Diabetes mellitus is the collective term for heterogeneous metabolic disorders whose main finding is chronic hyperglycaemia. The cause is either a disturbed insulin secretion or a disturbed insulin effect or usually both. ^* The team of authors has written the practical recommendation for the Commission for Laboratory Diagnostics in Diabetology/Kommission Labordiagnostik in der Diabetologie of the German Diabetes Society/Deutsche Diabetes Gesellschaft (DDG) and the German Society for Clinical Chemistry and Laboratory Medicine (DGKL)/ Deutschen Gesellschaft für Klinische Chemie und Laboratoriumsmedizin.

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Background: The accuracy of systems for self-monitoring of blood glucose is important, as reliable measurement results are a prerequisite for therapeutic decisions. Methods: This system accuracy evaluation study was performed according to DIN EN ISO 15197:2003 for 43 Conformité Européenne (CE)-labeled blood glucose (BG) monitoring systems. Measurement results of each system were compared with results of the designated comparison method (manufacturer's measurement procedure): glucose oxidase method (YSI 2300 glucose analyzer) or hexokinase method (Hitachi 917/ cobas 501). Results: Complete assessment according to the International Organization for Standardization (ISO) standard was performed for 34 out of 43 systems, and 27 (79.4%) meet the requirements of the standard, i.e., ≥95% of their results showed at least the minimum acceptable accuracy. For 9 of the 43 systems, complete accuracy assessment was not performed due to an oxygen sensitivity (manufacturer's labeling). The bias (according to Bland and Altman) of all 43 evaluated systems ranged from −14.1% to +12.4%. Conclusions: From the 34 systems completely assessed, 7 systems did not fulfill the minimal accuracy requirements of the ISO standard. The CE mark apparently does not guarantee that all BG systems provide accuracy according to the standard. Because inaccurate systems bear the risk of false therapeutic decisions, regular and standardized evaluation of BG meters and test strips should be requested in order to ensure adherence to quality standards.

Currently, patients with diabetes may choose between two major types of system for glucose measurement: blood glucose monitoring (BGM) systems measuring glucose within capillary blood and continuous glucose monitoring (CGM) systems measuring glucose within interstitial fluid. Although BGM and CGM systems offer different functionality, both types of system are intended to help users achieve improved glucose control. Another area in which BGM and CGM systems differ is measurement accuracy. In the literature, BGM system accuracy is assessed mainly according to ISO 15197:2013 accuracy requirements, whereas CGM accuracy has hitherto mainly been assessed by MARD, although often results from additional analyses such as bias analysis or error grid analysis are provided. The intention of this review is to provide a comparison of different approaches used to determine the accuracy of BGM and CGM systems and factors that should be considered when using these different measures of accuracy to make comparisons between the analytical performance (ie, accuracy) of BGM and CGM systems. In addition, real-world implications of accuracy and its relevance are discussed.

Background: Blood glucose (BG) monitoring systems enable diabetes patients to effectively control and adjust their therapy. BG monitoring systems with a Conformité Européenne (CE) label should meet the standard DIN EN ISO 15197:2003: ≥95% of the BG results shall fall within ±15 mg/dL of the reference method at BG concentrations <75 mg/dL and within ±20% at BG concentrations ≥75 mg/dL. We intended to verify if BG monitoring systems with a CE label fulfill these minimum accuracy requirements. Methods: We evaluated 27 BG monitoring systems from 18 manufacturers for system accuracy according to DIN EN ISO 15197:2003. Twenty-four systems were compared with the glucose oxidase reaction (YSI 2300 glucose analyzer [YSI Life Sciences, Yellow Springs, OH]) and three systems with the hexokinase reaction (Hitachi 917 [Roche Diagnostics GmbH, Mannheim, Germany]). Duplicate measurements of 100 blood samples with a defined distribution of BG concentrations from 20 mg/dL to 600 mg/dL from ≥100 subjects were included in the evaluation. Results: Sixteen of the 27 BG monitoring systems fulfilled the minimum accuracy requirements of the standard, i.e., ≥95% of their results showed the minimum acceptable accuracy. Overall, the mean percentage of results showing the minimum acceptable accuracy was 95.2 ± 5.2%, ranging from 80.0% to 100.0%. Conclusions: More than 40% of the evaluated BG monitoring systems did not fulfill the minimum accuracy requirements of DIN EN ISO 15197:2003. As inaccurate BG monitoring systems bear the risk of false treatment decisions by the diabetes patient and subsequent possible severe health injury, manufacturers should regularly and effectively check the quality of BG meters and BG test strips.