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Background: Frequent use of modern diabetes technologies increases the chance for optimal type 1 diabetes (T1D) control. Limited reimbursement influences the access of patients with T1D to these modalities and could worsen their prognosis. We aimed to describe the situation of reimbursement for insulins, glucometers, insulin pumps (CSII) and continuous glucose monitoring (CGM) for children with T1D in European countries participating in the SWEET Project and to compare data from EU countries with data from our previous study in 2009. Methods: The study was conducted between March 2017 and August 2017. First, we approached diabetes technology companies with a survey to map the reimbursement of insulins and diabetic devices. The data collected from these companies were then validated by members of the SWEET consortium. Results: We collected data from 29 European countries, whereas all types of insulins are mostly fully covered, heterogeneity was observed regarding the reimbursement of strips for glucometers (from 90 strips/month to no limit). CSII is readily available in 20 of 29 countries. Seven countries reported significant quota issues or obstacles for CSII prescription, and two countries had no CSII reimbursement. CGM is at least partially reimbursed in 17 of 29 countries. The comparison with the 2009 study showed an increasing availability of CSII and CGM across the EU. Conclusions: Although innovative diabetes technology is available, a large proportion of children with T1D still do not benefit from it due to its limited reimbursement. [ABSTRACT FROM AUTHOR]

Background: The possible advantage of hybrid closed-loop therapy (i.e., artificial pancreas) over sensor-augmented pump therapy in very young children with type 1 diabetes is unclear.Methods: In this multicenter, randomized, crossover trial, we recruited children 1 to 7 years of age with type 1 diabetes who were receiving insulin-pump therapy at seven centers across Austria, Germany, Luxembourg, and the United Kingdom. Participants received treatment in two 16-week periods, in random order, in which the closed-loop system was compared with sensor-augmented pump therapy (control). The primary end point was the between-treatment difference in the percentage of time that the sensor glucose measurement was in the target range (70 to 180 mg per deciliter) during each 16-week period. The analysis was conducted according to the intention-to-treat principle. Key secondary end points included the percentage of time spent in a hyperglycemic state (glucose level, >180 mg per deciliter), the glycated hemoglobin level, the mean sensor glucose level, and the percentage of time spent in a hypoglycemic state (glucose level, <70 mg per deciliter). Safety was assessed.Results: A total of 74 participants underwent randomization. The mean (±SD) age of the participants was 5.6±1.6 years, and the baseline glycated hemoglobin level was 7.3±0.7%. The percentage of time with the glucose level in the target range was 8.7 percentage points (95% confidence interval [CI], 7.4 to 9.9) higher during the closed-loop period than during the control period (P<0.001). The mean adjusted difference (closed-loop minus control) in the percentage of time spent in a hyperglycemic state was -8.5 percentage points (95% CI, -9.9 to -7.1), the difference in the glycated hemoglobin level was -0.4 percentage points (95% CI, -0.5 to -0.3), and the difference in the mean sensor glucose level was -12.3 mg per deciliter (95% CI, -14.8 to -9.8) (P<0.001 for all comparisons). The time spent in a hypoglycemic state was similar with the two treatments (P = 0.74). The median time spent in the closed-loop mode was 95% (interquartile range, 92 to 97) over the 16-week closed-loop period. One serious adverse event of severe hypoglycemia occurred during the closed-loop period. One serious adverse event that was deemed to be unrelated to treatment occurred.Conclusions: A hybrid closed-loop system significantly improved glycemic control in very young children with type 1 diabetes, without increasing the time spent in hypoglycemia. (Funded by the European Commission and others; ClinicalTrials.gov number, NCT03784027.). [ABSTRACT FROM AUTHOR]

Objective: We aimed to evaluate the longer-term safety and efficacy of hybrid closed-loop (CL) therapy in very young children with type 1 diabetes (T1D)., Research Design and Methods: Following a 16-week multinational, randomized crossover trial comparing hybrid CL with sensor-augmented pump (SAP) therapy in 74 very young children aged 1-7 years with T1D, participants were invited to an extension phase using CL for a further 18 months. Outcomes were compared with the primary-phase SAP period and primary-phase CL period., Results: After the primary study phase, 60 participants were eligible to enroll in the extension. Of these, 49 consented (mean ± SD age 6.6 ± 1.5 years) to continue use of CL for 18 months. Percentage time in range (TIR) 3.9-10.0 mmol/L was 8.4 percentage points (95% CI 6.7-10.1; P < 0.001) higher, while HbA1c was 0.4% ([5.0 mmol/mol], 95% CI 0.3-0.6 [3.7-6.2]; P < 0.001) lower during the CL extension phase compared with primary-phase SAP period. At 18 months, mean HbA1c was 6.7 ± 0.5% and TIR was 70 ± 7%, compared with 6.7 ± 0.5% and 71 ± 6% in the primary-phase CL period. Time in hypoglycemia (<3.9 mmol/L) was similar between CL extension phase and both primary-phase SAP (P = 0.31) and CL periods (P = 0.70). There were two severe hypoglycemia events and one other serious adverse event during the extension phase. One unexpected serious adverse device effect occurred., Conclusions: Use of the Cambridge hybrid CL system led to sustained improvements in glycemic control lasting more than 18 months in very young children with T1D., (© 2024 by the American Diabetes Association.)

People living with diabetes mellitus can be supported in the daily management by diabetes technology with automated insulin delivery (AID) systems to reduce the risk of hypoglycemia and improve glycemic control as well as the quality of life. Due to barriers in the availability of AID-systems, the use and development of open-source AID-systems have internationally increased. This technology provides a necessary alternative to commercially available products, especially when approved systems are inaccessible or insufficiently adapted to the specific needs of the users. Open-source technology is characterized by worldwide free availability of codes on the internet, is not officially approved and therefore the use is on the individual's own responsibility. In the clinical practice a lack of expertise with open-source AID technology and concerns about legal consequences, lead to conflict situations for health-care professionals (HCP), sometimes resulting in the refusal of care of people living with diabetes mellitus. This position paper provides an overview of the available evidence and practical guidance for HCP to minimize uncertainties and barriers. People living with diabetes mellitus must continue to be supported in education and diabetes management, independent of the chosen diabetes technology including open-source technology. Check-ups of the metabolic control, acute and chronic complications and screening for diabetes-related diseases are necessary and should be regularly carried out, regardless of the chosen AID-system and by a multidisciplinary team with appropriate expertise., (© 2024. The Author(s).)

