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  • Perspective
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Continuous glucose monitoring for the routine care of type 2 diabetes mellitus

Nature Reviews Endocrinology (2024)Cite this article

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Abstract

Although continuous glucose monitoring (CGM) devices are now considered the standard of care for people with type 1 diabetes mellitus, the uptake among people with type 2 diabetes mellitus (T2DM) has been slower and is focused on those receiving intensive insulin therapy. However, increasing evidence now supports the inclusion of CGM in the routine care of people with T2DM who are on basal insulin-only regimens or are managed with other medications. Expanding CGM to these groups could minimize hypoglycaemia while allowing efficient adaptation and escalation of therapies. Increasing evidence from randomized controlled trials and observational studies indicates that CGM is of clinical value in people with T2DM on non-intensive treatment regimens. If further studies confirm this finding, CGM could soon become a part of routine care for T2DM. In this Perspective we explore the potential benefits of widening the application of CGM in T2DM, along with the challenges that must be overcome for the evidence-based benefits of this technology to be delivered for all people with T2DM.

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Fig. 1: The unmet need for change in health-care services for effective management of people with type 2 diabetes mellitus.

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References

  1. Davies, M. J. et al. Management of hyperglycaemia in type 2 diabetes, 2022. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 65, 1925–1966 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Powers, M. A. et al. Diabetes self-management education and support in adults with type 2 diabetes: a consensus report of the American Diabetes Association, the Association of Diabetes Care and Education Specialists, the Academy of Nutrition and Dietetics, the American Academy of Family Physicians, the American Academy of PAs, the American Association of Nurse Practitioners, and the American Pharmacists Association. J. Acad. Nutr. Diet. 121, 773–788.e9 (2021).

    Article  PubMed  Google Scholar 

  3. Powers, M. A. 2016 Health Care & Education Presidential address: If DSME Were a Pill, Would You Prescribe It? Diabetes Care 39, 2101–2107 (2016).

    Article  PubMed  Google Scholar 

  4. Chrvala, C. A., Sherr, D. & Lipman, R. D. Diabetes self-management education for adults with type 2 diabetes mellitus: a systematic review of the effect on glycemic control. Patient Educ. Couns. 99, 926–943 (2016).

    Article  PubMed  Google Scholar 

  5. Fisher, L. et al. REDEEM: a pragmatic trial to reduce diabetes distress. Diabetes Care 36, 2551–2558 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Chatterjee, S. et al. Diabetes structured self-management education programmes: a narrative review and current innovations. Lancet Diabetes Endocrinol. 6, 130–142 (2018).

    Article  PubMed  Google Scholar 

  7. Stratton, I. M. et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ 321, 405–412 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Holman, R. R., Paul, S. K., Bethel, M. A., Matthews, D. R. & Neil, H. A. W. 10-Year follow-up of intensive glucose control in type 2 diabetes. N. Engl. J. Med. 359, 1577–1589 (2008).

    Article  CAS  PubMed  Google Scholar 

  9. UK Prospective Diabetes Study (UKPDS) Group. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet 352, 837–853 (1998).

    Article  Google Scholar 

  10. Khunti, K., Ceriello, A., Cos, X. & Block, C. D. Achievement of guideline targets for blood pressure, lipid, and glycaemic control in type 2 diabetes: a meta-analysis. Diabetes Res. Clin. Pr. 137, 137–148 (2018).

    Article  Google Scholar 

  11. American Diabetes Association Professional Practice Committee. 6. Glycemic targets: standards of medical care in diabetes—2022. Diabetes Care 45, S83–S96 (2021).

    Article  Google Scholar 

  12. Lind, M., Imberg, H., Coleman, R. L., Nerman, O. & Holman, R. R. Historical HbA1c values may explain the type 2 diabetes legacy effect: UKPDS 88. Diabetes Care 44, 2231–2237 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Paul, S. K., Klein, K., Thorsted, B. L., Wolden, M. L. & Khunti, K. Delay in treatment intensification increases the risks of cardiovascular events in patients with type 2 diabetes. Cardiovasc. Diabetol. 14, 100 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Mateo, J. F. et al. Multifactorial approach and adherence to prescribed oral medications in patients with type 2 diabetes. Int. J. Clin. Pract. 60, 422–428 (2006).

    Article  CAS  PubMed  Google Scholar 

  15. Safford, M. M. et al. Reasons for not intensifying medications: differentiating “clinical inertia” from appropriate care. J. Gen. Intern. Med. 22, 1648–1655 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Khunti, K. et al. Clinical inertia in intensifying therapy among people with type 2 diabetes treated with basal insulin. Diabetes Obes. Metab. 18, 401–409 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Seidu, S. et al. Therapeutic inertia amongst general practitioners with interest in diabetes. Prim. Care Diabetes 12, 87–91 (2018).

    Article  PubMed  Google Scholar 

  18. Khunti, K. & Davies, M. J. Clinical inertia – time to reappraise the terminology? Prim. Care Diabetes 11, 105–106 (2017).

    Article  PubMed  Google Scholar 

  19. Doyle-Delgado, K., Chamberlain, J. J., Shubrook, J. H., Skolnik, N. & Trujillo, J. Pharmacologic approaches to glycemic treatment of type 2 diabetes: synopsis of the 2020 American Diabetes Association’s Standards of Medical Care in Diabetes Clinical Guideline. Ann. Intern. Med. 173, 813–821 (2020).

    Article  PubMed  Google Scholar 

  20. National Institute for Health and Care Excellence (NICE). Type 2 diabetes in adults: management. NICE guideline [NG28]. nice.org.uk www.nice.org.uk/guidance/ng28/resources/type-2-diabetes-in-adults-management-pdf-1837338615493 (2022).

  21. Khunti, K. et al. Therapeutic inertia in the treatment of hyperglycaemia in patients with type 2 diabetes: a systematic review. Diabetes Obes. Metab. 20, 427–437 (2018).

    Article  PubMed  Google Scholar 

  22. Kaewbut, P. et al. Time to treatment intensification to reduce diabetes-related complications: a post hoc study. Healthcare 10, 1673 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Bain, S. C., Hansen, B. B., Hunt, B., Chubb, B. & Valentine, W. J. Evaluating the burden of poor glycemic control associated with therapeutic inertia in patients with type 2 diabetes in the UK. J. Med. Econ. 23, 98–105 (2019).

    Article  PubMed  Google Scholar 

  24. Tsotra, F. et al. The societal impact of early intensified treatment in patients with type 2 diabetes mellitus. J. Comp. Eff. Res. 11, 1185–1199 (2022).

