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.

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.