AGP for clinical trials:

Currently the IDC uses our CaptūrAGP® system as well as a SAS® program for producing research AGPs. The research AGP includes a second row of statistics: Glucose Variability, Exposure and Episodes close ups.

Our systems are able to produce SMBG, CGM and Insulin Pump + CGM reports. We can produce batched reports for different time periods, demographic sub populations and intervention arms. IDC provides AGP interpretation as well as research analytic reporting. If you want us to produce AGPs for your next research trial; we would be glad to help.
Research Intake Form

Research CGM AGP Report (Continuous Glucose Monitor)

Extended Statistics - Normally used in research, several of these will be blank if the data is from SMBG

Episodes close up: Episodes start when readings are within one of these ranges for at least 15 minutes; episodes end when there is a reading that is in target (70 -180). Fewer episodes are best for all these measures.
Avg. Min. per Day: How long in minutes the episodes of hypo- or hyperglycemia are per day on average
Mean Episodes/Day: How many episodes occur per day on average
Mean Duration (Min.): How long the episodes last on average

AUC Hourly: Measure of the space/ “area” beneath the median orange line; lower is better. Glucose exposures by period
Wake: between 6am and midnight Sleep: between midnight and 6am 24 Hours: from midnight to midnight

IQR (interquartile range): The range between the 75% and the 25% blue lines. The blue shaded area on the profile graph represents 50% of all the glucose measures. Ideally this shaded area is narrow, which shows less variation.
MAGE (Mean Amplitude of Glycemic Excursion): Measures the distance from a glucose high point to the low point or vice versa. This is the average of all excursions including the MAGE+ (going from low to high) and the MAGE– (going high to low); normally several per day. Lower is better.
MODD (Mean of Daily Differences): Compares the glucose level between two different days to help you understand the glucose patterns day to day. A patient with a higher MODD, has glucose patterns that fluctuate more widely. Lower is better.
LGBI (Low Blood Glucose Index): Index (0 – 100) of how many and how low glucose readings were in the measurement period. A high score means that there might be lots of mild low readings or a few very low readings or some of both. A low index is best.
HBGI (High Blood Glucose Index): Index (0 – 100) of how many and how high glucose readings were in the measurement period. A high score means that there might be lots of mild high readings or a few very highs or some of both. A low index is best.

"It is an efficient tool in standardizing CGM and SMBG data" -Clinician

"AGP is clean- across platforms!!" -Clinician

Where you can next meet our team:

ADA Annual Scientific Meeting in Orlando, FL June 22 - 26, 2018 Come see us in the ADA Exhibit Hall, Booth #1274.

Ongoing scientific trials:

  • NIH funded pilot study using Glooko AGP Report investigating patient barriers to diabetes management. (PI - Rich Bergenstal, MD)
  • Partnership study with Barbara Davis Center for Diabetes and IDC - using the AGP Report for patient downloads at home. (PI - Todd Alonso, MD)

  • References

    1. Danne, T., Nimri, R., Battelino, T., Bergenstal, R. M., Close, K. L., DeVries, J. H., ... & Beck, R. (2017). International consensus on use of continuous glucose monitoring. Diabetes Care, 40(12), 1631-1640.

    2. Riddle, Matthew C., Hertzel C. Gerstein, and William T. Cefalu. "Maturation of CGM and Glycemic Measurements Beyond HbA1c—A Turning Point in Research and Clinical Decisions." Diabetes Care, 40.12 (2017): 1611-1613.

    3. Petrie, J. R., Peters, A. L., Bergenstal, R. M., Holl, R. W., Fleming, G. A., & Heinemann, L. (2017). Improving the clinical value and utility of CGM systems: issues and recommendations. Diabetologia, 60(12), 2319-2328.

    4. Buckingham BA, Close KL, Bergenstal RM, Danne T, Grunberger G, Kowalski AJ, Peters A, Heller SR (2017). Reaching an International Consensus on Standardizing Continuous Glucose Monitoring (CGM) Outcomes―Aligning Clinicians, Researchers, Patients, and Regulators. American Diabetes Association 77th Scientific Meeting, San Diego, CA.

    5. Carlson, A. L., Mullen, D. M., & Bergenstal, R. M. (2017). Clinical use of continuous glucose monitoring in adults with type 2 diabetes. Diabetes Technology & Therapeutics, 19(S2), S-4.

    6. Mullen, D., et al. (2015). Reduced Staff Time with Optimized Work Flows and Standardized Ambulatory Glucose Profile (AGP) American Diabetes Association Scientific Meeting. Boston, MA.

    7. Mullen, D., et al. (2015). Understanding patient and clinician glucose reporting preferences in type 1 diabetes: Ambulatory Glucose Profile (AGP). Diabetologia, Springer, New York, NY.

    8. Mullen, D., et al. (2015). Understanding Patient and Clinician Glucose Reporting Preferences in Type 1 Diabetes: Ambulatory Glucose Profile (AGP) European Association for the Study of Diabetes Annual Meeting. Stockholm, Sweden.

    9. Bergenstal, R. M., et al. (2013). "Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the Ambulatory Glucose Profile (AGP)." Diabetes technology & therapeutics 15(3): 198-211.

    10. Matthaei, S. (2014). "Assessing the value of the Ambulatory Glucose Profile in clinical practice." British Journal of Diabetes 14(4): 148-152.

    11. Matthaei, S., et al. (2014). "Consensus recommendations for the use of Ambulatory Glucose Profile in clinical practice." British Journal of Diabetes 14(4): 153-157.

    12. Mazze, R. S., et al. (2008). "Characterizing glucose exposure for individuals with normal glucose tolerance using continuous glucose monitoring and ambulatory glucose profile analysis." Diabetes technology & therapeutics 10(3): 149-159.

    13. Mazze, R. S., et al. (1987). "Ambulatory glucose profile: representation of verified self-monitored blood glucose data." Diabetes Care 10(1): 111-117.