Evidence map›Paper›PMID 37731934›Full record

ArticleEClinicalMedicine2023

Characterisation and clinical outcomes in children and adolescents with diabetes according to newly defined subgroups: a cohort study from the DPV registry.

Katharina Warncke, Alexander Eckert, Ezio Bonifacio, Peter Achenbach, Olga Kordonouri, Thomas Meissner, Ute Ohlenschläger, Walter Bonfig, Anette-G Ziegler, Reinhard W Holl

Abstract read
In one paragraph

Article in EClinicalMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Early Onset of Type 1 Diabetes in Kuwait: Distinct Clinical, Metabolic, and Immunological Characteristics.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Katharina WarnckeTechnical University of Munich, Germany; Department of Pediatrics, TUM School of Medicine, Munich, Germany.
Alexander EckertInstitute of Epidemiology and Medical Biometry, ZIBMT, University of Ulm, Ulm, Germany.
Ezio BonifacioGerman Center for Diabetes Research (DZD), Munich-Neuherberg, Germany.
Peter AchenbachInstitute of Diabetes Research, Helmholtz Munich, German Center for Environmental Health, Munich, Germany.
Olga KordonouriKinder- und Jugendkrankenhaus AUF DER BULT, Hannover, Germany.
Thomas MeissnerDepartment of General Pediatrics, Neonatology and Pediatric Cardiology, University Children's Hospital, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Duesseldorf, Germany.
Ute OhlenschlägerAltonaer Kinderkrankenhaus, Hamburg, Germany.
Walter BonfigTechnical University of Munich, Germany; Department of Pediatrics, TUM School of Medicine, Munich, Germany.
Anette-G ZieglerInstitute of Diabetes Research, Helmholtz Munich, German Center for Environmental Health, Munich, Germany.
Reinhard W HollInstitute of Epidemiology and Medical Biometry, ZIBMT, University of Ulm, Ulm, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

ChildrenComplicationsDiabetesPersonalised medicineSubgroups

Identifiers

PMID37731934
PMCPMC10507204

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.