Incidence of Type 1 Diabetes in Children and Adolescents During the COVID-19 Pandemic in Germany: Results From the DPV Registry.

OBJECTIVE: The aim of this study was to investigate the incidence of type 1 diabetes in children and adolescents during the coronavirus disease 2019 (COVID-19) pandemic in Germany compared with previous years. RESEARCH DESIGN AND METHODS: Based on data from the multicenter German Diabetes Prospective Follow-up Registry, we analyzed the incidence of type 1 diabetes per 100,000 patient-years in children and adolescents from 1 January 2020 through 30 June 2021. Using Poisson regression models, expected incidences for 2020/21 were estimated based on the data from 2011 to 2019 and compared with observed incidences in 2020/21 by estimating incidence rate ratios (IRRs) with 95% CIs. RESULTS: From 1 January 2020 to 30 June 2021, 5,162 children and adolescents with new-onset type 1 diabetes in Germany were registered. The observed incidence in 2020/21 was significantly higher than the expected incidence (24.4 [95% CI 23.6-25.2] vs. 21.2 [20.5-21.9]; IRR 1.15 [1.10-1.20]; P < 0.001). IRRs were significantly elevated in June 2020 (IRR 1.43 [1.07-1.90]; P = 0.003), July 2020 (IRR 1.48 [1.12-1.96]; P < 0.001), March 2021 (IRR 1.29 [1.01-1.65]; P = 0.028), and June 2021 (IRR 1.39 [1.04-1.85]; P = 0.010). CONCLUSIONS: A significant increase in the incidence of type 1 diabetes in children was observed during the COVID-19 pandemic, with a delay in the peak incidence of type 1 diabetes by ∼3 months after the peak COVID-19 incidence and also after pandemic containment measures. The underlying causes are yet unknown. However, indirect rather than direct effects of the pandemic are more likely to be the cause.

Cataract in children and adolescents with type 1 diabetes. Insights from the German/Austrian DPV registry.

OBJECTIVE: To study diabetic cataract in type 1 diabetes in a large pediatric cohort. METHODS: The 92,633 patients aged 0.5-21 years from German/Austrian multicenter diabetes registry (DPV) were analyzed. The 235 patients (0.25%) with diabetic cataract were found, 200 could be categorized: 67 with early cataract (3 months before diabetes onset - 12 months afterwards), 133 with late cataract (>12 months after diabetes onset). Regression models adjusted for age and gender were used to compare clinical parameters at diabetes onset. Regression models for patients with late cataract were implemented for the total documentation period and additionally adjusted for diabetes duration. RESULTS: Rate of cataract development shows a peak at diabetes onset and declines with longer diabetes duration. Patients with cataract showed strong female preponderance. Patients developing early cataract were older at diabetes onset (12.8 years [11.8/13.9] vs. 8.9 [8.9/9.0]; p < 0.001) and showed higher HbA1c than patients without cataract (9.0% [8.55/9.38] vs. 7.6% [7.60/7.61]; p < 0.001). They had lower height-SDS, (-0.22 [-0.48/0.04] vs. 0.25 [0.24/0.26]; p < 0.001), lower weight-SDS (-0.31 [-0.55/-0.08] vs. 0.21 [0.20/0.21]; p < 0.001) and lower BMI-SDS (-0.25 [-0.49/-0.02] vs. 0.12 [0.12/0.13); p = 0.002). Patients with late cataract showed higher HbA1c at diabetes onset (8.35% [8.08/8.62] vs. 8.04% [8.03/8.05]; p = 0.023) and higher mean HbA1c during total documentation period (8.00% [7.62/8.34] vs. 7.62% [7.61/7.63]; p = 0.048). CONCLUSIONS: Our data confirm known demographic and clinical characteristics of patients developing early cataract. Hyperglycemia-induced osmotic damage to lens fibers at diabetes onset might be the main pathomechanism. Long term glycemic control is associated with cataract development.

Type 1 diabetes and epilepsy in childhood and adolescence: Do glutamic acid decarboxylase autoantibodies play a role? Data from the German/Austrian/Swiss/Luxembourgian DPV Registry.

AIMS: We aimed to analyze the relationship between epilepsy and glutamic acid decarboxylase autoantibodies (GADA) in patients with type 1 diabetes mellitus (T1DM) and the impact of GADA on demographic, clinical, and metabolic data in T1DM patients with epilepsy. METHODS: We searched for patients with T1DM ≤20 years and GADA measurements, and within this group for patients with epilepsy. We formed groups: T1DM + Epilepsy + GADA positive; T1DM + Epilepsy + GADA negative; T1DM + GADA positive; T1DM + GADA negative. We used logistic regression to analyze the relationship between epilepsy and GADA with odds ratio adjusted for sex, duration of diabetes (DOD), and age at diabetes onset (ADO). We used logistic regression with odds ratio adjusted for DOD and ADO onset using epilepsy as a dependent variable and GADA, HbA1c, ketoacidosis, severe hypoglycemia (SH), sex, celiac disease, and autoimmune thyroiditis as independent variables. We conducted regression analyses adjusted for sex, DOD, and ADO to analyze differences in clinical/metabolic parameters between the groups. RESULTS: Epilepsy was not more frequent in GADA-positive patients (GPP). Logistic regression including all patients with GADA measurements showed that hypoglycemia with coma (HC) correlated with epilepsy when compared to no SH. We found no differences in clinical and metabolic data between GPP and GADA-negative patients (GNP) with epilepsy. SH occurred more often in GPP with epilepsy in comparison to GPP without epilepsy. GNP with epilepsy had a higher rate of HC than GPP without epilepsy. CONCLUSION: We found no relationship between epilepsy and GADA. A relationship between T1DM and epilepsy might be explainable by SH.