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  3. A disease model for wheezing disorders in preschool children based on clinicians' perceptions
 

A disease model for wheezing disorders in preschool children based on clinicians' perceptions

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BORIS DOI
10.7892/boris.30352
Date of Publication
2009
Publication Type
Article
Division/Institute

Institut für Sozial- ...

Contributor
Spycher, Benorcid-logo
Institut für Sozial- und Präventivmedizin (ISPM)
Silverman, Michael
Barben, Juerg
Eber, Ernst
Guinand, Stéphane
Levy, Mark L
Pao, Caroline
van Aalderen, Willem M
van Schayck, Onno C P
Kühni, Claudia
Institut für Sozial- und Präventivmedizin (ISPM)
Series
PLoS ONE
ISSN or ISBN (if monograph)
1932-6203
Publisher
Public Library of Science
Language
English
Publisher DOI
10.1371/journal.pone.0008533
PubMed ID
20046874
Description
BACKGROUND: Wheezing disorders in childhood vary widely in clinical presentation and disease course. During the last years, several ways to classify wheezing children into different disease phenotypes have been proposed and are increasingly used for clinical guidance, but validation of these hypothetical entities is difficult. METHODOLOGY/PRINCIPAL FINDINGS: The aim of this study was to develop a testable disease model which reflects the full spectrum of wheezing illness in preschool children. We performed a qualitative study among a panel of 7 experienced clinicians from 4 European countries working in primary, secondary and tertiary paediatric care. In a series of questionnaire surveys and structured discussions, we found a general consensus that preschool wheezing disorders consist of several phenotypes, with a great heterogeneity of specific disease concepts between clinicians. Initially, 24 disease entities were described among the 7 physicians. In structured discussions, these could be narrowed down to three entities which were linked to proposed mechanisms: a) allergic wheeze, b) non-allergic wheeze due to structural airway narrowing and c) non-allergic wheeze due to increased immune response to viral infections. This disease model will serve to create an artificial dataset that allows the validation of data-driven multidimensional methods, such as cluster analysis, which have been proposed for identification of wheezing phenotypes in children. CONCLUSIONS/SIGNIFICANCE: While there appears to be wide agreement among clinicians that wheezing disorders consist of several diseases, there is less agreement regarding their number and nature. A great diversity of disease concepts exist but a unified phenotype classification reflecting underlying disease mechanisms is lacking. We propose a disease model which may help guide future research so that proposed mechanisms are measured at the right time and their role in disease heterogeneity can be studied.
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/103868
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