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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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Mullen, D. M., Bergenstal, R., Criego, A., Arnold, K. C., Goland, R., & Richter, S. (2018) · Journal of Diabetes Science and Technology · doi:10.1177/1932296817740592 · Cited by 22
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Crossen, S., Romero, C., Reggiardo, A., Michel, J., & Glaser, N. (2022) · JMIR Diabetes · doi:10.2196/33639 · Cited by 21
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Background
Current landscape and comprehensive management of glycemic variability in diabetic retinopathy
Chen, B., Shen, C., & Sun, B. (2024) · Journal of Translational Medicine · doi:10.1186/s12967-024-05516-w · Cited by 21
“In recent years, interquartile range (IQR), an important indicator in the ambulatory glucose profile, was proposed as a powerful tool for assessing GV, primarily reflecting interday variability [27, 36–38].”
Method
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Beck, R. W., & Bergenstal, R. M. (2021) · Diabetes Spectrum · doi:10.2337/ds20-0090 · Cited by 21
Time above range for predicting the development of type 2 diabetes
Marco, A., Pazos-Couselo, M., Moreno-Fernández, J., Díez‐Fernández, A., Alonso‐Sampedro, M., Fernández‐Merino, C., González‐Quintela, A., & Gudé, F. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.1005513 · Cited by 21
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Rai, S., Hulse, A., & Kumar, P. K. M. (2016) · Indian Journal of Endocrinology and Metabolism · doi:10.4103/2230-8210.192894 · Cited by 21
“The usefulness of AGP in adults has been studied and guidelines have been recommended by experts in the field.[10,11] To date, there are no studies looking into the feasibility of this tool in children.”
Background
Professional flash continuous glucose monitoring as a supplement to A1C in primary care
Hirsch, I. B. (2017) · Postgraduate Medicine · doi:10.1080/00325481.2017.1383137 · Cited by 24
“The classic AGP ‘dashboard,’ designed as one-page report, consists of three parts [15]:”
BackgroundMethodInfluential
It's Time to Move from the A1c to Better Metrics for Diabetes Control
Kowalski, A. J., & Dutta, S. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0060 · Cited by 21
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Beck, R. W. (2023) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2023.0602 · Cited by 20
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Forlenza, G. P., Pyle, L. L., Maahs, D. M., & Dunn, T. C. (2016) · Pediatric Diabetes · doi:10.1111/pedi.12474 · Cited by 20
“Numerically the AGP also presents average glucose, estimated HbA1c, glucose standard deviation and IQR, as well as percent time in various ranges and the option for “Close-Up” statistics on area under the curve (AUC) analysis, variability, and hyperglycemia/hypoglycemia episodes.(15) To evaluate the longitudinal benef…”
BackgroundMethod
Maternal–Fetal Outcomes in 34 Pregnant Women with Type 1 Diabetes in Sensor-Augmented Insulin Pump Therapy
Gómez, A. M., Carrillo, L. F. M., Correa, C. M. A., Múñoz, Ó., Rondón, M., Silva-Herrera, J. L., & Henao, D. C. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0030 · Cited by 20
The Ambulatory Glucose Profile: Opportunities for Enhancement
Rodbard, D. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0524 · Cited by 20
“8–25 This report summarizes a number of proposals for improvement of the effectiveness and informativeness of the AGP, some that had been presented years ago (e.g., log scale, 38 display of data points, 5,7 risks or rates of hypoglycemia and hyperglycemia, 9,17 and analysis by day of the week 7,16…”
Professional Flash Continuous Glucose Monitoring with Ambulatory Glucose Profile Reporting to Supplement A1c: Rationale and Practical Implementation
Hirsch, I. B., & Verderese, C. A. (2017) · Endocrine Practice · doi:10.4158/ep171962.ra · Cited by 22
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Reutrakul, S., Irsheed, G. A., Park, M., Steffen, A. D., Burke, L., Pratuangtham, S., Baron, K. G., Duffecy, J. L., Perez, R. I., Quinn, L., et al. (2023) · Sleep Health · doi:10.1016/j.sleh.2023.07.007 · Cited by 19
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Thyde, D. N., Mohebbi, A., Bengtsson, H. L., Jensen, M. L., & Mørup, M. (2020) · Journal of Diabetes Science and Technology · doi:10.1177/1932296820912411 · Cited by 24
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Aleppo, G., Chmiel, R., Zurn, A., Bandoske, R., Creamer, P., Neubauer, N., Wong, J., Andrade, S. B., & Hauptman, A. (2023) · Journal of Diabetes Science and Technology · doi:10.1177/19322968231196168 · Cited by 19
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Improved glycaemic control and treatment satisfaction with a simple wearable 3‐day insulin delivery device among people with Type 2 diabetes
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“The AGP report incorporates all the core CGM metrics and targets along with a 14-day composite glucose profile as an integral component of clinical decision making [19].”
