Blake Cooper, United States of America

Retina Associates Ophthalmology
Blake Cooper recently completed his Master of Public Health degree in Epidemiology at the Harvard T.H. Chan School of Public Health. He is a Chicago Medical School graduate, served an Ophthalmology residency and retina fellowship training at Washington University/Barnes-Jewish Hospital in St. Louis, MO. He has practiced in the Kansas City area for the last 18 years and is a partner in his practice, Retina Associates. He is a Board Certified Ophthalmologist, a Fellow in the American College of Surgeons, a member of many professional organizations and societies, including the American Academy of Ophthalmology, Alpha Omega Alpha Honor Medical Society, American Society of Retina Specialists, Association for Research in Vision and Ophthalmology, and various state and local groups. He has a deep professional and personal interest in improving the lives of those living with diabetes. Currently, he is serving on the Kansas/Missouri chapter board of JDRF, and his oldest daughter has been living well with T1D since 2012.

Presenter of 1 Presentation

 Conference Calendar
ORAL PRESENTATION SESSION

GLUCOSE MANAGEMENT INDICATOR (GMI) VARIABLY PREDICTS AVERAGE HBA1C LEVELS ACCORDING TO GLYCEMIC VARIABILITY (%CV) ACROSS THE LIFESPAN IN TYPE 1 DIABETES (T1D)

Date
Thu, 03.06.2021
Session Name
0260 - Oral Presentation 06 (ID 69)
Lecture Time
20:50 - 21:00
Presenter
Authors

Abstract

Background and Aims

Background and Aims: GMI can estimate average HbA1c based on the mean glucose from at least 14 days of CGM data. Using CGM data, one can also assess glycemic variability with coefficient of variation for glucose (CV, glucose SD/mean x 100%). Given that glycemic levels fluctuate across the lifespan, we aimed to evaluate the accuracy of GMI in estimating average A1c based on CV and age.

Methods

Methods: GMI was calculated from over 300 hours of baseline, masked CGM data collected before starting RT-CGM in 3 US studies in persons with T1D (SENCE [N=143, 2-6y] / CITY [N=152, 14-24y] / WISDM [N=203, 60-86y]). GMI (%) was calculated using the formula: 3.31 + 0.02392 x [mean glucose in mg/dL]. We assessed associations between baseline HbA1c, from a central laboratory, and CGM metrics (mean glucose, TIR (70-180mg/dL) by study and stratified by CV (≤36,>36).

Results

Results: Across all studies, lab HbA1c was strongly correlated with CGM metrics (p<0.0001). When CV>36 vs. CV≤36, GMI underestimated average HbA1c in all studies; greatest differences were seen in adolescents/young adults (CITY). Correlations between HbA1c and mean glucose and TIR were stronger when CV>36 (Table).

attd table.jpg

Conclusions

Conclusions: These 3 studies affirm that CGM metrics, both mean glucose and TIR, can estimate laboratory HbA1c. Notably, glycemic variability (CV) alters these associations across the lifespan in persons with T1D. Caution should be used in interpreting GMI in those with high variability due to risk for under-approximation; changes in RBC kinetics likely also impact these associations.

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