Time above range and no coefficient of variation is associated with diabetic retinopathy in individuals with type 1 diabetes and glycated hemoglobin within target.

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.

Effect of Christmas Holidays on Type 1 Diabetes Mellitus in Users of Glucose Flash Systems.

OBJECTIVE: Christmas holidays can impact weight and glycemic control in type 2 diabetes, but their effect on type 1 diabetes (T1D) remains understudied. This study assessed how Christmas holidays affect individuals with T1D who use flash continuous glucose monitoring systems. METHODS: This retrospective study involved 812 adults diagnosed with T1D recruited from 3 hospitals. Clinical, anthropometric, and socioeconomic data were collected. Glucose metrics from 14 days before January 1st, and before December 1st and February 1st as control periods, were recorded. Analyses adjusted for multiple variables were conducted to assess the holiday season's impact on glycemic control. RESULTS: The average time in range during the holidays (60.0 ± 17.2%) was lower compared to December (61.9 ± 17.2%, P < .001) and February (61.7 ± 17.7%, P < .001). Time above range (TAR > 180 mg/dL) was higher during Christmas (35.8 ± 18.2%) compared to December (34.1 ± 18.3%, P < .001) and February (34.2 ± 18.4%, P < .001). Differences were also observed in TAR >250 mg/dL, coefficient of variation, and average glucose (P < .05). No differences were found in time below range or other metrics. Linear regression models showed that the holidays reduced time in range by 1.9% (ß = -1.92, P = .005) and increased TAR >180 mg/dL by 1.8% (ß = 1.75, P = .016). CONCLUSION: Christmas holidays are associated with a mild and reversible deterioration in glucose metrics among individuals with T1D using flash continuous glucose monitoring, irrespective of additional influencing factors. These discoveries can be useful to advise individuals with diabetes during the festive season and to recognize potential biases within studies conducted during this timeframe.

Impact of socioeconomic status on chronic control and complications of type 1 diabetes mellitus in users of glucose flash systems: a follow-up study.

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.

Scans per day as predictors of optimal glycemic control in people with type 1 diabetes mellitus using flash glucose monitoring: what number of scans per day should raise a red flag?

AIMS: This study aimed to determine the minimum frequency of flash glucose monitoring (FGM) scans necessary for optimal glycemic control in patients with type 1 diabetes (T1D). METHODS: Data were collected from 692 patients (47.5% female, with a median age of 47.4 years) who used FGM systems daily and recorded their clinical variables and device data. RESULTS: Logistic regression models showed that performing more than 12 scans per day was associated with improved T1D control (OR = 4.22, p < 0.001) and a reduction in HbA1c (7.6 vs 7.0%, 60-53 mmol/mol p < 0.001). However, those performing less than 6 scans showed no improvement in HbA1c (7.9 vs 7.8%, 63-61 mmol/mol p = 0.514). Thirteen daily scans were determined as the optimal cutoff point for predicting optimal glycemic control using a maximally selected rank algorithm. Significant reductions were observed in mean glucose (< 0.001), coefficient of variation (< 0.001), HbA1c (< 0.001), and an increase in TIR (< 0.001) in patients who performed more than 12 daily scans. CONCLUSIONS: The results suggest that a higher frequency of daily scans by T1D patients using FGM systems leads to improved chronic glycemic control. The minimum recommended frequency for optimal control is 13 scans per day, and more than 6 daily scans are needed to improve HbA1c.