Background
Health-System-Based Interventions to Improve Care in Pediatric and Adolescent Type 1 Diabetes
Corathers, S. D., Schoettker, P. J., Clements, M. A., List, B. A., Mullen, D. M., OHMER, A. L., Shah, A. C., & Lee, J. M. (2015) · Current Diabetes Reports · doi:10.1007/s11892-015-0664-8 · Cited by 17
A randomized controlled trial to compare the effects of sulphonylurea gliclazide MR (modified release) and the DPP-4 inhibitor vildagliptin on glycemic variability and control measured by continuous glucose monitoring (CGM) in Brazilian women with type 2 diabetes
Vianna, A. G. D., de Lacerda, C. S., Pechmann, L. M., Polesel, M. G., Marino, E. C., & Faria‐Neto, J. R. (2018) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2018.03.035 · Cited by 17
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McQueen, R. B., Ellis, S. L., Maahs, D. M., Anderson, H. D., Nair, K. V., Libby, A. M., & Campbell, J. D. (2014) · Patient · doi:10.1007/s40271-014-0045-4 · Cited by 17
“Leaders in the type 1 diabetes research field have suggested using alternative metrics to describe glycemic control such as glycemic variability (GV) [32].”
Background
Profiling intra-patient type I diabetes behaviors
Contreras, I., Quirós, C., Giménez, M., Conget, I., & Vehı́, J. (2016) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2016.08.022 · Cited by 17
The ambulatory glucose profile and its interpretation
Lin, R., Brown, F., & Ekinci, E. I. (2022) · The Medical Journal of Australia · doi:10.5694/mja2.51666 · Cited by 15
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“FCGM personal and professional devices were among the first to feature the AGP, which is gradually being incorporated into other CGM systems (84,85).”
Background
How use of continuous glucose monitoring can address therapeutic inertia in primary care
Martens, T. W., & Parkin, C. G. (2022) · Postgraduate Medicine · doi:10.1080/00325481.2022.2080419 · Cited by 16
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Glucodensity functional profiles outperform traditional continuous glucose monitoring metrics
Matabuena, M., Ghosal, R., Aguilar, J. E., Keshet, A., Wagner, R. J., Fernández‐Merino, C., Castro, J. S., Zipunnikov, V., Onnela, J.-P. “., & Gudé, F. (2025) · Scientific Reports · doi:10.1038/s41598-025-18119-2 · Cited by 15
“The traditional CGM and non-CGM models include: (i) baseline FPG and HbA1c; and (ii) baseline FPG and HbA1c, along with CGM metrics like the Area Under the Curve (AUC), Mean Amplitude of Glycemic Excursions (MAGE), Continuous Overall Net Glycemic Action (CONGA), and hyperglycemia time-in-range.”
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McQueen, R. B., Ellis, S. L., Maahs, D. M., Anderson, H. D., Nair, K. V., & Campbell, J. D. (2014) · Endocrine Practice · doi:10.4158/ep14027.or · Cited by 14
Use of continuous glucose monitoring trend arrows in the younger population with type 1 diabetes
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Olsen, M. T., Klarskov, C. K., Dungu, A. M., Hansen, K. B., Pedersen‐Bjergaard, U., & Kristensen, P. L. (2024) · Journal of Diabetes Science and Technology · doi:10.1177/19322968231221803 · Cited by 14
“38 The AGP report has three major components: (1) glucose statistics and time in different glucose ranges, (2) a single 24-hour “modal” day that combines all daily CGM glucose data, referred to as AGP, and (3) daily glucose profiles.”