Objective: Many hybrid closed-loop (HCL) systems struggle to manage unusually high glucose levels as experienced with intercurrent illness or pre-menstrually. Manual correction boluses may be needed, increasing hypoglycemia risk with overcorrection. The Cambridge HCL system includes a user-initiated algorithm intensification mode ("Boost"), activation of which increases automated insulin delivery by approximately 35%, while remaining glucose-responsive. In this analysis, we assessed the safety of "Boost" mode., Methods: We retrospectively analyzed data from closed-loop studies involving young children (1-7 years, n = 24), children and adolescents (10-17 years, n = 19), adults (≥24 years, n = 13), and older adults (≥60 years, n = 20) with type 1 diabetes. Outcomes were calculated per participant for days with ≥30 minutes of "Boost" use versus days with no "Boost" use. Participants with <10 "Boost" days were excluded. The main outcome was time spent in hypoglycemia <70 and <54 mg/dL., Results: Eight weeks of data for 76 participants were analyzed. There was no difference in time spent <70 and <54 mg/dL between "Boost" days and "non-Boost" days; mean difference: -0.10% (95% confidence interval [CI] -0.28 to 0.07; P = .249) time <70 mg/dL, and 0.03 (-0.04 to 0.09; P = .416) time < 54 mg/dL. Time in significant hyperglycemia >300 mg/dL was 1.39 percentage points (1.01 to 1.77; P < .001) higher on "Boost" days, with higher mean glucose and lower time in target range ( P < .001)., Conclusions: Use of an algorithm intensification mode in HCL therapy is safe across all age groups with type 1 diabetes. The higher time in hyperglycemia observed on "Boost" days suggests that users are more likely to use algorithm intensification on days with extreme hyperglycemic excursions., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: RH reports having received speaker honoraria from Eli Lilly, Dexcom, and Novo Nordisk; receiving license fees from BBraun; patents related to closed-loop; and being director at CamDiab. JW reports receiving speaker honoraria from Ypsomed. YR is a consultant at CamDiab. MEW is a consultant at CamDiab and reports patents related to closed-loop. CKB reports receiving consultancy fees from CamDiab and speaker honoraria from Ypsomed. SH reports speaker and advisory board fees from Dexcom, Medtronic, Sanofi, and Ypsomed; being director at ASK Diabetes Ltd; and receiving consulting/training fees from CamDiab. LB reports receiving research support from Dexcom and CamDiab. REJB reports receiving speaking honoraria from Eli Lilly and Springer Healthcare, and sitting as a voluntary unpaid member of the NovoNordisk UK Foundation Research Selection committee. FMC reports receiving speaker honoraria from Eli Lilly, Dexcom, and Novo Nordisk and Insulet, and consultancy fees from Abbott Diabetes Care. EF-R reports having received speaker honoraria from Eli Lilly and Novo Nordisk, serving on advisory boards for Eli Lilly and Sanofi. MLE is a clinical triallist with or has served on advisory boards or received speakers or writers fees from Medtronic, Dexcom, Abbott Diabetes Care, Roche, AstraZeneca, Novo Nordisk, Eli Lilly, Zucara, Pila Pharma, and Imcyse Pharma. SEH has received speaker honoraria by Eli Lilly, Vertex, Minimed Medtronic, Insulet, Ypsomed, and Sanofi. TMK reports having received speaker honoraria from Eli Lilly and Novo. LL has received personal fees from Abbott Diabetes Care, Dexcom, Insulet, Medtronic, Novo Nordisk, Sanofi, and Diabetes Care. JKM is a member on the advisory board of Boehringer Ingelheim, Becton-Dickinson, Eli Lilly, Medtronic, Prediktor A/S, Roche Diabetes Care, and Sanofi-Aventis, and received speaker honoraria from Abbott Diabetes Care, AstraZeneca, Becton-Dickinson, Dexcom, Eli Lilly, Mercke Sharp & Dohme, NovoNordisk, Roche Diabetes Care, Sanofi, Servier, and Ypsomed. TR reports receiving speaker honoraria from Novo Nordisk and consultancy fees from Abbott Diabetes Care. HT reports receiving research support from Dexcom and speaker honoraria from Eli Lilly. MT reports having received speaker honoraria from Eli Lilly, Novo Nordisk, and Medtronic and advisory board fees from Abbott Diabetes Care. BR-M has received speaker honoraria from Abbott Diabetes Care, Eli Lilly, Medtronic, Novo Nordisk, Roche Diabetes Care, Sanofi, and Menarini and has been on the advisory boards of Eli Lilly, Roche Diabetes Care, and Abbott Diabetes Care. CdB has received speaker honoraria from Minimed Medtronic, and has been member of their European Psychology and e-learning Advisory Board. JMA reports training fees from CamDiab. DE, WMM, PN, TP, AG, AT, KD, and NT have no disclosures.

