Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis.

Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing "MODY calculator" cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish 'Better Diabetes Diagnosis' (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.

Prevalence and Predictive Factors for Celiac Disease in Children With Type 1 Diabetes: Whom and When to Screen? A Nationwide Longitudinal Cohort Study of Swedish Children.

OBJECTIVE: To examine the prevalence and predictive factors for celiac disease (CD) after a diagnosis of type 1 diabetes (T1D) in children and adolescents, to improve the current screening guidelines. RESEARCH DESIGN AND METHODS: The association between sex, age at T1D diagnosis, HLA, and diabetes autoantibodies, and a diagnosis of CD was examined in 5,295 children with T1D from the Better Diabetes Diagnosis study in Sweden. RESULTS: The prevalence of biopsy-proven CD was 9.8%, of which 58.2% already had a CD diagnosis before or at T1D onset. Almost all, 95.9%, were diagnosed with CD within 5 years after the T1D diagnosis. Younger age at the T1D diagnosis and being homozygote for DQ2 increased the risk of CD after T1D, but neither sex nor diabetes-related autoantibodies were associated with the risk. CONCLUSIONS: Age at and time after diabetes diagnosis should be considered in screening guidelines for CD in children with T1D.

Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data.

The type 1 diabetes community is coalescing around the benefits and advantages of early screening for disease risk. To be accepted by healthcare providers, regulatory authorities and payers, screening programmes need to show that the testing variables allow accurate risk prediction and that individualised risk-informed monitoring plans are established, as well as operational feasibility, cost-effectiveness and acceptance at population level. Artificial intelligence (AI) has the potential to contribute to solving these issues, starting with the identification and stratification of at-risk individuals. ASSET (AI for Sustainable Prevention of Autoimmunity in the Society; www.asset.healthcare ) is a public/private consortium that was established to contribute to research around screening for type 1 diabetes and particularly to how AI can drive the implementation of a precision medicine approach to disease prevention. ASSET will additionally focus on issues pertaining to operational implementation of screening. The authors of this article, researchers and clinicians active in the field of type 1 diabetes, met in an open forum to independently debate key issues around screening for type 1 diabetes and to advise ASSET. The potential use of AI in the analysis of longitudinal data from observational cohort studies to inform the design of improved, more individualised screening programmes was also discussed. A key issue was whether AI would allow the research community and industry to capitalise on large publicly available data repositories to design screening programmes that allow the early detection of individuals at high risk and enable clinical evaluation of preventive therapies. Overall, AI has the potential to revolutionise type 1 diabetes screening, in particular to help identify individuals who are at increased risk of disease and aid in the design of appropriate follow-up plans. We hope that this initiative will stimulate further research on this very timely topic.

Relative poverty is associated with increased risk of diabetic ketoacidosis at onset of type 1 diabetes in children. A Swedish national population-based study in 2014-2019.

AIMS: The aim of the study was to estimate the effect of household relative poverty on the risk of diabetic ketoacidosis at diagnosis of children with type 1 diabetes using an international standard measurement of relative poverty. METHODS: A national population-based retrospective study was conducted. The Swedish National Diabetes Register (NDR) was linked with data from Sweden's public statistical agency (Statistics Sweden). Children who were diagnosed with new-onset type 1 diabetes in the period of 2014-2019 were common identifiers. The definition of diabetic ketoacidosis was venous pH <7.30 or a serum bicarbonate level <18 mmol/L. The exposure variable was defined according to the standard definition of the persistent at-risk-of-poverty rate used by the statistical office of the European Union (Eurostat) and several other European public statistical agencies. Univariate and multi-variable analyses were used to calculate the effect of relative poverty on the risk of diabetic ketoacidosis. RESULTS: Children from households with relative poverty had a 41% higher risk of diabetic ketoacidosis (1.41, CI 1.12-1.77, p = 0.004) and more than double the risk of severe diabetic ketoacidosis (pH <7.10) (RR 2.10, CI 1.35-3.25, p = 0.001), as compared to children from households without relative poverty. CONCLUSIONS: Relative poverty significantly increases the risk of diabetic ketoacidosis at onset of type 1 diabetes in children, even in a high-income country with publicly reimbursed health care.