Evaluating a Glucose-Sensor-Based Tool to Help Clinicians and Adults With Type 1 Diabetes Improve Self-Management Skills
Toschi, E., Fisher, L., Wolpert, H. A., Love, M., Dunn, T. C., & Hayter, G. (2018) · Journal of Diabetes Science and Technology · doi:10.1177/1932296818791534 · Cited by 15
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Martyn-Nemeth, P. A., Duffecy, J. L., Quinn, L., Park, C., Mihailescu, D. V., & Penckofer, S. M. (2019) · Trials · doi:10.1186/s13063-019-3876-4 · Cited by 13
Standardized Hybrid Closed-Loop System Reporting
Shah, V. N., & Garg, S. K. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0622 · Cited by 14
“26 In addition, a recent study showed that mean glucose has the highest discrimination power, suggesting that mean glucose is the easiest and best indicator to discriminate between individuals.”
Influential
Standardizing Reporting of Glucose and Insulin Data for Patients on Multiple Daily Injections Using Connected Insulin Pens and Continuous Glucose Monitoring
Rodbard, D., & Garg, S. K. (2021) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2021.0030 · Cited by 13
Electrochemical Glucose Biosensors for Diabetes Care
Ocvirk, G., Buck, H., & DuVall, S. H. (2016) · Bioanalytical reviews · doi:10.1007/11663_2016_3 · Cited by 13
“The development of standardized, automated data analysis and display tools is enabling HCPs to evaluate the status of a patient in a convenient way [272].”
BackgroundMethod
Evaluation of accuracy of ambulatory glucose profile in an outpatient setting in children with type 1 diabetes
Hulse, A., Rai, S., & KUMAR, K. M. P. (2016) · Indian Journal of Endocrinology and Metabolism · doi:10.4103/2230-8210.190546 · Cited by 12
Relationships Between Glycemic Control and Cardiovascular Fitness
Moxley, E. W., SMITH, D. P., Quinn, L. T., & Park, C. (2018) · Biological Research For Nursing · doi:10.1177/1099800418767572 · Cited by 13
Flash Continuous Glucose Monitoring: Implications for Use of Continuous Data in Daily Diabetes Management
Hirsch, I. B., Nardacci, E., & Verderese, C. A. (2019) · Diabetes Spectrum · doi:10.2337/ds18-0059 · Cited by 12
“FCGM personal and professional devices were among the first to feature the AGP, which is now available with other CGM systems as well (88,89).”
Background
Advances in glucose monitoring: Improving diabetes management through evidence-based medicine
Mazze, R. S. (2020) · Primary care diabetes · doi:10.1016/j.pcd.2020.03.001 · Cited by 12
Letter to the Editor
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A Patient-level Analysis of Efficacy and Hypoglycaemia Outcomes Across Treat-to-target Trials with Insulin Glargine Added to Oral Antidiabetes Agents in People with Type 2 Diabetes
DeVries, J. H., Meneghini, L., Barnett, A. H., Reid, T., Dain, M., Sanofi, P., Landgraf, W., Vlajnic, A., Traylor, L., & Bergenstal, R. M. (2014) · touchREVIEWS in Endocrinology · doi:10.17925/ee.2014.10.01.23 · Cited by 11
Using the respective contributions of postprandial and basal glucose for tailoring treatments in type 2 diabetes
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Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens
Simonson, G. D., Criego, A. B., Battelino, T., Carlson, A. L., Choudhary, P., Franc, S., Gershenoff, D. C., Grunberger, G., Hirsch, I. B., Isaacs, D. M., et al. (2024) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2024.0107 · Cited by 11
Using Digital Health Technologies to Understand the Association Between Movement Behaviors and Interstitial Glucose: Exploratory Analysis
Kingsnorth, A. P., Whelan, M., Sanders, J. P., Sherar, L. B., & Esliger, D. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9471 · Cited by 11
“Mean glucose and SD of glucose were indicated as the most common and easily interpreted metrics [24], and MAGE is considered the gold standard for glucose variability measurement [25].”
Investigating Temporal Patterns of Glycemic Control around Holidays
Belsare, P. V., Lu, B., Bartolome, A., & Prioleau, T. (2022) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc48229.2022.9871646 · Cited by 10
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“19 This format was endorsed by the international consensus on TIR 17 and was also referenced by the American Diabetes Association 2023 Standards of Care 20 and the American Association of Clinical Endocrinology (AACE) consensus on the use of CGM. 21 The AGP report is now adopted by many CGM device…”
Evaluating Alignment Approaches in Superimposed Time-Series and Temporal Event-Sequence Visualizations
Zhang, Y., Bartolomeo, S. D., Sheng, F., Jimison, H. B., & Dunne, C. (2019) · Visualization · doi:10.1109/visual.2019.8933584 · Cited by 10
“2, and taskonomies for Type 1 diabetes management [1, 15].”
