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Volume 12 Issue 4
Jul.  2021
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Article Navigation >  Medical Journal of Peking Union Medical College Hospital  > 2021  >  12(4): 526-530
DENG Mingqun, ZHOU Liyuan, ZHAI Xiao, LIU Jieying, FU Junling, YU Ruiqi, PAN Yundi, MA Liyuan, YU Miao, XU Jianping, LI Wenhui, FENG Kai, XIAO Xinhua. Relationship between HbA1c and the Time in Range Derived from Flash Glucose Monitoring System[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(4): 526-530. doi: 10.12290/xhyxzz.20200035
Citation: DENG Mingqun, ZHOU Liyuan, ZHAI Xiao, LIU Jieying, FU Junling, YU Ruiqi, PAN Yundi, MA Liyuan, YU Miao, XU Jianping, LI Wenhui, FENG Kai, XIAO Xinhua. Relationship between HbA1c and the Time in Range Derived from Flash Glucose Monitoring System[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(4): 526-530. doi: 10.12290/xhyxzz.20200035
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Relationship between HbA1c and the Time in Range Derived from Flash Glucose Monitoring System

doi: 10.12290/xhyxzz.20200035

  • Department of Endocrinology, Key Laboratory of Endocrinology, National Health Commission of the People's Republic of China, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China

Funds:

