The impact of remote monitoring of glycemia self-control on carbohydrate metabolism and quality of life in patients with type 1 diabetes mellitus
https://doi.org/10.14341/probl13535
Abstract
BACKGROUND: Self-monitoring of blood glucose (SMBG) is the main tool to achieve carbohydrate metabolism targets in patients with type 1 diabetes mellitus (DM). Remote monitoring of SMBG in Russia appeared relatively recently and needs to be evaluated for effectiveness.
AIM: To evaluate the effect of remote monitoring of SMBG on carbohydrate metabolism and quality of life in patients with type 1 DM in order to form new therapeutic approaches.
MATERIALS AND METHODS: Patients with type 1 DM with glycated hemoglobin (HbA1c) from 8.0 to 12.0% were divided into the main (n=107) and control group (n=20). Patients from the main group performed SMBG using glucometers with the possibility of remote data transmission, patients from the control group continued the traditional SMBG. The dynamics of HbA1c, derived time spent in the target ranges, recognition of hypoglycemia (GOLD scale, Clarke questionnaire), quality of life according to the SF-36 questionnaire were evaluated. The statistical analysis was carried out in the SPSS Version 26.0 program (IBM, USA).
RESULTS: In the main group (n=88) the HbA1c was statistically significant decreased after 6 months from 9.0% [8.4; 9.9] to 8.1% [7.4; 9.2] (p<0.001), with SMBG more than 4 times a day - up to 7.3% [7.0; 7.8] (p=0.001). In the control group (n=20), by the 6th month, HbA1c increased to 10.1% [8,9; 11,2] (p=0,010). Derived Time In Range in the main group increased to 69.9±13.0 (95% CI 65.73–74.03; p<0.001); derived Time Above Range significantly decreased to 9.5% [6.4; 15.0] (p<0.001), derived Time Below Range — to 6.7% [2.8; 12.2] (p=0.044); Coefficient of Variation reached 36.3±7.9 (95% CI 33.7–38.8; p<0.001). According to the results of SF-36, the physical and psychological components of the quality of life in the main group significantly improved (p<0.001). Recognition of hypoglycemia improved in the intervention group (-4.5% of patients (p=0.046) according to the Clarke questionnaire; -8% (p=0.008) on the GOLD scale).
CONCLUSION: Remote monitoring of SMBG is a prospective therapeutic approach due to its positive effect on carbohydrate metabolism and quality of life in patients with type 1 DM.
About the Authors
L. A. SuplotovaRussian Federation
Lyudmila A. Suplotova, MD, PhD, Professor
54 Odesskaya street, 625023 Tyumen
O. O. Alieva
Russian Federation
Oksana O. Alieva, MD
Tyumen
L. I. Ibragimova
Russian Federation
Liudmila I. Ibragimova, MD, PhD
Moscow
References
1. Dedov II, Shestakova MV, Vikulova OK, et al. Diabetes mellitus in the Russian Federation: dynamics of epidemiological indicators according to the Federal Register of Diabetes Mellitus for the period 2010–2022. Diabetes mellitus. 2023;26(2):104-123. (In Russ.)] doi: https://doi.org/10.14341/DM13035
2. Runova GE. The role of glycemic self-control in diabetes management: based on the American Diabetes Association guidelines (2021). Meditsinskiy sovet = Medical Council. 2021;(12):286-292. (In Russ.)] doi: https://doi.org/10.21518/2079-701X-2021-12-286-292
3. Friedman JG, Cardona Matos Z, Szmuilowicz ED, Aleppo G. Use of Continuous Glucose Monitors to Manage Type 1 Diabetes Mellitus: Progress, Challenges, and Recommendations. Pharmgenomics Pers Med. 2023;16:263-276. doi: https://doi.org/10.2147/PGPM.S374663
4. Messer LH, Tanenbaum ML, Cook PF, et al. Cost, Hassle, and OnBody Experience: Barriers to Diabetes Device Use in Adolescents and Potential Intervention Targets. Diabetes Technol Ther. 2020;22(10):760-767. doi: https://doi.org/10.1089/dia.2019.0509
5. Mensh BD, Wisniewski NA, Neil BM, Burnett DR. Susceptibility of interstitial continuous glucose monitor performance to sleeping position. J Diabetes Sci Technol. 2013;7(4):863-870. doi: https://doi.org/10.1177/193229681300700408
6. Zaharieva DP, Turksoy K, McGaugh SM, et al. Lag Time Remains with Newer Real-Time Continuous Glucose Monitoring Technology During Aerobic Exercise in Adults Living with Type 1 Diabetes. Diabetes Technol Ther. 2019;21(6):313-321. doi: https://doi.org/10.1089/dia.2018.0364
7. Heinemann L. Interferences with CGM Systems: Practical Relevance. J Diabetes Sci Technol. 2022;16(2):271-274. doi: https://doi.org/10.1177/19322968211065065
8. Dedov II, Shestakova MV, Mayorov AYu, et al. Standards of specialized diabetes care. 10th edition. Diabetes mellitus. 2021;24(1S):1-148. (In Russ.)] doi: https://doi.org/10.14341/DM12802
9. ISO 15197–2015. In vitro diagnostic test systems. Requirements for blood glucose monitoring systems for self-testing in managing diabetes mellitus. Standartinform. 2015 (In Russ).]