    Article  CAS  PubMed  Google Scholar 

  25. Ward, J. E. F., Stetson, B. A. & Mokshagundam, S. P. L. Patient perspectives on self-monitoring of blood glucose: perceived recommendations, behaviors and barriers in a clinic sample of adults with type 2 diabetes. J. Diabetes Metab. Disord. 14, 43 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Polonsky, W. H., Fisher, L., Hessler, D. & Edelman, S. V. What is so tough about self‐monitoring of blood glucose? Perceived obstacles among patients with type 2 diabetes. Diabet. Med. 31, 40–46 (2014).

    Article  CAS  PubMed  Google Scholar 

  27. Monnier, L., Colette, C., Dunseath, G. J. & Owens, D. R. The loss of postprandial glycemic control precedes stepwise deterioration of fasting with worsening diabetes. Diabetes Care 30, 263–269 (2007).

    Article  PubMed  Google Scholar 

  28. Monnier, L., Colette, C., Dejager, S. & Owens, D. The dawn phenomenon in type 2 diabetes: how to assess it in clinical practice? Diabetes Metab. 41, 132–137 (2015).

    Article  CAS  PubMed  Google Scholar 

  29. Monnier, L., Colette, C. & Owens, D. R. Integrating glycaemic variability in the glycaemic disorders of type 2 diabetes: a move towards a unified glucose tetrad concept. Diabetes Metab. Res. Rev. 25, 393–402 (2009).

    Article  CAS  PubMed  Google Scholar 

  30. Monnier, L., Colette, C. & Owens, D. Three key indices in clinical practice to better comprehend the postprandial and basal glucose contributions in type 2 diabetes. Diabetes Technol. Ther. 24, 853–855 (2022).

    Article  PubMed  Google Scholar 

  31. Monnier, L., Colette, C., Dejager, S. & Owens, D. Magnitude of the dawn phenomenon and its impact on the overall glucose exposure in type 2 diabetes. Diabetes Care 36, 4057–4062 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Monnier, L., Colette, C. & Owens, D. Postprandial and basal glucose in type 2 diabetes: assessment and respective impacts. Diabetes Technol. Ther. 13, S25–S32 (2011).

    Article  PubMed  Google Scholar 

  33. Monnier, L., Colette, C., Dejager, S. & Owens, D. Residual dysglycemia when at target HbA1c of 7% (53 mmol/mol) in persons with type 2 diabetes. Diabetes Res. Clin. Pr. 104, 370–375 (2014).

    Article  CAS  Google Scholar 

  34. Monnier, L., Lapinski, H. & Colette, C. Contriutions of fasting and postprandial plasma glucose increments to the overall diurnal hyperglycemia of type 2 diabetic patients. Diabetes Care 26, 881–885 (2003).

    Article  PubMed  Google Scholar 

  35. Riddle, M., Umpierrez, G., DiGenio, A., Zhou, R. & Rosenstock, J. Contributions of basal and postprandial hyperglycemia over a wide range of A1C levels before and after treatment intensification in type 2 diabetes. Diabetes Care 34, 2508–2514 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Riddle, M. C. The treat-to-target trial and related studies. Endocr. Pract. 12, 71–79 (2006).

    Article  PubMed  Google Scholar 

  37. Monnier, L., Wojtusciszyn, A., Colette, C. & Owens, D. The contribution of glucose variability to asymptomatic hypoglycemia in persons with type 2 diabetes. Diabetes Technol. Ther. 13, 813–818 (2011).

    Article  CAS  PubMed  Google Scholar 

  38. Uemura, F., Okada, Y., Torimoto, K. & Tanaka, Y. Relation between hypoglycemia and glycemic variability in type 2 diabetes patients with insulin therapy: a study based on continuous glucose monitoring. Diabetes Technol. Ther. 20, 140–146 (2018).

    Article  CAS  PubMed  Google Scholar 

  39. Uemura, F. et al. Risk factor analysis for type 2 diabetes patients about hypoglycemia using continuous glucose monitoring: results from a prospective observational study. Diabetes Technol. Ther. 24, 435–445 (2022).

    Article  CAS  PubMed  Google Scholar 

  40. Battelino, T. et al. Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range. Diabetes Care 42, 1593–1603 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Monnier, L., Colette, C. & Owens, D. Below which threshold of glycemic variability is there a minimal risk of hypoglycemia in people with type 2 diabetes? Diabetes Technol. Ther. 24, 453–454 (2022).

    Article  PubMed  Google Scholar 

  42. Tang, X. et al. Glycemic variability evaluated by continuous glucose monitoring system is associated with the 10-y cardiovascular risk of diabetic patients with well-controlled HbA1c. Clin. Chim. Acta 461, 146–150 (2016).

    Article  CAS  PubMed  Google Scholar 

  43. Su, G. et al. Impact of admission glycemic variability, glucose, and glycosylated hemoglobin on major adverse cardiac events after acute myocardial infarction. Diabetes Care 36, 1026–1032 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Gerbaud, E. et al. Glycemic variability is a powerful independent predictive factor of midterm major adverse cardiac events in patients with diabetes with acute coronary syndrome. Diabetes Care 42, 674–681 (2019).

    Article  PubMed  Google Scholar 

  45. Nusca, A. et al. Glycemic variability assessed by continuous glucose monitoring and short-term outcome in diabetic patients undergoing percutaneous coronary intervention: an observational pilot study. J. Diabetes Res. 2015, 250201 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Lu, J. et al. Glycemic variability assessed by continuous glucose monitoring and the risk of diabetic retinopathy in latent autoimmune diabetes of the adult and type 2 diabetes. J. Diabetes Invest. 10, 753–759 (2019).

    Article  CAS  Google Scholar 

  47. Xu, F. et al. The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c. Diabetol. Metab. Syndr. 6, 139 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Pan, J. et al. Association of glycemic variability assessed by continuous glucose monitoring with subclinical diabetic polyneuropathy in type 2 diabetes patients. J. Diabetes Invest. 13, 328–335 (2021).

    Article  Google Scholar 

  49. Hu, Y. et al. Association of glycaemic variability evaluated by continuous glucose monitoring with diabetic peripheral neuropathy in type 2 diabetic patients. Endocrine 60, 292–300 (2018).

    Article  CAS  PubMed  Google Scholar 

  50. Gad, H. et al. Cardiovascular autonomic neuropathy is associated with increased glycemic variability driven by hyperglycemia rather than hypoglycemia in patients with diabetes. Diabetes Res. Clin. Pract. 200, 110670 (2023).

    Article  CAS  PubMed  Google Scholar 

  51. Choudhary, P. et al. The challenge of sustainable access to telemonitoring tools for people with diabetes in Europe: lessons from COVID-19 and beyond. Diabetes Ther. 12, 2311–2327 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Danne, T. et al. Telemonitoring, telemedicine and time in range during the pandemic: paradigm change for diabetes risk management in the post-COVID future. Diabetes Ther. 12, 2289–2310 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Edelman, S. V., Argento, N. B., Pettus, J. & Hirsch, I. B. Clinical implications of real-time and intermittently scanned continuous glucose monitoring. Diabetes Care 41, 2265–2274 (2018).

