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Glycemia According to the Use of Continuous Glucose Monitoring Among Adults with Type 1 Diabetes Mellitus in Korea: A Real-World Study

Overview
Specialty Endocrinology
Date 2023 Mar 5
PMID 36872066
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Abstract

Background: We explored the association between continuous glucose monitoring (CGM) use and glycemia among adults with type 1 diabetes mellitus (T1DM) and determined the status of CGM metrics among adults with T1DM using CGM in the real-world.

Methods: For this propensity-matched cross-sectional study, individuals with T1DM who visited the outpatient clinic of the Endocrinology Department of Samsung Medical Center between March 2018 and February 2020 were screened. Among them, 111 CGM users (for ≥9 months) were matched based on propensity score considering age, sex, and diabetes duration in a 1:2 ratio with 203 CGM never-users. The association between CGM use and glycemic measures was explored. In a subpopulation of CGM users who had been using official applications (not "do-it-yourself" software) such that Ambulatory Glucose Profile data for ≥1 month were available (n=87), standardized CGM metrics were summarized.

Results: Linear regression analyses identified CGM use as a determining factor for log-transformed glycosylated hemoglobin. The fully-adjusted odds ratio (OR) and 95% confidence interval (CI) for uncontrolled glycosylated hemoglobin (>8%) were 0.365 (95% CI, 0.190 to 0.703) in CGM users compared to never-users. The fully-adjusted OR for controlled glycosylated hemoglobin (<7%) was 1.861 (95% CI, 1.119 to 3.096) in CGM users compared to never-users. Among individuals who had been using official applications for CGM, time in range (TIR) values within recent 30- and 90-day periods were 62.45%±16.63% and 63.08%±15.32%, respectively.

Conclusion: CGM use was associated with glycemic control status among Korean adults with T1DM in the real-world, although CGM metrics including TIR might require further improvement among CGM users.

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References
1.
Bolinder J, Antuna R, Geelhoed-Duijvestijn P, Kroger J, Weitgasser R . Novel glucose-sensing technology and hypoglycaemia in type 1 diabetes: a multicentre, non-masked, randomised controlled trial. Lancet. 2016; 388(10057):2254-2263. DOI: 10.1016/S0140-6736(16)31535-5. View

2.
Vigersky R, McMahon C . The Relationship of Hemoglobin A1C to Time-in-Range in Patients with Diabetes. Diabetes Technol Ther. 2018; 21(2):81-85. DOI: 10.1089/dia.2018.0310. View

3.
Jin S, Kim T, Bae J, Hur K, Lee M, Lee M . Clinical factors associated with absolute and relative measures of glycemic variability determined by continuous glucose monitoring: an analysis of 480 subjects. Diabetes Res Clin Pract. 2014; 104(2):266-72. DOI: 10.1016/j.diabres.2014.02.003. View

4.
Choe J, Won S, Choe Y, Park S, Lee Y, Lee J . Temporal Trends for Diabetes Management and Glycemic Control Between 2010 and 2019 in Korean Children and Adolescents with Type 1 Diabetes. Diabetes Technol Ther. 2021; 24(3):201-211. DOI: 10.1089/dia.2021.0274. View

5.
Levey A, Stevens L, Schmid C, Zhang Y, Castro 3rd A, Feldman H . A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009; 150(9):604-12. PMC: 2763564. DOI: 10.7326/0003-4819-150-9-200905050-00006. View