BACKGROUND AND AIMS: The optimal basal and bolus insulin distribution in type 1 diabetes (T1D) is still controversial. Herein, we aimed to determine the variability of basal to total daily insulin dose according to treatment modality and diabetes technologies from the Better Control in Pediatric and Adolescent Diabetes: Working to Create Centers of Reference (SWEET) registry. Methods. The study cohort was generated by using the SWEET database. Patients with T1D for at least 2 years, aged between 2.5 and 18 years, with at least one clinic visit between June 2010 and June 2021, were included in the study. Four groups were composed according to treatment modality as follows: multiple daily injections (MDI) without continuous glucose monitoring (CGM); MDI with CGM; subcutaneous insulin infusion (CSII) without CGM; and CSII with CGM. Data of the participants were analyzed and compared for each treatment modality separately. RESULTS: A total of 38,956 children and adolescents were included in the study. Of the study sample, 48.6% were female, the median (range) age was 15.2 (11.9-17.2) years, and the median diabetes duration was 6.0 (3.8-9.0) years. The distribution of treatment modality was as follows: MDI without CGM, 32.9%; MDI with CGM, 18.0%; CSII without CGM, 11.7%; and CSII with CGM, 37.3%. In unadjusted data, regardless of treatment modality, all the analyses revealed a significant association between basal dose to total daily insulin dose (BD/TDD) with male gender, younger age group, and lower HbA1c, which were all related to a decreased ratio of BD/TDD (all p < 0.05). There was no association between BD/TDD and different diabetes technologies after the age, gender, and diabetes duration were adjusted. CONCLUSIONS: Herein, we showed that there was an association between lower proportions of basal to total insulin and lower hemoglobin A1c in a large cross-sectional cohort of children who had T1D. There was also an association between lower BD/TDD and younger age. There was no significant difference between BD/TDD ratios under different diabetes technologies (CGM and/or CSII).

• MeSH
• diabetes mellitus 1. typu * farmakoterapie   krev   MeSH
• dítě MeSH
• glykovaný hemoglobin analýza   MeSH
• hypoglykemika * aplikace a dávkování   MeSH
• inzulin * aplikace a dávkování   MeSH
• inzulinové infuzní systémy MeSH
• krevní glukóza analýza   MeSH
• lidé MeSH
• mladiství MeSH
• předškolní dítě MeSH
• registrace MeSH
• selfmonitoring glykemie MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• předškolní dítě MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Open-source automated insulin delivery systems, commonly referred to as do-it-yourself automated insulin delivery systems, are examples of user-driven innovations that were co-created and supported by an online community who were directly affected by diabetes. Their uptake continues to increase globally, with current estimates suggesting several thousand active users worldwide. Real-world user-driven evidence is growing and provides insights into safety and effectiveness of these systems. The aim of this consensus statement is two-fold. Firstly, it provides a review of the current evidence, description of the technologies, and discusses the ethics and legal considerations for these systems from an international perspective. Secondly, it provides a much-needed international health-care consensus supporting the implementation of open-source systems in clinical settings, with detailed clinical guidance. This consensus also provides important recommendations for key stakeholders that are involved in diabetes technologies, including developers, regulators, and industry, and provides medico-legal and ethical support for patient-driven, open-source innovations.

• MeSH
• diabetes mellitus 1. typu * farmakoterapie   MeSH
• hypoglykemika terapeutické užití   MeSH
• inzulin * terapeutické užití   MeSH
• inzulinové infuzní systémy MeSH
• lidé MeSH
• zdravotnický personál MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH
• Research Support, N.I.H., Extramural MeSH