How to take action beyond ambulatory glucose profile: Latin American expert recommendations on CGM data interpretation
Posted on 2025-05-09 - 03:31
Abstract Purpose This expert consensus provides a standardized methodology for interpreting continuous glucose monitoring (CGM) data to optimize diabetes management. It aims to help healthcare professionals recognize glycemic patterns and apply targeted interventions based on real-time glucose metrics. Methods A systematic literature review informed expert panel discussions. Specialists from Latin America assessed CGM interpretation challenges, reviewed key metrics, and reached consensus through an anonymous voting process. The recommendations align with international guidelines while addressing regional limitations in technology access and healthcare infrastructure. Results Reliable CGM data interpretation requires at least 70% sensor use over 14 days. The Ambulatory Glucose Profile (AGP) report serves as the primary tool, offering essential metrics such as time in range (TIR), time below range (TBR), time above range (TAR), coefficient of variation (CV), and glucose management indicator (GMI). Identifying hyperglycemia, hypoglycemia, and glucose variability allows for personalized treatment adjustments. The panel adopted international glycemic targets, adapting them to Latin American settings. The time in tight range (TITR) was considered but not included due to limited supporting evidence and regional barriers to advanced CGM technology. Conclusions Standardized CGM interpretation improves glycemic control and treatment decisions. These recommendations provide a structured approach to diabetes care, aiming to enhance clinical outcomes and address healthcare disparities in Latin America.
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Calliari, Luis Eduardo; Contreras Sepúlveda, Álvaro; Coronel-Restrepo, Nicolás; Kabakian, Laura; Lamounier, Rodrigo N.; Picasso, Emma; et al. (2025). How to take action beyond ambulatory glucose profile: Latin American expert recommendations on CGM data interpretation. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.7809117.v1