Background: CamAPS FX is a hybrid closed-loop smartphone app used to manage type one diabetes. The closed-loop algorithm has a default target glucose of 5.8 mmol/L (104.5 mg/dL), but users can select personal glucose targets (adjustable between 4.4 mmol/L and 11.0 mmol/L [79 mg/dL and 198 mg/dL, respectively])., Method: In this post-hoc analysis, we evaluated the impact of personal glucose targets on glycemic control using data from participants in five randomized controlled trials., Results: Personal glucose targets were widely used, with 20.3% of all days in the data set having a target outside the default target bin (5.5-6.0 mmol/L [99-108 mg/dL]). Personal glucose targets >6.5 mmol/L (117 mg/dL) were associated with significantly less time in target range (3.9-10.0 mmol/L [70-180 mg/dL]; 6.5-7.0 mmol/L [117-126 mg/dL]: mean difference = -3.2 percentage points [95% CI: -5.3 to -1.2; P < .001]; 7.0-7.5 mmol/L [126-135 mg/dL]: -10.8 percentage points [95% CI: -14.1 to -7.6; P < .001]). Personal targets >6.5 mmol/L (117 mg/dL) were associated with significantly lower time (<3.9 mmol/L [<70 mg/dL]; 6.5-7.0 mmol/L [117-126 mg/dL]: -1.85 percentage points [95% CI: -2.37 to -1.34; P < .001]; 7.0-7.5 mmol/L [126-135 mg/dL]: -2.68 percentage points [95% CI: -3.49 to -1.86; P < .001])., Conclusions: Discrete study populations showed differences in glucose control when applying similar personal targets., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: C.K.B. has received consulting fees from CamDiab and speaker honoraria from Ypsomed. J.W. has received speaker honoraria from Ypsomed. J.M.A. has received consulting fees from CamDiab. S.H. serves as a member of Sigma (Dexcom) and Medtronic advisory boards; is a consultant for CamDiab and a director of Ask Diabetes Ltd., providing training and research support in healthcare settings; and reports having received training honoraria from Medtronic, Sanofi, and Ypsomed. M.E.W. reports receiving license fees from B. Braun, patents related to closed-loop systems, and being a consultant at CamDiab. C.d.B. reports having received speaker honoraria from Medtronic and has served on the EU psychology e-learning board of Medtronic. E.F.-R. reports having received speaker honoraria from Medtronic, Eli Lilly and Company, Novo Nordisk, and Sanofi and serving on the advisory board for Eli Lilly and Company. S.E.H. has received speaker honoraria from Medtronic, Eli Lilly, Ypsomed, and Insulet. T.M.K. reports having received speaker honoraria from Eli Lilly, Merck Serono, and Novo Nordisk. B.R.-M. has received speaker honoraria from Abbott Diabetes Care, Eli Lilly, Medtronic, Novo Nordisk, Roche Diabetes Care, Sanofi, and Menarini and has been on the advisory boards of Eli Lilly, Roche Diabetes Care, and Abbott Diabetes Care. T.L.R. has received consultancy fees from Abbott Diabetes Care and speaker honoraria from Novo Nordisk. R.E.J.B. reports having received speaking honoraria from Eli Lilly and Springer Healthcare and sits as an unpaid member of the Novo Nordisk UK Research Foundation grant and selection committee. L.D. has received honoraria for taking part in an Interactive Advisory and Advocacy Forum on CGM Use in Pediatric Clinical Practice from Dexcom and has received conference fees from Novo Nordisk. H.T. reports having received research support from Dexcom and speaker honoraria from Eli Lilly and Dexcom. L.L. reports having received speaker honoraria from Animas, Abbott, Insulet, Medtronic, Novo Nordisk, Roche, and Sanofi; was on advisory panels for Animas, Abbott, Novo Nordisk, Dexcom, Medtronic, Sanofi, and Roche; and received research support from Novo Nordisk and Dexcom. M.L.E. reports having received speaker honoraria from Eli Lilly and Company, Novo Nordisk, Abbott Diabetes Care, Medtronic, AstraZeneca, and Ypsomed and acting on advisory boards for Medtronic, Novo Nordisk, Zucara Therapeutics, Pila Pharma, and Abbott Diabetes Care. J.K.M. is a member of the advisory boards of Abbott Diabetes Care, BD, Boehringer Ingelheim, Eli Lilly and Company, Medtronic, Novo Nordisk AS, Prediktor A/S, Roche Diabetes Care, and Sanofi; received speaker honoraria from Abbott Diabetes Care, AstraZeneca, Dexcom, Eli Lilly and Company, Menarini Diagnostics, Novo Nordisk A/S, Roche Diabetes Care, Servier, and Ypsomed; and is a cofounder and shareholder of decide Clinical Software Ltd. R.H. reports having received speaker honoraria from Eli Lilly and Company, Dexcom, and Novo Nordisk; receiving license fees from Medtronic; receiving patents related to closed-loop systems; and being the director at CamDiab. M.F., A.T., F.M.C., A.G., D.E., N.T., N.D., and L.B. have no conflict of interest to disclose.

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., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: ISF received speaker honoraria from Dexcom, Medtronic, Abbott, and Roche Diabetes Care. BRM reports speaker’s honoraria/advisory board activity from Dexcom, Abbott, Insulet, Medtronic, Eli Lilly, Novo Nordisk, Sanofi, and Ypsomed. JKM is a member of the advisory boards of Abbott Diabetes Care, Becton-Dickinson, Boehringer Ingelheim, Eli Lilly, Embecta, Medtronic, NovoNordisk A/S, Roche Diabetes Care, Sanofi-Aventis, and Viatris, and received speaker honoraria from A.Menarini Diagnostics, Abbott Diabetes Care, AstraZeneca, Boehringer Ingelheim, Dexcom, Eli Lilly, Medtrust, MSD, NovoNordisk A/S, Roche Diabetes Care, Sanofi, Servier, and Ypsomed; furthermore, she is shareholder of decide Clinical Software GmbH and elyte Diagnostics where she also serves as chief marketing officer (CMO). The other authors declare no conflict of interest.

Background: Since the introduction of insulin pumps into the therapy of pediatric subjects, different approaches have been taken to find optimal basal rates. Previously, the DPV registry provided circadian basal rate patterns for different age groups. As the number of pump users has increased recently and short-acting insulin analogues are now predominant, we performed a new analysis with a larger data pool. Methods: We included all recent basal profiles from type 1 diabetes (T1D) patients between 1 and 25 years from the DPV 2021 data pool. We excluded night-time-only pump users, human regular insulin users, and daily basal rates <0.05 and >1.0 U/(kgBW·d). Results: In the analysis of profiles from 25,718 young persons with T1D, differences in the daily pattern of basal rates were found between age groups. In addition, we saw significant ( P  < 0.001) differences in total daily basal dose between genders in all age groups except adults. In addition, the shape of the expected basal-rate pattern differed by body mass index, HbA1c, and use of continuous glucose monitoring. Discussion: This analysis demonstrates multiple factors influencing basal patterns and insulin requirement, including age group, gender, overweight, HbA1c, bolus frequency, and sensor use. As circadian basal rates are still mandatory for initiating insulin pump therapy with or without automation, a multimodal approach is necessary to estimate optimal basal rates.

