1107_diabetesupdate_draftguidelines[1]

Title: Guidelines and Recommendations for Laboratory Analysis

in the Diagnosis and Management of Diabetes Mellitus

Authors: David B. Sacks1?,Mark Arnold2, George L. Bakris3, David E. Bruns4, Andrea R. Horvath5, M. Sue Kirkman6, Ake Lernmark7, Boyd E. Metzger8, and David M. Nathan9 Addresses: 1Department of Pathology

Brigham and Women’s Hospital and Harvard Medical School

Thorn 530

75 Francis Street

Boston, MA 02115

2Department of Chemistry

University of Iowa

Iowa City, Iowa 52242

3Department of Medicine

Section of Endocrinology, Diabetes and Metabolism

University of Chicago

5841 South Maryland Avenue, MC1027

Chicago, IL 60637

4Department of Pathology

University of Virginia Medical School

Box 800168

Charlottesville, V A 22908-0001

5Department of Clinical Chemistry

University of Szeged

Albert Szent-Gyorgyi Medical and Pharmacological Centre

Somogyi Bela ter 1, Szeged

H-6725, Hungary

6American Diabetes Association

1701 N. Beauregard St.

Alexandria, V A 22311

7Department of Medicine

University of Washington

Office: K-165 HSC, Box 357710

1959 NE Pacific Street

Seattle, WA 98195-7710

8Northwestern University

The Feinberg School of Medicine

Division of Endocrinology

303 E. Chicago Ave., Tarry 15-735

Chicago, IL 60611

9Massachusetts General Hospital Diabetes Center

50 Staniford Street, Suite 340 Boston, MA 02114

Nonstandard abbreviations: OGTT, oral glucose tolerance test; FPG, fasting plasma glucose; IMD, immune-mediated diabetes; SMBG, self-monitoring of blood glucose; GHb, glycated hemoglobin; DCCT, Diabetes Control and Complications Trial; UKPDS, United Kingdom Prospective Diabetes Study; ADA, American Diabetes Association; NGSP, National Glycohemoglobin Standardization Program; CI, confidence intervals; GDM, gestational diabetes mellitus; WHO, World Health Organization; IGT, impaired glucose tolerance; IFG, impaired fasting glucose; DKA, diabetic ketoacidosis; AcAc, acetoacetate; βHBA, β hydroxybutyrate; CAP, College of American Pathologists; MODY, maturity onset diabetes of youth; ICA, islet-cell cytoplasm antibodies; GAD65, 65-kDa isoform of glutamic acid decarboxylase; IAA, insulin autoantibodies; JDF, Juvenile Diabetes Foundation; FDA, Food and Drug Administration; HDL, high density lipoprotein; LDL, low density lipoprotein; CAD, coronary artery disease; CDC, Centers for Disease Control.

INTRODUCTION

Diabetes mellitus is a group of metabolic disorders of carbohydrate metabolism in which glucose is underutilized, producing hyperglycemia. The disease is classified into several categories. The revised classification, published in 1997 (1) is indicated in Table 1. Type 1 diabetes mellitus, formerly known as insulin-dependent diabetes mellitus (IDDM) or juvenile onset diabetes mellitus, is caused by autoimmune destruction of the β-cells of the pancreas, rendering the pancreas unable to synthesize and secrete insulin (2). Type 2 diabetes mellitus, formerly known as non-insulin-dependent diabetes mellitus (NIDDM) or adult-onset diabetes, results from a combination of insulin resistance and inadequate insulin secretion (3, 4). Other types of diabetes are rare. Type 2 is the most common form, accounting for 90-95% of diabetes in developed countries. Some patients cannot be clearly classified as type 1 or type 2 diabetes (Balasubramanyam 2006).

In 1992 the costs of diabetes in the U.S. were estimated to be $98 billion (5). The mean annual per capita health care costs for an individual with diabetes are approximately 4-fold higher than those for individuals who do not have diabetes (5). Similarly, in the UK diabetes accounts for roughly 10% of the National Health Service budget (￡49 billion).

The high costs of diabetes are attributable to care for both acute conditions (such as hypoglycemia and ketoacidosis) and debilitating complications (6). The latter include both microvascular complications – predominantly retinopathy, nephropathy and neuropathy – and macrovascular complications, particularly stroke and coronary artery disease. Together these result in diabetes being the seventh most common cause of death in the developed world (7).

The American Diabetes Association (ADA) publishes in January each year a supplement, titled Clinical Practice Recommendations, to Diabetes Care. This is a compilation of all ADA position statements related to clinical practice and is an important resource for health care professionals who care for people with diabetes. The National Academy of Clinical Biochemistry has developed evidence-based guidelines for the practice of laboratory medicine. The guidelines in this document are based on the best available published evidence. An assessment was made of virtually all analytes used in the diagnosis and management of individuals with diabetes.

A new scheme to grade the quality of scientific evidence for diagnostic tests is under development. This scheme will be used in the final document to describe the quality of the evidence on which each recommendation is based. No ratings have been used in this draft version of the document.

To facilitate comprehension and assist the reader, each analyte is divided into several headings and subheadings (listed in parentheses). These are use (diagnosis, screening, monitoring and prognosis), rationale (diagnosis and screening), analytical considerations [preanalytical (including reference values) and analytical (such as methods)], interpretation (including frequency of measurement and turnaround time) and, where applicable, emerging considerations, which alert the reader to ongoing studies and potential future aspects relevant to that analyte.

This document is based on the guidelines published in 2002 (Sacks, 2002). All modifications and additions in this draft are indicated by bold font. New references are listed at the end of each section. To enhance clarity for the reader, deletions are not indicated, unless these pertain to a Recommendation.

NEW REFERENCES

Balasubramanyam A, Garza G, Rodriguez L, Hampe CS, Gaur L, Lernmark A, Maldonado MR. Accuracy and predictive value of classification schemes for ketosis-prone diabetes. Diabetes Care 2006; 29:2575-9.

Sacks DB, Bruns DE, Goldstein DE, Maclaren NK, McDonald JM, Parrott M. Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus. Clin Chem 2002; 48:436-72.

GLUCOSE

1. Use

A. Diagnosis/Screening

Recommendation: Glucose should be measured in plasma in an accredited laboratory to establish the diagnosis of diabetes.

Level of evidence: A TBD

Glucose should be measured in plasma in an accredited laboratory for screening of high-risk individuals. Outcome studies are needed to determine the effectiveness of screening.

