare

Guidelines, 2011).

The latest improvement in diabetes control is continuous glucose monitoring (CGM). The

Diabetes population this author works with on a daily basis varies in glucose control thus

resulting in a wide range of A1C and GM lab results in the short term which leads to long term

complications. A1C is a lab test that allows clinicians to be able to see what the patient’s

average blood glucose is over the past 3 month period of time (see Table 1). The glycomark test

allows doctors to evaluate what the patient’s average blood sugar has been over the last two

weeks postprandial (see Table 2). A1C values between 6.5 and 8.5% can be misleading. Up to

half of the patients in this range may not be in “near normal glycemic control” and may still be at

significant risk of complications of diabetes. GlycoMark® is uniquely positioned to differentiate

these patients from those who actually are in good control.


The Diabetes Control and Complications Trial (DCCT) and The United Kingdom

Prospective Diabetes Study (UKPDS) both show that lowering A1C from 8.5 to below 6.5%

significantly reduces the risk of complications from diabetes. The UKPDS showed that each 1%

reduction in A1C was associated with a 14% reduction in risk of MIs. Risk reductions were also

noted in the DCCT with cardiovascular (41%), neuropathy (60%), retinopathy (63%),

nephropathy (54%), decreasing when A1C drops from 9 to 7.2%. Unfortunately, less than half of

diabetic patients were able to achieve the targeted goal of an A1C less than 7.0% and fewer than

30% of those who reached this goal were able to maintain it over time (Dungan, 2008). 1, 5-

anhydroglucitol (GlycoMark) as a marker of short-term glycemic control and glycemic

excursions. Most patients have been successful in lowering A1C to below 8.5% by diet and

therapy; however, achieving levels below 6.5% is quite challenging. The GM can provide a clear

picture of actual glycemic control not provided by either A1C or fructosamine thereby allowing

you to effectively manage your patient through modifications of diet and/or therapy.

GlycoMark is unique among diabetes diagnostic markers. GM uniquely reflects all

postprandial hyperglycemia above the renal threshold (>180 mg/dl. serum glucose) over the prior

one to two weeks. Most hyperglycemia occurring at A1C less than 8.5% is postprandial glucose.

A1C and fructosamine (FA) average mean fasting glucose over 2 – 3 months and 2 – 3 weeks,

respectively these can produce misleading information regarding actual glycemic control.

GlycoMark is the trade name for a FDA approved blood test for 1, 5-anhydroglucitol (1, 5-AG),

a close analog of glucose. The normal serum 1, 5-AG range in adults and children is 10 to 30

µg/ml. The diagnostic range is from <2 to 10 µg/ml. Pharmaceutical companies use GlycoMark

to monitor the effects of postprandial anti-hyperglycemic therapy.


Several clinical studies are underway to assess GlycoMark as a screening test for diabetes

and as a marker for cardio-vascular disease. Major diagnostic laboratories provide GlycoMark

has a premier test for 2008.GlycoMark is a straightforward and stable assay and is adaptable to

any automated open chemistry analyzer (Dungan et al., 2006).

In using a CGM that checks blood sugars 200-300 times daily, a patient becomes more

aware and much more likely to take action on abnormal blood sugars than if the patient randomly

checks two to four times per day. This technique allows the patient to insert a sensor once every

3 to 7 days and monitors blood sugars every 3 to 5 minutes (Dexcom, 2010). This monitoring

calculates to approximately 200 to 300 times per day. Patients can achieve much better control

with tighter blood glucose monitoring. Short and long term complications can be minimized,

prolonged and even avoided with detailed blood sugar control. While the benefits are enormous,

the risk of hypoglycemia is very high with efforts for tight control which can lead to critical issue

including the possibility of death. A balance must be found in order for a positive outcome.

In research, findings were remarkable for decreasing the A1C result as well as increased

compliance for daily care of the disease. Patients report the inconvenience of wearing the device

sometimes plays a factor as well as the expense of the sensors. Overall, patients are willing to

use the device due to decrease in anxiety regarding hypoglycemic episodes during the night.

Spouses and parents also report the satisfaction of the patient wearing the device to alleviate

worry about the spouse or child during the night (Body, Beck, & Xing, 2009).


PICO Question

After establishing the need for better control of diabetes, the following PICO question

was developed.

In patients with Type 1 and Type 2 diabetes, how does using a continuous glucose

monitor compared to self-monitoring glucose affect patients of their diabetes control as evidence

by improving A1C and GM lab values and improving daily glucose control in the short term as

well as lowering the risk of chronic complications in the long term?

Each component is further explained in the following:

P – In patients with Type 1 and Type 2 diabetes

This population is in great need for trying to prevent and delay short and long term complications

from the chronic disease.

I – using a continuous glucose monitor

This device is FDA approved to guide patients in the interstitial monitoring of glucose checking

200-300 times daily and show results on the transmitter so the patient can be aware of fluctuating

blood sugars and possibly take action.

C – Compared to standard self-monitoring glucose

This is a method currently used by diabetes patients that checks blood sugar via finger stick

method and on average is done from two to four times daily.

O – Affect patients to achieve better control of their diabetes by reducing A1C and GM lab

values in the short term as well as lowering the risk of complications in the long term?


By making patients continuously aware of glucose control they are more likely to treat abnormal

blood sugars more often thus resulting in improved A1C and GM lab values in the short term as

well as daily improvement of blood sugars. This ultimately reduces long term complications.

Purpose of the Project

The purpose for choosing this project is to investigate the outcomes as it relates to better

glucose control. Is the use of a CGM beneficial in the short term and long term by improving

daily glucoses, improving A1C and GM results and preventing or further delaying long term

complications? The purpose would also include improved overall compliance as it relates to the

patients daily DM care. The epidemic of diabetes is growing stronger every day and evidence

suggests more complications are happening due to poor control. It is critical to maintain optimal

control for this reason.

Goal of the Project

The goal for the project is to improve diabetes control in patients. The downloaded

patient data has demonstrated to be crucial in the plan of care at office visits (See Figure 1).

Without this information provided to the doctor, diabetes regimens to provide improved control

at the times of day needed would be near impossible to predict. Evidence provided is to move

this suggestion into evidence-based practice.


Figure 1

Target Population

The target population will be adult Type 1 and Type 2 diabetes patients who have been

diagnosed for at least 6 months. The age range is 19 years old and above and used a temporary

CGM in the months of January 2011 through December 2011.

Framework

The EBP framework that will guide the development and implementation of this project

is the ACE Star model (See Figure 2). The Ace Star Model is a model for understanding the

cycles, nature, and characteristics of knowledge that are utilized in various aspects of evidence-

based practice (EBP).

Demonstration Patient Report


Figure 2

The Star Model organizes both

old and new concepts of improving care into a whole and provides a framework with which to

organize EBP processes and approaches (Stevens 2004). Known as the ACE Star Model, it is a

simple, parsimonious depiction of the relationships between various stages of knowledge

transformation, as newly discovered knowledge is moved into practice. Configured as a simple

5-point star, the model illustrates five major stages of knowledge transformation: 1) knowledge

discovery, 2) evidence summary, 3) translation into practice recommendations, 4) integration

into practice, and 5) evaluation. Evidence-based processes and methods vary from one point on

the Star Model to the next. Underlying premises of knowledge transformation include:

Knowledge transformation is necessary before research results are useable in clinical

decision making.