    Article  CAS  PubMed  Google Scholar 

  54. Beck, R. W. et al. Continuous glucose monitoring versus usual care in patients with type 2 diabetes receiving multiple daily insulin injections. Ann. Intern. Med. 167, 365–374 (2017).

    Article  PubMed  Google Scholar 

  55. Yaron, M. et al. Effect of flash glucose monitoring technology on glycemic control and treatment satisfaction in patients with type 2 diabetes. Diabetes Care 43, 1178–1184 (2019).

    Article  Google Scholar 

  56. Kröger, J., Fasching, P. & Hanaire, H. Three European retrospective real-world chart review studies to determine the effectiveness of flash glucose monitoring on HbA1c in adults with type 2 diabetes. Diabetes Ther. 11, 279–291 (2020).

    Article  PubMed  Google Scholar 

  57. Haak, T. et al. Flash glucose-sensing technology as a replacement for blood glucose monitoring for the management of insulin-treated type 2 diabetes: a multicenter, open-label randomized controlled trial. Diabetes Ther. 8, 55–73 (2017).

    Article  CAS  PubMed  Google Scholar 

  58. Martens, T. et al. Effect of continuous glucose monitoring on glycemic control in patients with type 2 diabetes treated with basal insulin. JAMA 325, 2262–2272 (2021).

    Article  CAS  PubMed  Google Scholar 

  59. Carlson, A. L. et al. Flash glucose monitoring in type 2 diabetes managed with basal insulin in the USA: a retrospective real-world chart review study and meta-analysis. BMJ Open Diabetes Res. Care 10, e002590 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Elliott, T. et al. The impact of flash glucose monitoring on glycated hemoglobin in type 2 diabetes managed with basal insulin in Canada: a retrospective real-world chart review study. Diabetes Vasc. Dis. Res. 18, 14791641211021374 (2021).

    Article  CAS  Google Scholar 

  61. Wright, E. E., Kerr, M. S. D., Reyes, I. J., Nabutovsky, Y. & Miller, E. Use of flash continuous glucose monitoring is associated with A1C reduction in people with type 2 diabetes treated with basal insulin or noninsulin therapy. Diabetes Spectr. 34, 184–189 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Wada, E. et al. Flash glucose monitoring helps achieve better glycemic control than conventional self-monitoring of blood glucose in non-insulin-treated type 2 diabetes: a randomized controlled trial. BMJ Open. Diabetes Res. Care 8, e001115 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Cox, D. J. et al. Minimizing glucose excursions (GEM) with continuous glucose monitoring in type 2 diabetes: a randomized clinical trial. J. Endocr. Soc. 4, bvaa118 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Aleppo, G. et al. The effect of discontinuing continuous glucose monitoring in adults with type 2 diabetes treated with basal insulin. Diabetes Care 44, 2729–2737 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Guerci, B. et al. Important decrease in hospitalizations for acute diabetes events following FreeStyle Libre® system initiation in people with type 2 diabetes on basal insulin therapy in France. Diabetes Technol. Ther. 25, 20–30 (2023).

    Article  CAS  PubMed  Google Scholar 

  66. Miller, E., Kerr, M. S. D., Roberts, G. J., Nabutovsky, Y. & Wright, E. Flash CGM associated with event reduction in nonintensive diabetes therapy. Am. J. Manag. Care 27, e372–e377 (2021).

    Article  PubMed  Google Scholar 

  67. Harris, S. & Levrat-Guillen, F. Use of the FreeStyle Libre® system in diabetes treatment for people with T2D: results from a retrospective cohort study using Canadian Private Payer Claims Database. Diabetes Obes. Metab. 25, 1704–1713 (2023).

    Article  PubMed  Google Scholar 

  68. Reach, G., Pechtner, V., Gentilella, R., Corcos, A. & Ceriello, A. Clinical inertia and its impact on treatment intensification in people with type 2 diabetes mellitus. Diabetes Metab. 43, 501–511 (2017).

    Article  CAS  PubMed  Google Scholar 

  69. Giugliano, D., Maiorino, M. I., Bellastella, G. & Esposito, K. Clinical inertia, reverse clinical inertia, and medication non-adherence in type 2 diabetes. J. Endocrinol. Invest. 42, 495–503 (2019).

    Article  CAS  PubMed  Google Scholar 

  70. Russell‐Jones, D., Pouwer, F. & Khunti, K. Identification of barriers to insulin therapy and approaches to overcoming them. Diabetes Obes. Metab. 20, 488–496 (2018).

    Article  PubMed  Google Scholar 

  71. Polonsky, W. H., Fisher, L., Guzman, S., Villa-Caballero, L. & Edelman, S. V. Psychological insulin resistance in patients with type 2 diabetes. Diabetes Care 28, 2543–2545 (2005).

    Article  PubMed  Google Scholar 

  72. Peyrot, M., Barnett, A. H., Meneghini, L. F. & Schumm‐Draeger, P. ‐M. Insulin adherence behaviours and barriers in the multinational global attitudes of patients and physicians in insulin therapy study. Diabet. Med. 29, 682–689 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. The ACCORD Study Group Long-term effects of intensive glucose lowering on cardiovascular outcomes. N. Engl. J. Med. 364, 818–828 (2011).

    Article  PubMed Central  Google Scholar 

  74. Zoungas, S. et al. Severe hypoglycemia and risks of vascular events and death. N. Engl. J. Med. 363, 1410–1418 (2010).

    Article  CAS  PubMed  Google Scholar 

  75. Pearson, S. M. et al. Reduction in cardiovascular mortality following severe hypoglycemia in individuals with type 2 diabetes: the role of a pragmatic and structured intervention. Cardiovasc. Diabetol. 20, 18 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  76. Langendam, M. et al. Continuous glucose monitoring systems for type 1 diabetes mellitus. Cochrane Database Syst. Rev. 2012, CD008101 (2012).

    PubMed Central  Google Scholar 

  77. Diabetes Research in Children Network (DirecNet) Study Group. Youth and parent satisfaction with clinical use of the GlucoWatch G2 biographer in the management of pediatric type 1 diabetes. Diabetes Care 28, 1929–1935 (2005).

    Article  Google Scholar 

  78. Lind, M. et al. Continuous glucose monitoring vs conventional therapy for glycemic control in adults with type 1 diabetes treated with multiple daily insulin injections: the GOLD randomized clinical trial. JAMA 317, 379–387 (2017).

    Article  CAS  PubMed  Google Scholar 

  79. Polonsky, W. H., Soriano, E. C. & Fortmann, A. L. The role of retrospective data review in the personal use of real-time continuous glucose monitoring: perceived impact on quality of life and health outcomes. Diabetes Technol. Ther. 24, 492–501 (2022).

    Article  PubMed  Google Scholar 

  80. Gilbert, T. R., Noar, A., Blalock, O. & Polonsky, W. H. Change in hemoglobin A1c and quality of life with real-time continuous glucose monitoring use by people with insulin-treated diabetes in the Landmark study. Diabetes Technol. Ther. 23, S35–S39 (2021).

    Article  PubMed  Google Scholar 

  81. Chesser, H., Srinivasan, S., Puckett, C., Gitelman, S. E. & Wong, J. C. Real-time continuous glucose monitoring in adolescents and young adults with type 2 diabetes can improve quality of life. J. Diabetes Sci. Technol. 23, 193229682211398 (2022).

    Article  Google Scholar 

  82. Volčanšek, Š., Lunder, M. & Janež, A. Acceptability of continuous glucose monitoring in elderly diabetes patients using multiple daily insulin injections. Diabetes Technol. Ther. 21, 566–574 (2019).

    Article  PubMed  Google Scholar 

  83. Polonsky, W. H., Peters, A. L. & Hessler, D. The impact of real-time continuous glucose monitoring in patients 65 years and older. J. Diabetes Sci. Technol. 10, 892–897 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Nathan, D. M. et al. Diabetes control and complications trial/epidemiology of diabetes interventions and complications study at 30 years: advances and contributions. Diabetes 62, 3976–3986 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Lu, J. et al. Association of time in range, as assessed by continuous glucose monitoring, with diabetic retinopathy in type 2 diabetes. Diabetes Care 41, 2370–2376 (2018).

    Article  CAS  PubMed  Google Scholar 

  86. Yang, J. et al. Association of time in range, as assessed by continuous glucose monitoring, with painful diabetic polyneuropathy. J. Diabetes Invest. 12, 828–836 (2021).

    Article  CAS  Google Scholar 

  87. Li, F. et al. TIR generated by continuous glucose monitoring is associated with peripheral nerve function in type 2 diabetes. Diabetes Res. Clin. Pract. 166, 108289 (2020).

    Article  CAS  PubMed  Google Scholar 

  88. van der Heide, F. C. T. et al. (Pre)diabetes, glycemia, and daily glucose variability are associated with retinal nerve fiber layer thickness in the Maastricht study. Sci. Rep. 12, 17750 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  89. Gad, H. et al. Continuous glucose monitoring reveals a novel association between duration and severity of hypoglycemia, and small nerve fiber injury in patients with diabetes. Endocr. Connect. 11, e220352 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Lu, J. et al. Time in range is associated with carotid intima-media thickness in type 2 diabetes. Diabetes Technol. Ther. 22, 72–78 (2020).

    Article  CAS  PubMed  Google Scholar 

  91. Zhou, H. et al. Time in range, assessed with continuous glucose monitoring, is associated with brachial-ankle pulse wave velocity in type 2 diabetes: a retrospective single-center analysis. Front. Endocrinol. 13, 1014568 (2022).

    Article  Google Scholar 

  92. Lu, J. et al. Time in range in relation to all-cause and cardiovascular mortality in patients with type 2 diabetes: a prospective cohort study. Diabetes Care 44, 549–555 (2021).

    Article  CAS  PubMed  Google Scholar 

  93. Li, J. et al. Association of time in range levels with lower extremity arterial disease in patients with type 2 diabetes. Diabetes Metab. Syndr. Clin. Res. Rev. 14, 2081–2085 (2020).

    Article  Google Scholar 

  94. Xie, P. et al. Time in range in relation to amputation and all‐cause mortality in hospitalised patients with diabetic foot ulcers. Diabetes Metab. Res. Rev. 38, e3498 (2022).

    Article  PubMed  Google Scholar 

  95. Mayeda, L. et al. Glucose time in range and peripheral neuropathy in type 2 diabetes mellitus and chronic kidney disease. BMJ Open Diabetes Res. Care 8, e000991 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  96. Guo, Q.-Y. et al. Continuous glucose monitoring defined time-in-range is associated with sudomotor dysfunction in type 2 diabetes. World J. Diabetes 11, 489–500 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  97. Kim, M. Y. et al. The association between continuous glucose monitoring-derived metrics and cardiovascular autonomic neuropathy in outpatients with type 2 diabetes. Diabetes Technol. Ther. 23, 434–442 (2021).

    Article  CAS  PubMed  Google Scholar 

  98. Guo, Q. et al. Time in range, as a novel metric of glycemic control, is reversely associated with presence of diabetic cardiovascular autonomic neuropathy independent of HbA1c in Chinese type 2 diabetes. J. Diabetes Res. 2020, 5817074 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  99. Yoo, J. H. et al. Association between continuous glucose monitoring-derived time in range, other core metrics, and albuminuria in type 2 diabetes. Diabetes Technol. Ther. 22, 768–776 (2020).

    Article  CAS  PubMed  Google Scholar 

  100. Tao, R. et al. A deep learning nomogram of continuous glucose monitoring data for the risk prediction of diabetic retinopathy in type 2 diabetes. Phys. Eng. Sci. Med. 46, 813–825 (2023).

    Article  PubMed  Google Scholar 

  101. Ahlqvist, E. et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 6, 361–369 (2018).

    Article  PubMed  Google Scholar 

  102. Hall, H. et al. Glucotypes reveal new patterns of glucose dysregulation. PLoS Biol. 16, e2005143 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  103. Schön, M. et al. Analysis of type 2 diabetes heterogeneity with a tree-like representation: insights from the prospective German Diabetes Study and the LURIC cohort. Lancet Diabetes Endocrinol. 12, 119–131 (2023).

    Article  PubMed  Google Scholar 

  104. Nair, A. T. N. et al. Heterogeneity in phenotype, disease progression and drug response in type 2 diabetes. Nat. Med. 28, 982–988 (2022).

    Article  CAS  PubMed  Google Scholar 

  105. Hirst, J. A., Farmer, A. J., Dyar, A., Lung, T. W. C. & Stevens, R. J. Estimating the effect of sulfonylurea on HbA1c in diabetes: a systematic review and meta-analysis. Diabetologia 56, 973–984 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Palmer, S. C. et al. Comparison of clinical outcomes and adverse events associated with glucose-lowering drugs in patients with type 2 diabetes: a meta-analysis. JAMA 316, 313–324 (2016).

    Article  CAS  PubMed  Google Scholar 

  107. Uemura, F., Okada, Y., Torimoto, K. & Tanaka, Y. Enlarged glycemic variability in sulfonylurea-treated well-controlled type 2 diabetics identified using continuous glucose monitoring. Sci. Rep. 11, 4875 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Buse, J. B. et al. 2019 update to: management of hyperglycaemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 63, 221–228 (2020).

    Article  PubMed  Google Scholar 

  109. Grace, T. & Salyer, J. Use of real-time continuous glucose monitoring improves glycemic control and other clinical outcomes in type 2 diabetes patients treated with less intensive therapy. Diabetes Technol. Ther. 24, 26–31 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Aronson, R. et al. Impact of flash glucose monitoring in people with type 2 diabetes inadequately controlled with non‐insulin antihyperglycaemic therapy (IMMEDIATE): a randomized controlled trial. Diabetes Obes. Metab. 25, 1024–1031 (2023).

    Article  CAS  PubMed  Google Scholar 

  111. Echouffo-Tcheugui, J. B. et al. Visit-to-visit glycemic variability and risks of cardiovascular events and all-cause mortality: the ALLHAT study. Diabetes Care 42, dc181430 (2019).

    Article  Google Scholar 

  112. Nyiraty, S. et al. Cardiovascular autonomic neuropathy and glucose variability in patients with type 1 diabetes: is there an association? Front. Endocrinol. 9, 174 (2018).

    Article  Google Scholar 

  113. Wakasugi, S. et al. Associations between continuous glucose monitoring-derived metrics and diabetic retinopathy and albuminuria in patients with type 2 diabetes. BMJ Open Diabetes Res. Care 9, e001923 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  114. Farhan, H. A., Bukhari, K., Grewal, N., Devarasetty, S. & Munir, K. Use of continuous glucose monitor as a motivational device for lifestyle modifications to improve glycaemic control in patients with type 2 diabetes treated with non-insulin therapies. BMJ Case Rep. 15, e248579 (2022).

    Article  PubMed  Google Scholar 

  115. Schubert-Olesen, O., Kröger, J., Siegmund, T., Thurm, U. & Halle, M. Continuous glucose monitoring and physical activity. Int. J. Environ. Res. Public Health 19, 12296 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Ziegler, R. et al. Intermittent use of continuous glucose monitoring: expanding the clinical value of CGM. J. Diabetes Sci. Technol. 15, 684–694 (2021).

    Article  PubMed  Google Scholar 

  117. American Diabetes Association Professional Practice Committee. 7. Diabetes technology: standards of medical care in diabetes—2022. Diabetes Care 45, S97–S112 (2021).

    Article  Google Scholar 

  118. Taylor, P. J., Thompson, C. H. & Brinkworth, G. D. Effectiveness and acceptability of continuous glucose monitoring for type 2 diabetes management: a narrative review. J. Diabetes Invest. 9, 713–725 (2018).

    Article  Google Scholar 

  119. Moon, S. J. et al. Efficacy of intermittent short‐term use of a real‐time continuous glucose monitoring system in non‐insulin-treated patients with type 2 diabetes: a randomized controlled trial. Diabetes Obes. Metab. 25, 110–120 (2022).

    Article  PubMed  Google Scholar 

  120. Price, D. A., Deng, Q., Kipnes, M. & Beck, S. E. Episodic real-time CGM use in adults with type 2 diabetes: results of a pilot randomized controlled trial. Diabetes Ther. 12, 2089–2099 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Vigersky, R. A., Fonda, S. J., Chellappa, M., Walker, M. S. & Ehrhardt, N. M. Short- and long-term effects of real-time continuous glucose monitoring in patients with type 2 diabetes. Diabetes Care 35, 32–38 (2012).

    Article  CAS  PubMed  Google Scholar 

  122. Monnier, L., Colette, C., Bonnet, F., Renard, E. & Owens, D. HbA1c variability and diabetes complications: assessment and implications. Diabetes Metab. 49, 101399 (2023).

    Article  CAS  Google Scholar 

  123. Klupa, T. et al. Expanding the role of continuous glucose monitoring in modern diabetes care beyond type 1 disease. Diabetes Ther. 14, 1241–1266 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Allen, N. A., Fain, J. A., Braun, B. & Chipkin, S. R. Continuous glucose monitoring counseling improves physical activity behaviors of individuals with type 2 diabetes: a randomized clinical trial. Diabetes Res. Clin. Pract. 80, 371–379 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  125. Gehlaut, R. R., Dogbey, G. Y., Schwartz, F. L., Marling, C. R. & Shubrook, J. H. Hypoglycemia in type 2 diabetes – more common than you think. J. Diabetes Sci. Technol. 9, 999–1005 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Eckel, R. H. et al. Obesity and type 2 diabetes: what can be unified and what needs to be individualized? Diabetes Care 34, 1424–1430 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  127. Heise, T. et al. Tirzepatide reduces appetite, energy intake, and fat mass in people with type 2 diabetes. Diabetes Care 46, 998–1004 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Wharton, S. et al. Two‐year effect of semaglutide 2.4 mg on control of eating in adults with overweight/obesity: STEP 5. Obesity 31, 703–715 (2023).

    Article  CAS  PubMed  Google Scholar 

  129. Bouillet, B. et al. Frequent and severe hypoglycaemia detected with continuous glucose monitoring in older institutionalised patients with diabetes. Age Ageing 50, 2088–2093 (2021).

    Article  PubMed  Google Scholar 

  130. Roussel, R. et al. Persistence with basal insulin and frequency of hypoglycemia requiring hospitalization in patients with type 2 diabetes. Diabetes Ther. 11, 1861–1872 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Idris, I. et al. Associated factors that influenced persistence with basal analog insulin therapy among people with type 2 diabetes: an exploratory analysis from a UK real-world sample. Prim. Care Diabetes 13, 106–112 (2019).

    Article  PubMed  Google Scholar 

  132. Fonda, S. J. et al. The cost-effectiveness of real-time continuous glucose monitoring (RT-CGM) in type 2 diabetes. J. Diabetes Sci. Technol. 10, 898–904 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  133. Roussel, R. et al. Important drop in the rate of acute diabetes complications in people with type 1 or type 2 diabetes after initiation of flash glucose monitoring in France: the RELIEF study. Diabetes Care 44, 1368–1376 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Bergenstal, R. M. et al. Flash CGM is associated with reduced diabetes events and hospitalizations in insulin-treated type 2 diabetes. J. Endocr. Soc. 5, bvab013 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  135. Riveline, J.-P. et al. Reduced rate of acute diabetes events with flash glucose monitoring is sustained for two-years after initiation: extended outcomes from the RELIEF study. Diabetes Technol. Ther. 24, 611–618 (2022).

    Article  CAS  PubMed  Google Scholar 

  136. Commission Nationale d’Evaluation des Dispositifs Medicaux et des Technologies de Sante. FreeStyle Libre 2, Système flash d’autosurveillance du glucose [French]. Haute Autorité de Santé www.has-sante.fr/jcms/p_3219919/fr/freestyle-libre-2-avis-de-la-cnedimts-du-20/10/2020 (2020).

  137. Jendle, J. et al. Cost-effectiveness of the FreeStyle Libre® system versus blood glucose self-monitoring in individuals with type 2 diabetes on insulin treatment in Sweden. Diabetes Ther. 12, 3137–3152 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Ajjan, R., Bilir, S. P., Hellmund, R. & Souto, D. Cost-effectiveness analysis of flash glucose monitoring system for people with type 2 diabetes receiving intensive insulin treatment. Diabetes Ther. 13, 1933–1945 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  139. Cho, N. H. et al. IDF diabetes atlas: global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res. Clin. Pract. 138, 271–281 (2018).

    Article  CAS  PubMed  Google Scholar 

  140. Bao, S., Bailey, R., Calhoun, P. & Beck, R. W. Effectiveness of continuous glucose monitoring in older adults with type 2 diabetes treated with basal insulin. Diabetes Technol. Ther. 24, 299–306 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Guerci, B. et al. Reduced acute diabetes events after FreeStyle Libre® system initiation in people 65 years or older with type 2 diabetes on intensive insulin therapy in France. Diabetes Technol. Ther. 25, 384–394 (2023).

    Article  CAS  PubMed  Google Scholar 

  142. Munshi, M. N. et al. Frequent hypoglycemia among elderly patients with poor glycemic control. Arch. Intern. Med. 171, 362–364 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  143. Lipska, K. J. et al. HbA1c and risk of severe hypoglycemia in type 2 diabetes. Diabetes Care 36, 3535–3542 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Meneilly, G. S. & Tessier, D. Diabetes in the elderly. Diabet. Med. 12, 949–960 (1995).

    Article  CAS  PubMed  Google Scholar 

  145. Meneilly, G. S. & Tessier, D. Diabetes in elderly adults. J. Gerontol. Ser. 56, M5–M13 (2001).

    Article  CAS  Google Scholar 

  146. Schütt, M. et al. Multiple complications and frequent severe hypoglycaemia in ‘elderly’ and ‘old’ patients with type 1 diabetes. Diabet. Med. 29, e176–e179 (2012).

    Article  PubMed  Google Scholar 

  147. Wallander, M., Axelsson, K. F., Nilsson, A. G., Lundh, D. & Lorentzon, M. Type 2 diabetes and risk of hip fractures and non‐skeletal fall injuries in the elderly: a study from the Fractures and Fall Injuries in the Elderly cohort (FRAILCO). J. Bone Miner. Res. 32, 449–460 (2017).

    Article  CAS  PubMed  Google Scholar 

  148. Mattishent, K. et al. The effects of hypoglycaemia and dementia on cardiovascular events, falls and fractures and all‐cause mortality in older individuals: a retrospective cohort study. Diabetes Obes. Metab. 21, 2076–2085 (2019).

    Article  PubMed  Google Scholar 

  149. Mattishent, K. & Loke, Y. K. Is avoidance of hypoglycaemia a better target than HbA1C in older people with diabetes? Br. J. Clin. Pharmacol. 87, 9–11 (2021).

    Article  PubMed  Google Scholar 

  150. Kosjerina, V. et al. Discontinuation of diabetes medication in the 10 years before death in Denmark: a register-based study. Lancet Health Longev. 2, e561–e570 (2021).

    Article  Google Scholar 

  151. Selvin, E. et al. Glucose patterns in very old adults: a pilot study in a community-based population. Diabetes Technol. Ther. 23, 737–744 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  152. Romano, S., Figueira, D., Teixeira, I. & Perelman, J. Deprescribing interventions among community-dwelling older adults: a systematic review of economic evaluations. Pharmacoeconomics 40, 269–295 (2022).

    Article  PubMed  Google Scholar 

  153. Nordyke, R. J., Appelbaum, K. & Berman, M. A. Estimating the impact of novel digital therapeutics in type 2 diabetes and hypertension: health economic analysis. J. Med. Internet Res. 21, e15814 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  154. Dabelea, D. et al. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA 311, 1778–1786 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Manfredo, J. et al. Short-term use of CGM in youth onset type 2 diabetes is associated with behavioral modifications. Front. Endocrinol. 14, 1182260 (2023).

    Article  Google Scholar 

  156. Chang, N., Barber, R. O. L. B., Alula, J. L., Durazo-Arvizu, R. & Chao, L. C. Continuous glucose monitoring versus standard of care in adolescents with type 2 diabetes: a pilot randomized cross-over trial. J. Diabetes Sci. Technol. 17, 1419–1420 (2023).

    Article  PubMed  Google Scholar 

  157. Seidu, S. et al. 2022 update to the position statement by Primary Care Diabetes Europe: a disease state approach to the pharmacological management of type 2 diabetes in primary care. Prim. Care Diabetes 16, 223–244 (2022).

    Article  CAS  PubMed  Google Scholar 

  158. Seidu, S. et al. A disease state approach to the pharmacological management of type 2 diabetes in primary care: a position statement by Primary Care Diabetes Europe. Prim. Care Diabetes 15, 31–51 (2020).

    Article  PubMed  Google Scholar 

  159. Battelino, T. et al. Continuous glucose monitoring and metrics for clinical trials: an international consensus statement. Lancet Diabetes Endocrinol. 11, 42–57 (2022).

    Article  PubMed  Google Scholar 

  160. Manickam, P. et al. Artificial intelligence (AI) and internet of medical things (IoMT) assisted biomedical systems for intelligent healthcare. Biosensors 12, 562 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  161. Assaf, S. A., Zelko, R. & Hanko, B. The effect of interventions led by community pharmacists in primary care for adults with type 2 diabetes mellitus on therapeutic adherence and HbA1c levels: a systematic review. Int. J. Environ. Res. Public Health 19, 6188 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  162. Coutureau, C., Slimano, F., Mongaret, C. & Kanagaratnam, L. Impact of pharmacists-led interventions in primary care for adults with type 2 diabetes on HbA1c levels: a systematic review and meta-analysis. Int. J. Environ. Res. Public Health 19, 3156 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Majjouti, K. et al. Family doctors’ attitudes toward peer support programs for type 2 diabetes and/or coronary artery disease: an exploratory survey among German practitioners. BMC Prim. Care 23, 220 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Bommer, C. et al. Global economic burden of diabetes in adults: projections from 2015 to 2030. Diabetes Care 41, 963–970 (2018).

    Article  PubMed  Google Scholar 

  165. Parker, E. D. et al. Economic costs of diabetes in the U.S. in 2022. Diabetes Care 47, 26–43 (2023).

    Article  Google Scholar 

  166. Hex, N., Bartlett, C., Wright, D., Taylor, M. & Varley, D. Estimating the current and future costs of type 1 and type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs. Diabet. Med. 29, 855–862 (2012).

    Article  CAS  PubMed  Google Scholar 

  167. Bansal, M. et al. Impact of reducing glycated hemoglobin on healthcare costs among a population with uncontrolled diabetes. Appl. Health Econ. Health Policy 16, 675–684 (2018).

    Article  PubMed  Google Scholar 

  168. Meng, J. et al. Effect of diabetes treatment-related attributes on costs to type 2 diabetes patients in a real-world population. J. Manag. Care Spéc. Pharm. 23, 446–452 (2017).

    PubMed  Google Scholar 

  169. Stedman, M. et al. Cost of hospital treatment of type 1 diabetes (T1DM) and type 2 diabetes (T2DM) compared to the non-diabetes population: a detailed economic evaluation. BMJ Open 10, e033231 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  170. Bilir, S. P. et al. The cost-effectiveness of a flash glucose monitoring system for management of patients with type 2 diabetes receiving intensive insulin treatment in Sweden. Eur. Endocrinol. 14, 80 (2018).

    PubMed  PubMed Central  Google Scholar 

  171. Bahia, L. et al. Cost-effectiveness of continuous glucose monitoring with FreeStyle Libre® in Brazilian insulin-treated patients with types 1 and 2 diabetes mellitus. Diabetol. Metab. Syndr. 15, 242 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Isitt, J. J. et al. Cost-effectiveness of a real-time continuous glucose monitoring system versus self-monitoring of blood glucose in people with type 2 diabetes on insulin therapy in the UK. Diabetes Ther. 13, 1875–1890 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Alshannaq, H. et al. Cost-utility of real-time continuous glucose monitoring versus self-monitoring of blood glucose in people with insulin-treated Type 2 diabetes in Canada. J. Comp. Eff. Res. 12, e230075 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  174. Alshannaq, H. et al. Cost-utility of real-time continuous glucose monitoring versus self-monitoring of blood glucose in people with insulin-treated type II diabetes in France. J. Comp. Eff. Res. 13, e230174 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  175. Sierra, J. A. et al. Clinical and economic benefits of professional CGM among people with type 2 diabetes in the United States: analysis of claims and lab data. J. Med. Econ. 21, 225–230 (2018).

    Article  PubMed  Google Scholar 

  176. Isaacson, B. et al. Demonstrating the clinical impact of continuous glucose monitoring within an integrated healthcare delivery system. J. Diabetes Sci. Technol. 16, 383–389 (2022).

    Article  PubMed  Google Scholar 

  177. Harris, S. et al. Person-centered, outcomes-driven treatment: a new paradigm for type 2 diabetes in primary care (American Diabetes Association, 2020).

  178. Evans, M. et al. Defining the role of SGLT2 inhibitors in primary care: time to think differently. Diabetes Ther. 13, 889–911 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. Fernando, K., Bain, S. C., Holmes, P., Jones, P. N. & Patel, D. C. Glucagon-like peptide 1 receptor agonist usage in type 2 diabetes in primary care for the UK and beyond: a narrative review. Diabetes Ther. 12, 2267–2288 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. Giunti, G., Guisado-Fernandez, E., Belani, H. & Lacalle-Remigio, J. R. Mapping the access of future doctors to health information technologies training in the European Union: cross-sectional descriptive study. J. Med. Internet Res. 21, e14086 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  181. Lupiáñez-Villanueva, F., Folkvord, F. & Fauli, C. Benchmarking deployment of eHealth among general practitioners. European Commission ec.europa.eu/newsroom/dae/document.cfm?doc_id=60210 (2018).

  182. Silva-Tinoco, R. & Torre-Saldaña, Vdela The imperious need for telemedicine for the care of diabetes during the COVID-19 pandemic. A comprehensive approach study. Gac. Med. Mex. 157, 309–312 (2021).

    PubMed  Google Scholar 

  183. Pogorzelska, K., Marcinowicz, L. & Chlabicz, S. A qualitative study of primary care physicians’ experiences with telemedicine during the COVID-19 pandemic in North-Eastern Poland. Int. J. Environ. Res. Public Health 20, 1963 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  184. Poitras, M.-E. et al. Chronic conditions patient’s perception of post-COVID-19 pandemic teleconsulting continuation in primary care clinics: a qualitative descriptive study. BMJ Open. 12, e066871 (2022).

    Article  PubMed  Google Scholar 

  185. Rubio-Valera, M. et al. Barriers and facilitators for the implementation of primary prevention and health promotion activities in primary care: a synthesis through meta-ethnography. PLoS ONE 9, e89554 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  186. Mackert, M., Mabry-Flynn, A., Champlin, S., Donovan, E. E. & Pounders, K. Health literacy and health information technology adoption: the potential for a new digital divide. J. Med. Internet Res. 18, e264 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  187. Dunn, P. & Hazzard, E. Technology approaches to digital health literacy. Int. J. Cardiol. 293, 294–296 (2019).

    Article  PubMed  Google Scholar 

  188. Polonsky, W. H. et al. Impact of participation in a virtual diabetes clinic on diabetes-related distress in individuals with type 2 diabetes. Clin. Diabetes 38, 357–362 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  189. Lee, J. Y. et al. Using telemedicine to support care for people with type 2 diabetes mellitus: a qualitative analysis of patients’ perspectives. BMJ Open. 9, e026575 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  190. Buysse, H., Coremans, P., Pouwer, F. & Ruige, J. Sustainable improvement of HbA1c and satisfaction with diabetes care after adding telemedicine in patients on adaptable insulin regimens: results of the TeleDiabetes randomized controlled trial. Health Inf. J. 26, 628–641 (2020).

    Article  Google Scholar 

  191. Rodríguez-Fortúnez, P. et al. Cross-sectional study about the use of telemedicine for type 2 diabetes mellitus management in Spain: patient’s perspective. The EnREDa2 Study. BMJ Open. 9, e028467 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  192. Torbjørnsen, A., Ribu, L., Rønnevig, M., Grøttland, A. & Helseth, S. Users’ acceptability of a mobile application for persons with type 2 diabetes: a qualitative study. BMC Health Serv. Res. 19, 641 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  193. Fernández-Rodríguez, R. et al. Are e-Health interventions effective in reducing diabetes-related distress and depression in patients with type 2 diabetes? A systematic review with meta-analysis. Telemed. e-Health https://doi.org/10.1089/tmj.2023.0374 (2023).

    Article  Google Scholar 

  194. Yoo, H. J. 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. 82, 73–79 (2008).

    Article  CAS  PubMed  Google Scholar 

  195. Karter, A. J., Parker, M. M., Moffet, H. H., Gilliam, L. K. & Dlott, R. Association of real-time continuous glucose monitoring with glycemic control and acute metabolic events among patients with insulin-treated diabetes. JAMA 325, 2273–2284 (2021).

