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Diabetes Management Blood Glucose Monitoring

Blood Glucose Monitoring in Paediatric Patients – Looking Towards Better Diabetes Management and Perspectives for the Future William L Clarke

Robert M Blizzard Professor of Pediatric Endocrinology and Chief of Pediatric Endocrinology, Department of Pediatrics, University of Virginia Health Sciences Center


Self-blood glucose monitoring (SBGM) is an important component of day-to-day diabetes management for children and their families. Despite some recent concerns in terms of its analytical accuracy, it has been used successfully to implement intensive glucose control in the Diabetes

control and complications trial (DCCT), reduce glycated haemoglobin (HbA1c) levels, prevent acute complications, and make it possible for children to attend school and participate in sports activities safely. While still in its infancy, continuous glucose monitoring (CGM) has been

shown to be useful in reducing the occurrence of nocturnal hypoglycaemia, lowering HbA1c levels and reducing glycaemic variability. Its analytical accuracy has prevented its approval as an alternative to SBGM for insulin decision-making. However, it has made possible the development and testing of closed-loop ‘artificial pancreas’ systems for controlling glucose levels in adults and adolescents.


Self-blood glucose monitoring, continuous glucose monitoring, clinical accuracy, glycaemic variability, hypoglycaemia, hyperglycaemia, artificial pancreas

Disclosure: The author has no conflicts of interest to declare. Acknowledgment: Supported in part by a National Institutes of Health (NIH) grant RO1 DK 51562. Received: 10 August 2010 Accepted: 26 October 2010 Citation: European Endocrinology, 2012;8(1):22–5 Correspondence: William L Clarke, Division of Pediatric Endocrinology, Department of Pediatrics, University of Virginia Health Sciences Center, Charlottesville, VA 22908, US. E:

Introduced into patient-directed self-management in the early 1980s, self-blood glucose monitoring (SBGM) is now recognised as integral to standard of care diabetes treatment for all age groups.1

Indeed, along with the development of stable and reproducible glycated

haemoglobin (HbA1c) assays, SBGM made possible the achievement of intensive therapy and the design and conduct of the Diabetes control and complications trial (DCCT).2

Today, most individuals with

type 1 diabetes use SBGM test results multiple times daily to adjust their treatment decisions. SBGM in paediatric patients is neither unique nor particularly different from that in adults. However, the improvements in SBGM technology, such as smaller sample size, alternate site testing and improvements in accuracy, have been particularly welcomed by children and their parents.3

The next

generation of glucose monitoring, continuous glucose monitoring (CGM), has been studied extensively in children, and its extension to the development of closed-loop (artificial pancreas) insulin-delivery systems is a long-awaited dream.

Self-blood Glucose Monitoring

Accuracy of Self-blood Glucose Monitoring Devices Even though SBGM devices have become smaller, more user-friendly and less susceptible to error from interfering substances, considerable concerns remain about their ability to produce reliable and reproducible results.4,5

both analytical and clinical terms. Analytical accuracy refers to standard statistical analyses that compare meter-generated glucose readings to simultaneous reference system results. Terms such as


‘absolute’ and ‘relative absolute’ differences are often used to describe these relationships, as are correlation coefficients and linear regression equations. The US Food and Drug Administration (FDA) requires new devices to achieve 95 % analytical accuracy as measured by International Standards Organization (ISO) 15197 criteria.4

These criteria state that meter readings should be within

20 % of reference values when the reference is >75 mg/dl and within 15 mg/dl of the reference when that value is ≤75 mg/dl. ‘Clinical accuracy’ refers to SBGM devices that produce readings that can result in clinically accurate treatment decisions.6 While analytical and clinical accuracy often coincide, this is not always the case. For instance, a correlation coefficient for a large data set may be highly significant across the entire blood glucose (BG) range, but differ significantly in the three critical BG ranges – hypoglycaemia, euglycaemia and hyperglycaemia.7

Our research group developed

error grid analysis (EGA) as a method for quantifying clinical accuracy of patient-determined BG values.6

EGA categorises the relationship

between a patient-generated BG level and a reference BG level in terms of the clinical status that would result from a treatment decision based on a patient-generated result. Parkes et al. have developed the consensus error grid (CEG), a similar method for describing clinical accuracy of SBGM.8

Both methods emphasise Accuracy of SBGM devices is described in

the importance of obtaining clinically accurate information across the entire BG range (hypoglycaemia, euglycaemia and hyperglycaemia).

The EGA divides the reference versus SBGM BG graph into five zones of clinical accuracy (see Figure 1). The basic assumptions of EGA are


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