PhD Scientific Days 2026

Poster Session 3.H - Pharmaceutical Sciences and Health Technologies

Differences in Continuous Glucose Monitoring Metrics Between Prediabetes and Normoglycemia: A Systematic Review and Meta-Analysis

Name of the presenter

Rákóczi, Gabriella

Institute/workplace of the presenter

Centre for Translational Medicine

Authors

Gabriella Rákóczi¹, Judit Nagy¹, Shaghayegh Jozaee², Shirin Jozaee², Boglárka Lilla Szentes¹, Jimin Lee¹, Anett Rancz¹, Péter Hegyi¹, Gergely Agócs¹, Emese Sipter¹
1: Centre for Translational Medicine
2: Semmelweis University

Text of the abstract

Introduction
Prediabetes often remains undiagnosed until it progresses to type 2 diabetes mellitus (T2DM), particularly among individuals with obesity or a family history of diabetes. Conventional tests, including fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), and the oral glucose tolerance test (OGTT), provide only static snapshots of glycemia and may fail to capture variability and postprandial excursions. Continuous glucose monitoring (CGM) offers dynamic insight into glucose regulation and may complement traditional diagnostic tools.
Aims
This study aimed to systematically evaluate differences in CGM-derived metrics between individuals with prediabetes and those with normoglycemia.
Methods
A systematic review and meta-analysis were conducted following PRISMA guidelines (PROSPERO: CRD42024608658). PubMed, EMBASE, and CENTRAL were searched from inception to September 3, 2025. Observational studies reporting CGM metrics in individuals without diabetes were included. The primary outcome was mean amplitude of glycemic excursions (MAGE), while secondary outcomes included time above range (TAR), 24-hour mean glucose, coefficient of variation (CV), and time in range (TIR).
Results
Sixteen studies were included in the systematic review, and ten (n = 1657 participants) in the meta-analysis. Prediabetes was associated with higher CGM-derived metrics than normoglycemia: MAGE (MD = 9.41 mg/dL, 95% CI: 4.31–15.31), TAR (MD = 5.68%, 1.04–10.32), and 24-hour mean glucose (MD = 7.91 mg/dL, 6.27–9.55).
Conclusion
These results provide the first quantitative evidence that CGM can discriminate between prediabetes and normoglycemia, supporting its potential as a complementary tool for refined metabolic risk assessment. Further prospective studies are needed to determine its predictive value for progression to T2DM.
Funding
This study was supported by the Centre for Translational Medicine, Semmelweis University, and the National Research, Development and Innovation Fund (TKP2021-EGA-23 to Péter Hegyi), as well as NKFIH project grants K131996 and K147265.