Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Comment
  • Published:

Hybrid closed loop and intensive insulin delivery technology: Reviewing the effect of improving ‘time in range’ glucose levels on diabetic retinopathy

Eye volume 39, pages 1028–1030 (2025)Cite this article

Subjects

Testing for glycated haemoglobin (HbA1c) was previously considered satisfactory for evaluating metabolic control in patients with diabetes, but in the last decade continuous glucose monitoring (CGM) sensors demonstrated that patients with comparable HbA1c levels may have wide variations in the pattern of their daily blood glucose profiles. There can be substantial alterations in the frequency and range of fluctuations in their blood glucose levels and CGM, by measurement of interstitial glucose levels every few minutes, can demonstrate more accurate reflection of glucose levels throughout the day and help predict both the direction and rate of change [1]. Glycaemic variability (GV) has therefore been pertinent, with CGM derived indicators of glucose fluctuations being an important part of glycaemic control in relation to the prevalence of diabetic retinopathy (DR) [2, 3], in both Type 1 diabetes mellitus (T1DM) and Type 2 diabetes mellitus (T2DM).

CGM now has an established role in capturing the unpredictability and extent of momentary changes in glucose levels and can therefore assess GV more accurately, reflecting both ‘metabolic memory’ as well as the ‘legacy effect’ [1, 2], as confirmed by the Diabetes Control and Complications Trial (DCCT). GV can be assessed short term, addressing the peaks and troughs of glucose within a 24-h period or between days, nonetheless it can also be ascribed to variability within markers of longer-term control such as HbA1c [4]. The limitations of HbA1c measurements and the increasing prominence and emergence of GV as a significant and clinically meaningful glycaemic metric has now been well established [3,4,5,6,7,8]. DCCT had also demonstrated several years ago, that GV was associated with DR [5, 6], and more recently this has been reiterated yet again [7, 8]. The association of ‘time in range’ (TIR) of glucose levels with progression through all grades of DR, has been particularly statistically significant independent of HbA1c, in large cohort studies involving adult patients with T2DM [7], and late autoimmune diabetes in adults (LADA) who usually have far fewer cardiometabolic risk factors [8]. Similarly, in T1DM education based intensive insulin therapy has been associated with less fluctuations in glucose levels, good metabolic control and a low prevalence of DR [9].

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

References

  1. Sartore G, Chilelli NC, Burlina S, Di Stefano P, Piarulli F, Fedele D, et al. The importance of HbA1c and glucose variability in patients with type 1 and type 2 diabetes: outcome of continuous glucose monitoring (CGM). Acta Diabetol. 2012;49:S153–160.

    Article  PubMed  Google Scholar 

  2. Sartore G, Chilelli NC, Burlina S, Lapolla A. Association between glucose variability as assessed by continuous glucose monitoring (CGM) and diabetic retinopathy in type 1 and type 2 diabetes. Acta Diabetol. 2013;50:437–42.

    Article  CAS  PubMed  Google Scholar 

  3. Brownlee M, Hirsch IB. Glycemic variability: a hemoglobin A1c-independent risk factor for diabetic complications. JAMA. 2006;295:1707–8.

    Article  CAS  PubMed  Google Scholar 

  4. Wilmot EG, Choudhary P, Leelarathna L, Baxter M. Glycaemic variability: The under-recognized therapeutic target in type 1 diabetes care. Diabetes Obes Metab. 2019;21:2599–608.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kilpatrick ES, Rigby AS, Atkin SL. The effect of glucose variability on the risk of microvascular complications in type 1 diabetes. Diabetes Care. 2006;29:1486–90.

    Article  CAS  PubMed  Google Scholar 

  6. Lachin JM, Bebu I, Bergenstal RM, Pop-Busui R, Service FJ, Zinman B, et al. DCCT/EDIC Research Group. Association of glycemic variability in type 1 diabetes with progression of microvascular outcomes in the diabetes control and complications trial. Diabetes Care. 2017;40:777–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Lu J, Ma X, Zhou J, Zhang L, Mo Y, Ying L, et al. Association of Time in Range, as assessed by continuous glucose monitoring, with diabetic retinopathy in type 2 diabetes. Diabetes Care. 2018;41:2370–6.

    Article  CAS  PubMed  Google Scholar 

  8. Lu J, Ma X, Zhang L, Mo Y, Ying L, Lu W, 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 Investig. 2019;10:753–9.

    Article  CAS  PubMed  Google Scholar 

  9. Hatz K, Minder AE, Lehmann R, Drescher T, Gerendas B, Schmidt-Erfurth U, et al. The prevalence of retinopathy in patients with type 1 diabetes treated with education-based intensified insulin therapy and its association with parameters of glucose control. Diabetes Res Clin Pract. 2019;148:234–9.

    Article  CAS  PubMed  Google Scholar 

  10. Yapanis M, James S, Craig ME, O’Neal D, Ekinci EI. Complications of Diabetes and Metrics of Glycemic Management Derived From Continuous Glucose Monitoring. J Clin Endocrinol Metab. 2022;107:e2221–36.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Rodbard D. Continuous glucose monitoring metrics (Mean Glucose, time above range and time in range) are superior to glycated haemoglobin for assessment of therapeutic efficacy. Diabetes Obes Metab. 2023;25:596–601.

    Article  CAS  PubMed  Google Scholar 

  12. Sherr JL, Heinemann L, Fleming GA, Bergenstal RM, Bruttomesso D, Hanaire H, et al. Automated insulin delivery: benefits, challenges, and recommendations. A Consensus Report of the Joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association. Diabetologia. 2023;66:3–22.