Background
Understanding Reflection Needs for Personal Health Data in Diabetes
Prioleau, T., Sabharwal, A., & Vasudevan, M. M. (2020) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.1145/3421937.3421972 · Cited by 10
“hen there is no supporting data of a patient’s blood glucose trends. (2) Low Blood Glucose is directly associated with acute complications such as loss of consciousness, seizures, and even death [4], [7], [23]. Following analysis for data sufficiency, identifying hypoglycemic (i.e. low blood glucose) events is a prior…”
BackgroundMethodInfluential
Device profile of the eversense continuous glucose monitoring system for glycemic control in type-1 diabetes: overview of its safety and efficacy
Irace, C., Cutruzzolà, A., Tweden, K. S., & KAUFMAN, F. R. (2021) · Expert Review of Medical Devices · doi:10.1080/17434440.2021.1982380 · Cited by 12
Choosing the duration of continuous glucose monitoring for reliable assessment of time in range: A new analytical approach to overcome the limitations of correlation‐based methods
Camerlingo, N., Vettoretti, M., Sparacino, G., Facchinetti, A., Mader, J. K., Choudhary, P., & Favero, S. D. (2021) · Diabetic Medicine · doi:10.1111/dme.14758 · Cited by 10
Inhibition of SGLT1 Alleviates the Glycemic Variability-Induced Cardiac Fibrosis via Inhibition of Activation of Macrophage and Cardiac Fibroblasts
Wu, W., Chai, Q., & Zhang, Z. (2021) · Molecular and Cellular Biology · doi:10.1128/mcb.00282-21 · Cited by 10
“ability is closer to the actual changes in blood sugar level in diabetic patients (5).”
Background
Is Continuous Glucose Monitoring a Tool, an Intervention, or Both?
Wright, E. E., & Subramanian, S. (2023) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2023.0025 · Cited by 10
Glucose concentrations in blood and tissue - a pilot study on variable time lag
Chlup, R., Krejčí, J., O’Connell, M. T., Sebestova, B., Plička, R., Ježová, L., Brozova, T., Doubravová, B., Zálešáková, H., Ďurajková, E., et al. (2015) · Biomedical Papers · doi:10.5507/bp.2015.007 · Cited by 10
Development of the Likelihood of Low Glucose (LLG) Algorithm for Evaluating Risk of Hypoglycemia
Dunn, T. C., Hayter, G., Doniger, K., & Wolpert, H. A. (2014) · Journal of Diabetes Science and Technology · doi:10.1177/1932296814532200 · Cited by 11
“There is a need for glucose reports that can provide standardized, efficient output to effectively guide therapeutic decision making.(12-14) Key benefits of glucose reports include consistent view of glucose trends and patterns over the day, and showing the detail that A1C cannot.”
Background
A guide for the use of LibreView digital diabetes platform in clinical practice: Expert paper of the Italian Working Group on Diabetes and Technology
Molfetta, S. D., Rossi, A., Assaloni, R., Cherubini, V., Consoli, A., Bartolo, P. D., Guardasole, V., Laurenzi, A., Lombardo, F., Maffeis, C., et al. (2022) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2022.109867 · Cited by 13
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Chlup, R., Doubravová, B., Bartek, J., Zapletalová, J., Krystyník, O., & Procházka, V. (2013) · Disease Markers · doi:10.1155/2013/702427 · Cited by 10
Applications of Variability Analysis Techniques for Continuous Glucose Monitoring Derived Time Series in Diabetic Patients
Kohnert, K., Heinke, P., Vogt, L., Augstein, P., & Salzsieder, E. (2018) · Frontiers in Physiology · doi:10.3389/fphys.2018.01257 · Cited by 10
“We used TIR as an established and clinically useful indicator of the quality of glycemic control, reflecting the time in predefined target ranges (Bergenstal et al., 2013 and Rodbard, 2018).”
MethodInfluential
A Markov model for inferring event types on diabetes patients data
de Carvalho, D. F., Kaymak, U., Gorp, P. M. E. V., & van Riel, N. A. W. (2022) · Healthcare Analytics · doi:10.1016/j.health.2022.100024 · Cited by 9
“To enable a less wide but still representative observation of glucose levels, the BG signal was discretized based on six recommended ranges according to clinical diagnosis and safety [34–36].”
