the management of diabetes has seen changes in the past 30  years , which have improved the lives of patients afflicted with this disease .
improvement in glucose measurement started with the introduction of selfmonitoring of blood glucose ( smbg ) in the late 1980s , which was one of those important changes .
as the second device for measurement of blood glucose level , the continuous glucose monitoring system ( cgm ) was introduced to the market around the beginning of this century .
it provides maximal information about fluctuations in blood glucose levels throughout the day and optimal treatment decisions to control diabetes . in 1999 , the food and drug administration approved the cgm device in the usa .
since then , the device has been improved dramatically , and the realtime cgm and insulin pumpintegrated system are already available commercially in the usa and europe . in japan , the history of cgm is relatively short .
the ministry of health , labor and welfare approved the cgm device in 2009 , approximately 10  years after the usa .
furthermore , the secondgeneration blind cgm , the minimed gold of medtronic , has been the only device approved under the governmentsupported medical insurance in japan .
a new wireless , but blind cgm , is going to be in japanese market in a very near future , at last . with this different historical background
, cgm has already been studied extensively in the usa and europe . at this stage , it is necessary for japanese clinicians to know what has already been investigated . in particular , we need to understand whether the continuous glucose monitoring system really is an accurate , safe and clinically effective device , or not . in the present article ,
we review the literature and introduce some useful information on diabetes care in the clinical setting especially to the physicians in countries with short history of cgm .
the diabetes control and complications trial ( dcct ) confirmed that patients treated intensively with insulin show better results with regard to the prevention of diabetic microvascular complications than those treated conventionally .
however , we also know that the intensive insulin therapy enhances the risk of hypoglycemia . patients who experience frequent episodes of hypoglycemia often develop various abnormalities and lose their ability to detect hypoglycemia .
hypoglycemia unawareness and it perpetrates  a vicious cycle of recurrent hypoglycemia. however , there is strong evidence showing that minimization of the hypoglycemic episodes through more meticulous glucose control can actually reverse many of the counterregulatory defects . for meticulous glucose control and prevention of hypoglycemia ,
the cgm is a useful device , as it provides maximal information about fluctuating blood glucose levels throughout the day .
the finger stick test provides only information on blood glucose at one point in time , so even if  hypoglycemia unawareness occurs between the measured points , we are not able to detect it . with the cgm , we might accomplish both purposes  better control with the intensive insulin therapy and prevention of 
hypoglycemia unawareness. the cgm is a method that provides constant checking of blood glucose level through measurement of glucose concentrations in the interstitial fluid .
the minimed gold of medtronic , which is currently available and used in japan under the governmentbased health insurance system , features a sensor inserted in the subcutaneous tissue just under the skin of the abdomen .
the sensor comprises a flexible , platinumplated electrode housed inside a permeable membrane , which can be used for up to 72  h. subcutaneous glucose level is measured by the glucoseoxidase method , and the interstitial glucose level measured every 10  s is sent to a monitor that shows the average blood glucose value every 5  min .
the minimed gold calculates blood glucose values in the range of 40400  mg / dl .
athough the user has no access to realtime glucose levels , the measured data can be downloaded into a spreadsheet .
this is carried out at least four times a day in the minimed gold , using the finger stick test .
it means that selfmonitoring of blood glucose is closer to real glucose levels , the venous glucose levels , at any one point in time .
it should be noted that the device has a time lag between blood and interstitial glucose levels .
there was no information on the performance of the sensor during sustained hypoglycemia or during recovery from hypoglycemia at that time .
venous blood glucose levels were maintained at euglycemia for the first 60  min , then fell to 45  mg / dl for 60  min , but were finally restored to euglycemia .
the sensor profiles paralleled blood glucose levels at each of the three plateaus with a correlation coefficient of 0.79 , and mean absolute error of 7% .
the drop in glucose level measured by the sensor closely matched the drop in blood glucose , but the recovery from hypoglycemia was delayed by an average of 26  min .
the device was the firstgeneration minimed cgm , which was probably less accurate than the secondgeneration , minimed gold . in 2003 , boyne et  al . tried to measure a time lag between the firstgeneration minimed cgm and blood glucose , and also between the different sensors .
a total of 14 patients with type 1 diabetes each had two sensors placed subcutaneously in the abdomen , acquiring data every 5  min . at the same time , blood glucose was sampled every 5  min for 8  h. the results showed that the  time differences between blood and interstitial glucose levels ranged from 4 to 10  min , with the interstitial glucose lagging behind blood glucose in 81% of cases .
the mean (   sd ) difference between the two sensors in each patient was 6.7    5.1  min , representing random variation in sensor response. the authors also showed that the lag times were statistically significant for the rise ( 10.1    10.1  min , p  <  0.001 ) , fall ( 6.9    8.5  min , p  =  0.017 ) and nadir ( 9.4    7.7  min , p  <  0.001 ) in glucose levels . in each case , blood glucose level preceded that of interstitial glucose .
other groups reported similar results , although there was some variability among the different studies .