Objective: To investigate the frequency, treatment, and outcome of patients with diabetes due to severe insulin resistance syndromes (SIRS)., Research Design and Methods: Based on data from the multicenter prospective Diabetes Registry DPV, we analyzed diagnosis, treatment, and outcome of 636,777 patients with diabetes from 1995 to 2022., Results: Diabetes due to SIRS was documented in 67 cases (62.7% females), 25 (37%) had lipodystrophies (LD) and 42 (63%) had congenital defects of insulin signaling. The relative frequency compared to type 1 diabetes (T1D) was about 1:2300. Median age at diabetes diagnosis in patients with SIRS was 14.8 years (interquartile range (IQR) 12.8-33.8). A total of 38 patients with SIRS (57%) received insulin and 34 (51%) other antidiabetics, mostly metformin. As high as 16% of patients with LD were treated with fibrates. Three out of eight patients with generalized LD (37.5%) were treated with metreleptin and one patient with Rabson-Mendenhall syndrome was treated with recombinant insulin-like growth factor 1. The median glycated hemoglobin level at follow-up was 7.1% (54 mmol/mol). Patients with LD had higher triglycerides than patients with T1D and T2D (P < 0.001 and P = 0.022, respectively), and also significantly higher liver enzymes and lower high-density lipoprotein cholesterol than patients with T1D (P < 0.001). Patients with insulin receptor disorders were significantly less likely to be treated with antihypertensive medication than patients with T2D (P = 0.042), despite having similar levels of hypertension., Conclusions: Diabetes due to SIRS is rarely diagnosed and should be suspected in lean children or young adults without classical T1D. Awareness of cardiovascular risk factors in these patients should be raised.

In contrast to adults, type 1 diabetes mellitus (T1D) is the most frequent form of diabetes in childhood and adolescence (> 90%). After diagnosis the management of children and adolescents with T1D should take place in highly specialized pediatric units experienced in pediatric diabetology. The lifelong substitution of insulin is the cornerstone of treatment whereby modalities need to be individually adapted for patient age and the family routine. In this age group the usage of diabetes technology (glucose sensors, insulinpumps and recently hybrid-closed-loop-systems) is recommended. An optimal metabolic control right from the start of therapy is associated with an improved long-term prognosis. Diabetes education is essential in the management of patients with diabetes and their families and needs to be performed by a multidisciplinary team consisting of a pediatric diabetologists, diabetes educator, dietitian, psychologist and social worker. The Austrian working group for pediatric endocrinology and diabetes (APEDÖ) and the ISPAD (International Society for Pediatric and Adolescent Diabetes) recommend a metabolic goal of HbA1c ≤ 7.0%, ((IFCC) < 53 mmol/mol), and a "Time in range" > 70% for all pediatric age groups without the presence of severe hypoglycemia. Age-related physical, cognitive and psychosocial development, screening for associated diseases, avoidance of acute diabetes-related complications (severe hypoglycemia, diabetic ketoacidosis) and prevention of diabetes-related late complications to ensure high quality of life are the main goals of diabetes treatment in all pediatric age groups., (© 2023. The Author(s).)

Hyperglycemia significantly contributes to complications in patients with diabetes mellitus. While lifestyle interventions remain cornerstones of disease prevention and treatment, most patients with type 2 diabetes will eventually require pharmacotherapy for glycemic control. The definition of individual targets regarding optimal therapeutic efficacy and safety as well as cardiovascular effects is of great importance. In this guideline we present the most current evidence-based best clinical practice data for healthcare professionals., (© 2023. The Author(s).)

This Guideline represents the recommendations of the Austrian Diabetes Association (ÖDG) on the use of diabetes technology (insulin pump therapy; continuous glucose monitoring, CGM; hybrid closed-loop systems, HCL; diabetes apps) and access to these technological innovations for people with diabetes mellitus based on current scientific evidence., (© 2023. The Author(s).)

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.

Objective: To evaluate the impact of CamAPS FX hybrid closed-loop (HCL) automated insulin delivery in very young children with type 1 diabetes (T1D) on caregivers' well-being, fear of hypoglycemia, and sleepiness., Research Design and Methods: We conducted a multinational, open-label, randomized crossover study. Children (age 1-7 years) with T1D received treatment for two 4-month periods in random order, comparing HCL with sensor augmented pump (control). At baseline and after each treatment period, caregivers were invited to complete World Health Organization-Five Well-Being Index, Hypoglycemia Fear Survey, and Epworth Sleepiness Scale questionnaires., Results: Caregivers of 74 children (mean ± SD age 5 ± 2 years and baseline HbA1c 7.3 ± 0.7%; 42% female) participated. Results revealed significantly lower scores for hypoglycemia fear (P < 0.001) and higher scores for well-being (P < 0.001) after HCL treatment. A trend toward a reduction in sleepiness score was observed (P = 0.09)., Conclusions: Our results suggest better well-being and less hypoglycemia fear in caregivers of very young children with T1D on CamAPS FX HCL., (© 2022 by the American Diabetes Association.)

Objectives: We explored parents' views about healthcare professionals having remote access to their young child's insulin and glucose data during a clinical trial to inform use of data sharing in routine pediatric diabetes care., Research Design and Methods: Interviews with 33 parents of 30 children (aged 1-7 years) with type 1 diabetes participating in a randomized trial (KidsAP02) comparing hybrid closed-loop system use with sensor-augmented pump therapy. Data were analyzed using a qualitative descriptive approach., Results: Parents reported multiple benefits to healthcare professionals being able to remotely access their child's glucose and insulin data during the trial, despite some initial concerns regarding the insights offered into everyday family life. Key benefits included: less work uploading/sharing data; improved consultations; and, better clinical input and support from healthcare professionals between consultations. Parents noted how healthcare professionals' real-time data access facilitated remote delivery of consultations during the COVID-19 pandemic, and how these were more suitable for young children than face-to-face appointments. Parents endorsed use of real-time data sharing in routine clinical care, subject to caveats regarding data access, security, and privacy. They also proposed that, if data sharing were used, consultations for closed-loop system users in routine clinical care could be replaced with needs-driven, ad-hoc contact., Conclusions: Real-time data sharing can offer clinical, logistical, and quality-of-life benefits and enhance opportunities for remote consultations, which may be more appropriate for young children. Wider rollout would require consideration of ethical and cybersecurity issues and, given the heightened intrusion on families' privacy, a non-judgmental, collaborative approach by healthcare professionals., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Aims: To explore parents' experiences of using remote monitoring technology when caring for a very young child with type 1 diabetes during a clinical trial., Methods: Interviews were conducted with parents of 30 children (aged 1-7 years) participating in a trial (the KidsAP02 study) comparing hybrid closed-loop insulin delivery with sensor-augmented pump therapy. In both arms, parents had access to remote monitoring technology. Data analysis focused on identification of descriptive themes., Results: Remote monitoring technology gave parents improved access to data which helped them pre-empt and manage glucose excursions. Parents observed how, when children were in their own care, they could be more absent while present, as their attention could shift to non-diabetes-related activities. Conversely, when children were others' care, remote monitoring enabled parents to be present while absent, by facilitating oversight and collaboration with caregivers. Parents described how remote monitoring made them feel more confident allowing others to care for their children. Parents' confidence increased when using a hybrid closed-loop system, as less work was required to keep glucose in range. Benefits to children were also highlighted, including being able to play and sleep uninterrupted and attend parties and sleepovers without their parents. While most parents welcomed the increased sense of control remote monitoring offered, some noted downsides, such as lack of respite from caregiving responsibilities., Conclusions: Remote monitoring can offer manifold benefits to both parents and very young children with type 1 diabetes. Some parents, however, may profit from opportunities to take 'time out'., (© 2022 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.)