Level of evidence: E TBD

Analysis in an accredited laboratory is not necessary for routine monitoring

Level of evidence: E TBD

The diagnosis of diabetes is established exclusively by the documentation of hyperglycemia (increased glucose concentrations in the plasma). In 1997, the diagnostic criteria (8) were modified (1) to better identify subjects at risk of retinopathy and nephropathy. The revised (current) criteria include: (a) symptoms of diabetes and casual (i.e., regardless of the time of the preceding meal) plasma glucose ≥11.1 mmol/L (200 mg/dL), (b) fasting plasma glucose (FPG) ≥ 7.0 mmol/L (126 mg/dL) or (c) 2-h postload glucose > 11.1 mmol/L (200 mg/dL) during an oral glucose tolerance test (OGTT) (1). If any one of these three criteria is met, confirmation by repeat testing on a subsequent day is necessary to establish the diagnosis. (Note that repeat testing is not necessary in patients who have unequivocal hyperglycemia with acute metabolic decompensation.) Although included as a criterion, the OGTT was not recommended for routine clinical use in non-pregnant individuals (see below).

In 2003 the ADA lowered the threshold for “normal” FPG from <6.1 mmol/L (110 mg/dL) to <5.6 mmol/L (100 mg/dL) (Genuth, 2003). This change is supported by data that individuals with FPG values between 5.6 mmol/L (100 mg/dL) and 6.05 mmol/L (109 mg/dL) are at increased risk for the development of type 2 diabetes (Tai, 2004; Gabir, 2000). Notwithstanding this reduction, more recent evidence, obtained from 13,163 men aged 26-45 years with FPG <5.55 mmol/L (100 mg/dL) who were followed for a mean of 5.7 years, indicates that lower FPG concentrations predict type 2 diabetes (Tirosh, 2005). Men with FPG 4.83-5.05 mmol/L (87-91 mg/dL) have a significantly increased risk of type 2 diabetes compared to those with FPG <4.5 mmol/L (81 mg/dL). Although the prevalence of diabetes is low at these glucose concentrations, the data support the concept of a continuum between FPG and the risk of diabetes. However,

there is no evidence that reducing the cutoff to a value lower than 5.6 mmol/L (100 mg/dL) is beneficial.

Population screening for type 2 diabetes, previously controversial, is now recommended for those at risk of developing the disease (American Diabetes Association, 2007)(9). The ADA proposes that all asymptomatic people aged 45 years or more, particularly those with BMI ≥ 25 kg/m2, should be screened in a health care setting. Either FPG or 2-h OGTT or both are appropriate for screening (American Diabetes Association, 2007). The FPG is more convenient, more reproducible, less costly and easier to administer than the 2-h OGTT. The FPG is therefore the recommended initial screening test (American Diabetes Association, 2007). If FPG is <5.6 mmol/L (100 mg/dL) and/or 2-h plasma glucose is <7.8 mmol/L (140 mg/dL), testing should be repeated at 3-year intervals. Screening should be considered at a younger age or be carried out more frequently in individuals at increased risk of diabetes (see Ref (American Diabetes Association, 2007) for conditions associated with increased risk). Because of the increasing prevalence of type 2 diabetes in children, screening of children is now advocated (10). Starting at age 10 years, testing should be performed every 2 years in overweight individuals who have two other risk factors, namely family history, race/ethnicity and signs of insulin resistance (10). Despite these recommendations and the demonstration that interventions can delay, and sometimes prevent, the onset of type 2 diabetes in individuals with impaired glucose tolerance (IGT) (Knowler, 2002; Tuomilehto, 2001), there is no published evidence that treatment based on screening has value. In addition, there is a lack of consensus in the published literature as to which screening procedure, FPG, OGTT and/or hemoglobin A1c (HbA1c), is the most appropriate (Icks, 2005; Perry, 2001; Jesudason, 2003). Based on evaluation of NHANES III, it has been proposed that an improved strategy is to screen by FPG whites who are ≥40 years and other propulations ≥30 years of age (Dallo, 2003). The cost-effectiveness of screening for type 2 diabetes has been estimated. The incremental cost of screening all persons aged 25 years or older was estimated to be $236,449 per life-year gained and $56,649 per quality-adjusted life-year (QALY) gained (11). Interestingly, screening was more cost-effective at ages younger than the 45 years currently recommended. In contrast, screening targeted to individuals with hypertension reduces the QALY from $360,966 to $34,375, with ages 55 to 75 years being most cost-effective (Hoerger, 2004). Modelling run on one million individuals suggests there is considerable uncertainty as to whether screening for diabetes would be cost effective (Glumer, 2006). Long-term outcome studies are necessary to provide evidence to resolve the question of the efficacy of screening for diabetes (Greenberg, 2002).

A.Monitoring/Prognosis

Recommendation: Although there is evidence linking high plasma glucose concentrations to adverse outcome, substantially more data are available that directly correlate increased glycated hemoglobin with complications of diabetes. Routine measurement of plasma glucose concentrations in an accredited laboratory is not recommended as the primary means of monitoring or evaluating therapy in individuals with diabetes.

Level of evidence: E TBD

There is a direct relationship between the degree of plasma glucose control and the risk of late renal, retinal and neurological complications. This correlation has been demonstrated for both type 1 (12) and type 2 (13) diabetes. Persons with type 1 diabetes who maintained lower average plasma

glucose concentrations exhibit a significantly lower incidence of microvascular complications, namely diabetic retinopathy, nephropathy and neuropathy (12). Although intensive insulin therapy reduced hypercholesterolemia by 34%, the risk of macrovascular disease was not significantly decreased in the original analysis (12). Longer follow up documented a significant reduction in cardiovascular disease in patients with type 1 diabetes who had intensive glycemic control (Nathan, 2005). The effects of tight glycemic control on microvascular complications in patients with type 2 diabetes (13) are almost identical to those with type 1. Intensive plasma glucose control in patients with type 2 diabetes significantly reduced microvascular complications. While meta analysis suggests that intensive glycemic control in individuals with type 2 diabetes reduces cardiovascular disease (Selvin, 2004), no significant difference in macrovascular disease (myocardial infarction or stroke) has been demonstrated in these patients (13). In both the Diabetes Complications and Control Trial (DCCT) and United Kingdom Prospective Diabetes Study (UKPDS), patients in the intensive group maintained lower median plasma glucose concentrations. Analyses of the outcomes were linked to glycated hemoglobin (GHb), which was used to evaluate glycemic control, rather than glucose concentration. Moreover, most clinicians use the ADA recommendations which define a target GHb concentration as the goal for optimum glycemic control (American Diabetes Association, 2000)(14).