thus , the main conclusions were that there is a time lag between the measured interstitial glucose levels and actual blood levels , and that the different sensors have different sensitivities in measuring interstitial glucose levels .
the clarke error grid analysis ( ega ) , designed by william l clarke , was first reported in 1987 .
the ega is designed for smbg to evaluate the agreement and discrepancy between blood glucose values and sensor readings at isolated static points in time .
this method was innovative , because it took into account not only the difference between the systemgenerated and reference blood glucose values , but also the clinical significance of this difference .
in other words , clarke et  al . tried to evaluate the accuracy and clinical significance of the continuous glucose monitoring system . in 2004
, they also reported an improvement to the original ega , and introduced the cgega , the continuous glucoseerror grid analysis .
cgega was specifically designed to evaluate the clinical accuracy of continuous glucose monitoring in terms of precision of both blood glucose readings and blood glucose rate of change .
temporal characteristics of the data , analyzing pairs of reference and sensor readings as a process in time represented by a  bidimensional time series and taking into account inherent physiological time lags . in this method
, they introduced a new concept of  rateerror grid analysis ( rega) in addition to modifying the traditional ega into a new  pointerror grid analysis ( pega) that reflects the temporal characteristics of blood glucose .
the rega is a rateerror grid analysis that assesses  the sensor s ability to capture the direction and rate of blood glucose fluctuations. for each pair of rbg ( reference blood glucose ) readings ( rbg [ t1 ] , rbg [ t2 ] ) taken at times t1 and t2 , the rbg rate is computed as bg divided by the elapsed time .
the rbg rate of change ( mg / dl / min )  =  ( rbg [ t2 ]    rbg [ t1])/(t2   
similarly , for each sensor blood glucose ( sbg ) pair ( sbg [ t1 ] , sbg [ t2 ] ) , sbg rate is computed as sbg rate of change ( mg / dl / min )  =  ( sbg [ t2 ]    sbg [ t1]/[t2    t1 ] ) .
then , the sbg rate is plotted against the rbg rate ( figure  1 ) .
the pega is a pointerror grid analysis that evaluates the sensor s accuracy in terms of  correct representation of blood glucose values. point accuracy reflects the difference between two paired samples at one point in time ( figure  2 ) .  the rateerror grid analysis ( rega ) divided into ar , br , cr , dr and er for sensor blood glucose ( sbg ) rate vs reference blood glucose ( rbg ) rate .
the pointerror grid analysis ( pega ) divided into ap , bp , cp , dp and ep for sensor blood glucose ( sbg ) vs reference blood glucose ( rbg ) .
the pega zones are defined based on the reference rate of changes in blood glucose .
both the rega and pega divide the glucose rate or glucose ranges into clinically meaningful zones : 
zone a , corresponding to clinically accurate reading ; zone b , corresponds to benign errors ; zone c , signifies overcorrection errors ; zone d , indicates failure to detect clinically significant rate of change in blood glucose ; and zone e , indicates an erroneous reading. the pega zones are defined depending on the reference rate of bg changes .
the cgega recognizes that the clinical meaning of rate accuracy depends greatly on the absolute blood glucose level , with different blood glucose levels requiring different interpretations of the combination rega  +  pega .
for this reason , the cgega computes the combined accuracy of rega  +  pega in three clinically relevant regions : hypoglycemia ( blood glucose 70  mg / dl ) , euglycemia and hyperglycemia ( blood glucose > 180  mg / dl ; figure  3 ) . as the cgega is intended for software application , most of these parameters could be user selectable .
for example , the time lag between blood and interstitial glucose has a default value of 7  min , based on literature data .
if a device has a longer technical lag , then the software would allow the time lag used by the pega to be changed . 
the continuous glucoseerror grid analysis ( cgega ) computes the accuracy of the combination of rateerror grid analysis ( rega ) plus pointerror grid analysis ( pega ) into three clinically relevant regions : hypoglycemia ( blood glucose 70  mg / dl ) , euglycemia and hyperglycemia ( blood glucose > 180  mg / dl ) .
used the cgega to evaluate the continuous glucose monitoring system , therasense freestyle navigator . using the cgega
, they reported that the accuracy of the navigator , measured as a percentage of accurate readings plus benign errors , was significantly different at hypoglycemia ( 73.5% ) , euglycemia ( 99% ) and hyperglycemia ( 95.4% ) .
wentholt et  al . explored the cgega by comparing it with classical accuracy assessment methods , such as correlation , linear regression and mean absolute difference ( mad ) , using data reported in a previous study that compared two different continuous glucose sensors in type 1 diabetic patients .
they found differences in the accuracy of mad and cgega , and that the cgega was not reliable .
in contrast , clarke et  al . responded by showing that the methods used by wentholt unfortunately failed to take into account the basic structure of continuous glucose monitoring data , which represents a time series analysis .
they reported that it is impossible to compare the different methods altogether , and approached the issue of accuracy by applying several different methods for  each different purpose .
using the different methods complementarily is the most effective way to prove the accuracy of the device .
the investment in cgega , which has been widely used by scholars until now , is really meaningful for assessing the accuracy of cgm . by using multiple established assessment methods for evaluation
, we can reach the true accuracy of cgm , thus ensuring the safety and clinical effectiveness of the device .
