Evaluating a Glucose-Sensor-Based Tool to Help Clinicians and Adults With Type 1 Diabetes Improve Self-Management Skills

评估一种基于血糖传感器的工具,以帮助临床医生和1型糖尿病成人患者提高自我管理技能

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Abstract

BACKGROUND: The goal of this uncontrolled pilot study was to assess the feasibility of a self-care management mobile app, called Sugar Sleuth, which incorporates the FreeStyle Libre™ glucose sensor, to help clinicians and people with type 1 diabetes (PWD) identify and mitigate self-care behaviors that contribute to glucose variability. METHODS: PWDs with a baseline A1c between 7.5 and 9.0% used the mobile app for 14 weeks. The app prompted the PWD to enter the suspected cause of detected glycemic excursions, and to record food and insulin information. PWDs met with clinicians to collaboratively review data, identify challenges, and devise a specific self-care plan. Outcome measures included a single glycemic outcome score (SGOS) and attitude rating scales to better understand how participant attitudes could affect glycemic outcome. RESULTS: Thirty enrolled PWDs had a mean age of 55 ± 2.6 years, and a mean diabetes duration of 32 ± 2.9 years. A significant average reduction in A1c of 0.5 ± 0.07% ( P < .01) and in mean daily carbohydrate intake of 43 ± 21 grams ( P = .05) was found. No statistically significant change in glycemic metrics, body weight, or total daily insulin dose was found. A significant negative association occurred between SGOS and "hypoglycemia tolerance" ( P = .04), and a positive correlation occurred that approached significance with "motivation to change behavior" ( P = .06). CONCLUSIONS: These findings suggest that this mobile app system, in conjunction with CGM, provides a useful platform for helping clinicians and adults with T1D improve self-management skills to improve glycemic control.

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