Optimization of methods of dynamic observation of children with manifestation of type 1 diabetes mellitus in conditions of limited availability of medical care and evaluation of their effectiveness
https://doi.org/10.14341/DM13397
Abstract
BACKGROUND: With the onset of the COVID-19 pandemic, restrictions were introduced on the availability of planned medical care, which could negatively affect the compensation of children, especially with newly diagnosed type 1 diabetes mellitus (T1DM). During this period, there was a need to improve the methods of dynamic monitoring of children with the manifestation of type 1 diabetes using modern remote technologies from the first days of discharge from the hospital.
AIM: To evaluate the effectiveness of methods for dynamic observation of children with manifestation of T1DM, optimized in conditions of limited availability of planned medical care.
MATERIALS AND METHODS: A single-center, 12-month prospective comparative study was conducted in three populations of children under 17 years of age with manifestation of T1DM during the COVID-19 pandemic, who were monitored using a standard approach, as well as methods optimized with the use of telemedicine consultations (TMC) and CGM and assessment of the HbA1c level and the proportion of patients with HbA1c<7.0% at the endpoint of observation.
RESULTS: The study included 137 children: 61 — standard observation (SO) group; 25 — TMC group and 51 — TMC+CGM group, which were comparable with each other by age, gender, proportion of children in puberty, anthropometric data, as well as by the severity of T1DM manifestation and daily insulin doses (p>0.05). After 12 months of observation, a significant decrease in the HbA1c level was found in the TMC and TMC+CGM groups compared to the SO group (7.1% and 6.7% vs. 8.3%; p=0.000), while HbA1c did not differ between the TMC and TMC+CGM groups (p=0.642). The proportion of patients who achieved HbA1c<7.0% in the TMC and TMC+CGM groups statistically significantly exceeded the proportion of patients in the SO group at the endpoint of observation (48.0% and 56.9% vs. 27.9%; p<0.001), however, the TMC and TMC+CGM groups did not differ from each other (p=0.466).
СONCLUSION: Methods of remote dynamic monitoring of children with manifestation of T1DM demonstrated better efficiency in achieving and maintaining glycemic control compared to standard monitoring, which dictates the need for their wider use in clinical practice. The main factor contributing to the achievement of compensation of T1DM in children is the availability of specialized medical care and regular consultations with a doctor.
About the Authors
I. A. ProminRussian Federation
Ivan A. Promin - MD.
Ekaterinburg
Competing Interests:
none
A. V. Kiiaev
Russian Federation
Alexey V. Kiiaev, MD, PhD.
1 Repina street, 620028 Ekaterinburg
Competing Interests:
none
V. M. Polyakova
Russian Federation
Valentina M. Polyakova - MD.
Ekaterinburg
Competing Interests:
none
E. S. Astashova
Russian Federation
Ekaterina S. Astashova - MD.
Ekaterinburg
Competing Interests:
none
M. A. Slovak
Russian Federation
Maria A. Slovak - MD.
Ekaterinburg
Competing Interests:
none
L. I. Savelyev
Russian Federation
Leonid Y. Saveliev - MD, PhD; Scopus Author ID: 55535477300
Ekaterinburg
Competing Interests:
none
References
1. The relationship of glycemic exposure (HbA1c) to the risk of development and progression of retinopathy in the diabetes control and complications trial. Diabetes. 1995;44(8):968-983
2. Stratton IM, Adler AI, Neil HA, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ. 2000;321(7258):405-412. doi: https://doi.org/10.1136/bmj.321.7258.405
3. Hirose A, Furushima D, Yamaguchi N, Kitano S, Uchigata Y. Prediction of retinopathy at 20 years after onset in younger-onset type 1 diabetes using mean metabolic memory-free HbA1c values: the importance of using HbA1c data of total, not partial, diabetes duration. Diabetes Care. 2013;36(11):3812-3814. doi: https://doi.org/10.2337/dc13-0532
4. Berezin A. Metabolic memory phenomenon in diabetes mellitus: Achieving and perspectives. Diabetes Metab Syndr. 2016;10(2 Suppl 1):S176-S183. doi: https://doi.org/10.1016/j.dsx.2016.03.016
5. Reynolds KA, Helgeson VS. Children with diabetes compared to peers: depressed? Distressed? A meta-analytic review. Ann Behav Med. 2011;42(1):29-41. doi: https://doi.org/10.1007/s12160-011-9262-4
6. Rechenberg K, Whittemore R, Grey M. Anxiety in Youth With Type 1 Diabetes. J Pediatr Nurs. 2017;32:64-71. doi: https://doi.org/10.1016/j.pedn.2016.08.007
7. Laffel LM, Kanapka LG, Beck RW, et al. Effect of Continuous Glucose Monitoring on Glycemic Control in Adolescents and Young Adults With Type 1 Diabetes: A Randomized Clinical Trial. JAMA. 2020;323(23):2388-2396. doi: https://doi.org/10.1001/jama.2020.6940
8. Thabit H, Prabhu JN, Mubita W, et al. Use of Factory-Calibrated Real-time Continuous Glucose Monitoring Improves Time in Target and HbA1c in a Multiethnic Cohort of Adolescents and Young Adults With Type 1 Diabetes: The MILLENNIALS Study. Diabetes Care. 2020;43(10):2537-2543. doi: https://doi.org/10.2337/dc20-0736
9. Miller KM, Bauza C, Kanapka LG, et al. Continuous Glucose Monitoring Provides Durable Glycemic Benefit in Adolescents and Young Adults with Type 1 Diabetes: 12-Month Follow-Up Results. Pediatr Diabetes. 2023;2023:6718115. doi: https://doi.org/10.1155/2023/6718115
10. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group, Tamborlane WV, Beck RW, et al. Continuous glucose monitoring and intensive treatment of type 1 diabetes. N Engl J Med. 2008;359(14):1464-1476. doi: https://doi.org/10.1056/NEJMoa0805017
11. Vermeire E, Hearnshaw H, Van Royen P, Denekens J. Patient adherence to treatment: three decades of research. A comprehensive review. J Clin Pharm Ther. 2001;26(5):331-342. doi: https://doi.org/10.1046/j.1365-2710.2001.00363.x
12. Laptev DN, Emelyanov AO, Samoilova YG, et al. Remote monitoring and treatment of children and adolescents with type 1 diabetes. Problems of Endocrinology. 2020;66(4):50-60. (In Russ.) doi: https://doi.org/10.14341/probl12201
13. Laptev DN, Emelyanov AO, Demina ES, et al. Remote glycemic control using devices for wireless data transmission in children with type 1 diabetes mellitus: interim results of clinical approbation. Problems of Endocrinology. 2025;71(3):39-45. (In Russ.) doi: https://doi.org/10.14341/probl13492
14. Lee SWH, Ooi L, Lai YK. Telemedicine for the Management of Glycemic Control and Clinical Outcomes of Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Studies. Front Pharmacol. 2017;8:330. doi: https://doi.org/10.3389/fphar.2017.00330
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1. Figure 1. Comparative analysis of glycated hemoglobin levels between groups after 12 months of follow-up. | |
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For citations:
Promin I.A., Kiiaev A.V., Polyakova V.M., Astashova E.S., Slovak M.A., Savelyev L.I. Optimization of methods of dynamic observation of children with manifestation of type 1 diabetes mellitus in conditions of limited availability of medical care and evaluation of their effectiveness. Diabetes mellitus. 2026;29(2):183-190. (In Russ.) https://doi.org/10.14341/DM13397
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