in the symposium , wolpert published some important points . as we already know , there is a lag time between interstitial and blood glucose .
the lag time ranges from 5 to 15  min depending on the rate of glucose change . increasing glucose levels are reflected first in capillary blood .
however , detecting decreases in glucose after insulin injection or exercise might be confounded by the placement of the cgm sensor .
for example , if the cgm sensor is placed next to an insulinsensitive tissue , the glucose level might decrease first in the interstitial fluid before it is reflected in capillary blood glucose . also , wolpert pointed out that the sensor needs to be calibrated when glucose is  in a steady state. if the patient carried out the calibration when glucose is rising at 3  mg / dl / min and there is a 10min lag , then there will be a discrepancy of approximately 30  mg / dl between the capillary glucose measurement and the interstitial glucose measurement .
another important point relates to the education of the patient . in the usa and europe ,
the realtime cgm are already available on the market , and many articles have been published on the device the realtime cgm wireless type is a very convenient and useful device , but it can potentially lead to excess treatment based on the measured data . if patients overcompensate for rising glucose levels using frequent bolus injections of insulin , they are at increased risk of hypoglycemia .
also , patients could reduce or discontinue basal insulin therapy in order to avoid hypoglycemia .
this occurs more commonly in patients who lack the understanding of the concept of the lag time between capillary and interstitial glucose , thus considering their glucose to be much lower than it actually is .
we need to educate these patients about insulin pharmacodynamics , as well as the factors that affect postprandial glucose patterns .
they must also be taught not to rely on interstitial glucose data alone to assess hypoglycemia .
a group at the mayo clinic concluded that the device was associated with a significant reduction in mean glycated hemoglobin ( hba1c ) .
it was true for adults with type 1 diabetes as well as type 2 diabetes .
there was no significant difference in hba1c reduction between studies of realtime vs nonrealtime devices , if the devices were appropriately used .
the metaanalysis by mayo clinic is important , because it was newly published in 2011 , and the number of the trials providing the data , 19 , was the biggest among the metaanalyses about cgm .
data of adverse events were available only in a few trials and comprised mainly mild reactions , such as redness and itching , at the sensor implantation site .
the device errors of data storage , and alarms going off infrequently occurred . in october 2011 ,  continuous glucose monitoring : an endocrine society clinical practice guideline was published .
even if there are various conclusions in metaanalyses about cgm , the task force evaluated  three potential uses of cgm : ( i ) realtime cgm in an adult hospital setting ; ( ii ) realtime cgm in children and adolescent outpatients ; and ( iii ) realtime cgm in adult outpatients .
the authors used the available data to develop evidencebased recommendations for good control of glycemia and limiting the risk of hypoglycemia . in that guideline ,
an alternative for patients who can not safely and effectively take advantage of the information provided to them by realtime cgm , even though there are some studies concluding that there was no significant difference in hba1c reduction between realtime vs nonrealtime devices .
however , it might be an appropriate statement in countries where the realtime cgm is the first choice cgm .
by reviewing the literature on cgm , we understand that this device has the potential to improve diabetes care in the clinical setting , provided we take into consideration its pros and cons .
there is a need for more knowledge about its accuracy , safety and clinical effectiveness through daily medical examination .
furthermore , the introduction of the more developed devices , such as realtime cgm available in the usa and europe , under the japan governmentsponsored healthcare system should be encouraged .
 abstractthe continuous glucose monitoring system ( cgm ) has been used for constant checking of glucose level by measuring interstitial glucose concentrations , since the early days of the 21st century . 
 it can potentially improve diabetes care if used carefully with the understanding of the characteristics of this system . 
 although there is a time lag of approximately 515  min between blood and interstitial glucose levels , the system is considered the most suitable device for meticulous glucose control and prevention of hypoglycemia . 
 a large number of studies have examined its accuracy , safety and clinical effectiveness . 
 the continuous glucoseerror grid analysis ( cgega ) , designed by wl clarke , evaluates the clinical accuracy of cgm . 
 it examines  
 temporal characteristics of the data , analyzing pairs of reference and sensor readings as a process in time represented by a  
 bidimensional time series and taking into account inherent physiological time lags . 
 investment in cgega is clearly meaningful , even though there are other methodologies for evaluation . 
 the use of each method complementarily is the most effective way to prove the accuracy of the device . 
 the device has improved gradually , and realtime cgm , which allows realtime monitoring of blood glucose level , is already available commercially . 
 the use of realtime cgm could potentially lead to over or undertreatment with insulin . 
 patient education through proper and effective handling of the new device is essential to improve diabetes care . 
 ( j diabetes invest , doi : 10.1111/j.20401124.2012.00197.x , 2012 ) 
Introduction
Merits of the Continuous Glucose Monitoring System
Time Lag Between Blood and Interstitial Glucose Levels
Continuous GlucoseError Grid Analysis
Pros and Cons of the CGEGA
Importance of Patient Education
MetaAnalysis and Guideline about CGM
Conclusion