Impact of glucose variability on the assessment of the glycemia risk index (GRI) and classic glycemic metrics

OBJECTIVE: To evaluate the impact of glucose variability on the relationship between the GRI and other glycemic metrics in a cohort of pediatric and adult patients with type 1 diabetes (T1D) using intermittent scanning continuous glucose monitoring (isCGM). METHODS: We performed a cross-sectional study of 202 patients with T1D under intensive insulin treatment (25.2% CSII) using isCGM. Clinical, metabolic, and glycemic metrics were collected, and the GRI was calculated with its hypoglycemia (CHypo) and hyperglycemia (CHyper) components. The correlation between the GRI and other classical glycometrics in relation to the coefficient of variation (CV) was evaluated. RESULTS: A total of 202 patients were included (53% male; 67.8% adults) with a mean age of 28.6 ± 15.7 years and 12.5 ± 10.9 years of T1D evolution (TIR 59.0 ± 17.0%; CV 39.8 ± 8.0%; GMI 7.3 ± 1.1%). The mean GRI was 54.0 ± 23.3 with a CHypo and CHyper component of 5.7 ± 4.8 and 23.4 ± 14.3, respectively. A strong negative correlation was observed between the GRI and TIR (R = −0.917; R(2) = 0.840; p < 0.001), showing differences when dividing patients with low glycemic variability (CV < 36%) (R = −0.974; R(2) = 0.948; p < 0.001) compared to those with greater CV instability (≥36%) (R = −0.885; R(2) = 0.784; p < 0.001). The relationship of GRI with its two components was strongly positive with CHyper (R = 0.801; R(2) = 0.641; p < 0.001) and moderately positive with CHypo (R = 0.398; R(2) = 0.158; p < 0.001). When the GRI was evaluated with the rest of the classic glycemic metrics, a strong positive correlation was observed with HbA1c (R = 0.617; R(2) = 0.380; p < 0.001), mean glucose (R = 0.677; R(2) = 0.458; p < 0.001), glucose standard deviation (R = 0.778; R(2) = 0.605; p < 0.001), TAR > 250 (R = 0.801; R(2) = 0.641; p < 0.001), and TBR < 54 (R = 0.481; R(2) = 0.231; p < 0.001). CONCLUSIONS: The GRI correlated significantly with all the glycemic metrics analyzed, especially with the TIR. Glycemic variability (GV) significantly affected the correlation of the GRI with other parameters and should be taken into consideration.