Continuous glucose monitoring (CGM) has markedly advanced diabetes care by enabling real-time visualization of glycaemic variability, prevention of hypoglycaemia, and direct integration into therapeutic decision-making. As CGM use expands in routine practice and automated insulin delivery systems, however, accuracy has become a critical determinant of treatment safety. This mini-review summarizes recent advances in CGM accuracy management across three major driving forces: (1) accelerating technological innovation, including multi-analyte sensors, non-invasive devices, and artificial intelligence (AI)-based signal processing; (2) systematization and international harmonization of regulatory accuracy frameworks, exemplified by U.S. Food and Drug Administration (FDA) integrated CGM (iCGM) and the proposed CGM in Europe (eCGM) concept; and (3) growing societal demands for transparency, including public disclosure of performance data and strengthened lot-to-lot evaluation. We outline the four key dimensions of CGM accuracy-analytical accuracy, clinical accuracy, trend accuracy, and precision. We then review the evolution of regional accuracy standards, focusing on highly influential frameworks in the United States and Europe. Key considerations in accuracy-study design are discussed, along with clinical risks associated with reduced accuracy optimization, and progress toward global standardization. Finally, we examine future directions in the era of next-generation technologies, such as multi-analyte and non-invasive sensors, AI-driven accuracy optimization, and progress toward international standardization. This review provides an overview of the current landscape and future directions of CGM accuracy management in an era where fluctuations in accuracy directly affect treatment safety. We aim to clarify the perspectives required in both clinical practice and research to ensure safe and effective use of CGM.
Torimoto et al. (2026) studied this question.