Knowledge derives from a variety of sources. In healthcare, sources of knowledge

include research evidence, experience, authority, trial and error, and theoretical

principles.

The most stable and generalizable knowledge is discovered through systematic processes

that control bias, namely, the research process.

Evidence can be classified into a hierarchy of strength of evidence. Relative strength of

evidence is largely dependent on the rigor of the scientific design that produced the

evidence. The value of rigor is that it strengthens cause-and-effect relationships.

Knowledge exists in a variety of forms. As research evidence is converted through

systematic steps, knowledge from other sources (expertise, patient preference) is added,

creating yet another form of knowledge.

The form ('package') in which knowledge exists can be referenced to its use; in the case

of EBP, the ultimate use is application in healthcare.

The form of knowledge determines its usability in clinical decision making. For example,

research results from a primary investigation are less useful to decision making than an

evidence-based clinical practice guideline.

Knowledge is transformed through the following processes: summarization into a single

statement about the state of the science, translation of the state of the science into clinical

recommendations, with addition of clinical expertise, guides from theory, and client preferences

integration of recommendations through organizational and individual actions evaluation of

impact of actions on targeted outcomes.


Each Stage Explanation

STAR POINT 1. Discovery

This is a knowledge generating stage. In this stage, new knowledge is discovered through

the traditional research methodologies and scientific inquiry. Research results are generated

through the conduct of a single study. This may be called a primary research study and research

designs range from descriptive to correlational to causal; and from randomized control trials to

qualitative. This stage builds the corpus of research about clinical actions Stevens, 2004). During

the knowledge generating stage of this project, the writer gained a better understanding of what

literature review and research had taken place on the particular topic of CGM devices.

STAR POINT 2. Evidence Summary

Evidence summary is the first unique step in EBP - the task is to synthesize the corpus of

research knowledge into a single, meaningful statement of the state of the science. The most

advanced EBP methods to date are those used to develop evidence summaries (i.e., evidence

synthesis, systematic reviews, e.g., the systematic review methods outlined in the Cochrane

Handbook) from randomized control trials. Some evidence summaries employ more rigorous

methods than others, yielding more credible and reproducible results. This stage is also

considered a knowledge generating stage, which occurs simultaneously with the summarization.

Evidence summaries produce new knowledge by combining findings from all studies to identify

bias and limit chance effects in the conclusions. The systematic methodology also increases

reliability and reproducibility of results. The following terms are used to refer to various forms of

evidence summaries: evidence synthesis (Agency for Healthcare Research and Quality),

systematic review (Cochrane Collaboration), meta-analysis (a statistical procedure), integrative


review, review of literature, and state of the science review (less rigorous and therefore less

reliable summary processes). This field of science is referred to as the 'science of research

synthesis'. The rigorous evidence summary step distinguishes EBP from the old paradigm of

research utilization. Largely due to the work of the Cochrane Collaboration, rigorous methods

for systematic reviews have been greatly advanced, using Meta analytic techniques and

developing other statistical summary strategies, such as Number Needed to Treat (NNT). The

evidence summary for this project reveals extensive research has been performed regarding the

use of CGM devices (Melnyk, 2011).

STAR POINT 3. Translation

The transformation of evidence summaries into actual practice requires two stages:

translation of evidence into practice recommendations and integration into practice. The aim of

translation is to provide a useful and relevant package of summarized evidence to clinicians and

clients in a form that suits the time, cost, and care standard. Recommendations are generically

termed clinical practice guidelines (CPGs) and may be represented or embedded in care

standards, clinical pathways, protocols, and algorithms. CPGs are tools to support informed

clinical decisions for clinician, organization, and client. Well-developed CPGs state benefits,

harms, and costs of various decision options. The strongest CPGs are developed systematically

using a process that is explicit and reproducible. Summarized research evidence is interpreted

and combined with other sources of knowledge (such as clinical expertise and theoretical guides)

and then contextualized to the specific client population and setting. Evidence-based CPGs

explicitly articulate the link between the clinical recommendation and the strength of supporting

evidence and/or strength of recommendation (Melnyk, 2011). The translation for this project


would be placed in recommendation format for the Endocrinologist office staff to review and

then a plan would be developed to phase in the change of practice.

STAR POINT 4. Integration

Integration is perhaps the most familiar stage in healthcare because of society's long-

standing expectation that healthcare be based on most current knowledge, thus, requiring

implementation of innovations. This step involves changing both individual and organizational

practices through formal and informal channels. Major aspects addressed in this stage are factors

that affect individual and organizational rate of adoption of innovation and factors that affect

integration of the change into sustainable systems (Melnyk, 2011). The formal and informal

channels of change through the Endocrinologist office would begin with the physician and office

manager and integrate to the office staff and patients.

STAR POINT 5. Evaluation

The final stage in knowledge transformation is evaluation. In EBP, a broad array of

endpoints and outcomes are evaluated. These include evaluation of the impact of EBP on patient

health outcomes, provider and patient satisfaction, efficacy, efficiency, economic analysis, and

health status impact. As new knowledge is transformed through the five stages, the final outcome

is evidence-based quality improvement of health care (Melnyk, 2011). The new process would

be continuously evaluated on a monthly basis at the Endocrinologist office to evaluate change

effectiveness and modify changes as needed in the new standard of practice implemented.


Rationale

The rationale for using this model is because of the inclusive of familiar processes and

also emphasizes the unique aspects of EBP. The ACE Star Model places nursing's previous

scientific work within the context of EBP, serves as an organizer for examining and applying

EBP, and mainstreams nursing into the formal network of EBP. The Star Model depicts various

forms of knowledge in a relative sequence, as research evidence is moved through several cycles,

combined with other knowledge and integrated into practice. The ACE Star Model provides a

framework for systematically putting evidence-based practice processes into operation (Stevens,

2004).

Review of Literature

The literature researched and reviewed for this project are multifaceted and broad in

selection. The review of research is important to be able support an idea based on evidence.

Randomized Control Trials (RCT) were the majority of the evaluation of evidence followed by a

systemic review.

Body, Beck and Xing (2009) had information with the purpose of sustained benefit in use

of CGM on A1C, glucose profiles, and hypoglycemia in adults with Type 1 diabetes. The

objective was to evaluate long-term effects of continuous glucose monitoring (CGM) in

intensively treated adults with type 1 diabetes. The research and design methods used were a

study of 83 of 86 individuals 25 years of age with type 1 diabetes who used CGM as part of a 6-

month randomized clinical trial in a subsequent 6-month extension study. The results found were

after 12 months, median CGM use was 6.8 days per week. Mean change in A1C level from


baseline to 12 months was 0.4 0.6% (P 0.001) in subjects with baseline A1C 7.0%. A1C

remained stable at 6.4% in those with baseline A1C 7.0%. The incidence rate of severe

hypoglycemia was 21.8 and 7.1 events per 100 person-years in the first and last 6 months,

respectively. Time per day with glucose levels in the range of 71–180 mg/dl increased

significantly (P =0.02) from baseline to 12 months. The conclusion in intensively treated adults

with type 1 diabetes, CGM use and benefit can be sustained for 12 months. In a 6-month

randomized trial of intensively treated individuals with type 1 diabetes and baseline A1C7.0%,

adults 25 years of age benefited from use of continuous glucose monitoring (CGM) compared

with adults using conventional blood glucose monitoring (1). In a contemporaneous parallel

study of individuals with type 1 diabetes that had A1C levels7.0%, those in the CGM group had

a reduction in biochemical hypoglycemia compared with those in the control group while

maintaining A1C levels in the target range. This report describes the 12-month follow-up of

adult subjects in the two randomized trials’ CGM groups. The research and design method was

described by grafts included in the article. The protocol has been analyzed in a 12-month

follow-up data for 83 of the 86 adults (25 years of age) who were initially randomized to the

