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2000
Volume 21, Issue 1
  • ISSN: 1573-3998
  • E-ISSN: 1875-6417

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.

© 2025 The Author(s). Published by Bentham Science Publishers. This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
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2024-01-16
2025-06-21
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References

  1. International Diabetes FederationIDF Diabetes Atlas.9th edBrussels, Belgium2019
    [Google Scholar]
  2. SabooB. ChawlaM. JhaS. Consensus and recommendations on continuous glucose monitoring.J. Diabetology201910141410.4103/jod.jod_45_18
    [Google Scholar]
  3. GarberA.J. AbrahamsonM.J. BarzilayJ.I. 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.20192516910110.4158/CS‑2018‑0535 30742570
    [Google Scholar]
  4. ChehregoshaH. KhamsehM.E. MalekM. HosseinpanahF. Ismail-BeigiF. A view beyond HbA1c: Role of continuous glucose monitoring.Diabetes Ther.201910385386310.1007/s13300‑019‑0619‑1 31037553
    [Google Scholar]
  5. KohnertK-D. VogtL. SalzseiderE. Advances in understanding glucose variability and the role of continuous glucose monitoring.Eur. J. Endocrinol.2010615356
    [Google Scholar]
  6. CerielloA. MonnierL. OwensD. Glycaemic variability in diabetes: Clinical and therapeutic implications.Lancet Diabetes Endocrinol.20197322123010.1016/S2213‑8587(18)30136‑0 30115599
    [Google Scholar]
  7. PenckoferS. QuinnL. ByrnM. FerransC. MillerM. StrangeP. Does glycemic variability impact mood and quality of life?Diabetes Technol. Ther.201214430331010.1089/dia.2011.0191 22324383
    [Google Scholar]
  8. UnnikrishnanA.G. PurandareV.B. Ambulatory glucose profile as an educational tool in the management of patients with type 2 diabetes mellitus.IJMRHS20208273473710.18203/2320‑6012.ijrms20200032
    [Google Scholar]
  9. LiY. XuL. ShenJ. 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.2010881424710.1016/j.diabres.2009.12.017 20060192
    [Google Scholar]
  10. BaoY.Q. ZhouJ. ZhouM. Glipizide controlled‐release tablets, with or without acarbose, improve glycaemic variability in newly diagnosed Type 2 diabetes.Clin. Exp. Pharmacol. Physiol.2010375-656456810.1111/j.1440‑1681.2010.05361.x 20082624
    [Google Scholar]
  11. SuhS. KimJ.H. Glycemic variability: How do we measure it and why is it important?Diabetes Metab. J.201539427328210.4093/dmj.2015.39.4.273 26301188
    [Google Scholar]
  12. PagaczK. StawiskiK. SzadkowskaA. MlynarskiW. FendlerW. GlyCulator2: An update on a web application for calculation of glycemic variability indices.Acta Diabetol.201855887788010.1007/s00592‑018‑1140‑0 29651558
    [Google Scholar]
  13. The DCCT Research GroupThe Diabetes Control and Complications Trial (DCCT). Design and methodologic considerations for the feasibility phase.Diabetes198635553054510.2337/diab.35.5.530 2869996
    [Google Scholar]
  14. HsiaD.S. GroveO. CefaluW.T. An update on SGLT2 inhibitors for the treatment of diabetes mellitus.Curr. Opin. Endocrinol. Diabetes Obes.2017241737910.1097/MED.0000000000000311 27898586
    [Google Scholar]
  15. ChaoE.C. SGLT-2 inhibitors: A new mechanism for glycemic control.Clin. Diabetes201432141110.2337/diaclin.32.1.4 26246672
    [Google Scholar]
  16. HirschI.B. SherrJ.L. HoodK.K. Connecting the dots: Validation of time in range metrics with microvascular outcomes.Diabetes Care201942334534810.2337/dci18‑0040 30787056
    [Google Scholar]
  17. BattelinoT. DanneT. BergenstalR.M. Clinical targets for continuous glucose monitoring data interpretation: Recommendations from the international consensus on time in range.Diabetes Care20194281593160310.2337/dci19‑0028 31177185
    [Google Scholar]
  18. SuzukiD. YamadaH. YoshidaM. 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.20201151230123710.1111/jdi.13240 32100964
    [Google Scholar]
  19. KaviarasanS. MuniandyS. QvistR. IsmailI.S F(2)-isoprostanes as novel biomarkers for type 2 diabetes: A review.J. Clin. Biochem. Nutr.20094511810.3164/jcbn.08‑266 19590700
    [Google Scholar]
  20. ServiceF.J. Glucose variability.Diabetes20136251398140410.2337/db12‑1396 23613565
    [Google Scholar]
  21. JinS.M. KimT.H. BaeJ.C. 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.2014104226627210.1016/j.diabres.2014.02.003 24630619
    [Google Scholar]
  22. YooS. ChinS.O. LeeS.A. KohG. Factors associated with glycemic variability in patients with type 2 diabetes: Focus on oral hypoglycemic agents and cardiovascular risk factors.Endocrinol. Metab.201530335236010.3803/EnM.2015.30.3.352 26248860
    [Google Scholar]
  23. ChibaK. NomotoH. NakamuraA. ChoK.Y. YamashitaK. ShibayamaY. Sodium–glucose cotransporter 2 inhibitors reduce day-to-day glucose variability in patients with type 1 diabetes.J. Diabetes Investig.202012217618310.1111/jdi.13335 32593203
    [Google Scholar]
  24. NathanD.M. KuenenJ. BorgR. ZhengH. SchoenfeldD. HeineR.J. Translating the A1C assay into estimated average glucose values.Diabetes Care20083181473147810.2337/dc08‑0545 18540046
    [Google Scholar]
  25. VigerskyR.A. McMahonC. The relationship of hemoglobin a1c to time-in-range in patients with diabetes.Diabetes Technol. Ther.2019212818510.1089/dia.2018.0310 30575414
    [Google Scholar]
  26. BorgR. KuenenJ.C. CarstensenB. Associations between features of glucose exposure and A1C: the A1C-Derived Average Glucose (ADAG) study.Diabetes20105971585159010.2337/db09‑1774 20424232
    [Google Scholar]
  27. VasilakouD. KaragiannisT. AthanasiadouE. MainouM. LiakosA. BekiariE. Sodium-glucose cotransporter 2 inhibitors for type 2 diabetes: A systematic review and meta-analysis.Ann. Intern. Med.2013159426227410.7326/0003‑4819‑159‑4‑201308200‑00007 24026259
    [Google Scholar]
  28. ShaoS.C. ChangK.C. LinS.J. 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.20201911710.1186/s12933‑020‑0990‑2 32050968
    [Google Scholar]
  29. TaylorP.J. LangeK. ThompsonC.H. GaryW. BrinkworthG.D. Association of glycemic variability and the anti-glycemic medication effect score in adults with type 2 diabetes.Diabetes Manag.201885117121
    [Google Scholar]
  30. KohnertK. HeinkeP. VogtL. ZanderE. FritzscheG. AugsteinP. 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.201112647210.4021/jem21w
    [Google Scholar]
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