    Article  CAS  PubMed  Google Scholar 

  196. Ajjan, R. A. et al. Multicenter randomized trial of intermittently scanned continuous glucose monitoring versus self-monitoring of blood glucose in individuals with type 2 diabetes and recent-onset acute myocardial infarction: results of the LIBERATES trial. Diabetes Care 46, 441–449 (2023).

    Article  CAS  PubMed  Google Scholar 

  197. The Diabetes Control and Complications Trial Research Group. 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. 329, 977–986 (1993).

    Article  Google Scholar 

  198. Danne, T. et al. International consensus on use of continuous glucose monitoring. Diabetes Care 40, 1631–1640 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  199. Agiostratidou, G. et al. Standardizing clinically meaningful outcome measures beyond HbA1c for type 1 diabetes: a consensus report of the American Association of Clinical Endocrinologists, the American Association of Diabetes Educators, the American Diabetes Association, the Endocrine Society, JDRF International, The Leona M. and Harry B. Helmsley Charitable Trust, the Pediatric Endocrine Society, and the T1D Exchange. Diabetes Care 40, 1622–1630 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  200. Beck, R. W. et al. The relationships between time in range, hyperglycemia metrics, and HbA1c. J. Diabetes Sci. Technol. 13, 614–626 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  201. Phillip, M. et al. The digital/virtual diabetes clinic: the future is now – recommendations from an international panel on diabetes digital technologies introduction. Diabetes Technol. Ther. 23, 146–154 (2020).

    Article  PubMed  Google Scholar 

  202. Danne, T. & Limbert, C. COVID-19, type 1 diabetes, and technology: why paediatric patients are leading the way. Lancet Diabetes Endocrinol. 8, 465–467 (2020).

    Article  CAS  PubMed Central  Google Scholar 

  203. Majithia, A. R. et al. Glycemic outcomes in adults with type 2 diabetes participating in a continuous glucose monitor-driven virtual diabetes clinic: prospective trial. J. Med. Internet Res. 22, e21778 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  204. Bergenstal, R. M. et al. Remote application and use of real-time continuous glucose monitoring by adults with type 2 diabetes in a virtual diabetes clinic. Diabetes Technol. Ther. 23, 128–132 (2020).

    Article  PubMed  Google Scholar 

  205. Wu, C. C., Wu, K. C., José, A. S. & Novin, N. Virtual endocrinology care emphasizing data-driven insights and continuous engagement and its impact on glycemic outcomes in patients with uncontrolled diabetes: a real-world retrospective case series. JMIR Diabetes 7, e30626 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  206. Khunti, K. et al. Diabetes registries and high-quality diabetes care. Lancet Diabetes Endocrinol. 11, 70–72 (2023).

    Article  PubMed  Google Scholar 

  207. European Commission. Commission Recommendation on a European Electronic Health Record exchange format. European Commission ec.europa.eu/newsroom/dae/document.cfm?doc_id=57253 (2019).

  208. Font, A. G. Work begins on developing the mConnecta Mobility Platform. TIC Salut Social ticsalutsocial.cat/en/noticia/work-begins-on-developing-the-mconnecta-mobility-platform/ (2019).

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Acknowledgements

The authors thank Abbott Diabetes Care for organizing the author discussion panel and for providing funding to R. Brines, Bite Medical Consulting, who conducted the literature search, and collated and compiled author revisions during the manuscript drafting process. Abbott Diabetes Care did not have any editorial input into the working group deliberations or the development of the manuscript, which reflects only the independent views of the authors.

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Authors and Affiliations

  1. The LIGHT Laboratories, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK

    Ramzi A. Ajjan

  2. Faculty of Medicine, University of Ljubljana Medical Centre, Ljubljana, Slovenia

    Tadej Battelino

  3. DAP Cat Research Group, Foundation University Institute for Primary Health Care Research Jordi Gol i Gorina, Barcelona, Spain

    Xavier Cos

  4. Section of Diabetes and Metabolic Diseases, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy

    Stefano Del Prato

  5. Diabetes, Nutrition, and Metabolic Disorders, University of Liège, Liège, Belgium

    Jean-Christophe Philips

  6. Department of Endocrinology, Diabetes and Nutrition, University Hospital, Strasbourg, France

    Laurent Meyer

  7. Division of Endocrinology and Diabetology, Department of Medicine II, Medical Centre, University of Freiburg, Freiburg, Germany

    Jochen Seufert

  8. Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK

    Samuel Seidu

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Competing interests

R.A.A. has received institutional research grants from Abbott, Bayer, Eli Lilly and Novo Nordisk, and honoraria, education support or consulting fees from Abbott, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lilly, GlaxoSmithKline, Menarini Pharmaceuticals, Merck Sharp & Dohme and Novo Nordisk. T.B. has received honoraria for participation on advisory boards for Novo Nordisk, Sanofi, Eli Lilly, Medtronic and Indigo Diabetes, and as a speaker for AstraZeneca, Eli Lilly, Novo Nordisk, Medtronic, Sanofi and Roche. His institution has received research grant support and travel expenses from Abbott Diabetes Care, Medtronic, Novo Nordisk, Sanofi, Sandoz and Novartis. X.C. has received speaking honoraria, consulting fees or travel support from Abbott, AstraZeneca, Boehringer Ingelheim, Lilly, Novartis, Novo Nordisk and Sanofi. X.C. is also the chair of Primary Care Diabetes Europe. S.D.P. reports grants from AstraZeneca and Boehringer Ingelheim; consulting fees from Applied Therapeutics, AstraZeneca, Boehringer Ingelheim, Eli Lilly and Company, Hengrui Pharmaceutical, Merck Sharpe and Dohme, Novartis Pharmaceuticals, Novo Nordisk and Sanofi; and honoraria as a speaker for AstraZeneca, Boehringer Ingelheim, Eli Lilly and Company, Merck Sharpe and Dohme, Novartis Pharmaceuticals, Novo Nordisk and Sanofi. J.-C.P. reports honoraria for participation in advisory boards for Abbott. L.M. has received honoraria as a speaker for Abbott, Dexcom and participation on advisory boards for Abbott. J.S. declares consulting fees, speaker honoraria and support for attending educational meetings from Abbott. S.S. reports personal fees from Amgen, AstraZeneca, Napp Pharmaceuticals, Eli Lilly, Merck Sharp & Dohme, Novartis, Novo Nordisk, Roche, Sanofi and Boehringer Ingelheim. Additionally, S.S. reports grants from AstraZeneca, Sanofi, Servier and Janssen.

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Ajjan, R.A., Battelino, T., Cos, X. et al. Continuous glucose monitoring for the routine care of type 2 diabetes mellitus. Nat Rev Endocrinol (2024). https://doi.org/10.1038/s41574-024-00973-1

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