Abstract

Continuous glucose monitoring (CGM) technology has brought about a paradigm shift in defining glycemic control in diabetes management and research. A1C and blood glucose monitoring have been widely accepted measurements in diabetes care, yet each has limitations in its clinical utility. A1C is established as an indicator of population health and long-term risk for microvascular complications but is less useful in personalizing glycemic goals, guiding therapy changes, or understanding patterns of glycemic excursions (1). Furthermore, A1C has limitations in accuracy and reliability in the context of hemoglobinopathy, anemia, iron deficiency (2), pregnancy (3), and racial differences (4). With increasing evidence regarding the relationship of glycemic variability with micro- and macrovascular risks, the definition of diabetes “control” is changing, and that change is bringing opportunity to tailor therapy decisions that truly improve outcomes (5). Self-monitoring of blood glucose (SMBG) has been an important tool for calculating insulin doses and gaining an understanding of daily glucose patterns. SMBG provides the glucose level at a single point in time without the context of past or future directionality and carries a burden of pain and inconvenience for patients, further limiting the amount of data available to analyze (1). The accuracy of an SMBG reading is dependent on the user’s testing technique and on the accuracy of the glucose meter itself; many glucose meters do not meet accuracy standards (6). Although CGM provides a wealth of information that A1C testing and SMBG lack, adoption of and persistence with this technology have been limited (7). However, with the arrival of systems for personal use (real-time use for patients) and professional use (blinded for patients with retrospective analysis by clinicians) that are more affordable and user-friendly (i.e., that do not require SMBG calibration and are indicated as an alternative to SMBG for making treatment …

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