The role of self-monitoring of glycemia in the treatment of patients with type 2 diabetes mellitus and the achievement of the target level of carbohydrate metabolism

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Abstract

Self-monitoring of blood glucose levels is an important part of the treatment of type 1 and type 2 diabetes mellitus (DM). Regardless of the type of therapy received, patients with type 2 DM who regularly conduct self-monitoring of glucose levels have better glycemic control through active participation in treatment and lifestyle changes, and also have the opportunity to timely adjust therapy by the attending physician as needed. Studies using structured glucose self-monitoring often show significantly greater improvement in glycemic control compared to unstructured self-monitoring. Modern glucometers have such advantages as high accuracy of readings, integration with a mobile application that combines the function of a self-monitoring diary, the ability to analyze results at the time of the study, and generate reports for interpretation by the attending physician. All this makes it possible to use self-monitoring of glucose as a convenient tool for the treatment of type 2 DM.

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About the authors

Tatiana Yu. Demidova

N.I. Pirogov Russian National Research Medical University of the Ministry of Healthcare of Russia

Author for correspondence.
Email: t.y.demidova@gmail.com

MD, Professor, Head of the Department of Endocrinology of the Faculty of General Medicine

Russian Federation, Moscow

Victoria V. Titova

N.I. Pirogov Russian National Research Medical University of the Ministry of Healthcare of Russia

