Assessing quality of glycemic control: Hypo- and hyperglycemia, and glycemic variability using mobile self-monitoring of blood glucose system

Abstract

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.

Patterns of Glycemic Variability During a Diabetes Self-Management Educational Program

“…Several other structured predominantly non-pharmacological interventions, like an introduction to mobile diabetic self-care system and real-time continuous glucose monitoring system, have also reported the decrement in GV measures following interventions [28,29]. All these interventions were of longer duration compared to the present intervention.…”

Effectiveness of a Nutrition Education Program for Patients with Type 2 Diabetes Mellitus

“…Awareness about diabetes complications and c quent improvements in dietary knowledge, attitude and practices lead to better cont the disease [47]. Different medications may also have different effects [48] and it portant to provide appropriate motivation for physical activity [49]. Our study di…”

Telemonitoring readiness among Austrian diabetic patients: A cross-sectional validation study

“…However, particularly suitable types of patients for telemonitoring could include newly diagnosed, insulin-dependent, gestational, or multimorbid diabetes patients, patients who live in rural areas, and very health conscious or anxious patients. [6][7][8][9] We designed and validated a German version of a well-established survey tool for the first time, thus providing a valuable instrument for further research in this area. We conducted PCA to present the items from the assessment tool as a set of new orthogonal variables and to display patterns of similarity of the observations, as our data met the assumptions for this procedure in accordance with comparable studies.…”

“…However, particularly suitable types of patients for telemonitoring could include newly diagnosed, insulin-dependent, gestational, or multimorbid diabetes patients, patients who live in rural areas, and very health conscious or anxious patients. 6–9…”

“…Relevant research has shown beneficial effects on objective health parameters including blood pressure, blood glucose levels, and body weight as well as reduced hospital admission rates. [6][7][8][9] However, the majority of telemonitoring pilot projects-although proven to be effective-fail to be implemented in standard medical care, mostly due to a lack of user acceptance, public funding, and incentives for health professionals. 6,[10][11][12] User awareness and perceptions of innovative health technologies aimed at influencing compliance and self-management of chronic conditions are essential for their successful adoption in everyday life.…”