Background: Hyperinsulinism results from inappropriate insulin secretion during hypoglycaemia. Down syndrome is causally linked to a number of endocrine disorders including Type 1 diabetes and neonatal diabetes. We noted a high number of individuals with Down syndrome referred for hyperinsulinism genetic testing, and therefore aimed to investigate whether the prevalence of Down syndrome was increased in our hyperinsulinism cohort compared to the population., Methods: We identified individuals with Down syndrome referred for hyperinsulinism genetic testing to the Exeter Genomics Laboratory between 2008 and 2020. We sequenced the known hyperinsulinism genes in all individuals and investigated their clinical features., Results: We identified 11 individuals with Down syndrome in a cohort of 2011 patients referred for genetic testing for hyperinsulinism. This represents an increased prevalence compared to the population (2.5/2011 expected vs. 11/2011 observed, p = 6.8 × 10 -5 ). A pathogenic ABCC8 mutation was identified in one of the 11 individuals. Of the remaining 10 individuals, five had non-genetic risk factors for hyperinsulinism resulting from the Down syndrome phenotype: intrauterine growth restriction, prematurity, gastric/oesophageal surgery, and asparaginase treatment for leukaemia. For five individuals no risk factors for hypoglycaemia were reported although two of these individuals had transient hyperinsulinism and one was lost to follow-up., Conclusions: Down syndrome is more common in patients with hyperinsulinism than in the population. This is likely due to an increased burden of non-genetic risk factors resulting from the Down syndrome phenotype. Down syndrome should not preclude genetic testing as coincidental monogenic hyperinsulinism and Down syndrome is possible., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Aims: To explore parents' experiences of using a hybrid closed-loop system (CamAPS FX) when caring for a very young child (aged 1-7 years) with type 1 diabetes., Methods: Interviews with n = 33 parents of 30 children who used the system during a randomised controlled trial. Data analysis used a descriptive thematic approach., Results: While some parents were initially reticent about handing control to the system, all reported clinical benefits to using the technology, having to do less diabetes-related work and needing less clinical input over time. Parents welcomed opportunities to enhance the system's efficacy (using Ease-off and Boost functions) as required. Parents described how the system's automated glucose control facilitated more normality, including sleeping better, worrying less about their child, and feeling more confident and able to outsource care. Parents also described more normality for the child (alongside better sleep, mood and concentration, and lessened distress) and siblings. Parents liked being able to administer insulin using a smartphone, but suggested refinements to device size and functionality., Conclusions: Using a hybrid closed-loop system in very young children can facilitate greater normality and may result in a lessened demand for health professionals' input. Systems may need to be customised for very young children., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Aims: To update and extend a previous cross-sectional international comparison of glycaemic control in people with type 1 diabetes., Methods: Data were obtained for 520,392 children and adults with type 1 diabetes from 17 population and five clinic-based data sources in countries or regions between 2016 and 2020. Median HbA 1c (IQR) and proportions of individuals with HbA 1c < 58 mmol/mol (<7.5%), 58-74 mmol/mol (7.5-8.9%) and ≥75 mmol/mol (≥9.0%) were compared between populations for individuals aged <15, 15-24 and ≥25 years. Logistic regression was used to estimate the odds ratio (OR) of HbA 1c < 58 mmol/mol (<7.5%) relative to ≥58 mmol/mol (≥7.5%), stratified and adjusted for sex, age and data source. Where possible, changes in the proportion of individuals in each HbA 1c category compared to previous estimates were calculated., Results: Median HbA 1c varied from 55 to 79 mmol/mol (7.2 to 9.4%) across data sources and age groups so a pooled estimate was deemed inappropriate. OR (95% CI) for HbA 1c < 58 mmol/mol (<7.5%) were 0.91 (0.90-0.92) for women compared to men, 1.68 (1.65-1.71) for people aged <15 years and 0.81 (0.79-0.82) aged15-24 years compared to those aged ≥25 years. Differences between populations persisted after adjusting for sex, age and data source. In general, compared to our previous analysis, the proportion of people with an HbA 1c  < 58 mmol/l (<7.5%) increased and proportions of people with HbA 1c ≥ 75 mmol/mol (≥9.0%) decreased., Conclusions: Glycaemic control of type 1 diabetes continues to vary substantially between age groups and data sources. While some improvement over time has been observed, glycaemic control remains sub-optimal for most people with Type 1 diabetes., (© 2021 Diabetes UK.)

Laboratory measured glycated haemoglobin (HbA1c) is the gold standard for assessing glycaemic control in people with diabetes and correlates with their risk of long-term complications. The emergence of continuous glucose monitoring (CGM) has highlighted limitations of HbA1c testing. HbA1c can only be reviewed infrequently and can mask the risk of hypoglycaemia or extreme glucose fluctuations. While CGM provides insights in to the risk of hypoglycaemia as well as daily fluctuations of glucose, it can also be used to calculate an estimated HbA1c that has been used as a substitute for laboratory HbA1c. However, it is evident that estimated HbA1c and HbA1c values can differ widely. The glucose management indicator (GMI), calculated exclusively from CGM data, has been proposed. It uses the same scale (% or mmol/mol) as HbA1c, but is based on short-term average glucose values, rather than long-term glucose exposure. HbA1c and GMI values differ in up to 81% of individuals by more than ±0.1% and by more than ±0.3% in 51% of cases. Here, we review the factors that define these differences, such as the time period being assessed, the variation in glycation rates and factors such as anaemia and haemoglobinopathies. Recognizing and understanding the factors that cause differences between HbA1c and GMI is an important clinical skill. In circumstances when HbA1c is elevated above GMI, further attempts at intensification of therapy based solely on the HbA1c value may increase the risk of hypoglycaemia. The observed difference between GMI and HbA1c also informs the important question about the predictive ability of GMI regarding long-term complications., (© 2022 John Wiley & Sons Ltd.)