Method
A systematic bibliometric analysis on the clinical practice of CGM in diabetes mellitus from 2012 to 2022
Kong, L., Deng, B., Guo, M., Chen, M., Wang, X., Zhang, M., Tang, H., Wang, Q., Yang, L., & Xiong, Z. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1229494 · Cited by 10
Flash Glucose Monitoring Improves Glucose Control in People with Type 2 Diabetes Mellitus Receiving Anti-diabetic Drug Medication
Chen, M.-Y., Li, H., Shen, Y., Liu, B., Yan, R., Sun, X., Ye, L., Lee, K., Ma, J., & Su, X. (2020) · Experimental and Clinical Endocrinology & Diabetes · doi:10.1055/a-0994-9850 · Cited by 9
Pump It Up! A randomized clinical trial to optimize insulin pump self-management behaviors in adolescents with type 1 diabetes
O’Donnell, H. K., Vigers, T., Johnson, S. B., Pyle, L. L., Wright, N. A., Deeb, L. C., & Driscoll, K. A. (2021) · Contemporary Clinical Trials · doi:10.1016/j.cct.2021.106279 · Cited by 10
“In fact, some T1D providers are uncertain about how to interpret and use the reports in clinical care and may not be able to invest the time necessary to become proficient in interpreting the data [14,15].”
Background
Insulin Pump-Associated Adverse Events: A Qualitative Descriptive Study of Clinical Consequences and Potential Root Causes
Estock, J. L., Codario, R. A., Keddem, S., Zupa, M. F., Rodriguez, K. L., & DiNardo, M. M. (2023) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0498 · Cited by 9
The different methods of assessing glycemic variability, quality of glycemic control and glycemic risk cannot be interpreted as equivalent in clinical practice
Múñoz, Ó., Gómez, A. M., Maira, G., Vargas, F. M. L., & Ruiz, Á. J. (2018) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2018.03.028 · Cited by 9
“Thus, IQR is a component of the international proposal for the standardized reporting on the ambulatory glucose profile [17].”
Background
A Primary Care Perspective on the Use of Continuous Glucose Monitoring in Clinical Practice
Bhide, M., Grey, J. M. S., Moser, E. G., & Garg, S. K. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0169 · Cited by 9
Unleashing the Potential of Blood Glucose Monitoring Data With the Ambulatory Glucose Profile Report
Simonson, G. D., Holt, E. H., Grady, M., Hurrell, G., Gaudiani, L., & Bergenstal, R. M. (2024) · Clinical Diabetes · doi:10.2337/cd23-0092 · Cited by 10
Expert Clinical Interpretation of Continuous Glucose Monitor Reports From Individuals Without Diabetes
Spartano, N. L., Prescott, B. R., Walker, M. E., Shi, E., Venkatesan, G., Fei, D., Lin, H., Murabito, J. M., Ahn, D. T., Battelino, T., et al. (2025) · Journal of Diabetes Science and Technology · doi:10.1177/19322968251315171 · Cited by 8
“15 We observed remarkable differences of opinion among clinicians in terms of how to interpret elevated post-prandial glucose levels (both brief and prolonged) or substantial time spent below range ( 70 mg/dL), including what glucose levels may be considered “elevated” or “low.””
Relationship Between Daytime Versus Nighttime Continuous Glucose Monitoring Metrics with A1C in Adults with Type 1 Diabetes
Shah, V. N., Aktürk, H. K., Vigers, T., Pyle, L. L., Oliver, N. S., & Klonoff, D. C. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0365 · Cited by 8
Possible Impacts of New Accuracy Standards of Self-Monitoring of Blood Glucose
Garg, S. K., Reed, K., Grey, J. M. S., Westerman, A., & Pediatrics, P. O. M. A. (2013) · US Endocrinology · doi:10.17925/use.2013.09.01.16 · Cited by 8
Resistance to data loss from the Freestyle Libre: impact on glucose variability indices and recommendations for data analysis
Kingsnorth, A. P., Whelan, M., Orme, M. W., Routen, A. C., Sherar, L. B., & Esliger, D. (2020) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2020-0386 · Cited by 8
“Mean daily glucose as a measure of glucose exposure was calculated as the average of all datapoints for a given data file, which has been reported as a metric which both patients and clinicians can understand (Bergenstal et al. 2013), and characterises daily variations in glucose concentrations.”