CGM group in either the 7.0% (n 49) or 7.0% n 34) baseline A1C cohorts; 2 subjects

discontinued study participation during the first 6 months and one after completion of the 9-

month visit. An insulin pump was used by 75 (90%) subjects and multiple daily injections

(MDIs) of insulin by 8 (10%). Subjects were provided with either a DexCom SEVEN (DexCom,

San Diego, CA), MiniMed Paradigm Real-Time System (Medtronic MiniMed, Northridge, CA),

or Freestyle Navigator (Abbott Diabetes Care, Alameda, CA). Follow-up visits during the

extension study occurred at 9 and 12 months post randomization. The reduction in A1C occurred

mainly in the first 8 weeks and then remained relatively stable through the next 44 weeks.


Subjects with baseline A1C 7.0%, A1C remained within the target range over the entire 12

months of the study (6.4, 6.3, and 6.4% at baseline, 6months, and 12 months, respectively (Body,

Beck, & Xing, 2009).

The discussion of CGM continues with the review of an article by Ehrhardt, Chellappa,

Walker, Fonda, & Vigersky, (2011). Real-time continuous glucose monitoring (RT-CGM)

improves hemoglobin A1c (A1C) and hypoglycemia in people with type 1 diabetes mellitus and

those with type 2 diabetes mellitus (T2DM) on prandial insulin; however, it has not been tested

in people with T2DM not taking prandial insulin. They evaluated the utility of RT-CGM in

people with T2DM on a variety of treatment modalities except prandial insulin. The method used

in this particular study had a prospective 52-week, two-arm, randomized trial comparing RT-

CGM (n = 50) versus self-monitoring of blood glucose (SMBG) (n = 50) in people with T2DM

not taking prandial insulin. Real-time continuous glucose monitoring was used for four 2-week

cycles (2 weeks on/1 week off). All patients were managed by their usual provider. This article

reports on changes in A1C 0–12 weeks. The results found include a mean (±standard deviation)

decline in A1C at 12 weeks was 1.0% (±1.1%) in the RT-CGM group and 0.5% (±0.8%) in the

SMBG group (p = .006). There were no group differences in the net change in number or dosage

of hypoglycemic medications. Those who used the RT-CGM for =48 days (per protocol) reduced

their A1C by 1.2% (±1.1%) versus 0.6% (±1.1%) in those who used it <48 days (p = .003).

Multiple regression analyses statistically adjusting for baseline A1C, an indicator for usage, and

known confounders confirmed the observed differences between treatment groups were robust (p

= .009). There was no improvement in weight or blood pressure. In conclusion of this article the

Real-time continuous glucose monitoring significantly improves A1C compared with SMBG in

patients with T2DM not taking prandial insulin. This technology might benefit a wider


population of people with diabetes than previously thought (Ehrhardt, Chellappa, Walker, Fonda,

& Vigersky, 2011).

The purpose of the STAR 3 Study was to evaluate improvements in metabolic control in

subjects with type 1 diabetes placed on sensor-augmented insulin pump therapy (SAP). These

subjects had previously failed to meet glycemic targets with multiple daily injections (MDI)

therapy and conventional blood glucose monitoring. This was an unmasked, randomized,

controlled trial conducted at 30 diabetes centers in the United States and Canada. Subject

eligibility criteria: Use of MDI for 3 months, documented self-monitoring of blood glucose

(SMBG) 4 times/day for the prior 30 days, 7-70 years of age, type 1 diabetes, and a baseline

A1C of =7.4% to =9.5%. Subjects were required to have access to a computer. Subjects were

randomized to SAP or MDI via block design stratified by site and age group: Adult group: 19-70

years of age Pediatric group: 7-18 years of age. Prior to randomization, all study subjects

received training in insulin diabetes management, carbohydrate counting and correction insulin

bolusing. Training for MDI and SAP subjects included use of diabetes management software

(CareLink® Therapy Management System for Diabetes-Clinical). The SAP subjects were placed

on the MiniMedParadigm®REAL-Time System (Medtronic) with insulin aspart for 2 weeks.

The MDI subjects used both insulin glargine and insulin aspart. All additional scheduled visits

following week 5 were the same in both groups. Sensor glucose values were collected for 1 week

periods at baseline, 6 months and 1 year in both groups. The MDI group used blinded continuous

glucose monitoring to collect sensor data. Subjects were seen at 3, 6, 9, and 12 months for

routine clinic visits. The results include 495 patients that were randomized; 10 lacked any

follow-up A1C values and were not included in the data analysis. Analyses were performed

using the intent-to-treat cohort comprised of these 485 subjects. There were no significant


differences in baseline characteristics between the two study groups except for weight among

adults. The difference in A1C between study groups favored the SAP group and was statistically

and clinically significant in both adult and pediatric subjects. The researchers concluded the

decrease in A1C levels in the SAP group was achieved at 3 months and sustained throughout the

1 year study. The improvement in A1C levels was achieved without an increase in the rate of

severe hypoglycemic events and without an increase in the time spent at an AUC <70 mg/dL. A

significantly greater number of adults and pediatric subjects in the SAP group reached ADA age

specific A1C targets (Bergenstal, Tamborlane, & Ahmann, 2010).

Bode, Beck, & Xing (2008), performed a study to evaluate the efficacy and safety of

continuous glucose monitoring (CGM) in adults and children with type 1 diabetes. Data

regarding CGM in both groups after the 26-week visit were used to estimate the amount of time

per day the subject’s glucose level was hypoglycemic (<70 mg/dL or <50 mg/dL),

hyperglycemic (>180 mg/dL or >250 mg/dL), and in the target range (71 to 180 mg/dL). The

study was a randomized, controlled trial that was conducted between February and December

2007 in 10 centers. Subject eligibility criteria included: age =8 years, type 1 diabetes =1 year,

use of either an insulin pump or =3 daily insulin injections, a baseline HbA1c value of 7.0%-

10.0%, and the completion of a blinded CGM run-in phase. Subjects were randomly assigned to

either the CGM group or the control group. Subjects assigned to the CGM group were provided

with one of the following devices: the DexCom™ SEVEN®, the Minimed Paradigm® REAL-

Time Insulin Pump and CGM System, or the Abbott FreeStyle Navigator™. Subjects were

instructed to use the device daily and to verify the device glucose measurement with a home

blood glucose meter before making treatment decisions. Control group subjects were asked to

perform self-monitoring of blood glucose (SMBG) at least 4 times per day. Subjects in the CGM


and the control groups were given written instruction on how to use CGM and SMBG data,

respectively, how to make insulin dose adjustments, and how to use computer software to review

data retrospectively to alter insulin dosing. Although it was not required, all subjects had a home

computer. Clinic visits were conducted at 1, 4, 8, 13, 19, and 26 weeks with one scheduled phone

contact between each visit. The control group used a blinded CGM device for one week

following the 13- and 26-week visits. A1C levels were measured at baseline, 13 weeks, and 26

weeks. Age groups were defined as 8 to 14 years of age, 15 to 24 years of age, and >25 years of

age. A total of 322 children and adults with type 1 diabetes were randomized in the study; 165

subjects were assigned to the CGM group and 157 were assigned to the control group. The

majority of the participants were using an insulin pump, measuring glucose levels >5 times per

day, and had mean A1C levels of <8.0%. Only three subjects dropped out of the study. There

was a significant between-group difference in the change in A1C levels from baseline to 26

weeks in subjects who were =25 years old, favoring the CGM group (mean difference: -0.53%;

95% confidence interval: -0.71% to -0.35%; p<0.001). CGM can lead to lower A1C levels and

tighter glycemic control without a significant increase in hypoglycemia for adults with type 1

diabetes. They observed significant difference in A1C levels in the >25 age group may be related

to substantially greater use of sensors in this group versus in the two younger age groups.