Objective: To assess personality factors, coping, developmental conditions and quality of life in female adolescents and young adults with type 1 diabetes (T1D) and high vs.low HbA1c., Methods: Patients were approached at the Department for Pediatrics, Medical University of Vienna; n = 129 female adolescents (10 to 23 years, mean age 15.21 ± 2.91) with type 1 diabetes were included. HIGH-A1c was defined as HbA1c > 7.5%, LOW-A1c as HbA1c ≤ 7.5% and compared to a sample of 56 age-matched female healthy controls. Self-rating questionnaires were used to assess psychosocial factors: Children's Depression Inventory (CDI); Junior Temperament and Character Inventory (J-TCI); Eating Disorders Inventory-2 (EDI-2); KIDCOPE; Subjective Family Image Test (SFIT) and Inventory of Life Quality in Children and Adolescents (ILC)., Results: T1D patients with HIGH-A1c were younger at the age of diabetes onset, had a longer diabetes duration, a higher maximum BMI, higher depression score, and higher frequency of diabetic ketoacidosis in the last year. They showed significantly higher levels of fatigue, lower levels of taking responsibility, lower ability to set goals and lower self-acceptance, as well as higher levels of ineffectiveness, lower levels of emotional attachment within the family, in particular with the fathers, and used negative coping strategies more often compared to patients with LOW-A1c. Furthermore, they reported significantly higher burden of illness and lower quality of life., Conclusions: Disadvantageous personality and coping styles as well as developmental conditions should be addressed in the treatment of female adolescents with T1D with management problems., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wagner, Zeiler, Karwautz, Schneider, Rami-Merhar and Berger.)

Objective: We analyzed the annual prevalence of onset-DKA (diabetic ketoacidosis) from 2012 to 2020 with a sub-analysis for lockdown-periods during the COVID-19 pandemic in 2020., Design: All newly diagnosed children with type 1 diabetes (T1D) aged <15 years are prospectively registered in the population-based Austrian Diabetes Incidence Study in Austria., Main Outcome Measures: The annual DKA prevalence was analyzed using Joinpoint regression. Definition of DKA: pH <7.3, mild DKA: pH 7.3 to ≤ 7.1, severe DKA: pH <7.1. DKA prevalence during the lockdown periods in 2020 and the corresponding periods in 2015-2019 were examined using Fisher's exact test., Results: In the years 2012-2020 the mean prevalence for onset-DKA in Austria was 43.6% [95%CI (confidence interval): 41.6, 45.7] and thus above the mean prevalence of previous decades (1989-2011) of 37,1 % (95%CI: 35.6, 38.6). A particularly high prevalence was found among children <2 years of age (72.0% DKA, 32.8% severe DKA). No significant gender difference was found. Prevalence of severe DKA at T1D-onset increased significantly since 2015 ( p = 0.023). During the lockdown in 2020, 59.3% of children were diagnosed with DKA at T1D-onset, compared to 42.1% during the previous 5 years ( p = 0.022). Moreover, 20% of children had severe DKA at T1D diagnosis, compared to 14% during the comparison period., Conclusions: The previously already high prevalence of DKA at T1D-onset has further increased over time. The COVID-19 pandemic has exacerbated the problem of a late or delayed diagnosis of diabetes in children resulting in onset-DKA. The alarmingly increased prevalence of DKA in Austrian children with T1D calls for urgent action., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Nagl, Waldhör, Hofer, Fritsch, Meraner, Prchla, Rami-Merhar and Fröhlich-Reiterer.)

Background: Type 1 diabetes in young children is a heavy parental burden. As part of pilot phase of the KIDSAP01 study, we conducted a baseline assessment in parents to study the association between hypoglycemia fear, parental well-being and child behavior., Methods: All parents were invited to fill in baseline questionnaires: hypoglycemia fear survey (HFS), WHO-5, Epworth Sleepiness Scale and Strength and Difficulties Questionnaire (SDQ)., Results: 24 children (median age: 5-year, range 1-7 years, 63% male, mean diabetes duration: 3 ± 1.7 years) participated. 23/24 parents filled out the questionnaires. We found a higher score for the hypoglycemia fear behavior 33.9 ± 5.6 compared to hypoglycemia worry 34.6 ± 12.2. Median WHO-5 score was 16 (8 - 22) with poor well-being in two parents. Median daytime sleepiness score was high in five parents (>10). For six children a high total behavioral difficulty score (>16) was reported. Pro social behavior score was lower than normal in six children (<6). Parental well-being was negatively associated with HFS total ( r = - 0.50, p <.05) and subscale scores ( r = - 0.44, p <.05 for HFS-Worry and HFS-Behavior), child behavior ( r = - 0.45, p = .05) and positively with child age and diabetes duration ( r = 0.58, p <.01, r = 0.6, p <.01). HFS, parental well-being nor daytime sleepiness are associated with the HbA1c., Conclusion: Regular screening of parental well-being, hypoglycemia fear and child behavior should be part of routine care to target early intervention., Competing Interests: MT reports having received speaker honoraria from Minimed Medtronic and Novo Nordisk. MFr has received speaker honoraria from Minimed Medtronic and has served on advisory boards for Eli Lilly. JM is a member in the advisory board of Becton-Dickinson, Boehringer Ingelheim, Eli Lilly, Medtronic and Sanofi, and has received speaker honoraria from ABBOTT Diabetes Care, Astra Zeneca, Eli Lilly, Nintamed, Novo Nordisk, Roche Diabetes Care, Sanofi, Servier and Takeda. MW has received license fees from Becton Dickinson and has served as a consultant to Beckton Dickinson. SH declares speaker honoraria from Eli Lilly and Sanofi. EF-R reports having received speaker honoraria from Minimed Medtronic and Eli Lilly, serving on advisory boards for Eli Lilly. TK has received speaker honoraria from Minimed Medtronic, Roche and Eli Lilly and is member of an advisory board for ABBOTTt Diabetes Care. CdB has received speaker honoraria from Minimed Medtronic and is member of their European Psychology Advisory Board. FC does attend Advisory Boards and obtain speaking fees for ABBOTTt, Medtronic, Lilly, and NovoNordisk. BR-M reports having received speaker honoraria from Minimed Medtronic, Eli Lilly, Roche, Menarini and Novo Nordisk, serving on advisory boards for Eli Lilly. RH reports having received speaker honoraria from Eli Lilly, Dexcom and Novo Nordisk, receiving license fees from Medtronic, and being director at CamDiab. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 de Beaufort, Pit-ten Cate, Schierloh, Cohen, Boughton, Tauschmann, Allen, Nagl, Fritsch, Yong, Metcalfe, Schaeffer, Fichelle, Thiele, Abt, Faninger, Mader, Slegtenhorst, Ashcroft, Wilinska, Sibayan, Kollman, Hofer, Fröhlich-Reiterer, Kapellen, Acerini, Campbell, Rami-Merhar and Hovorka.)

