Glycemic Variability: What Does Hemoglobin A1c Not Reveal About Clinical Risk?

Autores

  • Clayton Bonani Novais Must Universit
  • Ana Carla Gomes Rosa Universidade Anhanguera-UNIDERP
  • Nathalia Przybylek Becker

DOI:

https://doi.org/10.5281/zenodo.23287133

Palavras-chave:

Diabetes Mellitus, Glycated Hemoglobin, Continuous Glucose Monitoring, Glycemic Variability

Resumo

Introduction: Glycated hemoglobin (HbA1c) is widely used to assess glycemic control; however, it does not fully characterize glucose fluctuations or episodes of hypoglycemia and hyperglycemia. Objective: To analyze the scientific evidence on glycemic variability, its relationship with HbA1c, and its implications for clinical risk assessment in patients with diabetes mellitus. Methods: An integrative literature review was proposed to synthesize original studies, systematic reviews, meta-analyses, and clinical guidelines addressing glycemic variability and continuous glucose monitoring. Results: The reference literature indicates that metrics such as time in range, time below range, time above range, and glycemic coefficient of variation complement HbA1c by characterizing glucose fluctuation patterns and identifying clinically relevant glycemic events. However, the independent prognostic contribution of glycemic variability to long-term outcomes remains uncertain. Conclusion: Integrating HbA1c with continuous glucose monitoring metrics may improve the assessment of metabolic control and support individualized treatment. Nevertheless, these indicators should be interpreted in the clinical context and in light of the limitations of the available evidence.

Biografia do Autor

Clayton Bonani Novais, Must Universit

Gestor Hospitalar. Mestrado em Gestão em Saúde.

Ana Carla Gomes Rosa, Universidade Anhanguera-UNIDERP

Graduanda em Medicina . Doutorado em Saúde e Desenvolvimento na Região Centro-oeste, UFMS.

Nathalia Przybylek Becker

Médica.

Referências

1. Karczewski D, Karczewski T, Olsen M. Glycated hemoglobin and prediabetes: a systematic review of HbA1c thresholds for type

2 diabetes prevention. J Clin Med. 2026;15(12):4690. doi:10.3390/jcm15124690. 2. Andreadi A, Andreadi S, Todaro F, Cerilli M, Lodeserto P, Pinto G, et al. Glycemic variability and continuous glucose monitoring in occupational health: a narrative review of emerging evidence and potential applications in working populations. Healthcare (Basel). 2026;14(13):1979. doi:10.3390/healthcare14131979.

3. Williams E Jr, Rand C, Ayers A, Ho C, Dunova A, Klonoff D, et al. The evolving landscape of continuous glucose monitoring metrics in type 1 diabetes: narrative literature review. JMIR Diabetes. 2026;11:e92455. doi:10.2196/92455.

4. Fehér MD, Ilea CDN, Vesa CM, Venter AC, Birsan SD, Ghitea TC, et al. Glycemic status and glycemic variability related to mortality and morbidity in critically ill diabetic and non-diabetic patients: prospective doi:10.3390/clinpract16080145. observational study. Clin Pract. 2026;16(8):145.

5. 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(6):e2221-e2236. doi:10.1210/clinem/dgac034.

6. Lazar S, Ionita I, Reurean-Pintilei D, Timar R, Luca SA, Timar B. To what extent is HbA1c associated with glycemic variability in patients with type 1 diabetes? A retrospective, noninterventional study. J Clin Med. 2024;13(2):450. doi:10.3390/jcm13020450.

7. Bhargava S, Mahato K, Manocha A, Kankra M, Singla P, Sharma A, et al. Interpreting HbA1c in presence of deficiency anemias. Indian J Clin Biochem. 2021;36(3):360-4. doi:10.1007/s12291-020 00896-4.

8. Agmon O, Sigawi T, Ilan Y. The constrained disorder principle: a novel framework for understanding glycemic variability and optimizing diabetes management. Endocr Metab Sci. 2025; [volume and article number to confirm]. doi:10.1016/j.endmts.2025.100262.