Improved glycemic results were driven by subjects >25 years old who were motivated to both

use the technology and had the capability to incorporate it into their daily diabetes management.

Improvements by the youngest age group were probably due to the parental involvement of their

diabetes management (Bode, Beck, & Xing, 2008).

Hirsch, Abelseth, Bode, Fischer, & Kaufman,( 2008) evaluated the clinical effectiveness

and safety of an insulin pump augmented with real-time continuous glucose monitoring (CGM)


compared with an insulin pump plus self-monitoring of blood glucose. The study was a

randomized, treat-to-target, 6-month trial that was conducted at 7 centers in the U.S. Enrolled

subjects were between the ages of 12-72 years, had an A1C level of =7.5%, were diagnosed with

type 1 diabetes >1 year prior to study enrollment, and were previously treated with CSII for at

least 6 months. Following initial screening, all subjects wore blinded CGM for 10 days to obtain

baseline data. Subjects were randomized to either the Sensor Group (SG), which used a sensor-

augmented pump, or the Control Group (CG), which used self-monitoring of blood glucose

(SMBG). Other than the communication between the pump and the sensor in the SG, all other

pump functionality was identical. All subjects received intensive diabetes management training.

At week 13, A1C values were obtained and insulin pump data were downloaded. At the end of

the study (week 26), the CG wore two blinded CGM sensors for two consecutive 3-day periods.

Results included a total of 146 adults and adolescents with type 1 diabetes were enrolled and

randomized in the study; 72 subjects were assigned to the SG and 74 subjects were assigned to

the CG. Of the 138 subjects completing the study, 40 were adolescents 12 to 17 years of age and

98 were adults aged 18 years or older. The change in A1C levels from baseline was significant

in both groups (p<0.001). The between-group difference was not significant (p=0.3706). At

week 13, both groups showed a decrease in A1C values, while at the end of the study, A1C

values increased, although not to baseline values. Twenty (30.8%) SG subjects achieved A1C

values of 7.0% by week 13 compared with 8 (11.1%) CG subjects. The between-group

difference was significant (p=0.007). When compared with CG subjects, the number of SG

subjects who reached a 7.0% A1c level at either 13 weeks or at the end of study was greater to a

significant degree (p=0.0031). The between-group difference in adolescents and in adults was

not significant. At the end of the study, 16 subjects (24.2%) in the SG reached the target A1C


levels of <7.0% versus 12 (19.4%) in the CG on, A1C values were collected and insulin pump

data were downloaded for all subjects (Hirsch, Abelseth, Bode, Fischer, & Kaufman, 2008).

An investigated study has not been done to show the benefit of continuous glucose

monitoring (CGM) at insulin pump initiation in patients with poor metabolic control on multiple

daily injections (MDI). In RealTrend, continuous subcutaneous insulin infusion (CSII) therapy

was randomly initiated with either Paradigm® REAL-Time (PRT) or conventional CSII in

poorly controlled subjects who had been on optimized basal-bolus MDI regimens. Study

highlights included that A1C levels were significantly reduced within the PRT group and the

CSII group. The greatest A1C reduction occurred in the PRT group when using sensors at least

70% of the time in study; -0.96 ± 0.93% vs. -0.55 ± 0.93% (p<0.001). PRT subjects bolused

more frequently after one month of treatment and at study end. A higher percentage of insulin

was delivered as bolus in the PRT group vs. CSII group. Patient Benefits were that there were

twice as many study subjects in the PRT group reported that they made modifications to their

eating habits and lifestyle vs. study subjects using CSII alone. Over 90% of subjects in the PRT

group used CGM data to manage their diabetes by adjusting insulin doses, and 59% used CGM

data to manage glycemic excursions. Alarms and glucose trend information available to the PRT

subjects may have been responsible for more lifestyle modifications and insulin treatment

adjustments (Raccah, Sulmont, & Reznik, 2009).

Dungan et al, 2006 introduced a study regarding the GlycoMark test and how it relates to

CGM devices. Postprandial hyperglycemia is often inadequately assessed in diabetes

management. Serum 1, 5-anhydroglucitol (1, 5-AG) drops as serum glucose rises above the renal

threshold for glucose and has been proposed as a marker for postprandial hyperglycemia. The


objective of this study is to demonstrate the relationship between 1, 5-AG and postprandial

hyperglycemia, as assessed by the continuous glucose monitoring system (CGMS) in sub

optimally controlled patients with diabetes. Patients with type 1 or type 2 diabetes and an A1C

between 6.5 and 8% with stable glycemic control were recruited from two sites. A CGMS

monitor was worn for two consecutive 72-h periods. Mean glucose, mean post meal maximum

glucose (MPMG), and area under the curve for glucose above 180 mg/dl (AUC-180), were

compared with 1, 5-AG, fructosamine (FA), and A1C at baseline, day 4, and day 7. 1, 5-AG

varied considerably between patients (6.5 ± 3.2 µg/ml [means ± SD]) despite similar A1C (7.3 ±

0.5%). Mean 1, 5-AG (r = -0.45, P = 0.006) correlated with AUC-180 more robustly than A1C (r

= 0.33, P = 0.057) or FA (r = 0.38, P = 0.88). MPMG correlated more strongly with 1, 5-AG (r =

-0.54, P = 0.004) than with A1C (r = 0.40, P =0.03) or FA (r = 0.32, P = 0.07). The findings

were 1; 5-AG reflects glycemic excursions, often in the postprandial state, more robustly than

A1C or FA. 1, 5-AG may be useful as a complementary marker to A1C to assess glycemic

control in moderately controlled patients with diabetes.

Synthesis of literature

After reviewing the literature and selecting the articles that most applied to the PICO

questions, the following details were noted:

Population consisted of Type 1 DM- all articles and Type 2 DM had 1 article including adults

and children. There were 3 articles from the literature that were specific to the PICO question

which is looking at the benefit of the CGM on A1C versus SMBG control. One article

specifically focused on Type 2 DM who was not taking prandial insulin. Two articles focused

on effects of poor controlled patients being put on the insulin pump for the first time along with a


CGM. The total participants reviewed equal 1,260 (adults- 841, adolescents-419). All articles

were consistent in their findings that the outcome of the articles concluded improvement in A1C

with the use of a CGM versus a SMBG device. The length ranged from 3articles that were 6

month studies and 3 were 12 month studies. Bias includes 2 studies that no bias appeared to be

present and 4 studies Medtronic was a sponsor of the research article.

