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1.
J Diabetes Sci Technol ; : 19322968241230106, 2024 Feb 16.
Article in English | MEDLINE | ID: mdl-38366626

ABSTRACT

BACKGROUND: Automated insulin delivery (AID) systems have shown to improve glycemic control in a range of populations and settings. At the start of this study, only one commercial AID system had entered the Austrian market (MiniMed 670G, Medtronic). However, there is an ever-growing community of people living with type 1 diabetes (PWT1D) using open-source (OS) AID systems. MATERIALS AND METHODS: A total of 144 PWT1D who used either the MiniMed 670G (670G) or OS-AID systems routinely for a period of at least three to a maximum of six months, between February 18, 2020 and January 15, 2023, were retrospectively analyzed (116 670G aged from 2.6 to 71.8 years and 28 OS-AID aged from 3.4 to 53.5 years). The goal is to evaluate and compare the quality of glycemic control of commercially available AID and OS-AID systems and to present all data by an in-depth descriptive analysis of the population. No statistical tests were performed. RESULTS: The PWT1D using OS-AID systems spent more time in range (TIR)70-180 mg/dL (81.7% vs 73.9%), less time above range (TAR)181-250 mg/dL (11.1% vs 19.6%), less TAR>250 mg/dL (2.5% vs 4.3%), and more time below range (TBR)54-69 mg/dL (2.2% vs 1.7%) than PWT1D using the 670G system. The TBR<54 mg/dL was comparable in both groups (0.3% vs 0.4%). In the OS-AID group, median glucose level and glycated hemoglobin (HbA1c) were lower than in the 670G system group (130 vs 150 mg/dL; 6.2% vs 7.0%). CONCLUSION: In conclusion, both groups were able to achieve satisfactory glycemic outcomes independent of age, gender, and diabetes duration. However, the PWT1D using OS-AID systems attained an even better glycemic control with no clinical safety concerns.

2.
Diabetes Res Clin Pract ; 202: 110809, 2023 Aug.
Article in English | MEDLINE | ID: mdl-37385473

ABSTRACT

AIMS: This study aimed to provide a global insight into initiatives in type 1 diabetes care driven by the COVID-19 pandemic and associations with glycemic outcomes. METHODS: An online questionnaire regarding diabetes care before and during the pandemic was sent to all centers (n = 97, 66,985 youth with type 1 diabetes) active in the SWEET registry. Eighty-two responded, and 70 (42,798 youth with type 1 diabetes) had available data (from individuals with type 1 diabetes duration >3 months, aged ≤21 years) for all 4 years from 2018 to 2021. Statistical models were adjusted, among others, for technology use. RESULTS: Sixty-five centers provided telemedicine during COVID-19. Among those centers naive to telemedicine before the pandemic (n = 22), four continued only face-to-face visits. Centers that transitioned partially to telemedicine (n = 32) showed a steady increase in HbA1c between 2018 and 2021 (p < 0.001). Those that transitioned mainly to telemedicine (n = 33 %) improved HbA1c in 2021 compared to 2018 (p < 0.001). CONCLUSIONS: Changes to models of care delivery driven by the pandemic showed significant associations with HbA1c shortly after the pandemic outbreak and 2 years of follow-up. The association appeared independent of the concomitant increase in technology use among youth with type 1 diabetes.


Subject(s)
COVID-19 , Diabetes Mellitus, Type 1 , Telemedicine , Adolescent , Humans , Child , COVID-19/epidemiology , Diabetes Mellitus, Type 1/epidemiology , Diabetes Mellitus, Type 1/therapy , Pandemics , Glycated Hemoglobin , Registries
3.
Children (Basel) ; 9(12)2022 Dec 12.
Article in English | MEDLINE | ID: mdl-36553394

ABSTRACT

Background: The aim of this study was to assess and compare the time in range (TIR) of children with type 1 diabetes (T1D) before and during a diabetes summer camp using different therapy modalities. Methods: A retrospective analysis of continuous glucose monitoring (CGM) data collected from 26 children with T1D (mean age: 11.0 ± 1.4 years; 62% female; 62% on insulin pump; Hb1Ac 7.3 ± 0.8% (56.3 ± 8.7 mmol/mol) before and during a 14-day summer camp. CGM methods: 50% intermittently scanned CGM (isCGM) and 50% real-time CGM (rtCGM). No child was using a hybrid closed loop system. Results: Mean TIR during camp was significantly higher than before camp ((67.0 ± 10.7%) vs. 58.2% ± 17.4%, p = 0.004). There was a significant reduction in time above range (TAR) (p = 0.001) and increase in time below range (TBR) (p < 0.001), Children using isCGM showed a more pronounced improvement in TIR during camp compared to rtCGM-users (p = 0.025). The increase in TIR strongly correlated with numbers of scans per day in isCGM-users (r = 0.751, p = 0.003). Compared to isCGM-users, rtCGM-users showed significantly less TBR. The TIR target was met by 30.8% of participants during camp. Conclusion: Glycemic control improved significantly during the camp. However, on average, the therapy goal (TIR > 70%) could not be achieved despite great professional effort.

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