RESUMO
Objective: To analyze the Glycemic Risk Index (GRI) and assess their possible differences according to coefficient of variation (CV) in a cohort of real-life type 1 diabetes mellitus (DM) patient users of intermittently scanned continuous glucose monitoring (isCGM). Patients and Methods: In total, 447 adult users of isCGM with an adherence ≥70% were included in a cross-sectional study. GRI was calculated with its hypoglycemia (CHypo) and hyperglycemia (CHyper) components. Multivariate linear regression analysis was performed to evaluate the factors associated with GRI. Results: Mean age was 44.6 years (standard deviation [SD] 13.7), 57.7% being male; age of DM onset was 24.5 years (SD 14.3) and time of evolution was 20.6 years (SD 12.3). In patients with CV >36% (52.8%) versus CV ≤36% (47.2%), differences were observed in relation to GRI (18.8% [SD 1.9]; P < 0.001), CHypo (2.9% [SD 0.3]; P < 0.001), CHyper (6.3% [SD 1.4]; P < 0.001), and all classical glucometric parameters except time above range level 1. The variables that were independently associated with GRI in patient with CV >36% were time in range (TIR) (ß = -1.49; confidence interval [CI:] 95% -1.63 to -1.37; P < 0.001), glucose management indicator (GMI) (ß = -7.22; CI: 95% -9.53 to -4.91; P < 0.001), and CV (ß = 0.85; CI: 95% 0.69 to 1.02; P < 0.001). However, in patients with CV ≤36%, the variables were age (ß = 0.15; CI: 95% 0.03 to 0.28; P = 0.019), age of onset (ß = -0.15; CI: 95% -0.28 to -0.02; P = 0.023), TIR (ß = -1.35; CI: 95% -1.46 to -1.23; P < 0.001), GMI (ß = -6.67; CI: 95% -9.18 to -4.15; P < 0.001), and CV (ß = 0.33; CI: 95% 0.11 to 0.56; P = 0.004). Conclusions: In this study, the factors independently associated with metabolic control according to GRI are modified by glycemic variability.
RESUMO
OBJECTIVE: To analyze the degree of control based on classical glucometric parameters and Glycemia Risk Index (GRI) in real-life conditions in a cohort of patients with type 1 Diabetes Mellitus (DM) and Latent Autoimmune Diabetes in Adults (LADA) and to assess the factors that are associated with GRI. PATIENTS AND METHODS: Cross-sectional study. 447 adult patients with type 1 DM and LADA users of Intermittent Continuous Glucose Monitoring (iCGM) with an adherence ≥ 70% were included. GRI was calculated with its Hypoglycemia (CHypo) and Hyperglycemia (CHyper) Components. Multivariate linear regression analysis was performed to evaluate the factors associated with GRI. RESULTS: Mean age 44.6 years (SD 13.7); 57.7% men; 83.9% type 1 DM; 16.1% LADA; time of evolution 20.6 years (SD 12.3). In patients with type 1 DM vs. LADA, differences were observed in relation to age [-11.1 years (SD 1.7)], age of onset [-21.9 years (DE 1.5)], time of evolution [11.7 years (DE 1.5)], treatment modality (p < 0.001), Time in Range (TIR) [-6.3% (SD 2.2)], Time Below Range (TBR) [1.9% (SD 0.6)], TBR level 1 (TBR1) [1.4% (SD 0.5)], Time Above Range (TAR) level 2 (TAR2) [4.7% (SD 1.3)], Coefficient of Variation (CV) [4.6% (SD 0.9)], GRI [11.3% (SD 2.8)], CHypo [1.3% (SD 0.5)] and CHyper [4.8% (SD 1.7)]. The variables that were independently associated with GRI were TIR (ß = -1.34; CI 95% -1.43 to -1.25; p < 0.001), Glucose Management Indicator (GMI) (ß = -5.82; CI 95% -7.59 to -4.05; p < 0.001), CV (ß = 0.67; CI 95% 0.57 to 0.77; p < 0.001) and adherence to sensor usage (ß = -0.16; CI 95% -1.27 to -0.06; p < 0.002). CONCLUSIONS: LADA present better control according to some glucometric parameters and a low GRI. However, the type of DM is not a factor that is independently associated with GRI.
