Are Risk Indices Derived From CGM Interchangeable With SMBG-Based Indices?

Area of Science:

• Endocrinology
• Diabetes Technology
• Biomedical Engineering

Background:

• Traditional risk assessment for hypo- and hyperglycemia relies on self-monitoring blood glucose (SMBG) using Low Blood Glucose Index (LBGI) and High Blood Glucose Index (HBGI).
• These established metrics predict glycemic events but require validation for continuous glucose monitoring (CGM) data.
• Clinical cutoff values exist for SMBG-based indices, but their applicability to CGM is unconfirmed.

Purpose of the Study:

• To investigate the correlation between LBGI and HBGI calculated from CGM and SMBG data.
• To develop guidelines for computing LBGI and HBGI from CGM time series.
• To validate the use of established clinical cutoff values with CGM-derived indices.

Main Methods:

• Twenty-eight individuals with type 1 diabetes mellitus (T1DM) participated in a 4-week real-world study.
• Both SMBG and CGM systems were used concurrently for data collection.
• Linear and nonlinear regression models were employed to analyze the relationship between SMBG- and CGM-derived risk indices.

Main Results:

• CGM-derived LBGI values showed underestimation compared to SMBG-based LBGI, particularly at lower risk levels.
• A linear transformation effectively aligned CGM-based LBGI with SMBG-based LBGI.
• A simple linear model (unit slope, zero intercept) proved reliable for HBGI, indicating no correction is needed for CGM data.

Conclusions:

• Adapted versions of LBGI and HBGI are proposed for CGM data, accounting for signal characteristics.
• These adapted indices allow the extension of SMBG-based findings to CGM.
• Clinically relevant cutoff values can be applied to CGM-derived indices for prompt glycemic status classification.