Publications by authors named "A Lameijer"

Continuous glucose monitoring (CGM) usage has been shown to improve disease outcomes in people living with diabetes by facilitating better glycemic management. However, previous research has suggested that access to these devices can be influenced by nonmedical factors such as socioeconomic status and ethnicity. It is critical that equitable access to CGM devices is ensured as people from those groups experience poorer diabetes-related health outcomes.

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Aim: To evaluate real-life changes of glycemic parameters among flash glucose monitoring (FLASH) users who do not meet glycemic targets.

Methods: De-identified data were obtained between 2014 and 2021 from patients using FLASH uninterrupted for a 24-week period. Glycemic parameters during first and last sensor use were examined in four identifiable groups: type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM) on basal-bolus insulin, T2DM on basal insulin, and T2DM without insulin treatment.

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Introduction: Depressive disorders are more common among persons with diabetes, as compared with persons without diabetes. The burden of glucose management is known to associate with depressive symptoms. This study aims to assess the effects of commencement of FreeStyle Libre flash glucose monitoring (FSL-FGM) on the mental health status of persons with diabetes.

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Introduction: The FreeStyle Libre (FSL) is a flash glucose monitoring (FGM) system. The Flash Monitor Register in the Netherlands (FLARE-NL-4) study previously demonstrated the positive effects of FSL-FGM use during 1 year on glycemic control, quality of life and disease burden among persons with diabetes mellitus (DM). The present follow-up study assesses the effects of FSL-FGM after 2 years.

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Aims: To evaluate the association between Flash Glucose Monitoring (FLASH) frequency and glycemic parameters during real-life circumstances in the Netherlands.

Methods: Obtained glucose readings were de-identified and uploaded to a dedicated database when FLASH reading devices were connected to internet. Data between September 2014 and March 2020, comprising 16,331 analyzable readers (163,762 sensors) were analyzed.

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