Pediatric Diabetes最新文献

Background: Type 1 diabetes (T1D) incidence is rising globally, with significant regional variation. Data from highly homogeneous populations, such as Lithuanian, may contribute to a better understanding of contributing T1D factors. This study examines 24-year trends in childhood T1D incidence and seasonal patterns in Lithuania.

Methods: The annual incidence rates (IRs) were computed utilizing established methodologies per 100,000 children <15 years. The study included 2369 (1181 boys) patients with T1D.

Results: During 2001-2024, the mean IR was 21.4 per 100,000 < 15 years (95% CI: 20.89, 27.28). The incidence rose from 10.8 to 36.4 per 100,000 children under 15 years of age, with notable peaks observed in 2021 and 2022, temporally aligning with the highest COVID-19 infection waves. Subgroup analysis showed the most rapid increase in young teenagers (10-14 years). Most new cases (63.5%) were diagnosed from September to March.

Conclusions: This study demonstrates a rapidly increasing incidence of T1D in Lithuanian children over a 24-year period and is one of the highest in European countries. The seasonal distribution of new cases has been speculated to be due to reduced sunlight exposure and lower vitamin D levels, as well as increased school related stress and viral infections during autumn and winter months. However, additional contributing factors are likely involved, underscoring the need for further research.

Background: Chronic diseases such as type 1 diabetes mellitus (T1DM) may alter linear growth; however, reports regarding growth in children with T1DM have been inconsistent. This study aimed to investigate the height and growth velocity of patients with T1DM, and whether they were affected by various factors 5 years after the diagnosis.

Methods: This retrospective study included patients with T1DM between October 2005 and May 2022, with a follow-up period of at least 1 year. Patients with diabetes, thyroid disease, celiac disease, or any other chronic disease were excluded. We compared the mean height standard deviation score (H-SDS) and growth velocity between groups divided based on glycosylated hemoglobin (HbA1c) levels and use of continuous glucose monitoring (CGM) systems.

Results: Among the 150 patients, 45.3% were male, with a mean age at diagnosis of 7.8 ± 3.6 years. At diagnosis, the mean H-SDS was 0.38 ± 1.11. In males, H-SDS significantly decreased overtime, with an estimated slope (β) of -0.054 (standard error [SE] = 0.013, 95% confidence interval [CI]: -0.079 to -0.029, p  < 0.01). The decline in H-SDS was more pronounced in the poorly-controlled group (mean HbA1c ≥7.0%) compared to the well-controlled group (mean HbA1c <7.0%; β = -0.081, SE = 0.016, 95% CI: -0.112 to -0.050 vs. β = -0.007, SE = 0.020, 95% CI: -0.047 to -0.033, p  < 0.01). Among males using CGM, the decrease in H-SDS over the 5-year follow-up was significantly less than that observed in the non-CGM group (β = -0.012, SE = 0.023, 95% CI: -0.057 to -0.034 vs. β = -0.072, SE = 0.015, 95% CI: -0.101 to -0.042, p = 0.03). In the multivariable linear mixed model analysis, younger age at diagnosis (β = -0.009, 95% CI: -0.017 to -0.002, p = 0.02), female (β = 0.067, 95% CI: 0.033 to 0.100, p  < 0.01) and lower HbA1c levels (β = -0.026, 95% CI: -0.038 to -0.015, p < 0.01) were significantly associated with greater improvement in H-SDS over 5 years.

Conclusion: Glycemic control and CGM use positively affected linear growth in children with T1DM, especially in males. CGM use was associated with improved growth outcomes, which suggests that glucose monitoring may help mitigate the adverse effects of poor glycemic control on growth.

Objectives: The Tandem t:slim X2 insulin pump with the Control-IQ technology (Control-IQ) is an automated insulin delivery (AID) system for glycemic control but has limited data in Saudi pediatric and young adult populations. We aim to evaluate the efficacy and safety of Control-IQ therapy in children with insulin-dependent diabetes and previously treated with multiple daily injections (MDIs). The primary outcome is to assess the change in HbA1c 6 months after initiating Control-IQ technology.

Methods: This prospective observational study evaluated children aged 2-14 years with insulin-dependent diabetes who transitioned from treatment with MDI to the Control-IQ technology in the diabetes clinic at the King Faisal Specialist Hospital and Research Centre (KFSHRC) in Saudi Arabia.

Results: A total of 100 patients (44 boys and 56 girls; median age was 11 years) were included. Most (82%) had a history of severe hypoglycemia. Following Control-IQ initiation, median HbA1c significantly decreased from 9.2% to 6.9% at 6 months (-25.0%; p < 0.001), accompanied by a 24.4% reduction in the daily insulin dose. Time in range (TIR) (70-180 mg/dL) improved from 45.6% to 68.8% (+23.2%; p < 0.001), while time in significant hypoglycemia (<54 mg/dL) decreased by 88.9% (p < 0.001). At 6 months, 83% achieved ≥60% TIR, and 54% reached ≥70%. Adherence and engagement were high, with no severe hypoglycemia or discontinuations. Only 3% experienced mild/moderate ketoacidosis due to technical issues in the Control-IQ.

