Literature DB >> 28389582

The Impact of Continuous Glucose Monitoring on Markers of Quality of Life in Adults With Type 1 Diabetes: Further Findings From the DIAMOND Randomized Clinical Trial.

William H Polonsky1,2, Danielle Hessler3, Katrina J Ruedy4, Roy W Beck4.   

Abstract

OBJECTIVE: Continuous glucose monitoring (CGM) improves glycemic control, but data are inconclusive about its influence on quality of life (QOL). We investigated the impact of 24 weeks of CGM use on QOL in adults with type 1 diabetes (T1D) who use multiple daily insulin injections. RESEARCH DESIGN AND METHODS: DIAMOND (Multiple Daily Injections and Continuous Glucose Monitoring in Diabetes) was a prospective randomized trial that assessed CGM versus self-monitoring of blood glucose (SMBG) only in 158 adults with poorly controlled T1D. At baseline and study end, participants completed QOL measures that assessed overall well-being (WHO-5), health status (EQ-5D-5L), diabetes distress (DDS), hypoglycemic fear (worry subscale of the HFS-II), and hypoglycemic confidence (HCS). At study end, CGM participants completed the CGM Satisfaction Survey. Linear regression analyses compared treatment group changes in QOL outcomes over time. Associations between CGM satisfaction and change in QOL outcomes and in glycemic control indices were assessed.
RESULTS: The CGM group demonstrated a greater increase in hypoglycemic confidence (P = 0.01) and a greater decrease in diabetes distress (P = 0.01) than the SMBG group. No significant group differences in well-being, health status, or hypoglycemic fear were observed. CGM satisfaction was not significantly associated with glycemic changes but was associated with reductions in diabetes distress (P < 0.001) and hypoglycemic fear (P = 0.02) and increases in hypoglycemic confidence (P < 0.001) and well-being (P = 0.01).
CONCLUSIONS: CGM contributes to significant improvement in diabetes-specific QOL (i.e., diabetes distress, hypoglycemic confidence) in adults with T1D, but not with QOL measures not specific to diabetes (i.e., well-being, health status). CGM satisfaction was associated with most of the QOL outcomes but not with glycemic outcomes.
© 2017 by the American Diabetes Association.

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Year:  2017        PMID: 28389582     DOI: 10.2337/dc17-0133

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  63 in total

1.  Cost-effectiveness of Continuous Glucose Monitoring for Adults With Type 1 Diabetes Compared With Self-Monitoring of Blood Glucose: The DIAMOND Randomized Trial.

Authors:  Wen Wan; M Reza Skandari; Alexa Minc; Aviva G Nathan; Aaron Winn; Parmida Zarei; Michael O'Grady; Elbert S Huang
Journal:  Diabetes Care       Date:  2018-04-12       Impact factor: 19.112

2.  Impact of Human Factors Testing on Medical Device Design: Validation of an Automated CGM Sensor Applicator.

Authors:  Robert North; Christine Pospisil; Ryan J Clukey; Christopher G Parkin
Journal:  J Diabetes Sci Technol       Date:  2019-02-14

3.  Real-World Hypoglycemia Avoidance With a Predictive Low Glucose Alert Does Not Depend on Frequent Screen Views.

Authors:  Sarah Puhr; Mark Derdzinski; Andrew Scott Parker; John B Welsh; David A Price
Journal:  J Diabetes Sci Technol       Date:  2019-04-03

4.  Development of a Novel Tool to Support Engagement With Continuous Glucose Monitoring Systems and Optimize Outcomes.

Authors:  Katharine D Barnard-Kelly; William H Polonsky
Journal:  J Diabetes Sci Technol       Date:  2019-05-21

5.  From Wary Wearers to d-Embracers: Personas of Readiness to Use Diabetes Devices.

Authors:  Molly L Tanenbaum; Rebecca N Adams; Esti Iturralde; Sarah J Hanes; Regan C Barley; Diana Naranjo; Korey K Hood
Journal:  J Diabetes Sci Technol       Date:  2018-08-22

6.  COVID-19 and Diabetes: Could Diabetes Technology Research Help Pave the Way for Remote Healthcare?

Authors:  Julia Fuchs; Roman Hovorka
Journal:  J Diabetes Sci Technol       Date:  2020-05-30

7.  Cutaneous Reactions to Continuous Glucose Monitoring and Continuous Subcutaneous Insulin Infusion Devices in Type 1 Diabetes Mellitus.

Authors:  Rachel S Rigo; Laura E Levin; Donald V Belsito; Maria C Garzon; Rachelle Gandica; Kristen M Williams
Journal:  J Diabetes Sci Technol       Date:  2020-05-09

8.  Baseline Psychosocial Characteristics Predict Frequency of Continuous Glucose Monitoring in Youth with Type 1 Diabetes.

Authors:  Dayna E McGill; Lisa K Volkening; Deborah A Butler; Kara R Harrington; Michelle L Katz; Lori M Laffel
Journal:  Diabetes Technol Ther       Date:  2018-05-04       Impact factor: 6.118

9.  Accuracy of a Factory-Calibrated, Real-Time Continuous Glucose Monitoring System During 10 Days of Use in Youth and Adults with Diabetes.

Authors:  R Paul Wadwa; Lori M Laffel; Viral N Shah; Satish K Garg
Journal:  Diabetes Technol Ther       Date:  2018-06-14       Impact factor: 6.118

Review 10.  Continuous Glucose Monitoring Integration in Clinical Practice: A Stepped Guide to Data Review and Interpretation.

Authors:  Grazia Aleppo; Kimberly Webb
Journal:  J Diabetes Sci Technol       Date:  2018-11-19
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