Evidence directly links higher glucose concentrations to a poor prognosis. For example, the 10 year survival of 6681 people in a Japanese town was reduced if FPG was > 7.8 mmol/L (140 mg/dL) (15). Similar findings were obtained in 1939 patients with type 2 diabetes followed for a mean of 15 years where multiple logistic regression revealed that the risk of death was significantly increased for patients with FPG ≥ 7.8 mmol/L (140 mg/dL) (16). Subjects with type 2 diabetes with FPG > 7.8 mmol/L (140 mg/dL) had increased cardiovascular mortality (17). Furthermore, comparison of 300 patients with a first myocardial infarction and 300 matched controls revealed that a moderately increased FPG was a risk factor for infarction (18). A systematic review indicates that hyperglycemia increases the risk of in-hospital mortality after myocardial infarction in patients with and without diabetes (Capes, 2000). Notwithstanding these observations, neither random nor fasting glucose concentrations should be measured in an accredited laboratory as the primary means of routine monitoring of patients with diabetes. Laboratory plasma glucose testing can be used to supplement information from other testing, to test the accuracy of self-monitoring (see below) or when adjusting the dose of oral hypoglycemic agents (9, 19). In addition, individuals with well-controlled type 2 diabetes who are not on insulin therapy can be monitored with periodic measurement of FPG, although analysis need not be done in an accredited laboratory {Howe-Davies, 1980 #1266, 20)

2.Rationale

A.Diagnosis

The disordered carbohydrate metabolism that underlies diabetes manifests as hyperglycemia. Therefore, measurement of plasma glucose is the sole diagnostic criterion. This strategy is indirect as hyperglycemia reflects the consequence of the metabolic derangement, not the cause. However, until the underlying molecular pathophysiology of the disease is identified, plasma glucose concentrations are likely to remain an essential diagnostic modality.

B. Screening

Screening is recommended for several reasons. The onset of type 2 diabetes is estimated to occur ~4-7 years before clinical diagnosis (21) and epidemiological evidence indicates that complications

may begin several years before clinical diagnosis. Furthermore, at least 30% of people in the U.S. with type 2 diabetes are undiagnosed (22). Notwithstanding this recommendation, there is no evidence that population screening of plasma glucose concentrations provides any benefit. Outcome studies should be performed to justify screening.

3.Analytical Considerations

A.Preanalytical

Recommendation:Blood for fasting plasma glucose analysis should be drawn after the subject has fasted overnight (at least 8 h). Plasma should be separated from the cells within 60 min; if this is not possible, a tube containing a glycolytic inhibitor such as sodium fluoride should be used for collecting the sample.

Level of evidence: B TBD

Blood should be drawn in the morning after an overnight fast (no caloric intake for at least 8 h during which time the subject may consume water ad lib (1). Published evidence reveals a diurnal variation in FPG, with mean FPG higher in the morning than in the afternoon, indicating that many cases of diabetes would be missed in patients seen in the afternoon (23). Glucose concentrations decrease ex vivo with time in whole blood due to glycolysis. The rate of glycolysis—reported to average 5-7% (~ 0.6 mmol/L; 10 mg/dL) per hour (24)—varies with the glucose concentration, temperature, white blood cell count and other factors (25). Glycolysis can be attenuated by inhibition of enolase with sodium fluoride (2.5 mg fluoride/mL of blood) or, less commonly, lithium iodoacetate (0.5 mg/mL of blood). These reagents can be used alone or, more commonly, with anticoagulants such as potassium oxalate, EDTA, citrate or lithium heparin. Although fluoride maintains long-term glucose stability, the rates of decline of glucose in the first hour after sample collection in tubes with and without fluoride are virtually identical (24). To minimize glycolysis, blood should be collected in a tube containing heparin, immediately placed on ice and the cells should be separated from plasma within 60 min (Stahl, 2001). (Note that leukocytosis will increase glycolysis even in the presence of fluoride if the white cell count is very high.) After 4 h, the glucose concentration is stable in whole blood for 72 h at room temperature in the presence of fluoride (24). In separated, nonhemolyzed, sterile serum without fluoride the glucose concentration is stable for 8 h at 25 °C and 72 h at 4 °C (26).

Glucose can be measured in whole blood, serum or plasma, but plasma is recommended for diagnosis. [Note that while the ADA recommends only plasma (American Diabetes Association, 2007), the WHO accepts measurement of glucose in plasma as well as venous or capillary whole blood (World Health Organization, 1999).] The molality of glucose (i.e., amount of glucose per unit water mass) in whole blood and plasma is identical. Although red blood cells are essentially freely permeable to glucose (glucose is taken up by facilitated transport), the concentration of water (kg/L) in plasma is approximately 11% higher than that of whole blood. Therefore, glucose concentrations in plasma are approximately 11% higher than whole blood if the hematocrit is normal. Glucose concentrations in heparinized plasma were reported in 1974 to be 5% lower than in serum (27). The reasons for the latter difference are not apparent but have been attributed to the shift in fluid from erythrocytes to plasma caused by anticoagulants. In contrast, a more recent study determined that glucose concentration in serum is slightly [~0.2 mmol/L (3.6 mg/dL)] lower than plasma (Stahl, 2001). Other studies have observed that glucose values measured in serum and plasma are essentially the same (Boyanton, 2002; Miles, 2004). Based on these findings, it is unlikely that

there is a substantial difference between glucose values in plasma and serum when assayed on current instruments. Nevertheless, carefully controlled studies are necessary to unequivocally resolve this question. Note that measurement of glucose in serum is not recommended for the diagnosis of diabetes (American Diabetes Association, 2007; World Health Organization, 1999). The glucose concentrations during an OGTT in capillary blood are significantly higher than those in venous blood mean of 1.7 mmol/L (30 mg/dL), equivalent to 20-25% (28), but the mean difference in fasting samples is only 0.1 mmol/L (2 mg/dL) (28, 29).

Reference values: Glucose concentrations in healthy individuals vary with age. Reference intervals in children are 3.3 – 5.6 mmol/L (60-100 mg/dL), similar to the adult range of 4.1 – 5.6 mmol/L (74-100 mg/dL) (Sacks, 2007). Note that the ADA criteria (1), not the reference values, are used for the diagnosis of diabetes. Moreover, the threshold for diagnosis of hypoglycemia is variable. The reference values are not useful to diagnose these conditions. In adults, mean fasting plasma glucose increases with increasing age from the third to the sixth decade (30), but does not increase significantly after age 60 (31, 32). By contrast, glucose concentrations after a glucose challenge are substantially higher in older individuals (31, 32). Evidence of an association of increasing insulin resistance with age is inconsistent (33). Aging does not appear to influence glucose homeostatis and visceral obesity seems to be responsible for the reported decrease in glucose tolerance in middle-age (Imbeault, 2003).

B. Analytical

Recommendation: Enzymatic methods for glucose analysis are relatively well standardized. Despite the low imprecision at the diagnostic decision limits of 7.0 mmol/L (126 mg/dL) and 11.1 mmol/L (200 mg/dL), classification errors may occur. Because of the relatively large intraindividual biological variability (CVs of ~ 5-7%), FPG values of 5.8 – 6.9 mmol/L (105-125 mg/dL) should be repeated and individuals with FPG of 5.3 – 5.7 mmol/L (96-104 mg/dL) should be considered for follow-up at intervals shorter than the current ADA recommendation of every 3 years.