    Article  PubMed  Google Scholar 

  13. Shah VN, Kanapka LG, Akturk HK, Polsky S, Forlenza GP, Kollman C, et al. Time in Range Is Associated with Incident Diabetic Retinopathy in Adults with Type 1 Diabetes: A Longitudinal Study. Diabetes Technol Ther. 2024;26:246–51.

    Article  PubMed  Google Scholar 

  14. Zhu DD, Wu X, Cheng XX, Ding N. Time in range as a useful marker for evaluating retinal functional changes in diabetic retinopathy patients. Int J Ophthalmol. 2023;16:915–20.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Guo Y, Zheng X, He H, Zheng S. Retinal Microvasculopathy with different insulin infusion therapies in children with type 1 diabetes mellitus without clinical diabetic retinopathy. Retina. 2024;44:895–900.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Perais J, Agarwal R, Evans JR, Loveman E, Colquitt JL, Owens D, et al. Prognostic factors for the development and progression of proliferative diabetic retinopathy in people with diabetic retinopathy. Cochrane Database Syst Rev. 2023;2:CD013775.

    PubMed  Google Scholar 

  17. Tecce N, Cennamo G, Rinaldi M, Costagliola C, Colao A. Exploring the impact of glycemic control on diabetic retinopathy: emerging models and prognostic implications. J Clin Med. 2024;13:831.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Dunn TC, Ajjan RA, Bergenstal RM, Xu Y. Is It Time to Move Beyond TIR to TITR? Real-World Data from Over 20,000 Users of Continuous Glucose Monitoring in Patients with Type 1 and Type 2 Diabetes. Diabetes Technol Ther. 2024;26:203–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Varughese MS, Nayak AU, Jacob S. Fenofibrate therapy in reducing the progression of diabetic retinopathy: revisiting the FIELD and ACCORD-EYE studies through the LENS trial. Eye. 2025;39:15–7.

    Article  PubMed  Google Scholar 

  20. Varughese MS, Nayak AU. PCSK9 Inhibitors and Lipid Lowering: Viewpoint on Diabetic Retinopathy. Ophthalmic Surg Lasers Imaging Retina. 2025;56:62–3.

    Article  PubMed  Google Scholar 

  21. Varughese MS, Nayak AU, Jacob S. PCSK9 levels and diabetic retinopathy: opportunities for a potential target and novel therapeutic approach in conjunction with treating dyslipidaemia. Eye. 2024. https://doi.org/10.1038/s41433-024-03523-1.

  22. Varughese MS, Nayak AU. Diabetic macular edema: Variations in observations with intensive treatment optimizing glycemia. J Diabetes Complicat. 2025;39:108909.

    Article  Google Scholar 

  23. Varughese MS, Varadhan L. SGLT2 inhibitors and diabetic retinopathy: Insights from the management of nephropathy. Eye. 2025;39:213–4.

    Article  PubMed  Google Scholar 

  24. Dehghani Firouzabadi F, Poopak A, Samimi S, Deravi N, Nakhaei P, Sheikhy A, et al. Glycemic profile variability as an independent predictor of diabetic retinopathy in patients with type 2 diabetes: a prospective cohort study. Front Endocrinol. 2024;15:1383345.

    Article  Google Scholar 

  25. Varughese MS, Jacob S. Diabetic retinopathy and pregnancy: an overview of the predictive risk factors for progressive worsening of eye disease during the antenatal period. Eye. 2025. https://doi.org/10.1038/s41433-025-03677-6.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Benhalima K, Beunen K, Van Wilder N, Ballaux D, Vanhaverbeke G, Taes Y, et al. Comparing advanced hybrid closed loop therapy and standard insulin therapy in pregnant women with type 1 diabetes (CRISTAL): a parallel-group, open-label, randomised controlled trial. Lancet Diabetes Endocrinol. 2024;12:390–403.

    Article  CAS  PubMed  Google Scholar 

  27. Lee TTM, Collett C, Bergford S, Hartnell S, Scott EM, Lindsay RS, et al. AiDAPT Collaborative Group. Automated Insulin Delivery in Women with Pregnancy Complicated by Type 1 Diabetes. N Engl J Med. 2023;389:1566–78.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Sheffield Medical School, Royal Hallamshire Hospital, Sheffield, South Yorkshire, UK

    Maria S. Varughese

  2. University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, North Staffordshire, UK

    Ananth U. Nayak & Lakshminarayanan Varadhan

  3. School of Medicine, Faculty of Health, Keele University, Keele, North Staffordshire, UK

    Ananth U. Nayak & Lakshminarayanan Varadhan

Authors
  1. Maria S. Varughese
    View author publications

    Search author on:PubMed Google Scholar

  2. Ananth U. Nayak
    View author publications

    Search author on:PubMed Google Scholar

  3. Lakshminarayanan Varadhan
    View author publications

    Search author on:PubMed Google Scholar

Contributions

MSV wrote the manuscript and reviewed the literature, AUN examined the evidence base and revised the discussion. LV conceptualised the theme and edited the article. MSV, AUN and LV contributed equally to this COMMENT.

Corresponding author

Correspondence to Lakshminarayanan Varadhan.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Varughese, M.S., Nayak, A.U. & Varadhan, L. Hybrid closed loop and intensive insulin delivery technology: Reviewing the effect of improving ‘time in range’ glucose levels on diabetic retinopathy. Eye 39, 1028–1030 (2025). https://doi.org/10.1038/s41433-025-03730-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41433-025-03730-4

This article is cited by

Search

Advanced search

Quick links