Sex Differences in Age of Diagnosis, HLA Genotype, and Autoantibody Profile in Children With Type 1 Diabetes.

OBJECTIVE: To examine sex differences in children with newly diagnosed type 1 diabetes (T1D) with respect to age at diagnosis, presence of autoantibodies (GAD antibody [GADA], insulinoma-associated protein 2 [IA-2A], insulin autoantibody [IAA], and zinc transporter 8 autoantibody), and HLA risk. RESEARCH DESIGN AND METHODS: A population-based nationwide sample of 3,645 Swedish children at T1D diagnosis was used. RESULTS: Girls were younger at T1D diagnosis (9.53 vs. 10.23 years; P < 0.001), more likely to be autoantibody-positive (94.7% vs. 92.0%; P = 0.002), more often positive for multiple autoantibodies (P < 0.001), more likely to be positive for GADA (64.9% vs. 49.0%; P < 0.001), and less likely to be positive for IAA (32.3% vs. 33.8%; P = 0.016). Small sex differences in HLA risk were found in children <9 years of age. CONCLUSIONS: The disease mechanisms leading to T1D may influence the immune system differently in girls and boys.

Circulating microRNAs in young individuals with long-duration type 1 diabetes in comparison with healthy controls.

MicroRNAs (miRNAs) are short non-coding RNAs that are involved in post-transcriptional control of gene expression and might be used as biomarkers for diabetes-related complications. The aim of this case-control study was to explore potential differences in circulating miRNAs in young individuals with long-duration type 1 diabetes (T1D) compared to healthy controls, and how identified miRNAs are expressed across different tissues. Twelve adolescents, age 15.0-17.9 years, with T1D duration of more than 8 years (mean 11.1 years), were enrolled from the Swedish diabetes quality registry. An age-matched control group was recruited. Circulating miRNAs (n = 187) were analyzed by quantitative PCR. We observed that 27 miRNAs were upregulated and one was downregulated in T1D. Six of these miRNAs were tissue-enriched (blood cells, gastrointestinal, nerve, and thyroid tissues). Six miRNAs with the largest difference in plasma, five up-regulated (hsa-miR-101-3p, hsa-miR-135a-5p, hsa-miR-143-3p, hsa-miR-223-3p and hsa-miR-410-3p (novel for T1D)) and one down-regulated (hsa-miR-495-3p), with P-values below 0.01, were selected for further in-silico analyses. AKT1, VEGFA and IGF-1 were identified as common targets. In conclusion, 28 of the investigated miRNAs were differently regulated in long-duration T1D in comparison with controls. Several associations with cancer were found for the six miRNAs with the largest difference in plasma.

Insulin pump therapy is associated with higher rates of mild diabetic ketoacidosis compared to injection therapy: A 2-year Swedish national survey of children and adolescents with type 1 diabetes.

OBJECTIVES: Diabetic ketoacidosis (DKA) in type 1 diabetes (T1D) can occur during both insulin pump therapy (continuous subcutaneous insulin infusion, CSII) and insulin injection therapy (multiple daily injections, MDI). The primary aim of this study was to compare CSII and MDI regarding DKA frequency. A secondary aim was to compare metabolic derangement between CSII and MDI at hospital admission for DKA. RESEARCH DESIGN AND METHODS: Children 0-17.99 years with established T1D admitted for DKA in Sweden from February 1, 2015 to January 31, 2017 were invited to participate. Data regarding demographics, laboratory data, CSII or MDI, and access to ketone meters and CGM were provided through questionnaires and medical records. The Swedish National Diabetes Registry (SWEDIABKIDS) was used to compare the distribution of CSII and MDI in the national population with the population admitted for DKA, using the chi-square goodness-of-fit test. Distribution of CSII and MDI was then categorized in clinical severity grades for mild (pH 7.20-7.29), moderate (pH 7.10-7.29) and severe DKA (pH <7.10). RESULTS: The distribution of CSII at DKA admission was significantly larger than in the national pediatric population with T1D (74.7% vs. 59.7%, p = 0.002). CSII was overrepresented in mild DKA (85.2% vs. with CSII, p < 0.001), but not in moderate/severe DKA (57.9% with CSII, p = 0.82). Mean HbA1c at hospital admission was 73.9 mmol/mol with CSII and 102.7 mmol/mol with MDI. CONCLUSIONS: CSII was associated with higher risk of mild DKA than MDI. MDI was associated with markedly higher HbA1c levels than CSII at hospital admission for DKA.

