Evidence map›Paper›PMID 25884839›Full record

ArticleBMC pediatrics2015

A method for reporting and classifying acute infectious diseases in a prospective study of young children: TEDDY.

Maria Lönnrot, Kristian Lynch, Helena Elding Larsson, Åke Lernmark, Marian Rewers, William Hagopian, Jin-Xiong She, Olli Simell, Anette-G Ziegler, Beena Akolkar and 3 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in BMC pediatrics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
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

18 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Association of fever and infections with the subsequent risk of atopic diseases in children with genetic susceptibility for T1D: Results from the TEDDY cohort study.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Observational
  11. Article
  12. Review
  13. Article
  14. Prediabetes in youth - mechanisms and biomarkers.The Lancet. Child & adolescent health · 2017
    Article
  15. Article
  16. Article
  17. Factors That Increase Risk of Celiac Disease Autoimmunity After a Gastrointestinal Infection in Early Life.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2017
    Article
  18. 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

13 authors at 8 institutions in 4 countries.

Maria LönnrotUniversity of Tampere, Tampere, Finland. maria.lonnrot@uta.fi.
Kristian LynchUniversity of South Florida, Tampa, USA. kristian.lynch@epi.usf.edu.
Helena Elding LarssonLund University, Malmö, Sweden. helena.larsson@med.lu.se.
Åke LernmarkLund University, Malmö, Sweden. ake.lernmark@med.lu.se.
Marian RewersBarbara Davis Center for Childhood Diabetes, Denver, CO, USA. marian.rewers@ucdenver.edu.
William HagopianPacific Northwest Diabetes Research Institute, Seattle, USA. wah@u.washington.edu.
Jin-Xiong SheGeorgia Regents University, Augusta, USA. jshe@gru.edu.
Olli SimellUniversity of Turku, Turku, Finland. olli.simell@utu.fi.
Anette-G ZieglerInstitute of Diabetes Research, Helmholtz Zentrum München, and Klinikum rechts der Isar, Technische Universität München, and Forschergruppe Diabetes e.V, Neuherberg, Germany. anette-g.ziegler@helmholtz-muenchen.de.
Beena AkolkarNIH, Bethesda, USA. akolkarb@extra.niddk.nih.gov.
Jeffrey KrischerUniversity of South Florida, Tampa, USA. jeffrey.krischer@epi.usf.edu.
Heikki HyötyUniversity of Tampere, Tampere, Finland. heikki.hyoty@uta.fi.
TEDDY Study Group
Lund University · SEPacific Northwest Diabetes Research Institute · USUniversity of South Florida · USUniversity of Turku · FINational Institutes of Health · USTampere University · FITampere University · FITampere University of Applied Sciences · FI

