A Minimal Model Approach for Analyzing Continuous Glucose Monitoring in Type 2 Diabetes

Abstract

Continuous glucose monitoring (CGM), a technique that records blood glucose at a regular intervals. While CGM is more commonly used in type 1 diabetes, it is increasingly becoming attractive for treating type 2 diabetic patients. The time series obtained from a CGM provides a rich picture of the glycemic state of the subjects and may help have tighter control on blood sugar by revealing patterns in their physiological responses to food. However, despite its importance, the biophysical understanding of CGM is far from complete. CGM data series is complex not only because it depends on the composition of the food but also varies with individual physiology. All of these make a full modeling of CGM data a difficult task. Here we propose a simple model to explain CGM data in type 2 diabetes. The model combines a relatively simple glucose-insulin dynamics with a two-compartment food model. Using CGM data of a healthy and a diabetic individual we show that this model can capture liquid meals well. The model also allows us to estimate the parameters in a relatively straightforward manner. This opens up the possibility of personalizing the CGM data. The model also predicts insulin time series from the model, and the rate of appearance of glucose due to food. Our methodology thus paves the way for novel analyses of CGM which have not been possible before.

A Glucose-Only Model to Extract Physiological Information from Postprandial Glucose Profiles in Subjects with Normal Glucose Tolerance

“…This paper, for the first time, proposed a glucose-based model for the successful extraction of useful physiological information on glucose metabolism in subjects with NGT, thereby overcoming the weaknesses of existing GOM approaches. [8][9][10][11][12][13] The model's independence from insulin measurements and exclusive use of easily accessible data enable further developments and its potential application in research and clinical practice to a large number of subjects. In particular, the proposed model could allow a more sophisticated physiological interpretation of CGM profiles collected under ambulatory conditions.…”

A novel fast-slow model of diabetes progression: Insights into mechanisms of response to the interventions in the Diabetes Prevention Program

“…On the other hand, Goel et al . [91] suggested that while the linear approach used in Eq 16 is appropriate for liquid meals, it may also be used for mixed meals, albeit with a different (slower) dynamics compared to liquid meals. This issue is worth addressing here because, in general, a poor description of the rate of glucose appearance may confound the effects of other glucose transport, secretion or production mechanisms.…”

HAD-Net: Hybrid Attention-based Diffusion Network for Glucose Level Forecast

“…Here A 1,3 = −1 means remote insulin decreases glucose level. This matrix was inspired and extracted from the physiological models of Goel et al (2018) and Bergman (2005). Figure 4 illustrates this matrix by representing it as the corresponding GDPM with arbitrary weights.…”