Month of birth and the risk of developing type 1 diabetes among children in the Swedish national Better Diabetes Diagnosis Study.

AIM: Previous studies have reported an association between month of birth and incidence of type 1 diabetes. Using population-based data, including almost all newly diagnosed children with type 1 diabetes in Sweden, we tested whether month of birth influences the risk of type 1 diabetes. METHODS: For 8761 children diagnosed with type 1 diabetes between May 2005 and December 2016 in the Better Diabetes Diagnosis study, month of birth, sex and age were compared. Human leucocyte antigen (HLA) genotype and autoantibodies at diagnosis were analysed for a subset of the cohort (n = 3647). Comparisons with the general population used data from Statistics Sweden. RESULTS: We found no association between month of birth or season and the incidence of type 1 diabetes in the cohort as a whole. However, boys diagnosed before 5 years were more often born in May (p = 0.004). We found no correlation between month of birth and HLA or antibodies. CONCLUSION: In this large nationwide study, the impact of month of birth on type 1 diabetes diagnosis was weak, except for boys diagnosed before 5 years of age, who were more likely born in May. This may suggest different triggers for different subgroups of patients with type 1 diabetes.

Impact of Fat Intake on Blood Glucose Control and Cardiovascular Risk Factors in Children and Adolescents with Type 1 Diabetes.

Nutrition therapy is a cornerstone of type 1 diabetes (T1D) management. Glycemic control is affected by diet composition, which can contribute to the development of diabetes complications. However, the specific role of macronutrients is still debated, particularly fat intake. This review aims at assessing the relationship between fat intake and glycemic control, cardiovascular risk factors, inflammation, and microbiota, in children and adolescents with T1D. High fat meals are followed by delayed and prolonged hyperglycemia and higher glycated hemoglobin A1c levels have been frequently reported in individuals with T1D consuming high amounts of fat. High fat intake has also been associated with increased cardiovascular risk, which is higher in people with diabetes than in healthy subjects. Finally, high fat meals lead to postprandial pro-inflammatory responses through different mechanisms, including gut microbiota modifications. Different fatty acids were proposed to have a specific role in metabolic regulation, however, further investigation is still necessary. In conclusion, available evidence suggests that a high fat intake should be avoided by children and adolescents with T1D, who should be encouraged to adhere to a healthy and balanced diet, as suggested by ISPAD and ADA recommendations. This nutritional choice might be beneficial for reducing cardiovascular risk and inflammation.

Delayed referral is common even when new-onset diabetes is suspected in children. A Swedish prospective observational study of diabetic ketoacidosis at onset of Type 1 diabetes.

OBJECTIVE: Delayed treatment for new-onset diabetes Type 1 (T1D) can lead to diabetic ketoacidosis (DKA) with potentially devastating consequences. This prospective observational study aimed to characterize pediatric patients with DKA at hospital admission, regarding parental awareness of diabetes-related symptoms and delayed referrals from primary health care providers to pediatric emergency wards. RESEARCH DESIGN AND METHODS: Patients 0-18 years admitted to hospital with new-onset T1D and DKA between 2015 and 2017 were invited to participate. Questionnaires were filled out separately by the caregivers and by the attending hospital staff. Data from the Swedish National Diabetes Registry (SWEDIABKIDS) were used for comparison. Delayed referral was defined as a primary healthcare contact due to diabetes-related symptoms 0-4 weeks before hospital admission without immediate referral, or registered elevated glucose levels at primary healthcare centers without immediate referral. RESULTS: The study included 237 patients, among which parental suspicion of new-onset diabetes before healthcare contacts was reported in 39%. Parental suspicion of diabetes was associated with higher pH values at diagnosis. Patients in contact with primary health care providers before hospital admission had a delayed referral in 43% of the cases. Delayed referral was associated with lower pH values at hospital admission. Symptoms leading to primary healthcare contacts were similar regardless of whether delay occurred or not. CONCLUSIONS: Parental suspicion of diabetes was associated with milder DKA at hospital admission. Delayed referral was seen in a considerable proportion of children with primary healthcare contacts for symptoms associated with diabetes. Increased awareness of diabetes symptoms is of paramount importance.

