International Consensus on Use of Continuous Glucose Monitoring - PubMed (original) (raw)

Review

. 2017 Dec;40(12):1631-1640.

doi: 10.2337/dc17-1600.

Revital Nimri 2, Tadej Battelino 3, Richard M Bergenstal 4, Kelly L Close 5, J Hans DeVries 6, Satish Garg 7, Lutz Heinemann 8, Irl Hirsch 9, Stephanie A Amiel 10, Roy Beck 11, Emanuele Bosi [ 12](#full-view-affiliation-12 "Diabetes Research Institute, University "Vita-Salute" San Raffaele, Milan, Italy."), Bruce Buckingham 13, Claudio Cobelli 14, Eyal Dassau 15, Francis J Doyle 3rd 15, Simon Heller 16, Roman Hovorka 17, Weiping Jia 18, Tim Jones 19, Olga Kordonouri [ 20](#full-view-affiliation-20 "Diabetes Centre for Children and Adolescents, Children's and Youth Hospital "Auf Der Bult," Hannover, Germany."), Boris Kovatchev 21, Aaron Kowalski 22, Lori Laffel 23, David Maahs 13, Helen R Murphy 24, Kirsten Nørgaard 25, Christopher G Parkin 26, Eric Renard 27, Banshi Saboo 28, Mauro Scharf 29, William V Tamborlane 30, Stuart A Weinzimer 30, Moshe Phillip 2

Affiliations

Review

International Consensus on Use of Continuous Glucose Monitoring

Thomas Danne et al. Diabetes Care. 2017 Dec.

Abstract

Measurement of glycated hemoglobin (HbA1c) has been the traditional method for assessing glycemic control. However, it does not reflect intra- and interday glycemic excursions that may lead to acute events (such as hypoglycemia) or postprandial hyperglycemia, which have been linked to both microvascular and macrovascular complications. Continuous glucose monitoring (CGM), either from real-time use (rtCGM) or intermittently viewed (iCGM), addresses many of the limitations inherent in HbA1c testing and self-monitoring of blood glucose. Although both provide the means to move beyond the HbA1c measurement as the sole marker of glycemic control, standardized metrics for analyzing CGM data are lacking. Moreover, clear criteria for matching people with diabetes to the most appropriate glucose monitoring methodologies, as well as standardized advice about how best to use the new information they provide, have yet to be established. In February 2017, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address these issues. This article summarizes the ATTD consensus recommendations and represents the current understanding of how CGM results can affect outcomes.

© 2017 by the American Diabetes Association.

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Figures

Figure 1

Figure 1

The electronic AGP report visualizes the key CGM metrics: 1) mean glucose, 2) hypoglycemia: clinically significant/very low/immediate action required, 3) hypoglycemia: alert/low/monitor, 4) target range, 5) hyperglycemia: alert/elevated/monitor, 6) hyperglycemia: clinically significant/very elevated/immediate action required, 7) glycemic variability, 8) eA1C, 9) time blocks, 10) collection period, 11) percentage of expected readings, 12) hypoglycemia/hyperglycemia episodes, 13) area under the curve, 14) hypoglycemia/hyperglycemia risk, and 15) standardized rtCGM/iCGM visualization. AUC, area under the curve; Avg; average; IQR, interquartile range; MAGE, mean amplitude of glucose excursions; MODD, mean of daily differences.

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