Comparison of the Glycemic Response to a Standardized Meal and Oral Glucose Tolerance Test Using CGM and Blood Glucose

Continuous Glucose Monitoring Devices (CGMS) are increasingly being utilized in research to assess chronic, free-living changes in postprandial glycemic variability (GV). Standard test meals may allow researchers to capture reproducible, clinically relevant data in a way that is more tolerable for participants. The purpose of this research study is to validate a meal glucose tolerance test (MGTT), using a combination of a CGM + a standard breakfast meal, against an oral glucose tolerance test (OGTT). Subjects (n=13) completed 3 in-person visits for this study. On the first visit, body composition data was collected along with installing a CGM device. After a 3-day washout, participants reported to the lab on the second visit following a 10-hour overnight fast. A fasting blood sample was taken, and participants consumed the treatment randomized for that visit (standard meal or 75g glucose drink). Blood glucose samples were synchronized with the CGM measurements and taken every 15 minutes during the 2-hour postprandial period. After another 3-day washout on the third visit, the participants received the opposite treatment following the 10-hour overnight fast and repeated the same 2-hour blood glucose testing procedure. We hypothesized that the meal and the drink conditions would yield statistically different means yet have strong correlations for the following: area under the curve (AUC), time to peak (TTP) and peak glucose (PG). Preliminary results show that AUC for the meal condition for CGM and blood samples were statistically different using a student’s t-test (p=<0.0001) and exhibited a strong correlation using a Pearson correlation coefficient and coefficient of determination (r=0.7, r 2 = 0.49). The same was true with CGM and blood tests under the glucose drink condition (p=<0.0001, r=0.76, r 2 =0.58). Interestingly, when tested using the blood samples, the meal and drink conditions were not statistically different for AUC (p=0.31). Both conditions had no statistical difference when tested with the CGM either (p=0.25). The PG for the drink condition showed that CGM and blood samples were significantly different (p=0.0216) and correlated (r=0.628, r 2 =0.394). The PG for the meal condition showed similar results (p=0.002, r=0.75, r 2 =0.394). Lastly, TTP under the drink condition was statistically different between CGM and blood samples (p=0.0007), and was strongly correlated (r=0.8128, r 2 =0.66). In contrast to our hypothesis, the two conditions, the drink and meal test, were not statistically different from each other for AUC when analyzing blood or CGM samples. Our preliminary results suggest that the meal test may be predictive of the glucose drink using either glycemic measures from blood or interstitial measures from CGM. BYU Interdisciplinary Research Award, BYU Life Sciences College Undergraduate Research Award This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.