National Key Research and Development Program of China 2017YFC1309603

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  • Corresponding author: XIAO Xinhua  Tel: 86-10-69155513, E-mail: xiaoxh2014@vip.163.com
  • Received Date: 2020-02-17
  • Accepted Date: 2020-05-04
    • Available Online: 2021-02-05
  • Publish Date: 2021-07-30
    Abstract
  •   Objective  To explore the relationship between HbA1c and time in range (TIR) derived from flash glucose monitoring system (FGMS) in Chinese adults with type 1 diabetes mellitus (T1DM).  Methods  Adult T1DM patients attended the outpatient department of Peking Union Medical College Hospital (PUMCH) from October 2018 to March 2019 were included. HbA1c and data of FGMS were obtained at the same time. TIR was calculated, and the relationship between TIR and HbA1c was investigated by Spearman correlation and regression analysis.  Results  A total of 77 patients who met the inclusion and exclusion criteria were included in the analysis. The average HbA1c was (7.5±1.3)%; TIR was 62.0 (48.7, 67.8)% and coefficient of variation(CV) was (39.7±8.1)%. TIR derived from FGMS had a negative liner correlation with HbA1c (r=-0.645, P < 0.001). The regression equation is: HbA1c=10.58-0.05×TIR. The HbA1c level is decreased by 0.5% for every 10% increase in TIR. TIR was negatively correlated with HbA1c in patients with both stable glucose (CV < 36%) and unstable glucose (CV≥36%), but the correlation coefficient between TIR and HbA1c in patients with stable glucose was higher. For a specific TIR, HbA1c was higher in patients with stable glucose.  Conclusion  The FGMS-derived TIR could be helpful in the glucose management in Chinese adults with T1DM, and glucose variability should be taken into consideration while interpreting the relationship between TIR and HbA1c.
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  • [1] Beck RW, Connor CG, Mullen DM, et al. The Fallacy of Average: How Using HbA1c Alone to Assess Glycemic Control Can Be Misleading[J]. Diabetes Care, 2017, 40: 994-999. doi:  10.2337/dc17-0636
    [2] Danne T, Revital N, Tadej B, et al. International Consensus on Use of Continuous Glucose Monitoring[J]. Diabetes Care, 2017, 40: 1631-1640. doi:  10.2337/dc17-1600
    [3] Lu JY, Ma XJ, Zhou J, et al. Association of Time in Range, as Assessed by Continuous Glucose Monitoring, With Diabetic Retinopathy in Type 2 Diabetes[J]. Diabetes Care, 2018, 41: 2370-2376. doi:  10.2337/dc18-1131
    [4] American Diabetes Association. Disclosures: Standards of Medical Care in Diabetes—2020[J]. Diabetes Care, 2020, 43: S205-S206. doi:  10.2337/dc20-Sdis
    [5] 中华医学会糖尿病学分会. 中国持续葡萄糖监测临床应用指南(2017年版)[J]. 中华糖尿病杂志, 2017, 9: 667-675. doi:  10.3760/cma.j.issn.1674-5809.2017.11.002
    [6] Beck RW, Tonya RW, Katrina R, et al. Effect of Continu-ous Glucose Monitoring on Glycemic Control in Adults With Type 1 Diabetes Using Insulin Injections: The DIAMOND Randomized Clinical Trial[J]. JAMA, 2017, 317: 371-378. doi:  10.1001/jama.2016.19975
    [7] Ruedy KJ, Tamborlane WV. The Landmark JDRF Continu-ous Glucose Monitoring Randomized Trials: a Look Back at the Accumulated Evidence[J]. J Cardiovasc Transl Res, 2012, 5: 380-387. doi:  10.1007/s12265-012-9364-9
    [8] Ólafsdóttir AF, William P, Jan B, et al. A Randomized Clinical Trial of the Effect of Continuous Glucose Monitoring on Nocturnal Hypoglycemia, Daytime Hypoglycemia, Glycemic Variability, and Hypoglycemia Confidence in Persons with Type 1 Diabetes Treated with Multiple Daily Insulin Injections (GOLD-3)[J]. Diabetes Technol Ther, 2018, 20: 274-284. doi:  10.1089/dia.2017.0363
    [9] Battelino T, Conget I, Olsen B, et al. The use and efficacy of continuous glucose monitoring in type 1 diabetes treated with insulin pump therapy: a randomised controlled trial[J]. Diabetologia, 2012, 55: 3155-3162. doi:  10.1007/s00125-012-2708-9
    [10] Ajjan RA. How Can We Realize the Clinical Benefits of Continuous Glucose Monitoring? [J]. Diabetes Technol Ther, 2017, 19: 27-36.
    [11] Tanenbaum ML, Adams RN, Lanning MS, et al. Using Cluster Analysis to Understand Clinician Readiness to Promote Continuous Glucose Monitoring Adoption[J]. J Diabetes Sci Technol, 2018, 12: 1108-1115. doi:  10.1177/1932296818786486
    [12] 中华医学会糖尿病学分会血糖监测学组. 中国扫描式葡萄糖监测技术临床应用专家共识[J]. 中华糖尿病杂志, 2018, 10: 697-700.
    [13] Angellotti E, Sangeetha M, Siegel RD, et al. The Calculation of the Glucose Management Indicator Is Influenced by the Continuous Glucose Monitoring System and Patient Race[J]. Diabetes Technol Ther, 2020, 22: 651-657. doi:  10.1089/dia.2019.0405
    [14] Beck RW, Bergenstal RM, Riddlesworth TD, et al. Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials[J]. Diabetes Care, 2019, 42: 400-405. doi:  10.2337/dc18-1444
    [15] Beck RW, Bergenstal RM, Cheng PY, et al. The Relationships Between Time in Range, Hyperglycemia Metrics, and HbA1c[J]. J Diabetes Sci Technol, 2019, 13: 614-626. doi:  10.1177/1932296818822496
    [16] Vigersky RA, Chantal M. The Relationship of Hemoglobin A1C to Time-in-Range in Patients with Diabetes[J]. Diabetes Technol Ther, 2019, 2: 81-85.
    [17] American Diabetes Association. Diabetes Technology: Stan-dards of Medical Care in Diabetes—2020[J]. Diabetes Care, 2020, 43: S77-S88. doi:  10.2337/dc20-S007
    [18] Lu J, Ma X, Zhang L, et al. Glycemic variability modifies the relationship between time in range and hemoglobin A1c estimated from continuous glucose monitoring: A preliminary study[J]. Diabetes Res Clin Pract, 2020, 161: 108032. doi:  10.1016/j.diabres.2020.108032
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