Recommendations for Standardizing Glucose Reporting and Analysis to Optimize Clinical Decision Making in Diabetes: The Ambulatory Glucose Profile

Bergenstal, Richard M.; Ahmann, Andrew J.; Bailey, Timothy S.; Beck, Roy W.; Bissen, Joan; Buckingham, Bruce A.; Deeb, Larry C.; Dolin, Robert H.; Garg, Satish K.; Goland, Robin; Hirsch, Irl B.; Klonoff, David C.; Kruger, Davida F.; Matfin, Glenn; Mazze, Roger S.; Olson, Beth A.; Parkin, Christopher G.; Peters, Anne L.; Powers, Margaret A.; Rodriguez, Henry; Southerland, Phil; Strock, Ellie S.; Tamborlane, William V.; Wesley, David

doi:10.1177/193229681300700234

Cited by 127 publications

(158 citation statements)

References 55 publications

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“…Glycaemic variability refers to acute excursions in blood glucose levels, including hypoglycaemic events and postprandial hyperglycaemia, and may be known by some patients and physicians as daily glucose fluctuations 8. As HbA1c is a measure of overall blood glucose concentrations over 2‐3 months, it does not directly reflect the degree of glycaemic variability 9. Ideally, management of type 2 diabetes should strive for control of HbA1c levels and close approximation of normal diurnal glycaemic variability.…”

Section: Introductionmentioning

confidence: 99%

Exenatide once weekly improved 24‐hour glucose control and reduced glycaemic variability in metformin‐treated participants with type 2 diabetes: a randomized, placebo‐controlled trial

Frías

Nakhle²,

Ruggles

et al. 2016

Diabetes Obesity Metabolism

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AimTo assess the effects of once‐weekly exenatide on 24‐hour glucose control and variability.Materials and methodsThis double‐blind, placebo‐controlled trial randomized metformin‐treated adults with type 2 diabetes to once‐weekly exenatide 2.0 mg or placebo. Continuous glucose monitoring (CGM) was performed at baseline and weeks 4 and 10. The primary outcome was change in CGM‐measured 24‐hour mean glucose level.ResultsIn the once‐weekly exenatide (n = 60) and placebo (n = 56) groups (modified intention‐to‐treat population), the baseline glycated haemoglobin (HbA1c) concentrations were 8.2% and 8.0%, respectively, and the fasting plasma glucose (FPG) concentration was 9.86 and 9.32 mmol/L, respectively. Once‐weekly exenatide significantly (p < 0.001) reduced 24‐hour mean glucose level versus placebo (week 4, −1.44 vs −0.29 mmol/L; week 10, −1.71 vs −0.17 mmol/L), with consistent control throughout the week. Once‐weekly exenatide significantly reduced FPG and 2‐hour postprandial glucose (PPG) levels versus placebo at week 4 (FPG, −1.65 vs −0.11 mmol/L; PPG, −1.79 vs −0.11 mmol/L) and week 10 (FPG, −2.32 vs −0.28 mmol/L; PPG, −2.46 vs −0.33 mmol/L). At week 10, once‐weekly exenatide reduced the mean amplitude of glucose excursions (MAGE; −0.84 vs 0.16 mmol/L) and standard deviation (s.d.) of mean glucose (−0.35 vs 0.04 mmol/L). By week 10, once‐weekly exenatide‐treated participants spent more time in euglycaemia (once‐weekly exenatide, 77% vs placebo, 58%), less time in hyperglycaemia (22% vs 42%), and a similar time in hypoglycaemia (0.7% vs 0.3%). Common adverse events were injection‐site nodule (once‐weekly exenatide, 10.0% vs placebo, 0.0%), urinary tract infection (6.7% vs 8.9%) and nausea (6.7% vs 0.0%).ConclusionsIn metformin‐treated participants with type 2 diabetes, once‐weekly exenatide significantly improved daily glucose control and reduced glycaemic variability at weeks 4 and 10, as shown by reductions in 24‐hour glucose, FPG and PPG levels, MAGE and s.d., and increased time spent in euglycaemia.

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Section: Introductionmentioning

confidence: 99%

Exenatide once weekly improved 24‐hour glucose control and reduced glycaemic variability in metformin‐treated participants with type 2 diabetes: a randomized, placebo‐controlled trial

Frías

Nakhle²,

Ruggles

et al. 2016

Diabetes Obesity Metabolism

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“…The development of automated data visualization tools for continuous glucose monitoring systems has been a major focus of research in academia and in industry. [7][8][9][10][11] Many insurance companies in the United States now provide reimbursement to patients for CGM devices (hardware and sensors). Historically, an additional factor limiting the more widespread use of continuous glucose monitors has been the lack of reimbursement for physicians in assisting patients interpreting the data from their devices.…”

Section: Introductionmentioning

confidence: 99%

A Simple Composite Metric for the Assessment of Glycemic Status from Continuous Glucose Monitoring Data: Implications for Clinical Practice and the Artificial Pancreas

Hirsch

Balo

Sayer

et al. 2017

Diabetes Technology & Therapeutics

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Background: The potential clinical benefits of continuous glucose monitoring (CGM) have been recognized for many years, but CGM is used by a small fraction of patients with diabetes. One obstacle to greater use of the technology is the lack of simplified tools for assessing glycemic control from CGM data without complicated visual displays of data. Methods: We developed a simple new metric, the personal glycemic state (PGS), to assess glycemic control solely from continuous glucose monitoring data. PGS is a composite index that assesses four domains of glycemic control: mean glucose, glycemic variability, time in range and frequency and severity of hypoglycemia. The metric was applied to data from six clinical studies for the G4 Platinum continuous glucose monitoring system (Dexcom, San Diego, CA). The PGS was also applied to data from a study of artificial pancreas comparing results from open loop and closed loop in adolescents and in adults. Results: The new metric for glycemic control, PGS, was able to characterize the quality of glycemic control in a wide range of study subjects with various mean glucose, minimal, moderate, and excessive glycemic variability and subjects on open loop versus closed loop control. Conclusion: A new composite metric for the assessment of glycemic control based on CGM data has been defined for use in assessing glycemic control in clinical practice and research settings. The new metric may help rapidly identify problems in glycemic control and may assist with optimizing diabetes therapy during timeconstrained physician office visits.

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“…Currently this is limited to an expert panel recommendation for AGP as an effective standard for analysing glucose data. [2][3][4] Ideally, the technology now needs studying to determine benefit in terms of time and efficiency for health care professionals and users themselves in interpreting complex glycaemic data sets. Time is more than money here; in time-pressured and resource-limited healthcare systems, this may make the difference between identifying or missing a glycaemic pattern and an associated effective therapeutic change.…”

Section: Ambulatory Glucose Profilementioning

confidence: 99%

“…The Medtronic iPro system is "blinded" with data being downloaded after wearing for retrospective pattern analysis by healthcare professionals. The challenges with current CGM systems are that (1) they need calibration against SMBG, thus creating potential for operator error; (2) …”

Section: Continuous Glucose Monitoringmentioning

confidence: 99%

Current methods of assessing blood glucose control in diabetes

Evans

2016

Br J Diabetes

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The HbA1c measurement effectively "averages" blood glucose over the previous few months, but can conceal wide variations during that period and patients with apparently well-controlled HbA1c may have very different risks of potentially debilitating hypoglycaemia. Self-monitoring of blood glucose provides only "snapshots" of glycaemic control that are unlikely to reveal the true extent of glucose variability. Continuous glucose monitoring (CGM) systems offer a far more comprehensive 24-hour picture of glycaemia, but need regular calibration, are expensive, and limited by short sensor life. Also, the sheer volume of data from CGM downloads can render it difficult to identify patterns. The ambulatory glucose profile (AGP) presents glucose data in a standardised manner, with glucose values presented as a median with 10th, 25th, 75th and 90th centiles. Examination of the AGP can reveal patterns highlighting areas of hypoglycaemia risk or excessive glucose variability, in a way that helps patients to understand and accept the needed changes to their treatment. Software for analysis is available for current systems to indicate possible areas for attention, for example a simple traffic light system where the colour red shows a possible area of risk. AGP could make the difference between identifying or missing a glycaemic pattern and an associated effective therapeutic change, within the timepressured and resource-limited healthcare environment. Finally, the newer technique of "flash glucose monitoring" involves a small factory calibrated sensor which can store glucose data for up to 8 hours; users use a handheld receiver to "interrogate" the sensor rather than having information pushed through continuously as in CGM.Br J Diabetes 2016;16(Suppl1):S7-S9

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Recommendations for Standardizing Glucose Reporting and Analysis to Optimize Clinical Decision Making in Diabetes: The Ambulatory Glucose Profile

Cited by 127 publications

References 55 publications

Exenatide once weekly improved 24‐hour glucose control and reduced glycaemic variability in metformin‐treated participants with type 2 diabetes: a randomized, placebo‐controlled trial

Exenatide once weekly improved 24‐hour glucose control and reduced glycaemic variability in metformin‐treated participants with type 2 diabetes: a randomized, placebo‐controlled trial

A Simple Composite Metric for the Assessment of Glycemic Status from Continuous Glucose Monitoring Data: Implications for Clinical Practice and the Artificial Pancreas

Current methods of assessing blood glucose control in diabetes

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