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Cluster Analysis of Glucose Fluctuations in the Pre-Morning and Early Morning Hours in Patients with Type 1 Diabetes Научная публикация

Конференция IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics, and Biomedicine
28-29 сент. 2023 , Новосибирск/Екатеринбург
Сборник Труды 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine (CSGB)
Сборник, IEEE. 2023.
Вых. Данные Год: 2023, Страницы: 41 - 44 Страниц : 4 DOI: 10.1109/csgb60362.2023.10329848
Ключевые слова cluster analysis, continuous glucose monitoring, hierarchical clustering, hypoglycemia, insulin, Silhouette Score, type 1 diabetes
Авторы Kladov Danil E. 1 , Semenova Julia F. 1 , Berikov Vladimir B. 1 , Klimontov Vadim V. 1
Организации
1 Laboratory of Endocrinology, Research Institute of Clinical and Experimental Lymphology - Branch of the Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences

Информация о финансировании (1)

1 Российский научный фонд 20-15-00057

Реферат: Background and Aim: In patients with type 1 diabetes, glucose dynamic in the pre-morning and early morning hours may vary requiring a differentiated approach to glycemic management. In this study, we clustered data of continuous glucose monitoring from subjects with type 1 diabetes managed with basal-bolus insulin therapy in order to identify glucose fluctuation patterns. Materials and Methods: We used continuous glucose monitoring data obtained from 570 patients. Time intervals from 4:00 am to 8:00 am were analyzed. Clustering of time series was performed using a hierarchical clustering algorithm. Statistical significance of obtained cluster structure was evaluated using Monte Carlo method and the Silhouette Score. Results: We have identified 11 clusters, including 3 ones with at least one episode of hypoglycemia. Differences between the clusters included initial and final glucose levels, as well as the presence of uptrend or downtrend. Among clusters without hypoglycemia, two clusters showed normal or near normal glucose levels, two clusters were characterized by a slightly elevated glucose, other demonstrated moderate or severe hyperglycemia. In all clusters with hypoglycemia episode(s) the mean glucose level at the start of the time interval was close to the hypoglycemia threshold; patterns with an uptrend with a stable glucose level and a downtrend occurred in approximately equal proportions. Conclusion: Patients with type 1 diabetes demonstrate a variety of glucose patterns in the pre-morning and early morning hours. The data highlight the importance of differentiated approaches to therapy.
Библиографическая ссылка: Kladov D.E. , Semenova J.F. , Berikov V.B. , Klimontov V.V.
Cluster Analysis of Glucose Fluctuations in the Pre-Morning and Early Morning Hours in Patients with Type 1 Diabetes
В сборнике Труды 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine (CSGB). – IEEE., 2023. – C.41 - 44. DOI: 10.1109/csgb60362.2023.10329848 Scopus РИНЦ OpenAlex
Даты:
Опубликована в печати: 4 дек. 2023 г.
Опубликована online: 4 дек. 2023 г.
Идентификаторы БД:
Scopus: 2-s2.0-85180373059
РИНЦ: 59499585
OpenAlex: W4389302078
Цитирование в БД: Пока нет цитирований
Альметрики: