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Current Diabetes Reviews

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ISSN (Print): 1573-3998
ISSN (Online): 1875-6417

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Research Article

Comparative Effectiveness of Oral Hypoglycemic Agents for Glycemic Control and Glycemic Variability in Patients with Type 2 Diabetes Mellitus: Using Flash Glucose Monitoring

Author(s): Poongothai Venkatachalapathy, Karthik Kumar Dos Alagarswamy Mohandoss, Murali Munisamy and Mohan Sellappan*

Volume 21, Issue 1, 2025

Published on: 16 January, 2024

Article ID: e160124225706 Pages: 9

DOI: 10.2174/0115733998267817231227102553

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Abstract

Aim: The study aimed to compare the effectiveness of oral hypoglycemic agents (OHAs) as monotherapy, dual and quadruple therapy for glycemic control (GC) and glycemic variability (GV) in patients with type 2 diabetes (T2DM) using flash glucose monitoring system (FGM).

Background: Diabetes management largely relies on HbA1c monitoring. Glycemic variability has been an evolving glycemic target for preventing complications related to type 2 diabetes mellitus.

Objective: The purpose of the study was to compare glycemic control measures and glycemic variability measures among study groups and to study the relationships between GC and GV indices.

Methods: Retrospectively, FGM data were collected from 50 T2DM patients. The patients were classified based on prescribed number of OHAs as monotherapy [group 1: Dipeptidyl peptidase- 4 (DPP-4) inhibitors (n=10), group 2: Sodium-glucose co-transporter-2 (SGLT2) inhibitors (n=10), group 3: Sulphonylureas (n=10), group 4: Dual therapy (n=10), and group 5: Quadruple therapy (n=10)]. Measures of GC and GV were evaluated.

Results: Significant differences between study groups were observed in GC and GV measurements. The SGLT2 inhibitors monotherapy group demonstrated optimal GC [eA1c (%): 6.5 ± 2.2; MBG: 140.80 ± 63.94; TIR: 60.60 ± 19.96] and GV (SD: 42.38 ± 34.57; CV: 27.85 ± 6.68; MAGE: 96.76 ± 52.47; MODD: 33.96 ± 22.91) in comparison to other study groups. On using Pearson correlation analysis, mean blood glucose (MBG) and mean amplitude of glycemic excursion (MAGE) showed moderate correlation (r = 0.742)(r2 = 0.551), depicting distinct glucose variabilities at the same mean blood glucose levels.

Conclusion: The monotherapy group of SGLT2 inhibitors demonstrated glucose-lowering effects with reduced glycemic variability. Hence, optimum glycemic control is associated with decreased glycemic variability.

Keywords: Glycemic control, glycemic variability, type 2 diabetes mellitus, oral hypoglycemic agents, flash glucose monitoring, ambulatory glucose profile.

[1]
International Diabetes Federation. IDF Diabetes Atlas. (9th ed.), Brussels, Belgium 2019.
[2]
Saboo B, Chawla M, Jha S, et al. Consensus and recommendations on continuous glucose monitoring. J Diabetology 2019; 10(1): 4-14.
[http://dx.doi.org/10.4103/jod.jod_45_18]
[3]
Garber AJ, Abrahamson MJ, Barzilay JI, et al. Consensus statement by the American association of clinical endocrinologists and American college of endocrinology on the comprehensive type 2 diabetes management algorithm – 2019 executive summary. Endocr Pract 2019; 25(1): 69-101.
[http://dx.doi.org/10.4158/CS-2018-0535] [PMID: 30742570]
[4]
Chehregosha H, Khamseh ME, Malek M, Hosseinpanah F, Ismail-Beigi F. A view beyond HbA1c: Role of continuous glucose monitoring. Diabetes Ther 2019; 10(3): 853-63.
[http://dx.doi.org/10.1007/s13300-019-0619-1] [PMID: 31037553]
[5]
Kohnert K-D, Vogt L, Salzseider E. Advances in understanding glucose variability and the role of continuous glucose monitoring. Eur J Endocrinol 2010; 6(1): 53-6.
[6]
Ceriello A, Monnier L, Owens D. Glycaemic variability in diabetes: Clinical and therapeutic implications. Lancet Diabetes Endocrinol 2019; 7(3): 221-30.
[http://dx.doi.org/10.1016/S2213-8587(18)30136-0] [PMID: 30115599]
[7]
Penckofer S, Quinn L, Byrn M, Ferrans C, Miller M, Strange P. Does glycemic variability impact mood and quality of life? Diabetes Technol Ther 2012; 14(4): 303-10.
[http://dx.doi.org/10.1089/dia.2011.0191] [PMID: 22324383]
[8]
Unnikrishnan AG, Purandare VB. Ambulatory glucose profile as an educational tool in the management of patients with type 2 diabetes mellitus. IJMRHS 2020; 8(2): 734-7.
[http://dx.doi.org/10.18203/2320-6012.ijrms20200032]
[9]
Li Y, Xu L, Shen J, et al. Effects of short-term therapy with different insulin secretagogues on glucose metabolism, lipid parameters and oxidative stress in newly diagnosed Type 2 Diabetes Mellitus. Diabetes Res Clin Pract 2010; 88(1): 42-7.
[http://dx.doi.org/10.1016/j.diabres.2009.12.017] [PMID: 20060192]
[10]
Bao YQ, Zhou J, Zhou M, et al. Glipizide controlled‐release tablets, with or without acarbose, improve glycaemic variability in newly diagnosed Type 2 diabetes. Clin Exp Pharmacol Physiol 2010; 37(5-6): 564-8.
[http://dx.doi.org/10.1111/j.1440-1681.2010.05361.x] [PMID: 20082624]
[11]
Suh S, Kim JH. Glycemic variability: How do we measure it and why is it important? Diabetes Metab J 2015; 39(4): 273-82.
[http://dx.doi.org/10.4093/dmj.2015.39.4.273] [PMID: 26301188]
[12]
Pagacz K, Stawiski K, Szadkowska A, Mlynarski W, Fendler W. GlyCulator2: An update on a web application for calculation of glycemic variability indices. Acta Diabetol 2018; 55(8): 877-80.
[http://dx.doi.org/10.1007/s00592-018-1140-0] [PMID: 29651558]
[13]
The DCCT Research Group. The Diabetes Control and Complications Trial (DCCT). Design and methodologic considerations for the feasibility phase. Diabetes 1986; 35(5): 530-45.
[http://dx.doi.org/10.2337/diab.35.5.530] [PMID: 2869996]
[14]
Hsia DS, Grove O, Cefalu WT. An update on SGLT2 inhibitors for the treatment of diabetes mellitus. Curr Opin Endocrinol Diabetes Obes 2017; 24(1): 73-9.
[http://dx.doi.org/10.1097/MED.0000000000000311] [PMID: 27898586]
[15]
Chao EC. SGLT-2 inhibitors: A new mechanism for glycemic control. Clin Diabetes 2014; 32(1): 4-11.
[http://dx.doi.org/10.2337/diaclin.32.1.4] [PMID: 26246672]
[16]
Hirsch IB, Sherr JL, Hood KK. Connecting the dots: Validation of time in range metrics with microvascular outcomes. Diabetes Care 2019; 42(3): 345-8.
