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Characterisation and clinical outcomes in children and adolescents with diabetes according to newly defined subgroups: a cohort study from the DPV registry.
Warncke, Katharina; Eckert, Alexander; Bonifacio, Ezio; Achenbach, Peter; Kordonouri, Olga; Meissner, Thomas; Ohlenschläger, Ute; Bonfig, Walter; Ziegler, Anette-G; Holl, Reinhard W.
Afiliação
  • Warncke K; Technical University of Munich, Germany; Department of Pediatrics, TUM School of Medicine, Munich, Germany.
  • Eckert A; Institute of Diabetes Research, Helmholtz Munich, German Center for Environmental Health, Munich, Germany.
  • Bonifacio E; Institute of Epidemiology and Medical Biometry, ZIBMT, University of Ulm, Ulm, Germany.
  • Achenbach P; German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany.
  • Kordonouri O; German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany.
  • Meissner T; Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany.
  • Ohlenschläger U; Paul Langerhans Institute Dresden of the Helmholtz Munich at University Hospital Carl Gustav Carus and Faculty of Medicine, TU Dresden, Germany.
  • Bonfig W; Institute of Diabetes Research, Helmholtz Munich, German Center for Environmental Health, Munich, Germany.
  • Ziegler AG; German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany.
  • Holl RW; Forschergruppe Diabetes, School of Medicine, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany.
EClinicalMedicine ; 64: 102208, 2023 Oct.
Article em En | MEDLINE | ID: mdl-37731934
Background: Personalised therapy has emerged as a possibly more efficient approach taking disease heterogeneity into account. The aim of this study was to determine whether recently described subgroups of childhood diabetes have prognostic association with diabetes-specific complications and, therefore, might be a basis for personalised therapies. Methods: We applied a previously developed subgroup classification to pediatric patients (diabetes onset <18 years) from the prospective Diabetes Patient Follow-up (DPV) registry with documented data between January 1, 2000 and March 31, 2022, from diabetes centers in Germany, Austria, Switzerland, and Luxembourg. The classification required information on islet autoantibody status, age, haemoglobin A1c (HbA1c), and body-mass index (BMI-SDS) at disease manifestation, as well as follow up data after 2 and after 4 years, which was available in 22,719 patients. Patients without documented data on these parameters were excluded from the analysis. The cumulative risk of severe hypoglycemia, diabetic ketoacidosis (DKA), retinopathy, and nephropathy were analysed by Kaplan-Meier analyses over a median follow-up of 6.8 years (IQR 4.8-9.6). Findings: Patients were classified into 10 subgroups (P1-P7 islet autoantibody-positive, n = 19,811; N1-N3 islet autoantibody-negative, n = 2908). The groups varied markedly with respect to specific acute and chronic complications. Severe hypoglycemia was a characteristic feature in young islet autoantibody-positive subgroups P1, P3, P4 (10-year risk 46, 46 and 47%) and the islet autoantibody-negative groups N1, N2 (43 and 46%). Nephropathy was identified in patient groups P2 and P5 (10-year risk 16%), which had features of moderate disease such as preserved C-peptide, low HbA1c, and very low frequency of DKA at diabetes onset. Group P7, which was defined by a high BMI, was associated with poor metabolic control, DKA, and retinopathy. In contrast, islet autoantibody-negative patients with high BMI (N3) had a low risk for all four complications. Interpretation: Subgrouping of childhood diabetes at diabetes onset provided prognostic value for the development of acute and chronic diabetes-specific complications. Funding: The DPV initiative is supported by The German Ministry of Education and Research (BMBF) within the German Center for Diabetes Research, the diabetes surveillance of the Robert Koch Institute, the German Diabetes Association (DDG) and INNODIA.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article