It is overwhelming evidence that the use of CGM devices does in fact lower A1C %

points when used diligently up to 70% of the time. Patients are more conscious of the food

selection, remember to bolus for the carbohydrates more often and are more aware of the effects

food, stress and lack of blousing has on the blood sugar. Once a patient is aware of these short

term changes, it will only benefit the long term affects for decreasing risks of complications.

Critical Appraisal of Evidence

The appraisal and evaluation of the literature was found to prove validation for

application to the PICO question. The proposed question was supported in that the use of CGM

in patients with diabetes would result in decrease of A1C. The certainty of knowledge sources

need to continue to be researched because four of the articles received money for research from

Medtronic which indicates bias may exist in the research. More unbiased research needs to be

found in order to make the findings as valid as possible.

Rating the Strength of the scientific evidence: The article by Body, Beck & Xing, (2009)

is ranked at a level 2 which is discussing sustained benefit of continuous glucose monitoring on

A1C, glucose profiles, and hypoglycemia in adults with type 1 diabetes. This is a strong article

recommendation and good evidence that the service improves important health outcomes and

concludes that benefits substantially outweigh harms. After reviewing the article by Ehrhardt,


Chellappa, Walker, Fonda & Vigeisky (2011) is was found to be a level 2 uses the terms “might

be” beneficial but is biased and vaguer in the study. Findings are significant in A1C reductions

but the population is narrow using only Type 2 DM on non-prandial insulin. The Star Study by

Bergenstal, Tamborance, & Ahmann, (2010) proved to be a level 2 and is also a Randomized

Control Trial (RCT) and has many age groups as well as the largest population in literature

reviewed. It has bias though and could definitely be more beneficial without this factor. Next,

Body, Beck & Xing, (2008), scored a level 2 also had a large population from a RCT study and

divided out the study to be two armed so that there was a control group to compare CGM versus

SMBG while the article by Hirsch, Abelseth, Bode, Fischer & Kaufman (2008) also ranked a

level 2 and had a downfall for this article because of the shorter length of time of 6 months as

opposed to 12 months in some of the other articles. It also has bias noted. Lastly, Raccah,

Sulmaont & Reznik, (2009) had a level 2 article also had a 6 month study time as opposed to a

longer time frame. In researching future articles, it will be beneficial to select at least a 12 month

period of study. In all the articles, it is overwhelming the evidence found in the benefit Please

refer to Appendix A for greater detail on the articles used as evidence.

Recommendations

Based on the evidence presented in the literature review, it is recommended to implement

an evidence based evaluation need to just recommend use –Grade of recommendation- A. The

method of implementation will be discussed later. The lab findings of current A1C and GM

result findings can be documented as well as future results.


Current State in Organization

The long term effect of patients with Type 1 and Type 2 Diabetes are decreased when

using a continuous glucose monitor (CGM) as compared to checking blood sugars two to four

times daily. The Evidence Based Practice (EBP) evaluation in this project is to investigate the

outcomes as it relates to changes in A1C and GM in the short term and in preventing

complications in the long term. The current state of care delivery process in the organization is

providing temporary CGM devices to patients whose insurance does not cover the device and

allowing them to wear it for 7 days. After the 7 days is complete, the patient returns the device.

It is downloaded and a report is developed for evaluation of the patient’s current control state in

regards to the blood sugar control. Adjustments to current medication regimens are made to

insure proper care of diabetes is being obtained. Also, those patients who have purchased

devices are set up on a schedule to download their devices on a three month rotation so it can be

evaluated and adjustments made prior to their next visit. Opportunities for improvement would

be to assist patients to appeal insurance decisions to not pay for these devices so that it is

available for more patients to use and be paid for through insurance. If this procedure did not

take place in a medical office or facility, patients go 6 months to a year not knowing if their

current diabetes medication regimen is working correctly and benefiting the A1C and GM results

in the short term. This leads to delayed control of DM in the long term resulting in unwanted

complications.

The stakeholders are already on board with the use of CGM devices in the offices for

temporary use as well as encouraging every patient on insulin to apply for the device through

their insurance. The stakeholders are very proactive in the approach to patient education and

preventative care.


Implementation Plans

The EBP Environment Model has a core listing of key words: persistence, patience and

perseverance. These are constant reminders of what one must do when beginning change in any

environment. First, a vision for EBP must be created. Next, one must engage personnel and other

resources to be involved in the change. Integration of EBP and nourishing the culture then takes

place in the model. Finally, one must evaluate the evidence (Melnyk, 2011).

A practice change intervention for the target population of temporary CGM wearers for

2011 was not applicable in the retrospective study however, evidence and needs assessment

support the idea moving forward to continue promoting CGM device application in the

temporary condition provided by the physician’s office to encourage health promotion and

controlled blood sugars.

The project for implementation included several processes. The first step was to obtain

the list of 2011 temporary CGM patients. After this list was obtained, the next step was to

eliminate any patient who was under the age of 19. After establishing a list, patient charts were

obtained and lab results of A1C and GM prior to wearing the temporary CGM and post CGM

were documented in a controlled collection process. Patients were identified with a patient

number, male or female, type 1 or type 2 and age. The initial plans for implementation was to

perform a retrospective study on Type 1 and Type 2 patients ages 19 and older who wore a

temporary CGM for 7 days from January 2011 to December 2011. The plan was to acquire

approximately 20-50 patients from an Endocrinologist office that met these criteria.

Retrospective review each chart for Pre- CGM A1C and GM lab data and compare it to post

CGM lab data was to be performed The factors that made this a successful implementation was


good documentation of the visits for the year described. A barrier could have been poor

documentation and no way to track these patients or know when they wore the CGM device.

The resources used for this project was the office staff in obtaining charts and lab results, a

personal computer to store the data and excel spread sheet and a flash drive to save data in order

to send it to Auburn University SPSS system for analysis.

The small test of change included a final total of 56 patients. The original timeline was to

start collecting data in October 2011. The study originally was to evaluate patients who had

purchased their own CGM and interview to see what life style changes the patient had made as

well as review labs to see if there was an improvement in blood sugar control. The study

changed in December 2011 to the temporary CGM in a 7 day period because it was new data and

not much research has been done on temporary CGM effects to A1C and GM. Data was

collected late January 2012 and early February 2012. After completion of the data it was sent to

SPSS for analysis.

The vision for change has been established in the office this implementation project is to

take place. The physician is the mentor for my EBP project and is very much on board with

100% patient participation in his practice. Budget needs are not an issue due to the physician’s

office already having the temporary devices.

Evaluation Plan

The role of outcomes when evaluating practice change is vitally important. In 1988, Paul

Ellwood proposed a framework for outcomes management (OM). It was designed to help

patients, payers, and providers make rational medical care- related choices based on better


insight. In 1997, the Health Outcomes Institute’s Outcomes Management Model was developed

to take the OM framework and put it into actual steps. In the model there are four phases

discussed. The outcome process is identified in phase one (Melnyk, 2011).

1. Measurement of A1C results prior to wearing temporary CGM and post wearing the device for

7 days.

2. Measurement of the GM results prior to wearing temporary CGM and post wearing the device

for 7 days.

The results and outcomes achieved in the small test of change were positive and did show

significant different when wearing the CGM temporarily.