10. How Many People Have Smartphones Worldwide. [Internet] BankMyCell. [cited 2024 Aug 12]. Available from: http://www.bankmycell.com/blog/how-many-phones-are-in-the-world
11. Suplotova LA, Alieva OO. Evolution of blood glucose self-monitoring technology. Diabetes mellitus. 2023;26(6):566-574. (In Russ.)] doi: https://doi.org/10.14341/DM13063
12. Pi L, Shi X, Wang Z, Zhou Z. Effect of smartphone apps on glycemic control in young patients with type 1 diabetes: A meta-analysis. Front Public Health. 2023; 11:1074946. doi: https://doi.org/10.3389/fpubh.2023.1074946
13. Dedov II, Shestakova MV, Mayorov AY, Shamkhalova MS, Nikonova TV, Sukhareva OY, et al. Diabetes mellitus type 1 in adults. Clinical Recommendations. 2022 (In Russ.)]
14. Ware JE, Snow KK, Kosinski M, Gandek B. SF-36 Health Survey. Manual and interpretation guide. The Health Institute, New England Medical Center. Boston, Mass. 1993
15. Gold AE, MacLeod KM, Frier BM. Frequency of severe hypoglycemia in patients with type I diabetes with impaired awareness of hypoglycemia. Diabetes Care. 1994;17(7):697-703. doi: https://doi.org/10.2337/diacare.17.7.697
16. Lehmann R, Czock A, Egli M, et al. Schweizerische Gesellschaft für Endokrinologie und Diabetologie. Richtlinien bezüglich Fahreignung und Fahrfähigkeit bei Diabetes mellitus. 2017
17. Beck RW, Calhoun P, Kollman C. Use of continuous glucose monitoring as an outcome measure in clinical trials. Diabetes Technol Ther. 2012;14(10):877-882. doi: https://doi.org/10.1089/dia.2012.0079
18. Miller KM, Beck RW, Bergenstal RM, et al. Evidence of a strong association between frequency of self-monitoring of blood glucose and hemoglobin A1c levels in T1D exchange clinic registry participants. Diabetes Care. 2013;36(7):2009-2014. doi: https://doi.org/10.2337/dc12-1770
19. Pfützner A, Weissmann J, Mougiakakou S, et al. Glycemic Variability Is Associated with Frequency of Blood Glucose Testing and Bolus: Post Hoc Analysis Results from the ProAct Study. Diabetes Technol Ther. 2015;17(6):392-397. doi: https://doi.org/10.1089/dia.2014.0278
20. Udsen FW, Hangaard S, Bender C, et al. The Effectiveness of Telemedicine Solutions in Type 1 Diabetes Management: A Systematic Review and Meta-analysis. J Diabetes Sci Technol. 2023;17(3):782-793. doi: https://doi.org/10.1177/19322968221076874
21. Charpentier G, Benhamou PY, Dardari D, et al. The Diabeo software enabling individualized insulin dose adjustments combined with telemedicine support improves HbA1c in poorly controlled type 1 diabetic patients: a 6-month, randomized, open-label, parallel-group, multicenter trial (TeleDiab 1 Study). Diabetes Care. 2011;34(3):533-539. doi: https://doi.org/10.2337/dc10-1259
22. Klimontov VV. Impaired hypoglycemia awareness in diabetes: epidemiology, mechanisms and therapeutic approaches. Diabetes mellitus. 2018;21(6):513-523. (In Russ.)] doi: https://doi.org/10.14341/DM9597
23. Rossi MC, Nicolucci A, Di Bartolo P, et al. Diabetes Interactive Diary: a new telemedicine system enabling flexible diet and insulin therapy while improving quality of life: an open-label, international, multicenter, randomized study. Diabetes Care. 2010;33(1):109-115. doi: https://doi.org/10.2337/dc09-1327
Supplementary files
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1. Figure 1. Scheme of transferring SCG data from a patient to an endocrinologist | |
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2. Figure 2. Analysis of the dynamics of HbA1c depending on the observation group, Me [Q1; Q3], %. | |
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3. Figure 3. Dynamics of the HbA1c level of the main group depending on the frequency of SCG, Me [Q1; Q3], %. | |
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Type | Результаты исследования | |
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Review
For citations:
Suplotova L.A., Alieva O.O., Ibragimova L.I. The impact of remote monitoring of glycemia self-control on carbohydrate metabolism and quality of life in patients with type 1 diabetes mellitus. Problems of Endocrinology. 2025;71(1):40-49. (In Russ.) https://doi.org/10.14341/probl13535

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