Funding

Data Coordinating Center (DCC)for the Consortium for Identification of EnvironmenUC4DK095300 · NIDDK · UNIVERSITY OF SOUTH FLORIDA · PI KRISCHER, JEFFREY P · 2011 to 2011
$56.0M
Data Coordinating CenterU01DK063790 · NIDDK · UNIVERSITY OF SOUTH FLORIDA · PI KRISCHER, JEFFREY P · 2002 to 2006
$50.1M
Establish a Data Coordinating Center (DCC) for the Consortium for Identification UC4DK100238 · NIDDK · UNIVERSITY OF SOUTH FLORIDA · PI KRISCHER, JEFFREY P · 2014 to 2014
$28.9M
The Environmental Determinants of Diabetes in Young (TEDDY0U01DK063863 · NIDDK · HOSPITAL DISTRICT OF SOUTHWEST FINLAND · PI TOPPARI, JORMA · 2003 to 2022
$13.5M
The Environmental Triggers of Diabetes (TEDDY) in SwedenU01DK063861 · NIDDK · UNIVERSITY OF WASHINGTON · PI LERNMARK, AKE · 2003 to 2022
$13.4M
THE TEDDY STUDY - COLORADO CLINICAL CENTERU01DK063821 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI REWERS, MARIAN J · 2003 to 2022
$12.3M
The TEDDY Study: Georgia/Florida Clinical CenterU01DK063865 · NIDDK · MEDICAL COLLEGE OF GEORGIA (MCG) · PI MCINDOE, RICHARD A. · 2003 to 2022
$12.3M
The Environmental Determinants of Diabetes in Youth: Washington Clinical CenterU01DK063829 · NIDDK · PACIFIC NORTHWEST RESEARCH INSTITUTE · PI HAGOPIAN, WILLIAM A. · 2003 to 2022
$11.8M
Type 1 Diabetes triggers: diet modification in neonatesU01DK063836 · NIDDK · FORSCHERGRUPPE DIABETES E. V. · PI ZIEGLER, ANETTE · 2003 to 2022
$6.2M
The Environmental Triggers of Diabetes (TEDDY)UC4DK063861 · NIDDK · LUNDS UNIVERSITET · PI LERNMARK, AKE · 2013 to 2013
$5.7M
The Environmental Determinants of Diabetes in the Young (TEDDY) StudyUC4DK063863 · NIDDK · HOSPITAL DISTRICT OF SOUTHWEST FINLAND · PI TOPPARI, JORMA · 2013 to 2013
$5.6M
The TEDDY Study: Georgia/Florida Clinical CenterUC4DK063865 · NIDDK · AUGUSTA UNIVERSITY · PI SHE, JIN-XIONG · 2013 to 2013
$5.3M
NIDDK NIH HHS HHSN267200700014CNIDDK NIH HHS U01 DK063790NIDDK NIH HHS U01 DK063821NIDDK NIH HHS U01 DK063829NIDDK NIH HHS U01 DK063836NIDDK NIH HHS U01 DK063861NIDDK NIH HHS U01 DK063863NIDDK NIH HHS U01 DK063865NIDDK NIH HHS U01 DK63790NIDDK NIH HHS U01 DK63821NIDDK NIH HHS U01 DK63829NIDDK NIH HHS U01 DK63836NIDDK NIH HHS U01 DK63861NIDDK NIH HHS U01 DK63863NIDDK NIH HHS U01 DK63865NIDDK NIH HHS UC4 DK063821NIDDK NIH HHS UC4 DK063829NIDDK NIH HHS UC4 DK063836NIDDK NIH HHS UC4 DK063861NIDDK NIH HHS UC4 DK063863NIDDK NIH HHS UC4 DK063865NIDDK NIH HHS UC4 DK095300NIDDK NIH HHS UC4 DK100238NIDDK NIH HHS UC4 DK63821NIDDK NIH HHS UC4 DK63829NIDDK NIH HHS UC4 DK63836NIDDK NIH HHS UC4 DK63861NIDDK NIH HHS UC4 DK63863NIDDK NIH HHS UC4 DK63865NIDDK NIH HHS UC4 DK95300
6 · The paper itself

Abstract

backgroundEarly childhood environmental exposures, possibly infections, may be responsible for triggering islet autoimmunity and progression to type 1 diabetes (T1D). The Environmental Determinants of Diabetes in the Young (TEDDY) follows children with increased HLA-related genetic risk for future T1D. TEDDY asks parents to prospectively record the child's infections using a diary book. The present paper shows how these large amounts of partially structured data were reduced into quantitative data-sets and further categorized into system-specific infectious disease episodes. The numbers and frequencies of acute infections and infectious episodes are shown.

methodsStudy subjects (n = 3463) included children who had attended study visits every three months from age 3 months to 4 years, without missing two or more consecutive visits during the follow-up. Parents recorded illnesses prospectively in a TEDDY Book at home. The data were entered into the study database during study visits using ICD-10 codes by a research nurse. TEDDY investigators grouped ICD-10 codes and fever reports into infectious disease entities and further arranged them into four main categories of infectious episodes: respiratory, gastrointestinal, other, and unknown febrile episodes. Incidence rate of infections was modeled as function of gender, HLA-DQ genetic risk group and study center using the Poisson regression.

resultsA total of 113,884 ICD-10 code reports for infectious diseases recorded in the database were reduced to 71,578 infectious episodes, including 74.0% respiratory, 13.1% gastrointestinal, 5.7% other infectious episodes and 7.2% febrile episodes. Respiratory and gastrointestinal infectious episodes were more frequent during winter. Infectious episode rates peaked at 6 months and began declining after 18 months of age. The overall infectious episode rate was 5.2 episodes per person-year and varied significantly by country of residence, sex and HLA genotype.

conclusionsThe data reduction and categorization process developed by TEDDY enables analysis of single infectious agents as well as larger arrays of infectious agents or clinical disease entities. The preliminary descriptive analyses of the incidence of infections among TEDDY participants younger than 4 years fits well with general knowledge of infectious disease epidemiology. This protocol can be used as a template in forthcoming time-dependent TEDDY analyses and in other epidemiological studies.

Indexed as

ParentsSelf ReportAutoimmunityChild, PreschoolCommunicable DiseasesDatasets as TopicDiabetes Mellitus, Type 1Environmental ExposureFemaleFollow-Up StudiesGenetic Predisposition to DiseaseHumansInfantInternational Classification of DiseasesMaleProspective Studies

Identifiers

PMID25884839
PMCPMC4377063
OpenAlexW2124112243

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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.