Table 3

Type 1 and Type 2 patients

Paired Samples Statistics

Mean N Std. Deviation Std. Error Mean

Pair 1 GM1 6.3176 51 5.42633 .75984

GM2 7.2216 51 5.71182 .79982

Pair 2 A1C 8.7511 45 2.44230 .36408

A1C2 8.1000 45 1.67698 .24999

Paired Samples Test




Pair 1 GM1 6.3176 51 5.42633 .75984

GM2 7.2216 51 5.71182 .79982

Pair 2 A1C 8.7511 45 2.44230 .36408

t df Sig. (2-tailed)

Pair 1 GM1 - GM2 -2.777 50 .008 significant

Pair 2 A1C - A1C2 2.984 44 .005 significant

Overall, the GM and A1C improved in after the 7 day use. (See Graph 1). When breaking the

data down to Type 1 and Type 2 results separately the following were noted.

Table 4

Type 1 Data



Pair 1 GM1 3.7143 21 2.44710 .53400

GM2 4.7667 21 3.70841 .80924

Pair 2 A1C 8.5765 17 2.17788 .52821

A1C2 7.9471 17 1.81422 .44001

Paired Samples Test


Pair 1 GM1 - GM2 -1.468 20 .158




Pair 1 GM1 3.7143 21 2.44710 .53400

GM2 4.7667 21 3.70841 .80924

Pair 2 A1C 8.5765 17 2.17788 .52821

Pair 2 A1C - A1C2 2.554 16 .021

Glycomark was not significant but A1C was significant.

Looking at Type 2 patients, this population had the most significant change in labs. (See graph 2)

Table 5

T-Test – Type 2



Pair 1 GM1 8.1400 30 6.18823 1.12981

GM2 8.9400 30 6.27269 1.14523

Pair 2 A1C 8.8571 28 2.62275 .49565

A1C2 8.1929 28 1.61519 .30524

Paired Samples Test




Pair 1 GM1 8.1400 30 6.18823 1.12981

GM2 8.9400 30 6.27269 1.14523

Pair 2 A1C 8.8571 28 2.62275 .49565


Pair 1 GM1 - GM2 -3.230 29 .003 Significant

Pair 2 A1C - A1C2 2.071 27 .048 Significant

The Type 2 change revealed the most significant change (See Graph 3).

Findings/Discussion

The summary of findings in the small test of change was significant. If one evaluates the

data in Tables 3-5 and Graphs 1-3, evidence shows that the short term use of CGM device made

significant differences in the patients’ labs pre- and post CGM. This could be related to instant

feedback from the clinician and medicine regimen changes to more align with blood glucose

control as well as the patient possibly becoming more aware of how stress, sickness, food and

lack of medication effects blood sugar control.

Recommendations for future research and practice change

• Further evaluate use of CGM in relation to development of long-term complications –A

long term study of 2-5 years of continuous use of the CGM with pre- evaluation and post


evaluation of micro-vessel and macro -vessel disease, kidney function, nerve conduction

studies, gastric emptying studies, and lipid studies to determine if complications have

decreased as a result of better glucose control with the CGM.

• Evaluate results as to type of medications patient was on pre and post CGM (oral versus

insulin)- This would be interesting to see if Beta cell function returns with better glucose

control long term resulting in decreasing medications, possibly eliminating insulin in

Type 2 patients and less insulin needs in Type 1 patients.

• Evaluate lifestyle changes including dietary changes made as a result of wearing CGM-

Long term evaluation of food diary, weight management and exercise regimen changes or

beginning exercise programs as a result of seeing on the CGM how these changes in

lifestyle positively affect blood glucose control.

Conclusions

In concluding this project, the idea of evidence based practice has a new concept for this

author. Knowledge capacity has increased and a new respect for the process of studying effects

of change has tremendous respect. The key learning experiences learned in this process include

the preparation that takes place before a study can ever begin. The relevance for evidence base

practice when becoming a nurse practitioner is strong. Implementation is vital in the new

capacity this author will hold in the near future. In practicing, the goal is to stay involved in

evidence based research and possibly follow through this project in a larger capacity.


References

American Diabetes Association, (2011). Website; www.americandiabetesassociation.org.

Bergenstal, R.M., Tamborlane, W.V. & Ahmann, A. (2010). Effectiveness of sensor-augmented

insulin pump therapy in type 1 diabetes. New England Journal of Medicine, doi:

10.1056/NEJoal1002853

Bode, B., Beck, W.R., & Xing, D. (2008). Continuous glucose monitoring and intensive

treatment of type 1 diabetes. The New England Journal of Medicine, 359, 1464-1476.

Body, B., Beck, R.W., & Xing, D. (2009). Sustained benefit of continuous glucose monitoring

on A1C, glucose profiles, and hypoglycemia in adults with type 1 diabetes. Diabetes

Care, 32(11), 2047-2049.

Dungan, K. M., Buse, J. B., Largay, J., Kelly, M. M., Button, E. A., Kato, S., & Whittlin, S.

(2006). 1, 5-anhydroglucitol and postprandial hyperglycemia as measured by continuous

glucose monitoring system in moderately controlled patients with diabetes. Diabetes

care, 29(6), 1214-1219.

Dungan, K. M. (2008). 1, 5-anhydroglucitol (GlycoMark) as a marker of short-term glycemic

control and glycemic excursions. Expert review of molecular diagnostics, 8(1), 9-19.

http://www.americandiabetesassociation.org/


Ehrhardt, M.D., Chellappa, M., Walker, M.S., Fonda, S.J. & Vigersky, R.A. (2011). The effects

of real-time continuous glucose monitoring on glycemic control in patients with type 2

diabetes mellitus. Journal of Diabetes Science and Technology, 5(3), 668-675.

Hirsch, I.B, Abelseth, J., Bode, B.W., Fischer, J.S., & Kaufman, F.R. (2008). Sensor-augmented

insulin pump therapy: results of the first randomized treat-to-target study. Diabetes

Technology & Therapeutics, 10, 377-383.

Mcgill, J. B., Cole, T. G., Nowatzke, W., Houghton, S., Ammirati, E., Gautille, T., & Sarno, M.

(2004). Circulating 1, 5-anhydroglucitol levels in adult patients with diabetes reflect

longitudinal changes of glycemia: a U.S. trial of the glycomark assay. Diabetes care,

27(8), 1859-1865.

Manly, B.M., & Fineout-Overholt, E. (2011). Evidence-based practice in nursing and

healthcare. Philadelphia, Pennsylvania: Lippincott, Williams & Wilkins.

Raccah, D., Sulmont, V., & Reznik, Y. (2009). Incremental value of continuous glucose

monitoring when starting pump therapy in patients with poorly controlled type 1 diabetes:

the real-trend study. Diabetes Care, 32, 2245-2250.

Sousa, V.D., Hartman, S.W., Miller, E.H. & Carroll, M.A. (2009). New measures of diabetes

self-care agency, diabetes self-efficacy and diabetes self-management for treating

individuals with T2DM. Journal of Clinical Nursing.pp. 1305-1314.

Stevens, K. R. (2004). ACE Star Model of EBP: Knowledge Transformation. Academic Center

for Evidence-based Practice. The University of Texas Health Science Center at San

Antonio. www.acestar.uthscsa.edu

http://www.acestar.uthscsa.edu/


Wojner, A. W. (2001). Outcomes management: Application to clinical practice. St. Louis, MO:

Mosby.