Conclusions: The findings demonstrated that Control-IQ technology is both effective and safe in improving glycemic outcomes in children with insulin-dependent diabetes in a real-world clinical setting. However, successful implementation requires comprehensive training and continuous support.

Background: Diabetes distress is prevalent among youth with type 1 diabetes mellitus (T1DM) and can negatively impact their quality of life and metabolic control. Identifying modifiable factors to reduce this distress is crucial. This study investigates the interplay between diabetes distress, self-management, and quality of life in school-aged children with T1DM amidst the COVID-19 pandemic. Its primary objective is to identify modifiable factors that can assist these children as they navigate the challenges associated with transitioning into adolescence.

Methods: A cross-sectional study with data from 341 Chinese school-age children aged 8-12 was conducted. Data were collected through an online self-report survey during the COVID-19 pandemic (June-December 2022). The data included sociodemographic and clinical characteristics, diabetes distress, diabetes care activities and diabetes problem solving of diabetes self-management and quality of life. Structural equation modeling assessed relationships and mediation effects.

Results: All four domains of diabetes distress exhibited negative associations with quality of life (r = -0.74 to -0.77, p < 0.01). Care activities and problem-solving related to diabetes self-management mediated the associations of emotional burden and regimen-related distress with quality of life (both p < 0.05). Conversely, neither diabetes care activities nor diabetes problem-solving mediated the relationship between physician-related distress and quality of life.

Conclusions: Our findings indicate that problem-solving techniques related to diabetes self-management might be more effective at alleviating various aspects of diabetes distress-such as emotional burden, regimen-related distress, and interpersonal distress-compared to diabetes care activities. Interventions that teach structured problem-solving strategies could be beneficial. Given the ongoing pandemic, these findings could also serve as useful guidance for developing support strategies for school-age children with chronic conditions during future public health emergencies.

Background: Celiac disease (CD) occurs in ~6% of individuals with type 1 diabetes (T1D) and may complicate glycemic control due to conflicting dietary needs. Prior studies show mixed results regarding the impact of CD on Hemoglobin A1c (HbA1c), especially in pediatric populations. This study evaluates whether CD is associated with suboptimal glycemic control in pediatric patients with T1D.

Methods: This retrospective chart review analyzed pediatric patients (<18 years) diagnosed with T1D between 2012 and 2023 across Corewell Health East. Patients were identified via ICD-10 codes and stratified by CD status and glycemic control (controlled HbA1c <7% vs. uncontrolled HbA1c ≥7%). Statistical analyses include chi-square or Fisher's exact tests for categorical variables, Wilcoxon tests for continuous variables, and logistic regression for multivariable analysis.

Results: Among 2,203 pediatric patients with T1D, 101 (4.6%) had CD. Patients with both conditions were younger at T1D diagnosis (median age 9 vs. 12 years, p < 0.0001) and had more HbA1c measurements. A higher proportion of CD patients had uncontrolled diabetes (89.1% vs. 73.8%, p = 0.0006). CD was independently associated with uncontrolled HbA1c (adjusted OR: 2.59; 95% CI: 1.37-4.90; p = 0.003) after adjusting for age, sex, and race. Younger age and Black race were also associated with higher odds of uncontrolled diabetes.

Conclusion: CD is significantly associated with poorer glycemic control in pediatric patients with T1D, independent of age, race, and sex. These findings suggest the need for closer monitoring, individualized dietary counseling, and targeted interventions in this high-risk group.

Aims: Is the current screening for early-stage type 1 diabetes (T1D) associated with the rate of diabetic ketoacidosis (DKA) at T1D manifestation at population level?

Materials and methods: Children with T1D manifestation in 2015-2023 in Germany, aged 0.5 to <15 years from the multicenter diabetes registry (DPV) were included and allocated to federal states (FSs) based on their residential postal code. The relative risk (RR) with 95% confidence interval for DKA at manifestation of T1D by FS with vs. without screening, and demographic/context factors was calculated using logistic regression models.

Results: 24,408 children (54.3% males) were included with median onset age of 8.8 (quartiles: 5.3; 11.8) years. The RR for DKA was not significantly lower in FS with vs. without screening (RR: 0.96 [0.93-1.03], p = 0.393) overall, but in the sub-group of children with the highest probability of being screened (age 1.75-10.99 years, manifestation in Bavaria from 2020 to 2023, RR: 0.88 [0.80-0.97], p = 0.012). The most important predictor for DKA was manifestation age <3 years (RR: 1.83, [1.66-2.03], p < 0.001).

Conclusions: Until 2023, current regional screening initiatives for early-stage T1D were not associated with lower frequency of DKA at population level, but might be helpful in the future if the coverage can be markedly increased.