The SWEET Project 10-Year Benchmarking in 19 Countries Worldwide Is Associated with Improved HbA1c and Increased Use of Diabetes Technology in Youth with Type 1 Diabetes.

Objective: The international SWEET registry (NCT04427189) was initiated in 2008 to improve outcomes in pediatric diabetes. A 10-year follow-up allowed studying time trends of key quality indicators in 22 centers from Europe, Australia, Canada, and India in youth with type 1 diabetes (T1D). Methods: Aggregated data per person with T1D <25 years of age were compared between 2008-2010 and 2016-2018. Hierarchic linear and logistic regression models were applied. Models were adjusted for gender, age-, and diabetes duration groups. Results: The first and second time periods included 4930 versus 13,654 persons, 51% versus 52% male, median age 11.3 [Q1; Q3: 7.9; 14.5] versus 13.3 [9.7; 16.4] years, and T1D duration 2.9 [0.8; 6.4] versus 4.2 [1.4; 7.7] years. The adjusted hemoglobin A1C (HbA1c) improved from 68 (95% confidence interval [CI]: 66-70) to 63 (60; 65) mmol/mol (P < 0.0001) or 8.4 (95% CI: 8.2-8.6) to 7.9 (7.6; 8.1) % (P < 0.0001). Across all age groups, HbA1c was significantly lower in pump and sensor users. Severe hypoglycemia declined from 3.8% (2.9; 5.0) to 2.4% (1.9; 3.1) (P < 0.0001), whereas diabetic ketoacidosis events increased significantly with injection therapy only. Body mass index-standard deviation score also showed significant improvements 0.55 (0.46; 0.64) versus 0.42 (0.33; 0.51) (P < 0.0001). Over time, the increase in pump use from 34% to 44% preceded the increase in HbA1c target achievement (<53 mmol/mol) from 21% to 34%. Conclusions: Twice yearly benchmarking within the SWEET registry was associated with significantly improved HbA1c on a background of increasing pump and sensor use for 10 years in young persons with T1D. Trial Registration: NCT04427189.

Changes to care delivery at nine international pediatric diabetes clinics in response to the COVID-19 global pandemic.

BACKGROUND: Pediatric diabetes clinics around the world rapidly adapted care in response to COVID-19. We explored provider perceptions of care delivery adaptations and challenges for providers and patients across nine international pediatric diabetes clinics. METHODS: Providers in a quality improvement collaborative completed a questionnaire about clinic adaptations, including roles, care delivery methods, and provider and patient concerns and challenges. We employed a rapid analysis to identify main themes. RESULTS: Providers described adaptations within multiple domains of care delivery, including provider roles and workload, clinical encounter and team meeting format, care delivery platforms, self-management technology education, and patient-provider data sharing. Providers reported concerns about potential negative impacts on patients from COVID-19 and the clinical adaptations it required, including fears related to telemedicine efficacy, blood glucose and insulin pump/pen data sharing, and delayed care-seeking. Particular concern was expressed about already vulnerable patients. Simultaneously, providers reported 'silver linings' of adaptations that they perceived as having potential to inform care and self-management recommendations going forward, including time-saving clinic processes, telemedicine, lifestyle changes compelled by COVID-19, and improvements to family and clinic staff literacy around data sharing. CONCLUSIONS: Providers across diverse clinical settings reported care delivery adaptations in response to COVID-19-particularly telemedicine processes-created challenges and opportunities to improve care quality and patient health. To develop quality care during COVID-19, providers emphasized the importance of generating evidence about which in-person or telemedicine processes were most beneficial for specific care scenarios, and incorporating the unique care needs of the most vulnerable patients.

