A diagnostic codes-based algorithm improves accuracy for identification of childhood asthma in archival data sets-Reference-Cited by-同舟云学术

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A diagnostic codes-based algorithm improves accuracy for identification of childhood asthma in archival data sets

Published:2020-05-20 Issue:8 Volume:58 Page:1077-1086
ISSN:0277-0903
Container-title:Journal of Asthma
language:en
Short-container-title:Journal of Asthma

Author:

Seol Hee Yun¹²,Wi Chung-Il¹^ORCID,Ryu Euijung³^ORCID,King Katherine S.³,Divekar Rohit D.⁴,Juhn Young J.⁵^ORCID

Affiliation:

1. Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, USA

2. Department of Internal Medicine, Pusan National University Yangsan Hospital, Yangsan, Korea

3. Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA

4. Division of Allergic Disease, Mayo Clinic, Rochester, Minnesota, USA

5. Department of Pediatric and Adolescent Medicine/Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA

Publisher

Informa UK Limited

Subject

Pulmonary and Respiratory Medicine,Immunology and Allergy,Pediatrics, Perinatology, and Child Health

Link

https://www.tandfonline.com/doi/pdf/10.1080/02770903.2020.1759624

Reference45 articles.

1. National Health Interview Survey [Internet]. 2015.

2. The global burden of asthma: executive summary of the GINA Dissemination Committee Report

3. Worldwide variation in prevalence of symptoms of asthma, allergic rhinoconjunctivitis, and atopic eczema: ISAAC

4. Worldwide variations in the prevalence of asthma symptoms: the International Study of Asthma and Allergies in Childhood (ISAAC)

5. Global variation in the prevalence and severity of asthma symptoms: Phase Three of the International Study of Asthma and Allergies in Childhood (ISAAC)

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