Level of evidence: E TBD

Glucose is measured almost exclusively by enzymatic methods. Analysis of proficiency surveys conducted by the College of American Pathologists (CAP) reveals that hexokinase or glucose oxidase is used in virtually all the analyses performed in the U.S. (26). A few laboratories (~1%) use glucose dehydrogenase. At a plasma glucose concentration of ~8.6 mmol/L (154 mg/dL), imprecision among laboratories using the same method had a CV <3% (excluding manual methods) (Sacks, 2006). Similar findings have been reported for glucose analysis in samples from patients. For example, comparison of plasma samples from 240 subjects revealed a 5% difference in mean glucose concentrations measured by the hexokinase and glucose oxidase methods (34).

No consensus has been achieved on the goals for glucose analysis. Numerous criteria have been proposed to establish analytic goals. These include expert opinion (consensus conferences), opinion of clinicians, regulation, state of the art and biological variation (35). A rational and realistic recommendation that has received some support is to use biological criteria as the basis for analytic goals. It has been suggested that imprecision should not exceed one half of the within-subject biological CV (36, 37). For plasma glucose, a CV < 2.2% has been suggested as a target for imprecision, with 0% bias (37). Although this recommendation was proposed for within-laboratory error, it would be desirable to achieve this goal for inter-laboratory imprecision to minimize differences among laboratories in the diagnosis of diabetes in individuals whose glucose

concentrations are close to the threshold value.Therefore, the goal for glucose analysis should be to minimize total analytical error and methods should be without measureable bias. A national program using samples (e.g., fresh frozen plasma) that eliminate matrix effects should be developed to assist in the achievement of this objective.

4. Interpretation

Knowledge of intraindividual variability of FPG concentrations is essential for meaningful interpretation of patient values. An early study, which repeated the OGTT in 31 nondiabetic adults at 48 h intervals, revealed that FPG in 22 subjects (77%) varied by <10% and in 30 subjects (97%) varied by <20% (38). Biological variation includes within-subject and between-subject variation. Careful evaluation over several consecutive days revealed that intraindividual variation of FPG in healthy subjects [mean glucose of 4.9 mmol/L (88 mg/dL)] exhibited within- and between-subject CVs of 4.8-6.1 % and 7.5-7.8%, respectively (39, 40, 41). Larger studies have revealed 6.4-6.9% CVs for FPG in 246 normal {Mooy, 1996 #1339) and 193 newly diagnosed untreated patients with type 2 diabetes (42). The latter study, which measured FPG by glucose oxidase (intra- and interassay CVs <2%) on two consecutive days, obtained 95% confidence intervals (CI) of ± 14.8% for total variability and ±13.7% for biological variability. Similar findings were obtained with analysis of 685 adults from NHANES III where biological variability of FPG measured 2-4 weeks apart yielded 95% CI of 5.3-6.1% (mean 5.7%) (Selvin, 2007). Analysis of larger numbers of individuals from the same NHANES III database yielded within and between person CVs of 8.3 and 12.5, respectively, at a glucose concentration of ~5.1 mmol/L (92 mg/dL) (Lacher, 2005). If a CV (biological) of 6.9% is applied to a true glucose concentration of 7.0 mmol/L (126 mg/dL), the 95% CI would encompass glucose concentrations of 6.1-7.9 mmol/L (109-143 mg/dL). If the CV of the glucose assay (~3%) is included, the 95% CI is ~ ±18%. Thus, the 95% CI for a fasting glucose concentration of 7.0 mmol/L (126 mg/dL) would be 7.0 ±17% (126 ± 17%), namely 5.8-8.2 mmol/L (105-147 mg/dL). Using assay imprecision of 3% (CV) only (excluding biological variability), would yield 95% CI of 6.6 – 7.4 mmol/L (118-134 mg/dL) among laboratories for a true glucose concentration of 7.0 mmol/L (126 mg/dL). Performing the same calculations at the cutoff for impaired fasting glucose (IFG) yields 95% CI of 5.6 ± 18% (100 ± 18%), namely 4.6-6.6 mmol/L (82-118 mg/dL). One should bear in mind that these ranges include 95% of subjects and other individuals will be outside this range. The biological variability is substantially greater than analytic variability. Using biological variation as the basis for deriving analytical performance characteristics (35), the following desirable specifications for glucose have been proposed (43): analytical imprecision ≤3.3%, bias ≤2.5% and total error ≤7.9%.

A short turnaround time for glucose analysis is not usually necessary for the diagnosis of diabetes. In some clinical situations, such as acute hyper- or hypoglycemic episodes in the Emergency Department or treatment of diabetic ketoacidosis (DKA), rapid analysis is desirable. A turnaround time of 30 min has been proposed (44). However, this value is based on requirements by clinicians and no outcome data have been published that validate this figure. Inpatient management of diabetic patients may on occasion require a rapid turnaround time (minutes, not hours). Bedside monitoring with glucose meters (see below) has been adopted by many as a practical solution (45).

Frequency of measurement

The frequency of measurement of plasma glucose is dictated by the clinical situation. The ADA recommends that an increased FPG or abnormal OGTT must be confirmed to establish the diagnosis of diabetes (1). Screening by FPG is recommended every 3 years, more frequently in high-risk

individuals; however frequency of analysis in the latter group is not specified. Monitoring is performed by patients themselves who measure glucose with meters and by assessment of GHb in an accredited laboratory (see below). Appropriate intervals between measurements of glucose in acute clinical situations (e.g., patients in hospital, patients with DKA, neonatal hypoglycemia, etc.) are highly variable and may range from 30 min to 24 hours or more.

1.Emerging considerations

Non- or minimally-invasive analysis of glucose is addressed below.

NEW REFERENCES

American Diabetes Association. Standards of medical care in diabetes--2007. Diabetes Care 2007;30 Suppl 1:S4-S41.

Boyanton BL, Jr., Blick KE. Stability studies of twenty-four analytes in human plasma and serum. Clin Chem 2002;48:2242-7.

Capes SE, Hunt D, Malmberg K, Gerstein HC. Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic

overview. Lancet 2000;355:773-8.

Dallo FJ, Weller SC. Effectiveness of diabetes mellitus screening recommendations. Proc Natl Acad Sci U S A 2003;100:10574-9.

Gabir MM, Hanson RL, Dabelea D, Imperatore G, Roumain J, Bennett PH, Knowler WC.

The 1997 American Diabetes Association and 1999 World Health Organization criteria for hyperglycemia in the diagnosis and prediction of diabetes. Diabetes Care 2000;23:1108-12.