Celiac disease can be predicted by high levels of tissue transglutaminase antibodies in children and adolescents with type 1 diabetes.

OBJECTIVES: Children with type 1 diabetes (T1D) are not included in guidelines regarding diagnosis criteria for celiac disease (CD) without a diagnostic biopsy, due to lack of data. We explored whether tissue transglutaminase antibodies (anti-tTG) that were ≥ 10 times the upper limit of normal (10× ULN) predicted CD in T1D. METHODS: Data from the Swedish prospective Better Diabetes Diagnosis study was used, and 2035 children and adolescents with T1D diagnosed between 2005-2010 were included. Of these, 32 had been diagnosed with CD before T1D. The children without CD were repeatedly screened for CD using anti-tTG antibodies of immunoglobulin type A. In addition, their human leukocyte antigen (HLA) were genotyped. All children with positive anti-tTG were advised to undergo biopsy. Biopsies were performed on 119 children and graded using the Marsh-Oberhüber classification. RESULTS: All of the 60 children with anti-tTG ≥10x ULN had CD verified by biopsies. The degree of mucosal damage correlated with anti-tTG levels. Among 2003 screened children, 6.9% had positive anti-tTG and 5.6% were confirmed CD. The overall CD prevalence, when including the 32 children with CD before T1D, was 7.0% (145/2035). All but one of the children diagnosed with CD had HLA-DQ2 and/or DQ8. CONCLUSIONS: As all screened children and adolescents with T1D with tissue transglutaminase antibodies above 10 times the positive value 10x ULN had CD, we propose that the guidelines for diagnosing CD in screened children, when biopsies can be omitted, should also apply to children and adolescents with T1D as a noninvasive method.

Altered cortical bone strength and lean mass in young women with long-duration (19 years) type 1 diabetes.

To investigate bone health and body composition in young women with long-duration type 1 diabetes (T1D) in relation to matched controls. Twenty-three Swedish women, age 19.2-27.9 years, with a T1D duration of 10 years or more were recruited from the Swedish National Diabetes Registry (NDR). An age-, gender- and geography-matched control group was recruited. Bone mass and body composition were assessed by dual-energy X-ray absorptiometry and peripheral quantitative computed tomography. Data was retrieved from the NDR and SWEDIABKIDS registries. T1D individuals had a mean diabetes duration of 19 years. T1D individuals had reduced lean mass (40.0 ± 6.1 kg vs. 43.9 ± 4.9 kg) and were shorter (1.66 ± 0.06 m vs. 1.71 ± 0.06 m) although comparable BMI. Subjects with T1D had lower muscle area (P = 0.0045). No differences were observed for fractures; physical activity; total, lumbar spine or femur areal bone mineral density. The cortical bone strength strain index was lower for TD1 patients (1875 ± 399 mm3 vs. 2277 ± 332 mm3). In conclusion, young women with long-term diabetes duration showed reduced cortical bone strength, decreased periosteal circumference, endosteal circumference and altered body composition. These factors contribute to the health burden of TD1, which warrants further attention for advancing bone health in women with T1D.

Multiplexing DNA methylation markers to detect circulating cell-free DNA derived from human pancreatic ß cells.

It has been proposed that unmethylated insulin promoter fragments in plasma derive exclusively from ß cells, reflect their recent demise, and can be used to assess ß cell damage in type 1 diabetes. Herein we describe an ultrasensitive assay for detection of a ß cell-specific DNA methylation signature, by simultaneous assessment of 6 DNA methylation markers, that identifies ß cell DNA in mixtures containing as little as 0.03% ß cell DNA (less than 1 ß cell genome equivalent). Based on this assay, plasma from nondiabetic individuals (N = 218, aged 4-78 years) contained on average only 1 ß cell genome equivalent/mL. As expected, cell-free DNA (cfDNA) from ß cells was significantly elevated in islet transplant recipients shortly after transplantation. We also detected ß cell cfDNA in a patient with KATP congenital hyperinsulinism, in which substantial ß cell turnover is thought to occur. Strikingly, in contrast to previous reports, we observed no elevation of ß cell-derived cfDNA in autoantibody-positive subjects at risk for type 1 diabetes (N = 32), individuals with recent-onset type 1 diabetes (<4 months, N = 92), or those with long-standing disease (>4 months, N = 38). We discuss the utility of sensitive ß cell cfDNA analysis and potential explanations for the lack of a ß cell cfDNA signal in type 1 diabetes.