Email: meteora-vica@mail.ru
ORCID iD: 0000-0002-8684-6095
SPIN-code: 7864-2910

Assistant at the Department of Endocrinology of the Faculty of General Medicine

Russian Federation, Moscow

References

  1. Goldstein D.E., Little R.R., Lorenz R.A. et al. Tests of glycemia in diabetes. Diabetes Care. 2004; 27(7): 1761–73. https://dx.doi.org/10.2337/diacare.27.7.1761.
  2. Franciosi M., Pellegrini F., De Berardis G. et al. Self-monitoring of blood glucose in non-insulin-treated diabetic patients: A longitudinal evaluation of its impact on metabolic control. Diabet Med. 2005; 22(7): 900–6. https://dx.doi.org/10.1111/j.1464-5491.2005.01546.x.
  3. Machry R.V., Rados D.V., Gregorio G.R., Rodrigues T.C. Self-monitoring blood glucose improves glycemic control in type 2 diabetes without intensive treatment: A systematic review and meta-analysis. Diabetes Res Clin Pract. 2018; 142: 173–87. https://dx.doi.org/10.1016/j.diabres.2018.05.037.
  4. Diabetes Control and Complications Trial Research Group, Nathan D.M., Genuth S., Lachin J. et al. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993; 329(14): 977–86. https://dx.doi.org/10.1056/NEJM199309303291401.
  5. Benedict S.R. A reagent for the detection of reducing sugars. 1908. J Biol Chem. 2002; 277(16): e5.
  6. Hagedorn H.C., Jensen, B.N. The microdetermination of blood sugar by means of ferricyanide. Biochem. Z. 1923; (135): 46.
  7. Tonyushkina K., Nichols J.H. Glucose meters: A review of technical challenges to obtaining accurate results J Diabetes Sci Technol. 2009; 3(4): 971–80. https://dx.doi.org/10.1177/193229680900300446.
  8. American Diabetes Association. Diabetes technology: Standards of medical care in diabetes – 2019. Diabetes Care. 2019; 42(Suppl 1): S71–80. https://dx.doi.org/10.2337/dc19-S007.
  9. Parkin C.G., Buskirk A., Hinnen D.A., Axel-Schweitzer M. Results that matter: Structured vs. unstructured self-monitoring of blood glucose in type 2 diabetes. Diabetes Res Clin Pract. 2012; 97(1): 6–15. https://dx.doi.org/10.1016/j.diabres.2012.03.002.S0168-8227(12)00098-8.
  10. Mannucci E., Antenore A., Giorgino F., Scavini M. Effects of structured versus unstructured self-monitoring of blood glucose on glucose control in patients with non-insulin-treated type 2 diabetes: A meta-analysis of randomized controlled trials. J Diabetes Sci Technol. 2018; 12(1): 183–89. https://dx.doi.org/10.1177/1932296817719290.
  11. Xu Y., Tan D., Lee J. Evaluating the impact of self-monitoring of blood glucose frequencies on glucose control in patients with type 2 diabetes who do not use insulin: A systematic r–eview and meta-analysis. Int J Clin Pract. 2019; 73(7): e13357. https://dx.doi.org/10.1111/ijcp.13357.
  12. Viana L.V., Leitao C.B., Kramer C.K. et al. Poor glycaemic control in Brazilian patients with type 2 diabetes attending the public healthcare system: A cross-sectional study. BMJ Open. 2013; 3(9): e003336. https://dx.doi.org/10.1136/bmjopen-2013-003336.
  13. Rosenstock J., Davies M., Home P.D. et al. A randomised, 52-week, treat-to-target trial comparing insulin detemir with insulin glargine when administered as add-on to glucose-lowering drugs in insulin-naive people with type 2 diabetes. Diabetologia. 2008; 51(3): 408–16. https://dx.doi.org/10.1007/s00125-007-0911-x.
  14. Garber A.J. Treat-to-target trials: Uses, interpretation and review of concepts. Diabetes Obes Metab. 2014; 16(3): 193–205. https://dx.doi.org/10.1111/dom.12129.
  15. Lu J., Bu R.F., Sun Z.L. et al. Comparable efficacy of self-monitoring of quantitative urine glucose with self-monitoring of blood glucose on glycemic control in noninsulin-treated type 2 diabetes. Diabetes Res Clin Pract. 2011; 93(2): 179–86. https://dx.doi.org/10.1016/j.diabres.2011.04.012.
  16. Bonomo K., De Salve A., Fiora E. et al. Evaluation of a simple policy for pre- and post-prandial blood glucose self-monitoring in people with type 2 diabetes not on insulin. Diabetes Res Clin Pract. 2010; 87(2): 246–51. https://dx.doi.org/10.1016/j.diabres.2009.10.021.
  17. Schnell O., Amann-Zalan I., Jelsovsky Z. et al. Changes in A1C levels are significantly associated with changes in levels of the cardiovascular risk biomarker hs-CRP. Results from the SteP study. Diabetes Care. 2013; 36(7): 2084–89. https://dx.doi.org/10.2337/dc12-1711.
  18. Chidum E., Agbai D., Fidelis O. et al. Self-monitoring of blood glucose improved glycemic control and 10-year coronary heart disease risk profile of type 2 diabetic patients. Chin Med J (Engl). 2011; 124(2): 166–71.
  19. Schwedes U., Siebolds M., Mertes G. Meal-related structured self-monitoring of blood glucose: effect on diabetes control in non-insulin-treated type 2 diabetic patients. Diabetes Care. 2002; 25(11): 1928–32. https://dx.doi.org/10.2337/diacare.25.11.1928.
  20. Bosi E., Scavini M., Ceriello A. et al. Intensive structured self-monitoring of blood glucose and glycemic control in noninsulin-treated type 2 diabetes: The Prisma randomized trial. Diabetes Care. 2013; 36(12): e218. https://dx.doi.org/10.2337/dc13-1683.
  21. Khamseh M.E., Ansari M., Malek M. et al. Effects of a structured self-monitoring of blood glucose method on patient self-management behavior and metabolic outcomes in type 2 diabetes mellitus. J Diabetes Sci Technol. 2011; 5(2): 388–93. https://dx.doi.org/10.1177/193229681100500228.
  22. Li C.L., Wu Y.C., Kornelius E. et al. Comparison of different models of structured self-monitoring of blood glucose in type 2 diabetes. Diabetes Technol Ther. 2016; 18(3): 171–77. https://dx.doi.org/10.1089/dia.2015.0082.
  23. Nishimura A., Harashima S.I., Fujita Y. et al. Effects of structured testing versus routine testing of blood glucose in diabetes selfmanagement: A randomized controlled trial. J Diabet Complicat. 2017; 31(1): 228–33. https://dx.doi.org/10.1016/j.jdiacomp.2016.08.019.