Genuth S, Alberti KG, Bennett P, Buse J, Defronzo R, Kahn R, et al. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 2003;26:3160-7.

Glumer C, Yuyun M, Griffin S, Farewell D, Spiegelhalter D, Kinmonth AL, Wareham NJ.

What determines the cost-effectiveness of diabetes screening? Diabetologia 2006;49:1536-44.

Goldstein DE, Little RR, Lorenz RA, Malone JI, Nathan D, Peterson CM, Sacks DB. Tests of glycemia in diabetes. Diabetes Care 2004;27:1761-73.

Greenberg RA, Sacks DB. Screening for diabetes: is it warranted? Clin Chim Acta

2002;315:61-9.

Hoerger TJ, Harris R, Hicks KA, Donahue K, Sorensen S, Engelgau M. Screening for type 2 diabetes mellitus: a cost-effectiveness analysis. Ann Intern Med 2004;140:689-99.

Icks A, Rathmann W, Haastert B, John J, Lowel H, Holle R, Giani G. Cost-effectiveness of type 2 diabetes screening: results from recently published studies. Gesundheitswesen 2005;67 Suppl 1:S167-71.

Imbeault P, Prins JB, Stolic M, Russell AW, O'Moore-Sullivan T, Despres JP, et al. Aging per se does not influence glucose homeostasis: in vivo and in vitro evidence. Diabetes Care 2003;26:480-4.

Jesudason DR, Dunstan K, Leong D, Wittert GA. Macrovascular risk and diagnostic criteria for type 2 diabetes: implications for the use of FPG and HbA(1c) for cost-effective screening. Diabetes Care 2003;26:485-90.

Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002;346:393-403.

Lacher DA, Hughes JP, Carroll MD. Estimate of biological variation of laboratory analytes based on the third national health and nutrition examination survey. Clin Chem 2005;51:450-2.

Miles RR, Roberts RF, Putnam AR, Roberts WL. Comparison of serum and heparinized plasma samples for measurement of chemistry analytes. Clin Chem 2004;50:1704-5.

Nathan DM, Cleary PA, Backlund JY, Genuth SM, Lachin JM, Orchard TJ, et al. Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes. N Engl J Med 2005;353:2643-53.

Perry RC, Shankar RR, Fineberg N, McGill J, Baron AD. HbA1c measurement improves the detection of type 2 diabetes in high-risk individuals with nondiagnostic levels of fasting plasma glucose: the Early Diabetes Intervention Program (EDIP). Diabetes Care

2001;24:465-71.

Sacks DB. Carbohydrates. In: Burtis CA, Ashwood ER, Bruns DE, eds. Tietz Fundamentals of Clinical Chemistry, Vol. 6th ed. St. Louis. In press.: Elsevier Saunders, 2007.

Sacks DB. Carbohydrates. In: Burtis CA, Ashwood ER, Bruns DE, eds. Tietz Textbook of Clinical Chemistry and Molecular Diagnostics, Vol. 4th ed. St. Louis: Elsevier Saunders, 2006:837-902.

Selvin E, Crainiceanu CM, Brancati FL, Coresh J. Short-term variability in measures of glycemia and implications for the classification of diabetes. Arch Intern Med 2007;167:1545-51.

Selvin E, Marinopoulos S, Berkenblit G, Rami T, Brancati FL, Powe NR, Golden SH. Meta-analysis: glycosylated hemoglobin and cardiovascular disease in diabetes mellitus. Ann Intern Med 2004;141:421-31.

Stahl M, Jorgensen LG, Hyltoft Petersen P, Brandslund I, de Fine Olivarius N, Borch-Johnsen K. Optimization of preanalytical conditions and analysis of plasma glucose. 1. Impact of the new WHO and ADA recommendations on diagnosis of diabetes mellitus. Scand J Clin Lab Invest 2001;61:169-79.

Tai ES, Goh SY, Lee JJ, Wong MS, Heng D, Hughes K, et al. Lowering the criterion for

impaired fasting glucose: impact on disease prevalence and associated risk of diabetes and ischemic heart disease. Diabetes Care 2004;27:1728-34.

Tirosh A, Shai I, Tekes-Manova D, Israeli E, Pereg D, Shochat T, et al. Normal fasting plasma glucose levels and type 2 diabetes in young men. N Engl J Med 2005;353:1454-62.

Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, Ilanne-Parikka P, et al.

Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001;344:1343-50.

World Health Organization. Definition, Diagnosis and Classification of Diabetes Mellitus and its Complications: Report of a WHO Consultation. Part 1: Diagnosis and Classification of Diabetes Mellitus. Geneva: World Health Org., 1999.

METERS

Portable meters for measurement of blood glucose concentrations are used in three major settings: i) in acute and chronic care facilities (including intensive care units); ii) in physicians’ offices and iii) by patients at home, work and school. The last, self-monitoring of blood glucose (SMBG), is performed at least once a day by 40% and 26% of individuals with type 1 and 2 diabetes, respectively, in the United States(46). The ADA list ed the following indications for SMBG: i) achievement and maintenance of glycemic control; ii) prevention and detection of hypoglycemia; iii) avoidance of severe hyperglycemia; iv) adjusting to changes in life-style and v) determining the need for initiating insulin therapy in gestational diabetes mellitus (GDM) (48). It is recommended that most individuals with diabetes attempt to achieve and maintain blood glucose concentrations as close to those found in non-diabetic individuals as is safely possible.

https://www.wendangku.net/doc/b916710686.html,e

A.Diagnosis/Screening

Recommendation: There are no insufficient published data to support a role for portable meters and skin-prick (finger-stick) blood samples in the diagnosis of diabetes or for population screening. The imprecision of the metersresults, coupled with the substantial differences among meters, precludes their use in the diagnosis of diabetes and limits their usefulness in screening for diabetes.

Level of evidence: TBD

The criteria for the diagnosis of diabetes are based upon outcome data (the risk of micro- and macrovascular disease) correlated with plasma glucose concentrations—both fasting and 2 h after a glucose load—assayed in an accredited laboratory (1). Whole blood is used in portable meters. Although many portable meters have been programmed to report a plasma glucose concentration, the imprecision of the current meters (see below) precludes their use in the diagnosis of diabetes. Similarly, screening by portable meters, although attractive because of convenience, ease and accessibility, would generate many false positives and false negatives.

B.Monitoring/Prognosis

Recommendation: SMBG is recommended for all insulin-treated patients with diabetes. For type 1 patients, SMBG is recommended three or more times a day. SMBG may be desirable in patients treated with sulfonylureas or other insulin secretagogues oral agents and in all patients not achieving goals.

Level of evidence: TBD

In patients with type 2 diabetes, SMBG may help achieve better control, particularly when therapy is initiated or changed, but data are insufficient to suggest an associated improvement of health outcomes. However, there are no data to support this concept. The role of SMBG in patients with stable type 2 diabetes controlled by diet alone is not known.

