Glycemic deviation index: a novel method of integrating glycemic numerical value and variability

Abstract

Background: There are many continuous blood glucose monitoring (CGM) data-based indicators, and most of these focus on a single characteristic of abnormal blood glucose. An ideal index that integrates and evaluates multiple characteristics of blood glucose has not yet been established.

Methods: In this study, we proposed the glycemic deviation index (GDI) as a novel integrating characteristic, which mainly incorporates the assessment of the glycemic numerical value and variability. To verify its effectiveness, GDI was applied to the simulated 24 h glycemic profiles and the CGM data of type 2 diabetes (T2D) patients (n = 30).

Results: Evaluation of the GDI of the 24 h simulated glycemic profiles showed that the occurrence of hypoglycemia was numerically the same as hyperglycemia in increasing GDI. Meanwhile, glycemic variability was added as an independent factor. One-way ANOVA results showed that the application of GDI showed statistically significant differences in clinical glycemic parameters, average glycemic parameters, and glycemic variability parameters among the T2D groups with different glycemic levels.

Conclusions: In conclusion, GDI integrates the characteristics of the numerical value and the variability in blood glucose levels and may be beneficial for the glycemic management of diabetic patients undergoing CGM treatment.

Keywords: Continuous glucose monitoring; Diabetes; Glycemic variability.

Fig. 1

Functional images of MGI (a) and SDGI (b). The definitional domain of MGI is [2.8, 33.3], while the definitional domain of SDGI is [0, 7.4]. The value domain of both functions is [0, 10]

Fig. 2

Four CGM traces were simulated for over 24 h. Hyperglycemia with high variability (a); hyperglycemia with high variability and the occurrence of hypoglycemia (b); hyperglycemia with normal variability (c); normal blood glucose level (d)