A systematic bibliometric analysis on the clinical practice of CGM in diabetes mellitus from 2012 to 2022

BackgroundContinuous glucose monitoring (CGM) has revolutionized diabetes management, but a comprehensive analysis of its clinical implementation is lacking. This study aims to explore CGM in diabetes practice over the past decade using bibliometric analysis. It will identify trends, research focal points, and provide a framework for future investigations.Materials and methodsThe Web of Science Core Collection (WOSCC) was utilized to acquire literature pertaining to the employment of continuous glucose monitoring (CGM) in diabetes that was published between the years 2012 and 2022, and to conduct a comprehensive analysis of the associated citation data. To achieve bibliometric visualization and analysis of the collated data, the bibliography package in the Rstudio(v.4.2.2), Citespace 6.2.R4, and VOS viewer were employed.ResultsA total of 3024 eligible publications were extracted from 91 countries, with the United States being the leading country in terms of the number of issued articles. Furthermore, the annual publication rate has shown a gradual increase during the past decade. Among the various journals in this field, DIABETES TECHNOLOGY & THERAPEUTICS was identified as the most highly cited one. Keyword clustering analysis of the extracted publications indicates that the research hotspots in the past decade have primarily focused on “continuous glucose monitoring”, “glycemic variability”, “type 1 diabetes”, “hypoglycemia”, and “glycemic control”. Moreover, the analysis of keyword emergence reveals that “Time In Range” and “Young Adult” represent the current research frontiers for the years 2012-2022.ConclusionThe concept of Time in Range (TIR) has garnered considerable attention as a significant area of inquiry and an emerging research trend in the clinical practice of Continuous Glucose Monitoring (CGM) for Diabetes Mellitus. Moreover, recent investigations have demonstrated a growing focus on young adults with type 1 diabetes as the research population of interest. In the foreseeable future, research endeavors will persist in the pursuit of improving glycemic management among young adults through the utilization of continuous glucose monitoring (CGM) technology, while also delving into the examination of the Time in Range metric via supplementary clinical investigations

A study of factors influencing long-term glycemic variability in patients with type 2 diabetes: a structural equation modeling approach

AimThe present study aims to utilize structural equation modeling (SEM) to investigate the factors impacting long-term glycemic variability among patients afflicted with type 2 diabetes.MethodThe present investigation is a retrospective cohort study that involved the collection of data on patients with type 2 diabetes mellitus who received care at a hospital located in Chengdu, Sichuan Province, over a period spanning from January 1, 2013, to October 30, 2022. Inclusion criteria required patients to have had at least three laboratory test results available. Pertinent patient-related information encompassing general demographic characteristics and biochemical indicators was gathered. Variability in the dataset was defined by standard deviation (SD) and coefficient of variation (CV), with glycosylated hemoglobin variation also considering variability score (HVS). Linear regression analysis was employed to establish the structural equation models for statistically significant influences on long-term glycemic variability. Structural equation modeling was employed to analyze effects and pathways.ResultsDiabetes outpatient special disease management, uric acid variability, mean triglyceride levels, mean total cholesterol levels, total cholesterol variability, LDL variability, baseline glycated hemoglobin, and recent glycated hemoglobin were identified as significant factors influencing long-term glycemic variability. The overall fit of the structural equation model was found to be satisfactory and it was able to capture the relationship between outpatient special disease management, biochemical indicators, and glycated hemoglobin variability. According to the total effect statistics, baseline glycated hemoglobin and total cholesterol levels exhibited the strongest impact on glycated hemoglobin variability.ConclusionThe factors that have a significant impact on the variation of glycosylated hemoglobin include glycosylated hemoglobin itself, lipids, uric acid, and outpatient special disease management for diabetes. The identification and management of these associated factors can potentially mitigate long-term glycemic variability, thereby delaying the onset of complications and enhancing patients’ quality of life

Efficacy of a smartphone application for helping individuals with type 2 diabetes mellitus manage their blood glucose: a protocol for factorial design trial

Abstract Background China has the largest number of individuals with type 2 diabetes mellitus (T2DM) in the world, and most lack knowledge about glycemic control and health management. This trial will examine whether a smartphone application can improve blood glucose management among individuals with T2DM. Methods This will be a 2-center, factorial design, equal proportional distribution, superiority trial conducted in outpatient endocrinology clinics at two tertiary hospitals in Chengdu, China. The trial will enroll smartphone-literature individuals at least 18 years old who have been diagnosed with T2DM based on glycosylated hemoglobin (HbA1c) of at least 7.0%. Individuals will be randomly assigned to receive routine care with standard education about T2DM and glycemic control (Control), routine care as well as weekly telephone reminders to self-monitor blood glucose (Reminder), routine care and a smartphone application providing information about glycemic control and health management with T2DM (App), or the combination of routine care, the smartphone application, and weekly telephone reminders (App + Reminder). After 6 months of these interventions, participants will be analyzed for the primary outcome of HbA1c as well as the secondary outcomes of blood glucose monitoring frequency, body mass index, blood pressure, knowledge about diabetes, health beliefs related to diabetes, diabetes self-management behavior, and satisfaction with the smartphone application. Discussion This trial will determine whether a smartphone application can improve glycemic management among Chinese with T2DM. The findings may help guide the development of effective applications in China and elsewhere. Trial registration Registration in the Chinese Clinical Trial Registry (ChiCTR) under registration number ChiCTR2100042297: https://www.chictr.org.cn/bin/userProject . 17 January 2021