Level of evidence: TBD

SMBG is recommended for all patients with diabetes who use multiple daily insulin injections are receiving insulin. Tight glycemic control can decrease microvascular complications in individuals with type 1 (12) or type 2 (13) diabetes. Intensive plasma glucose control in patients with type 1 diabetes was achieved in the Diabetes Control and Complications Trial (DCCT) by participants performing SMBG at least four times per day (12). Therapy in patients with type 2 diabetes in the United Kingdom Prospective Diabetes Study (UKPDS) (13) was adjusted according to FPG concentrations – SMBG was not evaluated.

Use of SMBG in individuals with type 2 diabetes has generated considerable controversy (Ipp 2005). Faas et al. (49) reviewed eleven studies, published between 1976 and 1996, that evaluated SMBG in patients with type 2 diabetes. Only one of the published studies reported that SMBG produced a significantly positive improvement, namely lower GHb. The authors of the review concluded that the efficacy of SMBG in type 2 diabetes is questionable (49). Similar conclusions were drawn in a meta-analysis (50) and in a sample of patients with type 2 diabetes in the National Health and Nutrition Examination Survey (NHANES) (51) and in the Freemantle Diabetes Study (Davis, 2006) . Two recent randomized trials have assessed the use of glucose meters in individuals with type 2 diabetes (Guerci, 2003; Davidson, 2005). One (Guerci, 2003) had statistical power to detect a 0.5% reduction in A1c, but reported only a modest decrease (0.3%) of A1c in poorly controlled patients treated with oral agents. The second study (Davidson, 2005) found no evidence of a lower A1c in patients who were assigned to use meters.

For individuals with type 2 diabetes, cross-sectional and longitudinal observational studies in several countries have failed to demonstrate an improvement of glycemic control, as measured

by mean hemoglobin A1c concentrations, associated with use of self-monitoring of blood glucose (Franciosi, 2005; Karter, 2006; Martin, 2006). This lack of effect was seen in individuals treated with insulin, oral agents or both. Frequency of meter use did not predict A1c.

A 2005 Cochrane review (Welschen, 2005, Welschen, 2005) of self monitoring of blood glucose in individuals with type 2 diabetes not using insulin concluded that self-monitoring of blood glucose might be effective in improving glucose control. There was insufficient evidence to study if it was beneficial for improving quality of life, well-being, patient satisfaction, or decreasing the number of hypoglycaemic episodes.

The recently reported randomized controlled DiGEM Trial (Farmer, 2007) studied people with type 2 diabetes, a third of whom were treated with diet alone. The investigators concluded that

“evidence is not convincing of an effect of self monitoring blood glucose in improving glycaemic control [as assessed by HbA1c] compared with usual care in reasonably well controlled non-insulin treated patients with type 2 diabetes.”

2. Rationale

SMBG allows patients with diabetes to achieve and maintain specific glycemic goals. Knowledge of plasma or blood glucose concentrations is necessary for insulin-requiring patients, particularly those with type 1 diabetes, to determine appropriate insulin doses at different times of the day (48). Patients adjust the amount of insulin according to their plasma or blood glucose concentration. Frequent SMBG is particularly important for tight glycemic control in type 1 diabetes.

Hypoglycemia is a major, potentially life-threatening complication of the treatment of diabetes. The risk of hypoglycemia increases significantly with pharmacologic therapy directed towards maintaining the glycemic range as close to those found in non-diabetic individuals as possible (12, 13). The incidence of major hypoglycemic episodes—requiring third-party help or medical intervention—was 2- to 3-fold higher in the intensive group than in the conventional group in clinical trials of patients with type 1 and type 2 diabetes (12, 13). Furthermore, many patients with diabetes, particularly those with type 1 diabetes, lose the autonomic warning symptoms that normally precede neuroglycopenia (“hypoglycemic unawareness”) (52), increasing the risk of hypoglycemia. SMBG can be useful for detecting asymptomatic hypoglycemia and allowing patients to avoid major hypoglycemic episodes.

3. Analytical Considerations

A.Preanalytical

Recommendation: Patients should be instructed in the correct use of glucose meters, including quality control. Comparison between SMBG and concurrent laboratory glucose analysis should be performed at regular intervals to evaluate the accuracy performance of the meters in the patient’s hands results.

Level of evidence: TBD

Multiple factors can interfere with glucose analysis with portable meters. Several of these, such as improper application, timing and removal of excess blood (26), have been eliminated by advances in technology. Important variables that may influence the results of bedside glucose monitoring include changes in hematocrit (53), altitude, environmental temperature or humidity, hypotension, hypoxia and high triglyceride concentrations (54). Furthermore, most meters are inaccurate at very high or very low glucose concentrations. Another important factor is variability of results among different glucose meters. Different assay methods and architecture result in lack of correlation among meters, even from a single manufacturer. In fact, two meters of the same brand have been observed to differ substantially in accuracy (55, 56). Patient factors are also important, particularly adequate training. Recurrent education at clinic visits and comparison of SMBG with concurrent laboratory glucose analysis improved the accuracy of patients’ blood glucose readings (57). In addition, it is important to evaluate the patient’s technique at regular intervals (9).

B. Analytical

Recommendation: Multiple performance goals for portable glucose meters have been proposed. These targets vary widely and are highly controversial. No published study has achieved reported results that meet the goals proposed by the ADA of less than 5% total error. Manufacturers should work to improve the imprecision of current meters.

Level of evidence: TBD

We recommend meters that measure and report plasma glucose concentrations to facilitate comparison with assays performed in accredited laboratories.

Level of evidence: TBD

Virtually all glucose meters use strips that contain glucose oxidase or glucose dehydrogenase.

A drop of whole blood is applied to a strip that contains all the reagents necessary for the assay. Some meters have a porous membrane that separates erythrocytes and analysis is performed on the resultant plasma. Meters can be calibrated to report plasma glucose values, even when glucose is measured in whole blood. An IFCC working group recommended that glucose meters report concentrations of glucose in plasma, irrespective of the sample type or technology (59; D’Orazio, 2005); this approach can improve harmonization and allow comparision with laboratory-generated results (Steffes, 2005)). The meters use reflectance photometry or electrochemistry to measure the rate of the reaction or the final concentration of the products. The meter provides a digital readout of glucose concentration. Manufacturers typically claim a reportable range of approximately 1.7-33.3 mmol/L (30-600 mg/dL).

Several important technological advances decrease operator error. These include “no wipe” strips, automatic commencement of timing when both the sample and the strip are in the meter, smaller sample volume requirements, an error signal if sample volume is inadequate, “lock out” if controls are not assayed, bar code readers and the ability to store up to several hundred results that can subsequently be downloaded for analysis. Together these improvements have improved performance by new meters (60, Bohme, 2003). Nonetheless, meter performance in the hands of patients does not equal potential performance as judged by performance in the hands of skilled medical technologists (Skeie, 2002) .