Introduction: Type 1 diabetes mellitus (T1DM) is an autoimmune disease that damages insulin-producing pancreatic cells, often appearing in childhood. Global incidence is rising at 2%-3% yearly. Its exact cause is unclear. Prenatal exposures and maternal autoimmune disorders have been reported as potential risk factors. This study aimed to explore how maternal autoimmune conditions might correlate with the onset of T1DM, employing a population-focused approach.

Methods: This is a retrospective population-based cohort study with a nested case-control analysis. Primary data were derived from the Maternal and Child Health Database (MCHD) and the National Health Insurance Research Database (NHIRD). This study enrolled a total of 2,036,051 newborns born between 2004 and 2014. They were followed up until the end of 2020. A total of 1273 children under the age of 17 with T1DM were identified from 2004 to 2020. A 1:10 control group, matched by birth date and sex, was selected for comparison. T1DM patients were identified through the Catastrophic Illness Registry Database. Maternal autoimmune diseases were determined using the primary diagnosis codes for hospitalizations and outpatients' visits.

Results: After adjusting for cofactors, the offspring of mothers with an autoimmune disease had a higher risk of T1DM (adjusted odds ratio [aOR] 1.95, 95% confidence interval [CI]: 1.45-2.63, p  < 0.001). For individual autoimmune diseases, T1DM (aOR: 6.81, 95% CI: 2.30-20.16, p  < 0.001), Hashimoto thyroiditis (aOR: 3.75, 95% CI: 1.85-7.60, p  < 0.001), rheumatoid arthritis (aOR: 2.49, 95% CI: 1.08-5.77, p = 0.033), and Graves' disease (aOR: 1.85, 95% CI: 1.14-2.99, p = 0.013) significantly increase the risk of developing T1DM in their children.

Conclusions: Offspring of mothers diagnosed with autoimmune disease, notably T1DM, autoimmune thyroiditis, and rheumatoid arthritis, may indeed have a heightened likelihood of developing T1DM. These findings underscore the importance of targeted screening programs for T1DM in children of affected mothers.

Background: Managing severe insulin resistance (IR) is challenging, necessitating a multifaceted approach, including dietary restriction, exercise, and pharmacotherapy. This paper will detail our utilization of dapagliflozin in a series of cases involving patients with severe IR of various etiology and inadequate glycemic control.

Case studies: We describe six cases of extreme IR with distinct clinical diagnoses: four with Rabson-Mendenhall syndrome (RMS), one with IR type 1A, and a patient with type 1 diabetes mellitus (T1DM) and severe subcutaneous (SC) IR. These cases exhibit the observable characteristics of IR, characterized by an inability to effectively manage blood glucose (BG) with a standard treatment plan. Every case had a remarkable response to dapagliflozin. Subsequent assessment demonstrated improved HgbA1C, fasting glucose, insulin, and C-peptide concentrations. Furthermore, several cases demonstrated improvement in the clinical manifestations of IR following the administration of dapagliflozin, while others showed a reduction in the frequency of diabetic ketoacidosis (DKA). There were no documented adverse reactions with the use of dapagliflozin for a duration of 2-4 years in these patients.

Conclusion: Dapagliflozin appeared both safe and effective as a standalone treatment or when used alongside other antidiabetes medications such as insulin in a case series of children with T1DM and severe IR or IR syndromes (IRS).

Objective: Adolescents with type 1 diabetes (T1D) face unique barriers to physical activity (PA), and most do not meet recommended targets despite its recognised health benefits. To address the lack of tailored, evidence-based support for this group, this study explores how adolescents manage PA and how it is influenced by the wider support system, including parents, carers, and healthcare professionals (HCPs).

Research design and methods: Semi-structured interviews were conducted with adolescents with T1D (n = 11), parents/carers (n = 15), and HCPs (n = 11). Adolescents were aged between 12 and 18 (64% female). HCPs were dieticians (n = 7), nurses (n = 2), a doctor (n = 1) and a health and wellbeing practitioner (n = 1). Interviews explored practical, emotional, and contextual factors influencing PA. Data were analysed using thematic analysis.

Results: Participants described cognitive, emotional, and practical demands of managing T1D during PA. Thematic analysis identified three overarching themes: (1) the mental effort required to manage diabetes with PA, including parental anxiety, desire for normality, and unpredictability of glucose responses; (2) practical and organisational challenges, such as access to supportive environments, technology, and activity-specific logistics; and (3) adaptive management strategies, including trial and error, parental involvement, peer learning, and variable clinical support. Current support was often generic, leading families to rely on self-devised strategies and informal networks to support their individual needs.

Conclusion: Enhanced, youth-friendly, and activity-specific guidance is needed for adolescents with T1D. This should include training for healthcare professionals, teachers, and coaches. Future work should prioritise the co-design of resources and interventions with young people and families, integrating structured peer support.