Revolutionizing OGTT: Unlocking the Real-Time Insights and Expanded Data of Continuous Glucose Monitoring

The article by Gonzalez et al (1) evaluated the feasibility, acceptability, and validity of a home-based continuous glucose monitor (CGM)-based oral glucose tolerance test (OGTT) for type 2 diabetes (T2D) screening in youth, in comparison to traditional 2-hour research laboratory-based OGTT. This study addresses an important challenge of early diagnosis of T2D among youth with overweight/obesity body habitus, prediabetes, or with 1 or more T2D risk factors. Seventy-seven percent (n = 39) of the participants met overall feasibility criteria with high overall acceptability, with 69% stating that they preferred home-OGTT to research-OGTT as a strategy to screen for T2D in youth (1). The study showed high sensitivity (100% for fasting and 80% 2-hour glucose) and a high negative predictive value (100% for fasting and 85.7% for 2-hour glucose), indicating the test's reliability in ruling out abnormal cases (1). However, the validity results were mixed with low specificity and low positive predictive values for fasting and 2-hour glucose (1). The authors highlight that a key barrier to implementation was the challenge of precisely timing the glucose beverage consumption and defining glucose thresholds. They emphasize optimizing glucose ingestion protocols and refining dysglycemia criteria.

This timely study addresses urgent concerns surrounding the rapid rise and delayed diagnosis of T2D among youth. One-hour plasma glucose of 155 mg/dL or greater during an OGTT is a better predictor of future diabetes than glycated hemoglobin A_1c (HbA_1c) but requires proper specimen handling. This limitation has sparked interest in CGM as an alternative to detect early β-cell dysfunction, though its utility in high-risk youth with normal A_1c remains uncertain. A few studies have investigated the use of CGM with or without an OGTT in diagnosing conditions such as gestational diabetes or cystic fibrosis–related diabetes. For example, a qualitative study by Kusinski et al (2) demonstrated that home-based CGM with or without OGTT is a feasible, convenient, well-accepted diagnostic tool by pregnant women for gestational diabetes diagnosis. A study by Filippo et al (3) found that women preferred CGM over traditional OGTT for diagnosing gestational diabetes. The study evaluated the use of Freestyle Libre Pro 2 as a diagnostic test for gestational diabetes, comparing its results with OGTT results, a risk-factor-based total risk score, and sonographic features of gestational diabetes suggesting potential overdiagnosis (3). In a study among patients with cystic fibrosis (n = 30, aged 10-18 years), CGM monitoring detected glucose abnormalities missed by traditional OGTT, providing an advantage for early diagnosis and management of prediabetes (4). However, CGM-based OGTTs have not been investigated among high-risk youth without T2D. In a pilot study by Dorcely et al (5), participants underwent a CGM-based OGTT, demonstrating that 1-hour plasma glucose and CGM-derived glycemic variability (GV) can effectively identify dysglycemia, even in individuals with normal HbA_1c levels . A study by Erdős et al (6) found that CGM values combined with insulin data during OGTT in individuals with overweight and obesity effectively calibrated personalized models of glucose-insulin dynamics.

Accurate thresholds are critical to identifying early dysglycemia and preventing overdiagnosis or underdiagnosis, particularly in high-risk youth. Prior studies have reported poor reproducibility of OGTT in youth with overweight habitus, with discordant results associated with insulin resistance, lower glucose disposition index, and higher low-density lipoprotein cholesterol, suggesting an elevated risk for T2D (7). Given there are no CGM-based criteria for diabetes diagnosis, one study analyzed the potential implications of this variability on the classification of glycemic status based on current plasma glucose–based diagnostic guidelines. Investigating fasting GV with CGM in adults aged 40 to 70 years, without diabetes, this study revealed intrapersonal, day-to day variability in the values (8). Similarly, in the current study, CGM values tended to be higher than laboratory-based measurements. Therefore, CGM values could not be directly used to diagnose impaired fasting glucose or impaired glucose tolerance based on standard definitions.

Additionally, several factors can influence the accuracy and reliability of a CGM-based OGTT.

For example, in this study, accurately determining the timing of glucose beverage consumption remained challenging, even with the support of text message reminders and participant logging. Medications (eg, acetaminophen), improper sensor placement, and calibration errors can compromise the accuracy of CGM-based OGTT results. Test factors such as differences in each patient's adherence to protocols (eg, glucose drink timing) and posttest factors such as sensor lag, data artifacts (eg, signal loss, device malfunction), and absence of CGM-specific glucose cutoffs, can influence reliability of CGM-based OGTT results.

Real-time CGMs have transformed how glycemic patterns are monitored and managed in the past few years. Integrating this innovation with a home-based OGTT offers the convenience of eliminating hospital visits and enables participants to perform the test in the comfort of their homes. However, some adolescents might prefer laboratory-based tests to avoid at-home procedures. Device visibility can be a limiting factor for adolescents due to the stigma around diabetes. Despite these considerations, home-based CGM OGTT offers flexibility, comfort, and the unique advantage of more real-time data points and responses to activities, facilitating more personalized assessments.

In conclusion, home-based CGM OGTT, especially when integrated with CGM for a certain period of time, holds substantial potential to individualize screening and revolutionize the diagnosis and management of prediabetes in individuals with overweight, obesity, and risk factors for T2D. To fully realize its potential, further refinement is required including development of standardized CGM protocols, establishing CGM-specific glucose thresholds, and examining their relationship with prediabetes-associated complications such as insulin resistance and metabolic syndrome. Defining dysglycemia in this high-risk population with normal A_1c levels requires the development of evidence-based criteria that consider age, body mass index, pubertal staging, and unique physiological characteristics. Ultimately, further research is required to establish criteria that connect CGM patterns, such as GV and postprandial hyperglycemia, to long-term risks, such as progression to development of T2D and cardiovascular disease. Future study designs should also focus on repeated fasting and postprandial measurements to consider intraindividual variability. Using CGM for diagnostic and predictive approaches can help with timely interventions and personalized management strategies to delay the onset of T2D in vulnerable youth.

Abbreviations

CGM

continuous glucose monitoring

GV

glycemic variability

HbA_1c

hemoglobin A_1c

OGTT

oral glucose tolerance test

T2D

type 2 diabetes

Funding

L.E. receives salary support from the National Institute of Diabetes and Digestive and Kidney Diseases (K23 DK121942). No funding support was received by S.S.

Disclosures

L.E.'s institution has received research support from Breakthrough T1D, Medtronic, MannKind, and Abbott, and she has served on the advisory board of Abbott, Diabetes Center Berne, Sequel, and Medtronic. She has received consulting fees from Jaeb and Tandem Diabetes Care, and has received honorarium fees from Med Learning Group (Sanofi-sponsored grant), Tandem Diabetes Care, Medtronic, and Insulet. S.S. has no conflicts of interest or financial disclosures to report.