Table 1

Hemoglobin A1C chart and reference numbers


Table 2

GlycoMark Table reference


Graph 1

Type 1 and Type 2 Results illustration


Pre CGM Post CGM0

1

2

3

4

5

6

7

8

9

10 56 Total patients

A1CGM

Graph 2

Type 1 Results Chart


A1C GM0123456789

108.6

3.7

7.9

4.8

TYPE 1 RESULTS22 patients

PRE CGM POST CGM

Graph 3

Type 2 Results


A1C GM7.27.47.67.8

88.28.48.68.8

99.2

8.9

8.2

7.9

9

TYPE 2 RESULTS29 patients

PRE CGM POST CGM


Appendix A

Article citation in APA format

Purpose of study/research questions

Design type and methods (sampling method/sample size, description of interventions (if any), and outcomes measured

Major findings/findings relevant to project

Critique of validity, bias and significance

Body, B., Beck, R.W., & Xing, D. (2009). Sustained benefit of continuous glucose monitoring on a1c, glucose profiles, and hypoglycemia in adults with type 1 diabetes. Diabetes Care, 32(11), 2047-2049.

Level of Evidence= ll

The purpose of this study was to evaluate the long-term effects of the continuous glucose monitoring in the intensively treated type 1 diabetes patients.

Design: Randomized clinical trial witha 12-month follow-upMethod: 83 of 86 adults in the age of ≥ 25yrs Randomized to the continuous glucose monitoring system (CGMSSampling method-Convenience Outcomes- CGMS use

The median CGMS use was 7.0 days per week. Among subjects with baseline A1C ≥ 7.0% mean change in A1C from baseline to 12 months was -0.4 ± 0.6% (P< 0.001). The reduction in A1C occurred mainly in the first 8 weeks and then remained relatively stable though the next 44 weeks. Hypoglycemic events fell from 21.8% per 100 person-years during the first 6 months

Weaknesses: Some patients were on insulin pumps and some patients were on multiple daily injections. The different methods of regimen do lead to different outcomes. There were a low number of patient entries which decreases the validity of the significance for my project. The study was only conducted at one institution and decreases the wide variety of sampling in different subjects.

Strengths: Subjects had a sustained benefit of improved glucose


control noted by A1C levels and the amount of time sensor glucose values were in the target range. Low rate of severe hypoglycemic events during the extension phase of the study. A1C of 6.8% was a mean compared to the Diabetes Control and Complications Trial (DCCT) mean A1C of 7.1%. This is the guideline that most primary physicians use to tag a subject “controlled”. This study is very significant to my PICO question.

Significance to my project: This research article made me aware of the different types of continuous glucose monitors. It only studied adults who were randomly assigned to groups and is randomized so the information will help


me in my project. It also helped me identify important outcomes for CGM.

Ehrhardt, M.D., Chellappa, M., Walker, M.S., Fonda, S.J. & Vigersky, RA., (2011). The effects of real-time continuous glucose monitoring on glycemic control in patients with type 2 diabetes mellitus. Journal of Diabetes Science and Technology, 5(3), 668-675.


The purpose of this study was to test type 2 diabetes with Real-time continuous glucose monitoring (RT-CGM) on a variety of treatment modalities except prandial insulin.

Design: 52 week, prospective, two-arm, randomized controlled studyMethod: intervention

group compared to control group who used only self-monitoring of blood glucose (SMBG).Outcomes:A1c change at 12 weeks; change in number and dosage of hypoglycemic medications; difference in A1c

The mean (±standard deviation) decline in the A1C was 1.0% (±1.1%) in the RT-CGM group and 0.5% (±0.8%) in the SMBG group (p =0.006). There were no group differences in the net change in number or dosage of hypoglycemic medications. Those who used the RT-CGM for ≥48 days (per protocol) reduced the A1C by 1.2% (±1.1%) versus 0.6% (±1.1%) in those who used it <48 days (p= 0.003). There was no improvement in weight or blood pressure.

Weaknesses: There were a low number of patient entries which decreases the validity of this study. It would not provide adequate significant impact to my study. Only one location was used in this study.

Strengths: Study proved it is possible that those using a variety of therapies and all age groups may benefit from this type of an intervention

Significance for project: My project includes the T2DM population, a focus of this study. I have learned that CGM use has support for being effective in T2 no matter the tx.


Bergenstal, R.M., Tamborlane, W.V. & Ahmann, A. (2010). Effectiveness of sensor-augmented insulin pump therapy in type 1 diabetes. New England Journal of Medicine, doi: 10.1056/NEJoal1002853


The purpose of this study is to evaluate improvements in metabolic control in subjects with type 1 diabetes placed on sensor-augmented insulin pump therapy.

Design: Unmasked randomized, controlled trialMethod: Conducted at 30 diabetes centers in the United States and Canada.Sampling Method: Subjects used of MDI for 3 months, self-monitoring of blood glucose (SMBG) 4Xd for the previous 30 days

485 patients were analyzed. The difference in A1C between study groups favored pump patients on sensors as compared to MDI patients on sensors. The difference in A1C in the SAP group fell rapidly from baseline to 3 months and remained lower than levels in the MDI group for the rest of the study. An increased frequency of sensor use was associated with a greater reduction in A1C values from baseline to 1 year.

Weaknesses: There was no set determining amount of designated time to wear the sensor. It was not outlined in the study.

Strengths: Large number of subjects obtained for this study. Improvement in A1C levels was achieved without an increase in hypoglycemic events. A large number of adults and pediatric subjects in the SAP group reached ADA age specific A1C targets.

Significance to my project:I will definitely use the information obtained from this project mainly because of a large subject population in the study.


Bode, B., Beck, W.R., & Xing, D., (2008). Continuous glucose monitoring and intensive treatment of type 1 diabetes. The New England Journal of Medicine, 359, 1464-1476.


The Purpose of this study was to evaluate the efficacy and safety of continuous glucose monitoring (CGM) in adults and children with type 1 diabetes.

Design: Randomized control trialMethod:Eligibility criteria included: age ≥8 years, type 1 diabetes ≥ 1 year, use of either an insulin pump or ≥ 3 daily insulin injectionsSampling Method: Randomly assigned to either the CGM group or the control group.Clinic visits were conducted at 1, 4, 8, 13, 19, and 26 weeksOutcomes: change in glycated hemoglobin (A1C) from baseline to 1 year between the two study groups consisting of SAP and MDI

A mean A1C of <8.0%. There was a significant between-group difference in the change in A1C levels from baseline to 26 weeks in the subjects who were ≥ 25 years old, in favor of the CGM group (mean difference: -0.53%; 95% confidence interval: - 0.71% to -0.35%. CGM can lead to lower A1C levels and tighter control without a significant increase in hypoglycemia for adults with type 1 diabetes. Improvements by the youngest age group were due to more parental involvement.

Weaknesses: All subjects were not required to wear a sensor for the same amount of time. Only includes T1DM subjects which limit the study. T1DM population is only 10% of the diabetes population. The length of the study is not very long, therefore hard to obtain a true outcome.

Strengths: I like the wide age range included in the study. It allows me to see a true evaluation of the subjects studied. Provided knowledge that CGM does lower A1C without the increase in hypoglycemic events. A large population was studied and it was random. This allows me to trust the outcomes of this study for my project.