9. Fatulla P, Imberg H, Sterner Isaksson S, Hirsch IB, Mårtensson J, Liljebäck H, et al. Evaluating the adequacy of coefficient of variation and standard deviation as metrics of glucose variability in type 1 diabetes based on data from the GOLD and SILVER trials. Diabetes Technol Ther. 2025;27(8):606 12. doi:10.1089/dia.2024.0540.

10. Urakami T, Terada H, Tanabe S, Mine Y, Aoki M, Aoki R, et al. Clinical significance of coefficient of variation in continuous glucose monitoring for glycemic management in children and adolescents with type 1 diabetes. J Diabetes Investig. 2024;15(11):1669-74. doi:10.1111/jdi.14303. International Journal of Health and Surgical Research (IJHSR) Brazil, v.2, n.10, p.17-28, 2026. 27 ISSN 3086-2574

11. Ohara M, Takahashi N, Takehana N, Osaka N, Sugita H, Terasaki M, et al. Association of glycemic variability with oxidative stress and AGE accumulation in type 2 diabetes. Sci Rep. 2025;16(1):2055. doi:10.1038/s41598-025-31845-x.

12. Yoo JH, Kim JH. Time in range from continuous glucose monitoring: a novel metric for glycemic control. Diabetes Metab J. 2020;44(6):828-39. doi:10.4093/dmj.2020.0257.

13. Pi L, Zheng Y, Shi X, Wang Z, Zhou Z. Using point-of-care HbA1c to facilitate the identification of diabetes and abnormal glucose regulation in primary healthcare settings. Front Public Health. 2023;11:1078361. doi:10.3389/fpubh.2023.1078361.

14. Guo QY, Lu B, Guo ZH, Feng ZQ, Yuan YY, Jin XG, et al. Continuous glucose monitoring defined time-in-range is associated with sudomotor dysfunction in type 2 diabetes. World J Diabetes. 2020;11(11):489-500. doi:10.4239/wjd.v11.i11.489.

15. Al Hayek A, Al Mashali M, Al Dawish MA. Evaluation of glycemia risk index and continuous glucose monitoring-derived metrics in type 1 diabetes: a real-world observational study. J Diabetes Metab Disord. 2025;24(1):59. doi:10.1007/s40200-025-01569-w.

16. Canha D, Choudhary P, Cosson E, Banu I, Barraud S, Valéro R, et al. Time below range alone is insufficient to identify severe hypoglycaemia risk in type 1 diabetes: the critical role of hypoglycaemia awareness: results from the SFDT1 study. Diabetologia. 2025;68(12):2719-31. doi:10.1007/s00125 025-06536-x.

17. De Meulemeester J, Charleer S, Visser MM, De Block C, Mathieu C, Gillard P. The association of chronic complications with time in tight range and time in range in people with type 1 diabetes: a retrospective cross-sectional doi:10.1007/s00125-024-06171-y. real-world study. Diabetologia. 2024;67(8):1527-35.

18. Miller EM. Using continuous glucose monitoring in clinical practice. Clin Diabetes. 2020;38(5):429-38. doi:10.2337/cd20-0043.

19. Sager-La Ganga C, Arranz-Martin JA, Jiménez-Díaz J, Hernando-Alday I, Navas-Moreno V, Fandiño García MDM, et al. The GMI/HbA1c ratio does not independently predict diabetic retinopathy in adults with type 1 diabetes. Sci Rep. 2025;15(1):35825. doi:10.1038/s41598-025-19705-0.

20. Bernardi FA, Alves D, Crepaldi N, Yamada DB, Lima VC, Rijo R. Data quality in health research: integrative literature review. J Med Internet Res. 2023;25:e41446. doi:10.2196/41446.

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Publicado

2026-10-11

Como Citar

Novais, C. B., Rosa, A. C. G., & Becker, N. P. (2026). Glycemic Variability: What Does Hemoglobin A1c Not Reveal About Clinical Risk? . International Journal of Health and Surgical Research, 2(10), 17–28. https://doi.org/10.5281/zenodo.23287133