Novel Detection and Progression Markers for Diabetes Based on Continuous Glucose Monitoring Data Dynamics.

contextStatic measures of continuous glucose monitoring (CGM) data, such as time spent in specific glucose ranges (70-180 mg/dL or 70-140 mg/dL), do not fully capture the dynamic nature of blood glucose, particularly the subtle gradual deterioration of glycemic control over time in individuals with early-stage type 1 diabetes.

objectiveDevelop a diabetes diagnostic tool based on 2 markers of CGM dynamics: CGM entropy rate (ER) and Poincaré plot (PP) ellipse area (S).

methodsA total of 5754 daily CGM profiles from 843 individuals with type 1, type 2 diabetes, or healthy individuals with or without islet autoantibody status were used to compute 2 individual dynamic markers: ER (in bits per transition; BPT) of daily probability matrices describing CGM transitions between 8 glycemic states, and the area S (mg2/dL2) of individual CGM PP ellipses using standard PP descriptors. The Youden index was used to determine "optimal" cut-points for ER and S for health vs diabetes (case 1); type 1 vs type 2 (case 2); and low vs high type 1 immunological risk (case 3). The markers' discriminative power was assessed through the area under the receiver operating characteristics curves (AUC).

resultsOptimal cutoff points were determined for ER and S for each of the 3 cases. ER and S discriminated case 1 with AUC = 0.98 (95% CI, 0.97-0.99) and AUC = 0.99 (95% CI, 0.99-1.00), respectively (cutoffs ERcase1 = 0.76 BPT, Scase1 = 1993.91 mg2/dL2), case 2 with AUC = 0.81 (95% CI, 0.77-0.84) and AUC = 0.76 (95% CI, 0.72-0.81), respectively (ERcase2 = 1.00 BPT, Scase2 = 5112.98 mg2/dL2), and case 3 with AUC = 0.72 (95% CI, 0.58-0.86), and AUC = 0.66 (95% CI, 0.47-0.86), respectively (ERcase3 = 0.52 BPT, Scase3 = 923.65 mg2/dL2).

conclusionCGM dynamics markers can be an alternative to fasting plasma glucose or glucose tolerance testing to identify individuals at higher immunological risk of progressing to type 1 diabetes.