Significance for my project: I will use the data from this study because I like the age range that is used as well as the large population studied in this article.


Hirsch, I.B, Abelseth, J., Bode, B.W., Fischer, J.S., & Kaufman, F.R., (2008). Sensor-augmented insulin pump therapy: results of the first randomized treat-to-target study. Diabetes Technology &Therapeutics, 10, 377-383.


The purpose of the study was to evaluate the clinical effectiveness and safety of an insulin pump augmented with a real-time continuous glucose monitoring (CGM) compared with an insulin pump plus self-monitoring of blood glucose (SMBG).

Design: Randomized, treat-to-target, 6-month trial Subjects were between the ages of 12-72 years old.Method: Blinded CGM for 10 days to get a baseline data. Subjects were randomized to either the sensor group; which used a sensor-augmented pump, or the control group, which used SMBG.values wereSampling Method: End of the study the control group wore two blinded CGM sensors for two consecutive 3-day periods.Outcomes: AIC changes at 13, 26 weeks

A total of 146 adults and adolescents with type 1 diabetes were enrolled and randomized in the study; 72 subjects were assigned to the sensor group and 74 were assigned to the control group. Of the 138 subjects completing the study, 40 were adolescents 12 to 17 years of age and 98 were adults aged 18 years and older. A1C changes were significant in both groups. Twenty (30.8%) sensor subjects achieved A1C values of 7.0% by week 13 compared with 8 (11.1%) of the control subjects. At the end of the study, 16 subjects (24.2%) in the sensor group reached the target A1C of < 7.0% versus 12 (19.4%) in the control group.

Weaknesses: There were a low number of patients in the study which decreased the validity of the study. There is no way to determine if the improvement is from the intensive education or the continuous glucose monitor.

Strengths: Multiple sites were used for the study- 10 locations. Multiple age groups were studied to allow for more factors, life styles, and activities to be studied. Only subjects in the sensor group improved their blood sugar control without increasing the amount of time spent in the hypoglycemic range. It was found that the greater the sensor utilization, the more significant the glycemic improvement. The study found that patent selection for CGM


therapy should take into account patient willingness and ability to use the technology appropriately.

Significance to my project: The treat-to target concept is vital to making A1C goals. This article speaks to this concept very clearly and I will focus part of my assignment on this article.


Raccah, D., Sulmont, V., & Reznik, Y. (2009). Incremental value of continuous glucose monitoring when starting pump therapy in patients with poorly controlled type 1 diabetes: the real-trend study. Diabetes Care, 32, 2245-2250.

Level of Evidence= II

The purpose of the study wasto investigate the benefit of continuous glucose monitoring (CGM) with the initiation of insulin pump therapy in subjects with poor metabolic control despite optimized basal-bolus insulin injection therapy.

Design: 132 subjects, randomized, parallel-group, two-arm, open-label trial. Eight centers in France (6 adult centers and 2 pediatric centers)Method: 6 month study duration.

Blinded CGM was used by all subjects for biochemical hyperglycemia and hypoglycemia parameters at the beginning and end of the study.Sampling Method: CSII subjects fitted with Minimed pump and agreed to use sensors at least 70% of the time.

A1C levels were significantly reduced within the Paradigm Real-Time (PRT) group and the pump group. The greatest A1c reduction occurred in the PRT group when using sensors at least 70% of the time in study. PRT subjects bloused more frequently after one month of treatment and at study end. A higher percentage of insulin was delivered as bolus in the PRT group vs. CSII group. Twice as many study subjects in the PRT group reported that they made modifications to their eating habits and lifestyle vs. study subjects using CSII alone. Over 90% of subjects in the PRT group used CGM data to manage their diabetes by adjusting insulin doses and 59% used CGM data to manage glycemic excursions.

Weaknesses: The study does not have a minimal SMBG testing frequency prior to the study as a requirement. No education was provided (or at least mentioned) for all patients prior to the study. Short trial duration. Not in U.S. Alarms and glucose trends information available to the PRT subjects may have been helpful for control.

Strengths: The study that continuous glucose monitoring does improve glycemic control. According to this study, no study had investigated the benefit of continuous glucose monitoring (CGM) at insulin pump initiation in patients with poor metabolic control on multiple daily injections (MDI). PRT subjects bloused more frequently


after one month of treatment and at study end.

Significance to my project:The focus of my PICO question is addressed in this article but I feel that the specifics are not strong. Several details, if you note my “weaknesses” comments bring concern to me. I will use some of the information for my project.


Dungan, K. M., Buse, J. B., Largay, J., Kelly, M. M., Button, E. A., Kato, S., & Whittlin, S. (2006). 1, 5-anhydroglucitol and postprandial hyperglycemia as measured by continuous glucose monitoring system in moderately controlled patients with diabetes. Diabetes care, 29(6), 1214-1219.

The purpose of this study is to demonstrate the relationship between 1,5-AG and postprandialhyperglycemia, as assessed by the continuous glucose monitoring system (CGMS) in sub optimallycontrolled patients with diabetes.

The design: Patients with type 1 or type 2 diabetes andan HbA1c (A1C) between 6.5 and 8% with stable glycemic control were recruited from two sites.

A CGMS monitor was worn for two consecutive 72-h periods. Mean glucose, mean post mealmaximum glucose (MPMG), and area under the curve for glucose above 180 mg/dl (AUC-180),were compared with 1, 5-AG, fructosamine (FA), and A1C at baseline, day 4, and day 7.

Results: 1,5-AG reflects glycemic excursions, often in the postprandial state,more robustly than A1C or FA. 1,5-AG may be useful as a complementary marker to A1C toassess glycemic control in moderately controlled patients with diabetes.

Weaknesses: The one weakness seen in this study was the small testing population of only 40 participants. It is hard to establish data on a small patient study.

Strengths: This study directly correlates to the significance of evidence for this project. There is much data regarding A1C lab work but not many on the GM lab results and effects.

Significance to Project: This article is very significant to my project and the contents of the study.


Mcgill, J. B., Cole, T. G., Nowatzke, W., Houghton, S., Ammirati, E., Gautille, T., & Sarno, M. (2004). Circulating 1, 5-anhydroglucitol levels in adult patients with diabetes reflect longitudinal changes of glycemia: a U.S. trial of the glycomark assay. Diabetes care, 27(8), 1859-1865.

Level of Evidence=II

The purpose of this study is to evaluate the ability of 1, 5-AG measurements to monitor glycemic control.

Glycemic control in a cohort of 77 patients with diabetes ( 22 with type 1 DM and 55 with Type 2 diabetes) who presented with suboptimal glycemic control at baseline (defined as A1C) >or= 7%. Each patient received DM education, counseling and addition or dose adjustment of various insulins or oral antihyperglycemic medications. Therapy was targeted to reduce mean A1C by > 1% over the monitoring period. 1,5AG, A1C and random glucose measurements were performed at baseline and at 2, 4 and 8 weeks.

1,5AG, and glucose values progressed significantly toward euglycemia by week 2 of monitoring with median changes of 93, -7, and -13% for 1,5AG and glucose respectively. In contrast, A1C results did not respond significantly to therapy until week 4.

Weakness: Not enough participants to be valid. Needs further testing. No mention of CGM devices.

Strengths: Very closely related to what evidence trial to studying in PICO question.

Relevance to study: Very relevant to this evidence based study as it relates to correlating the importance of A1C results as well as GM.


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