NMR Spectroscopic Analysis to Evaluate the Quality of Insulin: Concentration, Variability, and Excipient Content.

Known and consistent bioactivity between samples of insulin is essential to correctly estimate the dose. Insulin concentration is not the same thing as bioactivity, however, and methods to correctly determine both are required. Here we show that one dimensional nuclear magnetic resonance (1D NMR), in contrast to, for example, reverse phase high pressure liquid chromatography, can be used to determine both insulin concentration as well as confirm the structural integrity required for activity. In response to the report by Carter and Heinemann, we decided to investigate insulin intended for public use. Insulin from several manufacturers was investigated. Correct insulin concentrations were found in all tested samples although the general sample variability, which possibly could influence the bioactivity, varied depending on insulin type and manufacturer.

Absence of Islet Autoantibodies and Modestly Raised Glucose Values at Diabetes Diagnosis Should Lead to Testing for MODY: Lessons From a 5-Year Pediatric Swedish National Cohort Study.

OBJECTIVE: Identifying maturity-onset diabetes of the young (MODY) in pediatric populations close to diabetes diagnosis is difficult. Misdiagnosis and unnecessary insulin treatment are common. We aimed to identify the discriminatory clinical features at diabetes diagnosis of patients with glucokinase (GCK), hepatocyte nuclear factor-1A (HNF1A), and HNF4A MODY in the pediatric population. RESEARCH DESIGN AND METHODS: Swedish patients (n = 3,933) aged 1-18 years, diagnosed with diabetes May 2005 to December 2010, were recruited from the national consecutive prospective cohort Better Diabetes Diagnosis. Clinical data, islet autoantibodies (GAD insulinoma antigen-2, zinc transporter 8, and insulin autoantibodies), HLA type, and C-peptide were collected at diagnosis. MODY was identified by sequencing GCK, HNF1A, and HNF4A, through either routine clinical or research testing. RESULTS: The minimal prevalence of MODY was 1.2%. Discriminatory factors for MODY at diagnosis included four islet autoantibody negativity (100% vs. 11% not-known MODY; P = 2 × 10-44), HbA1c (7.0% vs. 10.7% [53 vs. 93 mmol/mol]; P = 1 × 10-20), plasma glucose (11.7 vs. 26.7 mmol/L; P = 3 × 10-19), parental diabetes (63% vs. 12%; P = 1 × 10-15), and diabetic ketoacidosis (0% vs. 15%; P = 0.001). Testing 303 autoantibody-negative patients identified 46 patients with MODY (detection rate 15%). Limiting testing to the 73 islet autoantibody-negative patients with HbA1c <7.5% (58 mmol/mol) at diagnosis identified 36 out of 46 (78%) patients with MODY (detection rate 49%). On follow-up, the 46 patients with MODY had excellent glycemic control, with an HbA1c of 6.4% (47 mmol/mol), with 42 out of 46 (91%) patients not on insulin treatment. CONCLUSIONS: At diagnosis of pediatric diabetes, absence of all islet autoantibodies and modest hyperglycemia (HbA1c <7.5% [58 mmol/mol]) should result in testing for GCK, HNF1A, and HNF4A MODY. Testing all 12% patients negative for four islet autoantibodies is an effective strategy for not missing MODY but will result in a lower detection rate. Identifying MODY results in excellent long-term glycemic control without insulin.

Persistent heterogeneity in diabetes technology reimbursement for children with type 1 diabetes: The SWEET perspective.

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.