[http://dx.doi.org/10.2337/dci18-0040] [PMID: 30787056]
[17]
Battelino T, Danne T, Bergenstal RM, et al. Clinical targets for continuous glucose monitoring data interpretation: Recommendations from the international consensus on time in range. Diabetes Care 2019; 42(8): 1593-603.
[http://dx.doi.org/10.2337/dci19-0028] [PMID: 31177185]
[18]
Suzuki D, Yamada H, Yoshida M, et al. Sodium–glucose cotransporter 2 inhibitors improved time‐in‐range without increasing hypoglycemia in Japanese patients with type 1 diabetes: A retrospective, single‐center, pilot study. J Diabetes Investig 2020; 11(5): 1230-7.
[http://dx.doi.org/10.1111/jdi.13240] [PMID: 32100964]
[19]
Kaviarasan S, Muniandy S, Qvist R, Ismail IS. F(2)-isoprostanes as novel biomarkers for type 2 diabetes: A review. J Clin Biochem Nutr 2009; 45(1): 1-8.
[http://dx.doi.org/10.3164/jcbn.08-266] [PMID: 19590700]
[20]
Service FJ. Glucose variability. Diabetes 2013; 62(5): 1398-404.
[http://dx.doi.org/10.2337/db12-1396] [PMID: 23613565]
[21]
Jin SM, Kim TH, Bae JC, et al. 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.
[http://dx.doi.org/10.1016/j.diabres.2014.02.003] [PMID: 24630619]
[22]
Yoo S, Chin SO, Lee SA, Koh G. Factors associated with glycemic variability in patients with type 2 diabetes: Focus on oral hypoglycemic agents and cardiovascular risk factors. Endocrinol Metab 2015; 30(3): 352-60.
[http://dx.doi.org/10.3803/EnM.2015.30.3.352] [PMID: 26248860]
[23]
Chiba K, Nomoto H, Nakamura A, Cho KY, Yamashita K, Shibayama Y. Sodium–glucose cotransporter 2 inhibitors reduce day-to-day glucose variability in patients with type 1 diabetes. J Diabetes Investig 2020; 12(2): 176-83.
[http://dx.doi.org/10.1111/jdi.13335] [PMID: 32593203]
[24]
Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ. Translating the A1C assay into estimated average glucose values. Diabetes Care 2008; 31(8): 1473-8.
[http://dx.doi.org/10.2337/dc08-0545] [PMID: 18540046]
[25]
Vigersky RA, McMahon C. The relationship of hemoglobin a1c to time-in-range in patients with diabetes. Diabetes Technol Ther 2019; 21(2): 81-5.
[http://dx.doi.org/10.1089/dia.2018.0310] [PMID: 30575414]
[26]
Borg R, Kuenen JC, Carstensen B, et al. Associations between features of glucose exposure and A1C: the A1C-Derived Average Glucose (ADAG) study. Diabetes 2010; 59(7): 1585-90.
[http://dx.doi.org/10.2337/db09-1774] [PMID: 20424232]
[27]
Vasilakou D, Karagiannis T, Athanasiadou E, Mainou M, Liakos A, Bekiari E. Sodium-glucose cotransporter 2 inhibitors for type 2 diabetes: A systematic review and meta-analysis. Ann Intern Med 2013; 159(4): 262-74.
[http://dx.doi.org/10.7326/0003-4819-159-4-201308200-00007] [PMID: 24026259]
[28]
Shao SC, Chang KC, Lin SJ, et al. Favorable pleiotropic effects of sodium glucose cotransporter 2 inhibitors: Head-to-head comparisons with dipeptidyl peptidase-4 inhibitors in type 2 diabetes patients. Cardiovasc Diabetol 2020; 19(1): 17.
[http://dx.doi.org/10.1186/s12933-020-0990-2] [PMID: 32050968]
[29]
Taylor PJ, Lange K, Thompson CH, Gary W, Brinkworth GD. Association of glycemic variability and the anti-glycemic medication effect score in adults with type 2 diabetes. Diabetes Manag 2018; 8(5): 117-21.
[30]
Kohnert K, Heinke P, Vogt L, Zander E, Fritzsche G, Augstein P. Reduced glucose variability is associated with improved quality of glycemic control in patients with type 2 diabetes: A 12-month observational study. J Endocrinol Metab 2011; 1(2): 64-72.
[http://dx.doi.org/10.4021/jem21w]

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