Multiple analytical goals have been proposed for the performance of glucose meters. The rationale for these is not always clear. In 1987 the ADA recommended a goal of total error (user plus analytical) of < 10% at glucose concentrations of 1.7-22.2 mmol/L (30-400 mg/dL) 100% of the time (61). In addition, it was proposed that values should differ by < 15% from those obtained by a laboratory reference method. The recommendation was modified in response to the significant reduction in complications by tight glucose control in the DCCT. The revised performance goal, published in 1996 (48), is for total analytic al error < 5%. To our knowledge, there are no published studies of patients with diabetes achieving t he ADA goal of analytic error of <5%with any glucose meters.

The CLIA 88 goal is less stringent than that of the ADA; results with meters should be within 10% of target values or ± 0.3 mmol/L (6 mg/dL), whichever is larger. NCCLS recommendations (62) propose that for test readings >4.2 mmol/L (75 mg/dL), the discrepancy between meters and central laboratory should be <20%; for glucose ≤ 4.2 mmol/L (75 mg/dL), the discrepancy should not exceed 0.83 mmol/L (15 mg/dL).

In 2003, the International Organisation for Standardisation (ISO) published evenless stringent requirements for blood glucose monitoring systems for self-testing in managing diabetes (International Organization for Standardization, 2003). These criteria serve as de facto minimal quality requirements for manufacturers wishing to sell meters. The criteria for acceptability are: For reference glucose ≤75 mg/dL, meter results must fall within ±15 mg/dL; for reference glucose >75 mg/dL, meter results must be within 20% of reference results. Thus, a concentration of 45 mg/dL may be read as 30 mg/dL or 60 mg/dL and be considered acceptable. Such errors are not acceptable for reliable detection of hypoglycemia. Similarly, errors of 20% can lead to errors in insulin dosing which, when combined with other factors, can lead to hypoglycemia.

D ifferent approach es to establishing quality requirements have been proposed by others. Clarke (63) developed an Error Grid that attempts to define clinically important errors by identifying fairly broad target ranges. In another approach, 201 patients with longstanding type 1 diabetes were questioned to estimate quality expectations for glucose meters (64). Based on patients’ perceptions of their needs and of their reported actions in response to changes in measured glucose concentrations, a goal for analytical quality at hypoglycemic concentrations was a CV of 3.1%. Excluding hypoglycemia, the analytical CV to meet the expectations of 75% of the patients was 6.4%-9.7%. The authors recommended an analytical CV of 5%, with a bias ≤5% (64). A third approach used simulation modeling of errors in insulin dose (65). The results revealed that meters that achieve both a CV and a bias <5% rarely lead to major errors in insulin dose. However, to provide the intended insulin dosage 95% of the time, the bias and CV needed to be <1%-2%, depending upon the dosing schedule for insulin and the ranges of glucose concentrations for the individual patient (65). No meters have been shown to achieve CVs of 1-2% in routine use.

The lack of consensus on quality goals for glucose meters reflects the absence of agreed objective criteria. Using the same biological variation criteria described above for glucose analysis in accredited laboratories, (Section 4, Interpretation), we suggest a goal for total error (including both bias and imprecision) of ≤7.9%. However, additional studies are necessary to define a goal that is related to medical needs.

Current meters, as predicted, exhibit performance superior to prior generations of meters (60, Bohme, 2003), but there is room for improvement. In a study conducted under carefully controlled conditions in which all assays were performed by a single medical technologist, only about 50% of analyses met the ADA criterion of < 5% deviation from reference values (60). Another study that evaluated meter performance in 226 hospitals by split-samples analyzed simultaneously on meters and laboratory glucose analyzers revealed that 45.6%, 25% and 14% differed from each other by > 10%, > 15% and > 20%, respectively (66). In another study, none of the meters met the ADA criterion (67). Finally, in a recent study (The Diabetes Research in Children Network (DirecNet) Study Group, 2005) in which “all testing was performed by trained study staff in an inpatient Clinical Research Center setting”, only 81% of results of meter results were within ±10% of results from a central laboratory using a hexokinas method. We are aware of no studies that document patient-generated results that meet the ADA criteria. Moreover, a recent meta-analysis of published studies of glucose meters demonstrated that the studies suffered from deficiencies in study design, methodology and reporting. (Mahoney, 2007), raising the possibility that reported total error underestimates the true total error of the meters. A standardized method for evaluation of meters has been developed in Norway (Mahoney, 2007), and the Norwegian Health Authorities have decided that all SMBG instruments marketed in Norway should be examined by a similar procedure (Kristensen, GB).

Glucose meters are also used to support tight control of glucose in patients in intensive care units settings. The integrity of results of finger-stick samples can be compromised by factors

such as shock, hypoxia and low hematocrit that are common in these settings (Dungan, 2007). In

a recent study (Finkielman, 2005), the agreement of meter results with central laboraotyr results was poor: Among 767 paired results, the 95% limits of agreement were + 43.1to –27.2 mg /dL.. The authors concluded that"for the individual patient, bedside glucose meter measurement gives an unreliable estimate of plasma glucose" (Finkielman, 2005).

Recommendation: Clinical studies are needed to determine the analytical goals for glucose meters in self monitoring of blood glucose and in intensive care units. At a minimum, the end-points in studies of self-monitoring of glucose should be glycated hemoglobin and frequency of hypoglycemic episodes. Ideally, outcomes (e.g., long-term complications and hypoglycemia) should also be examined.

Level of evidence: TBD

Frequency of measurement

SMBG should be performed at least three times per day in patients with type 1 diabetes. Monitoring less frequently than four times a day results in a deterioration of glycemic control (48, 68, 69). Self-monitoring is performed by patients much less frequently than recommended. Data from NHANES III collected between 1988 and 1994 reveal that SMBG was performed at least once a day by 39% of patients taking insulin and 5-6% of those treated with oral agents or diet alone (51). Moreover, 29% and 65% of patients treated with insulin and oral agents, respectively, monitored their blood glucose less than once per month. However, no evaluation has been performed to verify that four times a day is ideal or whether some other frequency or timing (e.g., post-prandial testing) would improve glycemic control. For example, adjustment of insulin therapy in women with GDM according to the results of post-prandial, rather than pre-prandial, plasma glucose concentrations improved glycemic control and reduced the risk of neonatal complications (70). The optimal frequency of SMBG for patients with type 2 diabetes is unknown.

Current ADA recommendations suggest that SMBG be performed 3 or more times per day by patients treated with multiple daily injections of insulin (American Diabetes Association, 2006), and that “SMBG is useful in achieving glycemic goals” in other patients. The latter statement is based on expert opinion.

