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AIMS: This study aimed to investigate the association between glucose metrics and diabetic retinopathy in type 1 diabetes (T1D) patients using flash continuous glucose monitoring (FGM) systems, including those maintaining glycated hemoglobin (HbA1c) within the target range. METHODS: We conducted a cross-sectional study involving 1070 T1D patients utilizing FGM systems. Data on clinical, anthropometric, and socioeconomic characteristics were collected and retinopathy was classified based on international standards. RESULTS: Patients' mean age was 47.6 ± 15.0 years, with 49.4% of them being females. Within the cohort, 24.8% of patients presented some form of retinopathy. In the analysis involving the entire sample of subjects, male gender (OR = 1.51, p = 0.027), Time Above Range (TAR) > 250 mg/dL (OR = 1.07, p = 0.025), duration of diabetes (OR = 1.09, p < 0.001), smoking (OR = 2.30, p < 0.001), and history of ischemic stroke (OR = 5.59, p = 0.025) were associated with diabetic retinopathy. No association was observed between the coefficient of variation and diabetic retinopathy (p = 0.934). In patients with HbA1c < 7%, the highest quartile of TAR > 250 was independently linked to diabetic retinopathy (OR = 8.32, p = 0.040), in addition to smoking (OR = 2.90, p = 0.031), duration of diabetes (OR = 1.09, p < 0.001), and hypertension (OR = 2.35, p = 0.040). CONCLUSION: TAR > 250 mg/dL significantly emerges as a modifiable factor associated with diabetic retinopathy, even among those patients maintaining recommended HbA1c levels. Understanding glucose metrics is crucial for tailoring treatment strategies for T1D patients.
RESUMO
BACKGROUND: This study investigates the association between socioeconomic status (SES) and glycemic control in individuals with type 1 diabetes (T1D) using flash glucose monitoring (FGM) devices within a public health system where these technologies are freely available and utilized according to recommended guidelines. METHODS: A follow-up study of 1060 adults (mean age 47.4 ± 15.0 years, 49.0% women) with T1D, receiving care at three Spanish university hospitals that regularly employ the FGM system. SES was assessed using the Spanish Deprivation Index and the average annual net income per person. Glycemic data were collected over a 14-day follow-up period, including baseline glycated hemoglobin (HbA1c) levels prior to sensor placement, the last available HbA1c levels, and FGM-derived glucose metrics. Individuals with sensor usage time < 70% were excluded. Chronic micro and macrovascular complications related to diabetes were documented. Regression models, adjusted for clinical variables, were employed to determine the impact of SES on optimal sensor control (defined as time in range (TIR) ≥ 70% with time below range < 4%) and disease complications. RESULTS: The average follow-up was of 2 years. The mean TIR and the percentage of individuals with optimal control were higher in individuals in the highest SES quartile (64.9% ± 17.8% and 27.9%, respectively) compared to those in the lowest SES quartile (57.8 ± 17.4% and 12.1%) (p < 0.001). Regression models showed a higher risk of suboptimal control (OR 2.27, p < 0.001) and ischemic heart disease and/or stroke (OR 3.59, p = 0.005) in the lowest SES quartile. No association was observed between SES and the risk of diabetic nephropathy and retinopathy. FGM system improved HbA1c levels across all SES quartiles. Although individuals in the highest SES quartile still achieved a significantly lower value at the end of the follow-up 55 mmol/mol (7.2%) compared to those in the lowest SES quartile 60 mmol/mol (7.6%) (p < 0.001), the significant disparities in this parameter between the various SES groups were significantly reduced after FGM technology use. CONCLUSIONS: Socioeconomic status plays a significant role in glycemic control and complications in individuals with T1D, extending beyond access to technology and its proper utilization. The free utilization of FGM technology helps alleviate the impact of social inequalities on glycemic control.