Method
The Future of Glucose Monitoring
Garg, S. K. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0421 · Cited by 8
Practical Approaches to Continuous Glucose Monitoring in Primary Care: A UK-Based Consensus Opinion
Fernando, K., Alabraba, V., Welsh, J. B., Seidu, S., Strain, W. D., Bell, H. E., Davies, S., & Evans, M. (2025) · Diabetes Therapy · doi:10.1007/s13300-025-01706-x · Cited by 7
“The ambulatory glucose profile (AGP) was introduced in 2013 as a standardised way to present CGM data [20, 21], and most CGM manufacturers license it for use with their systems’ data.”
The Relationship Between Parent Fear of Hypoglycemia and Youth Glycemic Control Across the Recent-Onset Period in Families of Youth with Type 1 Diabetes
Monzon, A. D., Majidi, S., Clements, M. A., & Patton, S. R. (2023) · International Journal of Behavioral Medicine · doi:10.1007/s12529-023-10159-0 · Cited by 7
“…child’s glucometer for the 2 weeks before their study visit, and researchers used the glucose value ranges recommended by Bergenstal and colleagues [35] to estimate the percentage of glucose levels that were below the target range (< 70 mg/dl), within the target range (70–180 mg/dl), and above the…”
Kernel-based adaptive learning improves accuracy of glucose predictive modelling in type 1 diabetes: A proof-of-concept study
Georga, E. I., Príncipe, J. C., Rizos, E. C., & Fotiadis, D. I. (2017) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2017.8037430 · Cited by 7
“Ambulatory Glucose Profile (AGP) report [20] of a typical subject (Subject #1) is portrayed in Fig.”
Background
Blood Glucose Monitoring Before and After Type 1 Diabetes Clinic Visits
Driscoll, K. A., Johnson, S. B., Wang, Y., Wright, N. A., & Deeb, L. C. (2017) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsx151 · Cited by 8
Diabetes Healthcare Professionals Use Multiple Continuous Glucose Monitoring Data Indicators to Assess Glucose Management
Sheng, T., Offringa, R., Kerr, D. E., Clements, M. A., Fischer, J., Parks, L. J., & Greenfield, M. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819873641 · Cited by 7
“While HbA1c is widely used as an indicator of recent (approximately three months) glycemic control, it is limited in its use to predict hypoglycemia risk(10) or as a rapid indicator following treatment and/or behavior change.(11) This is particularly important in the context of calculating safe and effective doses of…”
Background
Relationship between interstitial glucose variability in ambulatory glucose profile and standardized continuous glucose monitoring metrics; a pilot study
Tokutsu, A., Okada, Y., Torimoto, K., & Tanaka, Y. (2020) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-020-00577-5 · Cited by 5
“AGP is an excellent tool that clearly and visually presents the trends in interstitial glucose variability for the individual patient [9]; our study showed that AIQR is a valuable index for use in AGP.”
Method
Use of ambulatory glucose monitoring and analysis of ambulatory glucose profile in clinical practice for diabetes management; a position statement of the Arab Society of Paediatric Endocrinology and diabetes
Deeb, A., Muammar, T., Alsaffar, H., Sedaghat, S., Hassani, N. A., Odeh, R., Alkhayyat, H., Sinani, A. A., Attia, N. A., Adhami, S., et al. (2021) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2021.108671 · Cited by 7
Closing the Loop
Nimri, R., Murray, N., Ochs, A., Pinsker, J. E., & Dassau, E. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.2504 · Cited by 8
Practical Application of Continuous Glucose Monitoring in Clinical Practice: Case Studies
Unger, J., & Franco, D. R. (2023) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2023.0080 · Cited by 7
“29 Originally created by Mazze et al., 30 the AGP was further reﬁned by the International Diabetes Center (Min-neapolis, MN).”
Optimizing Diabetes Care With the Standardized Continuous Glucose Monitoring Report
Chun, J. H., & O’Neill, M. S. (2020) · Clinical Diabetes · doi:10.2337/cd19-0066 · Cited by 6
“A key contributor to clinicians’ reluctance to embrace CGM,particularly in the primary care setting, has been the large amount of data to interpret without a standardized report format to allow for efficient clinical application (7).”