Objective: To characterize patients with diabetes treated with a tubeless insulin pump (Omnipod ® Insulin Management System; Insulet Corp., Acton, MA), and to evaluate the frequency of acute complications with long-term use of the system. Methods: This retrospective analysis of the German/Austrian Diabetes Patienten Verlaufsdokumentation (DPV) registry included data from 3657 patients with diabetes ( n  = 3582 type 1, n  = 25 type 2, n  = 50 latent autoimmune diabetes in adults/other) treated with a tubeless insulin pump. Hemoglobin A1c (HbA1c) levels and frequency of diabetic ketoacidosis (DKA) and severe hypoglycemia (SH) were compared between 1 year pre- and 1 year ( n  = 2911) or up to 3 years ( n  = 1311) post-tubeless insulin pump initiation and compared with a contemporary cohort on multiple daily injections (MDI) with 3-year data ( n  = 1874). Results: Patients using tubeless insulin pump therapy had a median age of 13.7 years [interquartile range 10.8, 17.3], diabetes duration 3.7 years [1.7, 8.0], and HbA1c 7.5% [6.9, 8.2]. In patients with 3 years of follow-up data ( n  = 1311), the percentage with ≥1 episode of DKA, SH (Level 3, requiring assistance), and SH (coma) event with prior treatment was 6.3%, 5.5%, and 1.7%, respectively. After 3 years of tubeless insulin pump therapy, the frequency of DKA, SH (Level 3), and SH (coma) decreased to 2.2%, 4.1%, and 0.5%, respectively. Both DKA and SH remained significantly lower compared with MDI after adjustment in multiple regression analysis. High treatment retention rates (>90%) were observed. Conclusion: Real-world registry data document that tubeless insulin pump therapy is associated with good glycemic control and a low frequency of DKA and SH in an age group prone to acute complications.

Background and Objective: Intermittent scanning continuous glucose monitoring (iscCGM) is increasingly used for glycemic monitoring in diabetes care. In this cross-sectional real-world analysis, iscCGM data were compared to traditional parameters of glycemic control in young people with type 1 diabetes. Methods: Using the DPV registry, most recent data from children and adolescents aged <18 years with uploaded iscCGM sensor profiles with at least 14 days of data and a > 50% completeness were evaluated using recommended parameters of sensor metrics. Analysis was performed stratified by age group, glycemic control, and type of therapy; data were taken from DPV data pool in February 2020. Results: Glucose sensor profiles and clinical data from 1809 individuals (mean age 13.4 years, 53% male, and mean diabetes duration 5.02 years) were evaluated in this study. More than 50% of this population ( n  = 965) reached the current German treatment target of hemoglobin A1c (HbA1c) <7.5%. In this target, the mean scanning frequency was higher than in groups with HbA1c >7.5 or >8.0% (12.0 vs. 10.2 vs 7.6 times per day). The group of preschool children had the highest frequency of scanning (16.6 vs. 13.3 times per day in school kids and 7.9 in adolescents), the lowest HbA1c level, and the lowest risk for hypoglycemia (low blood glucose index 0.8 vs. 1.0 vs 1.2). Conclusion: Real-world data will help to determine the value of iscCGM to improve clinical and patient-related outcomes in pediatric diabetology. Not only the use of a device but also the intensity of use seems to have a high and direct impact on glycemic control.

