Journal: Journal of Diabetes Science and Technology

Article Title: Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space

doi: 10.1177/1932296819855670

Figure Lengend Snippet: Listing of Clinical Trials With Different CGM Systems Summarizing Key Study Information and the MARD Obtained.

Article Snippet: Dexcom G5 (or G4 Platinum sensor + Software 505) , , , , , , , , , , .

Techniques: Clinical Proteomics, Comparison, Software

Journal: Diabetes Care

Article Title: Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring

doi: 10.2337/dc18-1581

Figure Lengend Snippet: Plot of CGM-measured mean glucose concentration vs. central laboratory–measured A1C used to compute the formula to estimate GMI, combining data from four randomized trials using the Dexcom G4 sensor with 505 software ( N = 528) described in the Supplementary Data . The shaded area represents the 95% CI of the regression line. The regression equation to compute GMI (%) = 3.31 + 0.02392 × [mean glucose in mg/dL] or GMI (mmol/mol) = 12.71 + 4.70587 × [mean glucose in mmol/L]. A calculator to compute GMI is available at www.jaeb.org/gmi and www.AGPreport.org/agp/links .

Article Snippet: More recently, Beck et al. ( ) published an equation (3.38 + 0.02345 × [mean glucose in mg/dL]) to estimate A1C from CGM-measured mean glucose concentration using modern CGM technology (Dexcom G4 Platinum CGM System with software 505; Dexcom, Inc., San Diego, CA) and using up to 91 days of CGM data (median 66 days) from 387 individuals with diabetes, combining data from three clinical trials (315 with T1D and 72 with T2D) ( – ).

Techniques: Concentration Assay, Software

Journal: Diabetes Care

Article Title: Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring

doi: 10.2337/dc18-1581

Figure Lengend Snippet: Explaining GMI to individuals with diabetes

Article Snippet: More recently, Beck et al. ( ) published an equation (3.38 + 0.02345 × [mean glucose in mg/dL]) to estimate A1C from CGM-measured mean glucose concentration using modern CGM technology (Dexcom G4 Platinum CGM System with software 505; Dexcom, Inc., San Diego, CA) and using up to 91 days of CGM data (median 66 days) from 387 individuals with diabetes, combining data from three clinical trials (315 with T1D and 72 with T2D) ( – ).

Techniques:

Journal: Diabetes Care

Article Title: Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring

doi: 10.2337/dc18-1581

Figure Lengend Snippet: Difference between GMI (calculated from CGM-derived mean glucose) and laboratory-measured A1C ( N = 528)

Article Snippet: More recently, Beck et al. ( ) published an equation (3.38 + 0.02345 × [mean glucose in mg/dL]) to estimate A1C from CGM-measured mean glucose concentration using modern CGM technology (Dexcom G4 Platinum CGM System with software 505; Dexcom, Inc., San Diego, CA) and using up to 91 days of CGM data (median 66 days) from 387 individuals with diabetes, combining data from three clinical trials (315 with T1D and 72 with T2D) ( – ).

Techniques:

Journal: Journal of Diabetes Science and Technology

Article Title: The Relationships Between Time in Range, Hyperglycemia Metrics, and HbA1c

doi: 10.1177/1932296818822496

Figure Lengend Snippet: Descriptions of the Four Studies.

Article Snippet: For analyses reporting baseline data or assessing change from baseline, a minimum of 240 hours (10 days) of masked baseline CGM data were required. provides details of the 4 studies. table ft1 table-wrap mode="anchored" t5 Table 1. caption a7 JDRF CGM RCT a DIAMOND (T1D) REPLACE-BG HypoDE Time period of study February 2007-June 2009 October 2014-May 2016 May 2015-September 2016 March 2016-July 2017 CGM(s) Dexcom Seven, MiniMed Paradigm, Abbott Freestyle Navigator Dexcom G4 with software 505 Dexcom G4 with software 505 Dexcom G5 Method for A1C measurement A1C measured with NGSP-certified method (Tosoh A1c 2.2 Plus Glycohemoglobin Analyzer), performed at University of Minnesota A1C measured with NGSP-certified method (G8 Tosoh Biosciences), performed at Northwest Lipid Research Laboratories, University of Washington, Seattle A1C measured with NGSP-certified method (G8 Tosoh Biosciences), performed at Northwest Lipid Research Laboratories, University of Washington, Seattle A1C measured with NGSP-certified method (G8 Tosoh Biosciences), performed at MLM Medical Labs, Moenchengladbach, Germany A1C eligibility range ≤10.0% 7.5%-9.9% ≤9.0% ≤9.0% Insulin delivery Pump and MDI users (predominately pump) 100% MDI 100% pump users 100% MDI Number of participants included in the analyses 93 99 212 141 Age (years) Mean ± SD 38 ± 13 46 ± 14 45 ± 14 46 ± 11 [Range] [18 to 73] [26 to 72] [20 to 78] [20 to 69] Female % 52 (56%) 43 (43%) 107 (50%) 56 (40%) White race % 90 (97%) 86 (88%) 195 (92%) n/a Diabetes duration (years) Median (IQR) 20 (14-31) 19 (9-31) 23 (15-32) 21 (9-31) [Range] [2 to 63] [2 to 57] [2 to 64] [2 to 54] A1C (%)—baseline Mean ± SD 7.2 ± 0.8 8.6 ± 0.7 7.1 ± 0.6 7.5 ± 1.0 [Range] [4.7 to 9.2] [7.5 to 9.9] [5.2 to 8.7] [4.9 to 10.0] A1C (%)—6 months Mean ± SD 6.8 ± 0.6 7.6 ± 0.8 7.0 ± 0.7 7.3 ± 0.9 [Range] [5.0 to 8.9] [6.0 to 10.1] [5.2 to 8.8] [5.3 to 9.7] A1C—change from baseline (%) Mean ± SD −0.4 ± 0.5 −1.0 ± 0.8 0.0 ± 0.5 −0.2 ± 0.5 [Range] [−2.0 to +0.9] [−3.0 to +0.7] [−1.4 to +1.4] [−1.8 to +1.5] Open in a separate window a Includes both the A1C ≥7.0% and A1C <7.0% cohorts.

Techniques: Software

Journal: Sensors (Basel, Switzerland)

Article Title: A Comprehensive Review of Continuous Glucose Monitoring Accuracy during Exercise Periods

doi: 10.3390/s21020479

Figure Lengend Snippet: Reported data in chronological order of publication of the surveyed studies that carried out exercise trials. GS stands for Gold Standard glucose reference. Δ MARD = M A R D e − M A R D r where M A R D e is the MARD of the samples within exercise periods and M A R D r is the counterpart for the samples during rest periods. Asterisks (*) indicate that M A R D r was extracted from the articles mentioned in Table 2 . The shaded rows correspond to those papers that reported necessary data to assess sensor accuracy during exercise, 17 in total. The labels that will later be used in the graphics to uniquely identify a study and branch have also been added to the MARD exercise column.

Article Snippet: Forlenza et al. [ ] , 2019 , 12 , – , Aerobic , Dexcom G4 (505) , – , – , – , SMBG.

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: A Comprehensive Review of Continuous Glucose Monitoring Accuracy during Exercise Periods

doi: 10.3390/s21020479

Figure Lengend Snippet: Reported MARD data for resting periods for the sensors that the studies in Table 1 did not originally provide.

Article Snippet: Forlenza et al. [ ] , 2019 , 12 , – , Aerobic , Dexcom G4 (505) , – , – , – , SMBG.

Techniques: