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

Bergenstal, Richard M., Ahmann, Andrew J., Bailey, Timothy, Beck, Roy W., Bissen, Joan, Buckingham, Bruce, Deeb, Larry, 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, Peters, Anne, Powers, Margaret A., Rodriguez, Henry, Southerland, Phil, Strock, Ellie S., Tamborlane, William, Wesley, David M.·2013·Diabetes Technology & Therapeutics

DOI 10.1089/dia.2013.0051

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Abstract

Abstract Underutilization of glucose data and lack of easy and standardized glucose data collection, analysis, visualization, and guided clinical decision making are key contributors to poor glycemic control among individuals with type 1 diabetes. An expert panel of diabetes specialists, facilitated by the International Diabetes Center and sponsored by the Helmsley Charitable Trust, met in 2012 to discuss recommendations for standardization of analysis and presentation of glucose monitoring data, with the initial focus on data derived from CGM systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile (AGP), and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This paper provides a summary of the topics and issues discussed during the meeting and presents recommendations from the expert panel regarding the need to standardize glucose profile summary metrics and the value of a uniform glucose report to aid clinicians, researchers, and patients.

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Background
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Background
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Glycemic variability: Measurement, target, impact on complications of diabetes and does it really matter?
Mo, Y., Lu, J., & Zhou, J. (2023) · Journal of Diabetes Investigation · doi:10.1111/jdi.14112 · Cited by 53
“Ambulatory glucose pro ﬁ le condenses CGM data into a 24-h representation, and IQR, represented by the 25th to 75th percentile trend lines on ambulatory glucose pro ﬁ le, serves as a powerful visual tool for assessing GV 19,20 .”
Method
Essential Continuous Glucose Monitoring Metrics: The Principal Dimensions of Glycemic Control in Diabetes
Montaser, E., Fabris, C., & Kovatchev, B. P. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0104 · Cited by 44
Emerging Diabetes Technologies: Continuous Glucose Monitors/Artificial Pancreases
ALMURASHI, A. M., Rodriguez, E., & Garg, S. K. (2023) · Journal of the Indian Institute of Science · doi:10.1007/s41745-022-00348-3 · Cited by 55
Basal Glucose Can Be Controlled, but the Prandial Problem Persists—It’s the Next Target!
Riddle, M. C. (2017) · Diabetes Care · doi:10.2337/dc16-2380 · Cited by 43
“0 mmol/L) as a summary indicator of glycemic control (34).”
Background
Design of FLAT-SUGAR: Randomized Trial of Prandial Insulin Versus Prandial GLP-1 Receptor Agonist Together With Basal Insulin and Metformin for High-Risk Type 2 Diabetes
The FLAT-SUGAR Trial Investigators (2015) · Diabetes Care · doi:10.2337/dc14-2689 · Cited by 38
Consensus recommendations for the use of Ambulatory Glucose Profile in clinical practice
Matthaei, S., Antuna, R., Bosi, E., Evans, M. L., Geelhoed-Duijvestijn, N., & Joubert, M. (2014) · The British Journal of Diabetes · doi:10.15277/bjdvd.2014.046 · Cited by 38
A New Era in Continuous Glucose Monitoring: Food and Drug Administration Creates a New Category of Factory-Calibrated Nonadjunctive, Interoperable Class II Medical Devices
Garg, S. K., & Aktürk, H. K. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0142 · Cited by 37
Effect of Professional CGM (pCGM) on Glucose Management in Type 2 Diabetes Patients in Primary Care
Simonson, G. D., Bergenstal, R. M., Johnson, M. L., Davidson, J. L., & Martens, T. W. (2021) · Journal of Diabetes Science and Technology · doi:10.1177/1932296821998724 · Cited by 37
Self-citation
The Impact of Insulin Pump Therapy on Glycemic Profiles in Patients with Type 2 Diabetes: Data from the OpT2mise Study
Conget, I., Castañeda, J., Petrovski, G., Guerci, B., Racault, A.-S., Reznik, Y., Cohen, O., Runzis, S., de Portu, S., Aronson, R., et al. (2015) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0159 · Cited by 38
Ambulatory Glucose Profile (AGP) Report in Daily Care of Patients with Diabetes: Practical Tips and Recommendations
Czupryniak, L., Dzida, G. J., Fichna, P., Jarosz-Chobot, P. A., Gumprecht, J., Klupa, T., Myśliwiec, M., Szadkowska, A., Bomba-Opon, D. A., Czajkowski, K., et al. (2022) · Diabetes Therapy · doi:10.1007/s13300-022-01229-9 · Cited by 35
Continuous Glucose Monitoring to Optimize Management of Diabetes in Patients with Advanced CKD
Galindo, R. J., de Boer, I. H., Neumiller, J. J., & Tuttle, K. R. (2022) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.04510422 · Cited by 35
Key indices of glycaemic variability for application in diabetes clinical practice
Monnier, L., Bonnet, F., Colette, C., Renard, É., & Owens, D. R. (2023) · Diabetes & Metabolism · doi:10.1016/j.diabet.2023.101488 · Cited by 35
Technological advances shaping diabetes care
Aktürk, H. K., & Garg, S. K. (2019) · Current Opinion in Endocrinology Diabetes and Obesity · doi:10.1097/med.0000000000000467 · Cited by 34
Impact of errors in paper-based and computerized diabetes management with decision support for hospitalized patients with type 2 diabetes. A post-hoc analysis of a before and after study
Donsa, K., Beck, P., Höll, B., Mader, J. K., Schaupp, L. A., Plank, J., Neubauer, K. M., Baumgärtner, C., & Pieber, T. R. (2016) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2016.03.007 · Cited by 35
Diurnal Glycemic Patterns during an 8-Week Open-Label Proof-of-Concept Trial of Empagliflozin in Type 1 Diabetes
Perkins, B. A., Cherney, D. Z. I., Soleymanlou, N., Lee, J. A., Partridge, H., Menezes, H. T., Zinman, B., Mazze, R., Fagan, N. M., Kaspers, S., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0141085 · Cited by 32
“CGM results were analyzed and averaged over 2-week AGP assessment periods to provide modal day estimates of pre-specified conventional parameters of glycemic exposure, glycemic variability, and glycemic stability during the 2-week placebo runin period (baseline), weeks 7 and 8 (end-of-treatment) and the two week perio…”
Method
Clinical Application of Time in Range and Other Metrics
Aleppo, G. (2021) · Diabetes Spectrum · doi:10.2337/ds20-0093 · Cited by 32
Consistency of Quantitative Scores of Hypoglycemia Severity and Glycemic Lability and Comparison with Continuous Glucose Monitoring System Measures in Long-Standing Type 1 Diabetes
Senior, P. A., Bellin, M. D., Alejandro, R., Yankey, J. W., Clarke, W. R., Qidwai, J. C., Schwieger, T., Eggerman, T. L., Robien, M. A., & Rickels, M. R. (2015) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2014.0289 · Cited by 33
“We used the software-generated CGMS SD and CGMS CV available at the start of the CIT trials as measures of glycemic variability for this analysis as there is no consensus for how best to use CGMS to quantify glucose variability.(20) If we had had access to raw sensor data, it would have been possible to calculate othe…”
Method
The clinical importance of measuring glycaemic variability: Utilising new metrics to optimise glycaemic control
Ajjan, R. (2024) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16098 · Cited by 35
Understanding Continuous Glucose Monitoring Data
Bergenstal, R. (2018) · Role of Continuous Glucose Monitoring in Diabetes Treatment · doi:10.2337/db20181-20 · Cited by 37
Development and Assessment of a Mobile Health Application for Monitoring the Linkage Among Treatment Factors of Type 1 Diabetes Mellitus
Bellei, E. A., Biduski, D., Lisboa, H. R. K., & Marchi, A. C. B. D. (2019) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2018.0329 · Cited by 35
“65–71 The interactive visualization within Soins DM aims to facilitate the identification of patterns and treatment failures, the understanding of impact food have on glycemia, and how food interacts with exercise and insulin to prevent hypo-and hyperglycemia.”
HbA1c
Carlson, A. L., Criego, A. B., Martens, T. W., & Bergenstal, R. M. (2019) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2019.10.010 · Cited by 33
Reexamining the Hypoglycemia Fear Survey for Parents of Young Children in a Sample of Children Using Insulin Pumps
Patton, S. R., Noser, A. E., Clements, M. A., Dolan, L. M., & Powers, S. W. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2016.0389 · Cited by 29
“Mild dysglycemia” in type 2 diabetes: to be neglected or not?
Monnier, L., Colette, C., Dejager, S., & Owens, D. R. (2014) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2014.12.004 · Cited by 28
“Such an observation therefore indicates that, in persons with diabetes mellitus, there exist large inter-individual variations in blood glucose patterns (Bergenstal et al., 2013).”
Background
Use of Technology When Assessing Adherence to Diabetes Self-Management Behaviors
Driscoll, K. A., & Young-Hyman, D. L. (2014) · Current Diabetes Reports · doi:10.1007/s11892-014-0521-1 · Cited by 27
Continuous Glucose Monitoring Integration for Remote Diabetes Management: Virtual Diabetes Care with Case Studies
Carlson, A. L., Martens, T. W., Johnson, L., & Criego, A. B. (2021) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2021.0241 · Cited by 28
Continuous glucose monitoring in persons with type 2 diabetes not using insulin
Cowart, K., Updike, W. H., & Franks, R. B. (2021) · Expert Review of Medical Devices · doi:10.1080/17434440.2021.1992274 · Cited by 29
“CGM allows the PWD and clinician to analyze the impact that diet, exercise, stress, and medication can have on the management of T2D[10].”
BackgroundInfluential
Software Packages and Tools for the Analysis of Continuous Glucose Monitoring Data
Piersanti, A., Giurato, F., Göbl, C. S., Burattini, L., Tura, A., & Morettini, M. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0237 · Cited by 31
“16 Such template is currently adopted by the majority of CGM device manufacturers; however, international consensus on CGM data analysis and standard metrics that should be computed for clinical care has been reached only recently.”
Assessing the value of the Ambulatory Glucose Profile in clinical practice
Matthaei, S. (2014) · The British Journal of Diabetes · doi:10.15277/bjdvd.2014.045 · Cited by 27
Accuracy Evaluation of CONTOUR®PLUS Compared With Four Blood Glucose Monitoring Systems
Dunne, N., Viggiani, M. T., Pardo, S. A., Robinson, C., & Parkes, J. L. (2015) · Diabetes Therapy · doi:10.1007/s13300-015-0121-3 · Cited by 27
Update on the American Diabetes Association Standards of Medical Care
Zitkus, B. S. (2014) · The Nurse Practitioner · doi:10.1097/01.npr.0000451880.48790.50 · Cited by 25
Short‐term exercise training reduces glycaemic variability and lowers circulating endothelial microparticles in overweight and obese women at elevated risk of type 2 diabetes
Rafiei, H., Robinson, E., Barry, J., Jung, M. E., & Little, J. P. (2019) · European Journal of Sport Science · doi:10.1080/17461391.2019.1576772 · Cited by 25
“…can best be measured using continuous glucose monitoring (CGM) that is more informative than fasting plasma glucose or HbA1C as it allows for monitoring minute by minute changes in glucose levels in response to a short-term intervention and under free-living conditions (Bergenstal et al., 2013).”
Background
Practical guidance for using the FreeStyle Libre flash continuous glucose monitoring in primary care
Unger, J., Kushner, P. R., & Anderson, J. E. (2020) · Postgraduate Medicine · doi:10.1080/00325481.2020.1744393 · Cited by 27
“When reviewing the glucose data, we suggest you start with the AGP report [47], which is common to all download programs (Figure 2).”
Method
Time-in-range and frequency of continuous glucose monitoring: Recommendations for South Asia
Kesavadev, J., Misra, A., Saboo, B., Agarwal, S., Sosale, A., Joshi, S., Hussain, A., Somasundaram, N. P., Basit, A., Choudhary, P., et al. (2021) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2021.102345 · Cited by 24
Utilizing continuous glucose monitoring in primary care practice: What the numbers mean
Edelman, S. V., Cavaiola, T. S., BOEDER, S. C., & Pettus, J. (2020) · Primary care diabetes · doi:10.1016/j.pcd.2020.10.013 · Cited by 25
Chinese clinical guidelines for continuous glucose monitoring (2018 edition)
Bao, Y., Chen, L., Chen, L., Dou, J., Gao, Z., Gao, L., Guo, L., Guo, X., Ji, L., Ji, Q., et al. (2019) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.3152 · Cited by 23
“Therefore, standardization of CGM reports is extremely important.(114) Currently, CGM monitoring reports generally include three parts: (a) general items: basic information about the subject, clinical diagnosis, inspection date, medical staff signature and date; (b) CGM data; and (c) clinical implications of the resul…”
Background
Glucose Variability
Floch, J. P. L., & Kessler, L. (2016) · Journal of Diabetes Science and Technology · doi:10.1177/1932296816632003 · Cited by 23
“However, indices of glucose variability could be especially useful to analyze ambulatory glucose profiles and optimize decision making in diabetes.(16) For the clinician, it is important to get simple indices, poorly dependent of the mean glucose value commonly estimated with HbA1c and associated with glucose fluctuat…”
Background
Indication, organization, practical implementation and interpretation guidelines for retrospective CGM recording: A French position statement
Joubert, M., Baillot-Rudoni, S., Catargi, B., Charpentier, G., Esvant, A., Franc, S., Guerci, B., Guilhem, I., Melki, V., Merlen, E., et al. (2015) · Diabetes & Metabolism · doi:10.1016/j.diabet.2015.07.001 · Cited by 22
Recommendations for self-monitoring in pediatric diabetes: a consensus statement by the ISPED
Diabetes Study Group of the Italian Society for Pediatric Endocrinology and Diabetology, Scaramuzza, A. E., Cherubini, V., Tumini, S., Bonfanti, R., Buono, P., Cardella, F., d’Annunzio, G., Frongia, A. P., Lombardo, F., et al. (2013) · Acta Diabetologica · doi:10.1007/s00592-013-0521-7 · Cited by 22
“It is our belief that the National Health Service should provide all necessary resources to provide SMBG and possibly CGM to all children and adolescents with type 1 diabetes, according to the standards of care provided by these recommendations [1] and internationally [14, 17, 18, 71–74].”
Method

Authors: Bergenstal, R. M., Ahmann, A. J., Bailey, T., Beck, R. W., Bissen, J., Buckingham, B., Deeb, L., Dolin, R. H., Garg, S. K., Goland, R., Hirsch, I. B., Klonoff, D. C., Kruger, D. F., Matfin, G., Mazze, R. S., Olson, B. A., Parkin, C., Peters, A., Powers, M. A., Rodriguez, H., Southerland, P., Strock, E. S., Tamborlane, W., & Wesley, D. M.
Affiliations: Park Nicollet Clinic (US)
Oregon Health & Science University (US)
University of California San Diego (US)
Jaeb Center for Health Research (US)
Lucile Packard Children's Hospital (US)
Florida State University (US)
Lantana Consulting Group
University of Colorado Denver (US)
Columbia University Irving Medical Center (US)
University of Washington (US)
University of California, San Francisco (US)
Henry Ford Health (US)
CGParkin Communications, Inc.
University of Southern California (US)
University of South Florida (US)
Team Type 1, Atlanta, Georiga.
Yale University (US)
Corresponding author: Bergenstal, Richard M.
ORCID: Bergenstal, Richard M.
Ahmann, Andrew J.
Bailey, Timothy
Beck, Roy W.
Buckingham, Bruce
Dolin, Robert H.
Garg, Satish K.
Hirsch, Irl B.
Klonoff, David C.
Kruger, Davida F.
Parkin, Christopher
Peters, Anne
Rodriguez, Henry
Tamborlane, William
Venue: Diabetes Technology & Therapeutics
Publisher: SAGE Publications
Published: 2013-03
Volume: 15
Issue: 3
Pages: 198-211
ISSN: 1520-9156 (ISSN-L)
1557-8593
DOI: 10.1089/dia.2013.0051
OpenAlex: W2388765709
Cited by: 307
References: 55
Citations by year: 2026: 17 · 2025: 13 · 2024: 14 · 2023: 21 · 2022: 24 · 2021: 25 · 2020: 26 · 2019: 31 · 2018: 31 · 2017: 33 · 2016: 22 · 2015: 20 · 2014: 16 · 2013: 14
Type: conference abstract
Language: en
Open access: closed
Licence: journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Diabetes Technology & Therapeutics (publishedVersion)
PubMed (publishedVersion)
Funders: Leona M. and Harry B. Helmsley Charitable Trust
U.S. Food and Drug Administration
Abbott Diabetes Care
Topics: Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
Keywords: ambulatory glucose profile, continuous glucose monitoring, type 1 diabetes, glycemic control, clinical decision-making, expert panel recommendations
MeSH terms: Blood Glucose, Decision Making, Diabetes Mellitus, Female, Humans, Hyperglycemia, Hypoglycemia, Male, Reference Standards, Software, United States, Blood Glucose Self-Monitoring, Monitoring, Ambulatory

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

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