  24. Polonsky W.H., Fisher L., Schikman C.H. et al. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes: results from the Structured Testing Program study. Diabetes Care. 2011; 34(2): 262–67. https://dx.doi.org/10.2337/dc10-1732.
  25. Parsons S.N., Luzio S.D., Harvey J.N. et al. Effect of structured self-monitoring of blood glucose, with and without additional TeleCare support, on overall glycaemic control in non-insulin treated Type 2 diabetes: the SMBG Study, a 12-month randomized controlled trial. Diabet Med. 2019; 36(5): 578–90. https://dx.doi.org/10.1111/dme.13899.
  26. Yoo H.J., An H.G., Park S.Y. et al. Use of a real time continuous glucose monitoring system as a motivational device for poorly controlled type 2 diabetes. Diabetes Res Clin Pract. 2008; 82(1): 73–79. https://dx.doi.org/10.1016/j.diabres.2008.06.015.
  27. Farmer A.J., Perera R., Ward A. et al. Meta-analysis of individual patient data in randomised trials of self monitoring of blood glucose in people with non-insulin treated type 2 diabetes. BMJ. 2012; 344: e486. https://dx.doi.org/10.1136/bmj.e486.
  28. O’Kane M.J., Bunting B., Copeland M., Coates V.E.; ESMON study group. Efficacy of self monitoring of blood glucose in patients with newly diagnosed type 2 diabetes (ESMON study): Randomised controlled trial. BMJ. 2008; 336(7654): 1174–77. https://dx.doi.org/10.1136/bmj.39534.571644.BE.
  29. Jung H.S. Clinical implications of glucose variability: Chronic complications of diabetes. Endocrinol Metab (Seoul). 2015; 30(2): 167–74. https://dx.doi.org/10.3803/EnM.2015.30.2.167.
  30. Mazze R.S. Making sense of glucose monitoring technologies: From SMBG to CGM. Diabetes Technol Ther. 2005; 7(5): 784–87. https://dx.doi.org/10.1089/dia.2005.7.784.
  31. Kilpatrick E.S., Rigby A.S., Goode K., Atkin S.L. Relating mean blood glucose and glucose variability to the risk of multiple episodes of hypoglycaemia in type 1 diabetes. Diabetologia. 2007; 50(12): 2553–61. https://dx.doi.org/10.1007/s00125-007-0820-z.
  32. Gorst C., Kwok C.S., Aslam S. et al. Long-term glycemic variability and risk of adverse outcomes: A systematic review and meta-analysis. Diabetes Care. 2015; 38(12): 2354–69. https://dx.doi.org/10.2337/dc15-1188
  33. Nusca A., Tuccinardi D., Albano M. et al. Glycemic variability in the development of cardiovascular complications in diabetes. Diabetes Metab Res Rev. 2018; 34(8): e3047. https://dx.doi.org/10.1002/dmrr.3047.
  34. Meynaar I.A., Eslami S., Abu-Hanna A. et al. Blood glucose amplitude variability as predictor for mortality in surgical and medical intensive care unit patients: a multicenter cohort study. J Crit Care. 2012; 27(2): 119–24. https://dx.doi.org/10.1016/j.jcrc.2011.11.004.
  35. Madeo B., Diazzi C., Granata A.R.M. et al. Effect of a standard schema of self-monitoring blood glucose in patients with poorly controlled, non-insulin-treated type 2 diabetes mellitus: A controlled longitudinal study. J Popul Ther Clin Pharmacol. 2020; 27(S Pt 2): e1–e11. https://dx.doi.org/10.15586/jptcp.v27iSP2.680.
  36. Sia H.K., Kor C.T., Tu S.T. et al. Self-monitoring of blood glucose in association with glycemic control in newly diagnosed non-insulin-treated diabetes patients: A retrospective cohort study. Sci Rep. 2021; 11(1): 1176. https://dx.doi.org/10.1038/s41598-021-81024-x.
  37. IDF Clinical Practice Recommendations for managing Type 2 Diabetes in Primary Care. 2017. URL: https://idf.org/media/uploads/2023/05/attachments-63.pdf (date of access – 01.06.2023).
  38. Chang Y.T., Tu Y.Z., Chiou H.Y. Et al. Real-world benefits of diabetes management app use and self-monitoring of blood glucose on glycemic control: Retrospective analyses. JMIR Mhealth Uhealth. 2022; 10(6): e31764. https://dx.doi.org/10.2196/31764.
  39. Алгоритмы специализированной медицинской помощи больным сахарным диабетом. Под редакцией И.И. Дедова, М.В. Шестаковой, А.Ю. Майорова. 11-й выпуск. М. 2023. [Algorithms of specialized medical care for patients with diabetes mellitus. Ed. by Dedov I.I., Shestakova M.V., Mayorov A.Yu. 11th edition. Moscow. 2023 (In Russ.)]. https://dx.doi.org/10.14341/DM13042.
  40. Grady M., Lamps G., Shemain A. et al. Clinical evaluation of a new, lower pain, one touch lancing device for people with diabetes: Virtually pain-free testing and improved comfort compared to current lancing systems. J Diabetes Sci Technol. 2021; 15(1): 53–59. https://dx.doi.org/10.1177/1932296819856665.
  41. Harrison B., Brown D. Accuracy of a blood glucose monitoring system that recognizes insufficient sample blood volume and allows application of more blood to the same test strip. Expert Rev Med Devices. 2020; 17(1): 75–82. https://dx.doi.org/10.1080/17434440.2020.1704253.
  42. Katz L.B., Stewart L., Guthrie B., Cameron H. Patient satisfaction with a new, high accuracy blood glucose meter that provides personalized guidance, insight, and encouragement. J Diabetes Sci Technol. 2020; 14(2): 318–23. https://dx.doi.org/10.1177/1932296819867396.
  43. Shaw R.J., Yang Q., Barnes A. et al. Self-monitoring diabetes with multiple mobile health devices. J Am Med Inform Assoc. 2020; 27(5): 667–76. https://dx.doi.org/10.1093/jamia/ocaa007.
  44. Bailey T.S., Wallace J.F., Pardo S. et al. Accuracy and user performance evaluation of a new, wireless-enabled blood glucose monitoring system that links to a smart mobile device. J Diabetes Sci Technol. 2017; 11(4): 736–43. https://dx.doi.org/10.1177/1932296816680829.
  45. Otto E.A., Tannan V. Evaluation of the utility of a glycemic pattern identification system. J Diabetes Sci Technol. 2014; 8(4): 830–38. https://dx.doi.org/10.1177/1932296814532210.

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