Background
The phenomenon of HbA1c stability and the risk of hypoglycemia in long-standing type 1 diabetes
Wolnik, B., Orłowska-Kunikowska, E., Błaszkowska, M., Graff, B., Wolf, J., Czupryniak, L., & Narkiewicz, K. (2019) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2019.05.010 · Cited by 7
Resolution on the results of the first working meeting of the scientific advisory board «Actual problems of glycemic variability as a new criterion of glycemic control and safety of diabetes therapy»
Antsiferov, M. B., Galstyan, G. R., Zilov, A. V., Mayorov, A. Y., Markova, T. N., Demidov, N. A. D., Koteshkova, O. M. K., Лаптев, Д. Н., & Vitebskaya, A. V. (2019) · Diabetes Mellitus · doi:10.14341/dm10227 · Cited by 8
Clinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus
Lee, W., Kim, N., Jung, I., Park, S. Y., Yu, J. H., Seo, J. A., Kim, J., Kim, K. J., Kim, N. H., Yoo, H. J., et al. (2023) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2022.0273 · Cited by 6
“Currently, continuous glucose monitoring (CGM) has been recommended as an indicator of glycemic control and for decision making in treatment regimens [5] and as a tool to assess GV [6,7].”
BackgroundMethod
Testing versus guessing blood glucose values: impact on self-care behaviors in type 2 diabetes
Pettus, J., Stenger, P., Schachner, H. C., Dunne, N., Parkes, J. L., Pardo, S. A., & Edelman, S. V. (2014) · Current Medical Research and Opinion · doi:10.1185/03007995.2014.929097 · Cited by 6
HYPOalert
Faiola, A. J., Vatani, H., Greenhill, K., Bhuma, M., & Agarwal, M. (2018) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.1145/3240925.3240975 · Cited by 6
AGP in daily clinical practice: a guide for use with the FreeStyle Libre flash glucose monitoring system
Gibb, F. W., Jennings, P. L., Leelarathna, L., & Wilmot, E. G. (2020) · British Journal of Diabetes · doi:10.15277/bjd.2020.240 · Cited by 6
FDA Supports Standardized Reporting and Analysis on CGM Devices
Serrano, K. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.8313 · Cited by 6
Beyond Glycated Hemoglobin: Harnessing Data From Sensor-Based Technology to Improve Glucose Variability, Time in Range and Hypoglycemia in Adult Patients With Type 1 Diabetes
Chan, A. J., & Halperin, I. J. (2020) · Canadian Journal of Diabetes · doi:10.1016/j.jcjd.2020.08.103 · Cited by 6
Sleep optimization to improve glycemic control in adults with type 1 diabetes: study protocol for a randomized controlled parallel intervention trial
Martyn-Nemeth, P. A., Duffecy, J. L., Quinn, L., Reutrakul, S., Steffen, A. D., Burke, L., Withington, M. H. C., Irsheed, G. A., Perez, R., Park, M., et al. (2022) · Trials · doi:10.1186/s13063-022-06565-6 · Cited by 6
“Variables to be derived from the CGM are mean glucose level, standard deviation (SD), coefficient of variation (CV), percentage of time spent in range (70–180 mg/dL), percentage of time < 70 mg/dl, and percentage of time ≥ 180 mg/dl [65, 66].”
Background
Jointly Predicting Postprandial Hypoglycemia and Hyperglycemia Using Continuous Glucose Monitoring Data in Type 1 Diabetes
Cui, R., Nolan, C. J., Daskalaki, E., & Suominen, H. (2023) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc40787.2023.10340094 · Cited by 8
How to Use Continuous Glucose Monitoring Efficiently in Diabetes Management: Opinions and Recommendations by German Experts on the Status and Open Questions
Thomas, A., Haak, T., Tombek, A., Kulzer, B., Ehrmann, D., Kordonouri, O., Kröger, J., Schubert-Olesen, O., Kolassa, R., Siegmund, T., et al. (2024) · Journal of Diabetes Science and Technology · doi:10.1177/19322968241267768 · Cited by 5
“15,16 17-19 More recently, another parameter was proposed that overcomes some of the limitations of the other parameters, which eventually will become the preferred metric for outcomes trials using CGM, the glycemic risk index (GRI).”
Evaluation of a Clinical Tool to Test and Adjust the Programmed Overnight Basal Profiles for Insulin Pump Therapy: A Pilot Study
Orszag, A., Falappa, C. M., Lovblom, L. E., Partridge, H., Menezes, H. T., Boulet, G., Picton, P. E., Cafazzo, J. A., & Perkins, B. A. (2015) · Canadian Journal of Diabetes · doi:10.1016/j.jcjd.2015.01.005 · Cited by 5

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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