The aim of this study was to assess accuracy of the three most commonly used continuous glucose monitoring (CGM) systems in almost real-life situation during a diabetes camp in children with type 1 diabetes (T1D) aged 9-14 years. Data was gathered during a 2-week summer camp under physicians' supervision. Out of 38 participating children with T1D (aged: 11.0 [9.9; 12.1] years; 57% girls, mean HbA1c 7.2 [6.9; 7.7] %,) 37 wore a CGM system (either Abbott FreeStyle Libre (FSL), Dexcom G6 (DEX) or Medtronic Enlite (ENL)) throughout the camp. All concomitantly available data pairs of capillary glucose measurements and sensor values were used for the analysis. Mean absolute relative difference (MARD) was calculated and Parkes Error Grid analyses were done for all three systems used. In total 2079 data pairs were available for analysis. The overall MARDs of CGM systems used at the camp was FSL: 13.3% (6.7;21.6). DEX: 10.3% (5.8; 16.7) and ENL 8.5% (3.6; 15.6). During eu-, hypo- and hyperglycemia MARDs were lowest in ENL. Highest MARDs were seen in hypoglycemia, where all three systems exhibited MARDs above 15%. Overnight MARDs of all systems was higher than during daytime. All sensors performed worst in hypoglycemia. Performance of the adequately calibrated Medtronic system outperformed the factory-calibrated sensors. For clinical practice, it is important to adequately train children with T1D and families in the correct procedures for sensors that require calibrations., (© 2020 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Introduction: Diabetes management in very young children remains challenging. Glycaemic targets are achieved at the expense of high parental diabetes management burden and frequent hypoglycaemia, impacting quality of life for the whole family. Our objective is to assess whether automated insulin delivery can improve glycaemic control and alleviate the burden of diabetes management in this particular age group., Methods and Analysis: The study adopts an open-label, multinational, multicentre, randomised, crossover design and aims to randomise 72 children aged 1-7 years with type 1 diabetes on insulin pump therapy. Following screening, participants will receive training on study insulin pump and study continuous glucose monitoring devices. Participants will be randomised to 16-week use of the hybrid closed-loop system (intervention period) or to 16-week use of sensor-augmented pump therapy (control period) with 1-4 weeks washout period before crossing over to the other arm. The order of the two study periods will be random. The primary endpoint is the between-group difference in time spent in the target glucose range from 3.9 to 10.0 mmol/L based on sensor glucose readings during the 16-week study periods. Analyses will be conducted on an intention-to-treat basis. Key secondary endpoints are between group differences in time spent above and below target glucose range, glycated haemoglobin and average sensor glucose. Participants' and caregivers' experiences will be evaluated using questionnaires and qualitative interviews, and sleep quality will be assessed. A health economic analysis will be performed., Ethics and Dissemination: Ethics approval has been obtained from Cambridge East Research Ethics Committee (UK), Ethics Committees of the University of Innsbruck, the University of Vienna and the University of Graz (Austria), Ethics Committee of the Medical Faculty of the University of Leipzig (Germany) and Comité National d'Ethique de Recherche (Luxembourg). The results will be disseminated by peer-reviewed publications and conference presentations., Trial Registration Number: NCT03784027., Competing Interests: Competing interests: SEH declares speaker honoraria from Eli Lilly, Pfizer and Sanofi. EF-R reports having received speaker honoraria from Minimed Medtronic and Eli Lilly, serving on advisory boards for Eli Lilly. TMK has received speaker honoraria from Minimed Medtronic, Roche and Eli Lilly and consulted Sanofi-Aventis. CdB has received speaker honoraria from Minimed Medtronic, and is member of their European Psychology Advisory Board. BR-M reports having received speaker honoraria from Abbott, Minimed Medtronic, Eli Lilly, Roche, Menarini and Novo Nordisk, serving on advisory boards for Eli Lilly. FC has received speaking fees from Abbott, Medtronic and Eli Lilly. RH reports having received speaker honoraria from Eli Lilly and Novo Nordisk, serving on advisory panel for Eli Lilly and Novo Nordisk; receiving license fees from BBraun and Medtronic; having served as a consultant to BBraun, patents and patent applications related to closed-loop insulin delivery, and director at CamDiab. JKM is shareholder of Decide Clinical Software, a member in the advisory board of Boehringer Ingelheim, Eli Lilly, Medtronic, Prediktor A/S, Roche Diabetes Care, Sanofi-Aventis and received speaker honoraria from Abbott Diabetes Care, Astra Zeneca, Dexcom, Eli Lilly, NovoNordisk A/S, Roche Diabetes Care, Servier and Takeda., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Objective: To analyze the time trends of nationwide diabetes incidence <15 years of age from 1989 until 2017 in Austria., Methods: The Austrian Diabetes Incidence Study Group registers all newly diagnosed patients with diabetes mellitus <15 years of age in a prospective population-based study. The diabetes type was classified on the basis of clinical and laboratory findings according to American Diabetes Association criteria. Time trends were estimated by Joinpoint analysis., Results: 1311 patients were diagnosed with type 1 diabetes (T1D) between 1989 and 1999 and 4624 patients with any type of diabetes (1999-2017). T1D accounted for the majority of cases (94.2%), 1.8% were classified as type 2 (T2D) and 4.0% as other specific types of diabetes (1999-2017). In the total cohort (age 0 to <15 years), a constant increase until 2012 (annual percent change [APC] 4.5, 95% confidence interval [CI]: 3.94, 5.06) was observed, followed by a leveling off with a corresponding drop (APC 0.28, 95%CI: -3.94, 4.69). This observation was mainly driven by the dynamic in the youngest age group (0-4 years) with a steep increase until 2007 (APC 7.1, 95%CI: 5.05, 9.19) and a decrease from 2007 to 2017 (APC -0.86, 95%CI: 4.41, 2.82). No significant increase of T2D <15 years was detected. Over the observed time period (APC = 3.7, 95%CI: -0.30, 7.78)., Conclusions: The incidence of T1D is declining in young children aged 0 to 4 years, but is still rising in children 5 to 14 years in Austria. Incidence of T2D did not increase significantly and other specific types of diabetes occur twice as often compared to T2D., (© 2020 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Aims/hypothesis: The aim of this work was to evaluate geographical variability and trends in the prevalence of diabetic ketoacidosis (DKA), between 2006 and 2016, at the diagnosis of childhood-onset type 1 diabetes in 13 countries over three continents., Methods: An international retrospective study on DKA at diagnosis of diabetes was conducted. Data on age, sex, date of diabetes diagnosis, ethnic minority status and presence of DKA at diabetes onset were obtained from Australia, Austria, Czechia, Denmark, Germany, Italy, Luxembourg, New Zealand, Norway, Slovenia, Sweden, USA and the UK (Wales). Mean prevalence was estimated for the entire period, both overall and by country, adjusted for sex and age group. Temporal trends in annual prevalence of DKA were estimated using logistic regression analysis for each country, before and after adjustment for sex, age group and ethnic minority status., Results: During the study period, new-onset type 1 diabetes was diagnosed in 59,000 children (median age [interquartile range], 9.0 years [5.5-11.7]; male sex, 52.9%). The overall adjusted DKA prevalence was 29.9%, with the lowest prevalence in Sweden and Denmark and the highest in Luxembourg and Italy. The adjusted DKA prevalence significantly increased over time in Australia, Germany and the USA while it decreased in Italy. Preschool children, adolescents and children from ethnic minority groups were at highest risk of DKA at diabetes diagnosis in most countries. A significantly higher risk was also found for females in Denmark, Germany and Slovenia., Conclusions/interpretation: DKA prevalence at type 1 diabetes diagnosis varied considerably across countries, albeit it was generally high and showed a slight increase between 2006 and 2016. Increased awareness of symptoms to prevent delay in diagnosis is warranted, especially in preschool children, adolescents and children from ethnic minority groups.

Background To investigate longitudinal trends of admissions with diabetic ketoacidosis (DKA) in new-onset type 1 diabetes (T1D) and subsequent duration of hospitalization in association with structural health care properties, such as size of treatment facility, population density and linear distance between home and treatment centers. Methods Data from 24,321 German and Austrian pediatric patients with newly-diagnosed T1D between 2008 and 2017 within the DPV registry were analyzed. Results Onset-DKA rates fluctuated at around 19% and slightly increased over the observation period (p<0.001). Compared to children without onset-DKA, children with onset-DKA were more frequently treated at centers located closer to their homes, independent of center size or urbanity. Annual median duration of hospitalization decreased from 13.1 (12.6;13.6) to 12.7 (12.3;13.2) days (p<0.001). It was highest in patients younger than 5 years, with migration background, and in severe DKA. Conclusion Patients with onset-DKA are admitted to the nearest hospital, independent of center size. Facilities close to patients' homes therefore play an important role in the acute management of T1D onset. In Germany and Austria, diabetes education at diagnosis is mainly performed in inpatient settings. This is reflected by a long duration of hospitalization, which has decreased only slightly over the past decade.