Mackay Medical College, New Taipei City.
Health Informatics J. 2020 Mar;26(1):287-297. doi: 10.1177/1460458218824756. Epub 2019 Jan 29.
Although mobile applications bring potential benefits of metabolic control for patients with diabetes, their effect on glycemic fluctuation has been less widely explored. The goal of this study was to utilize data from the Mobile Self-Monitoring of Blood Glucose System to obtain a picture of the metabolic progression. Twenty-seven adults with type 2 diabetes mellitus were recruited to receive a mobile diabetes self-care system for a six-week period. The approach to the interpretation of glycemic control patterns, utilizes the following methods: 1) Graphical displays of the percentage of hyper-and-hypoglycemia episodes; 2) Pattern recognition of glycemic variability based on a simple equation involving both the standard deviation and the mean. Analytical results reveal that short-term usage of the developed system stabilizes the week-by-week glycemic fluctuations. Four categories were established to distinguish different patterns of patients' glycemic variation. If patterns of glycemic control can be recognized or interpreted by newly designed mobile applications, then the collection and analysis of metabolic variation will greatly help both health care providers and patients in effective diabetes management.
尽管移动应用程序为糖尿病患者带来了潜在的代谢控制益处，但它们对血糖波动的影响尚未得到广泛探讨。本研究的目的是利用来自移动自我监测血糖系统的数据来了解代谢进展情况。招募了 27 名 2 型糖尿病患者，在六周内使用移动糖尿病自我护理系统。解释血糖控制模式的方法如下：1）以图形方式显示高血糖和低血糖发作的百分比；2）基于涉及标准差和平均值的简单方程对血糖变异性进行模式识别。分析结果表明，该系统的短期使用可稳定每周的血糖波动。建立了四个类别来区分患者血糖变化的不同模式。如果可以通过新设计的移动应用程序识别或解释血糖控制模式，那么代谢变化的收集和分析将极大地帮助医疗保健提供者和患者进行有效的糖尿病管理。