NEW REFERENCES

American Diabetes Association. Standards of Medical Care in Diabetes–2006. Diabetes Care 2006;29:S4-S42.

Bohme P, Floriot M, Sirveaux M-A, Durain D, Ziegler O, Drouin P, Guerci B. Evolution of Analytical Performance in Portable Glucose Meters in the Last Decade. Diabetes Care 2003;26:1170-5.

D’Orazio P, Burnett RW, Fogh-Andersen N, Jacobs E, Kuwa K, Külpmann WR, et al. for the International Federation of Clinical Chemistry Scientific Division Working Group on Selective Electrodes and Point of Care Testing. Approved IFCC Recommendation on Reporting Results for Blood Glucose (Abbreviated). Clin Chem 2005;51:1573–6.

Davidson MB, Castellanos M, Kain D, Duran P. The effect of self monitoring of blood glucose concentrations on glycated hemoglobin levels in diabetic patients not taking insulin: a blinded, randomized trial. Am J Med 2005;118:422–5.

Davidson MB. Counterpoint: Self-Monitoring of Blood Glucose in Type 2 Diabetic Patients not Receiving Insulin: A waste of money. Diabetes Care, 2005; 28:1531-3.

Davis WA, Bruce DG, Davis TME: Is self-monitoring of blood glucose appropriate for all type 2 diabetic patients? The Fremantle Diabetes Study. Diabetes Car 2006;29:1764–70.

Dungan K, Chapman J, Braithwaite SS, Buse J. Glucose measurement: confounding issues in setting targets for inpatient management. Diabetes Care 2007;30:403-9.

Farmer A, Wade A, Goyder E, Yudkin P, French D, Craven A, Holman R, Kinmonth AL, Neil A. Impact of self monitoring of blood glucose in the management of patients with non-insulin treated diabetes: open parallel group randomised trial. BMJ 2007;21;335:132.

Finkielman J, Oyen L, Afessa B: Agreement between bedside blood and plasma glucose measurement in the ICU setting. Chest 2005;127:1749-51.

Franciosi M, Pellegrini F, De Berardis G, Belfiglio M, Di Nardo B, Greenfield S, Kaplan SH, Rossi MCE, Sacco M, Tognoni G, Valentini M, Nicolucci A, the QuED Study Group. Self-monitoring of blood glucose in non-insulin-treated diabetic patients: a longitudinal evaluation of its impact on metabolic control. Diabet Med 2005;22:900–6.

Guerci B, Drouin P, Grange V, Bougneres P, Fontaine P, Kerlan V, Passa P, Thivolet C, Vialettes B, Charbonnel B, the ASIA Group. Self-monitoring of blood glucose significantly improves metabolic control in patients with type 2 diabetes mellitus: the Auto-Surveillance Intervention Active (ASIA) study. Diabetes Metab 2003; 29:587–94.

International Organization for Standardization. In vitro diagnostic test systems-Requirements for blood-glucose monitoring systems for self-testing in managing diabetes mellitus. ISO 15197. Geneva, Switzerland, 2003.

Ipp E, Aquino RL, ChristensoP. Point: Self-Monitoring of Blood Glucose in Type 2 Diabetic Patients not Receiving Insulin: The sanguine approach. Diabetes Care 2005;28:1528-30.

Karter AJ, Chan J, Parker MM, Moffet HH, Spence MM, Chan J, Ettner SL, Selby JV. Longitudinal study of new and prevalent use of self-monitoring of blood glucose. Diabetes Care 2006;29:1757–63.

Kristensen GB, Nerhus K, Thue G, Sandberg S. Standardized evaluation of instruments for self-monitoring of blood glucose by patients and a technologist. Clin Chem 2004; 50:1068-71. Mahoney J, Ellison J. Assessing the Quality of Glucose Monitor Studies: A Critical Evaluation of Published Reports. Clin Chem 2007;53:1122-8.

Martin S, Schneider B, Heinemann L, Lodwig V, Kurth H-J, Kolb H, Scherbaum WA, the ROSSO Study Group. Self-monitoring of blood glucose in type 2 diabetes and long-term outcome: an epidemiological study. Diabetologia 2006;49:271–8.

Skeie S, Thue G, Nerhus K, Sandberg S. Instruments for self-monitoring of blood glucose: comparisons of testing quality achieved by patients and a technician. Clin Chem 2002;48:994 - 1003.

Steffes MW, Sacks DB. Measurement of Circulating Glucose Concentrations: The Time Is Now for Consistency among Methods and Types of Samples. Clin Chem 2005;51:1569-70.

The Diabetes Research in Children Network (DirecNet) Study Group. Accuracy of newer generation home blood glucose meters in a Diabetes Research in Children Network (DirecNet) Inpatient Exercise Study. Diabetes Technol Ther 2005;7:675–83.

Welschen LMC, Bloemendal E, Nijpels G, Dekker JM, Heine RJ, Stalman WAB, Bouter LM. Self-monitoring of blood glucose in patients with type 2 diabetes mellitus who are not using insulin. Cochrane Database of Systematic Reviews 2005, Issue 2. Art. No.: CD005060.

Welschen LMC, Bloemendal E, Nijpels G, Dekker JM, Heine RJ, Stalman WAB, Bouter LM: Self-monitoring of blood glucose in patients with type 2 diabetes who are not using insulin: a systematic review. Diabetes Care 2005;28:1510–7.

MINIMALLY-INVASIVE CONTINUOUS GLUCOSE ANALYSES

Recommendation:

Non-invasive glucose analyses cannot be recommended as replacements for D+SMBG or glucose measurements by an accredited laboratory. Ongoing developments in the field, such as use of the new Gluco Watch Biographer, may influence this recommendation.

New recommendation: Continuous glucose monitoring may be of value in selected patients for hypoglycemia detection, reduction of glycemic variability, and possibly improvement in glycemic control. Patients require extensive training in using the device. Available devices must be calibrated with SMBG readings, and the latter are recommended for making treatment changes.

Level of evidence: TBD

1. Use

The

development of a device for “continuous” in vivo monitoring of glucose concentrations in blood is a very high priority as patients are required to control their plasma glucose more closely (12, 72, 90). Currently, several devices are approved by the FDA for minimally-invasive interstitial fluid glucose sensing, the transcutaneous “GlucoWatch Biographer” (Animus), and two implanted-catheter systems:the “Continuous Glucose Monitoring System” (Medtronic) and the Seven System (DexCom). Several more devices of the latter type are available in Europe and/or currently under FDA review, including the GlucoDay microdialysis device (Menarini Diagnostics) and the FreeStyle Navigator (Therasense). The Gluco Watch Biographer is no