Diagnosis of asthma in children: findings from the Swiss Paediatric Airway Cohort

Author:

de Jong Carmen C.M.ORCID,Pedersen Eva S.L.,Mozun RebecaORCID,Müller-Suter Dominik,Jochmann Anja,Singer FlorianORCID,Casaulta Carmen,Regamey Nicolas,Moeller AlexanderORCID,Ardura-Garcia CristinaORCID,Kuehni Claudia E.ORCID

Abstract

IntroductionDiagnosing asthma in children remains a challenge because respiratory symptoms are not specific and vary over time.AimIn a real-life observational study, we assessed the diagnostic accuracy of respiratory symptoms, objective tests and two paediatric diagnostic algorithms (proposed by the Global Initiative for Asthma (GINA) and the National Institute for Health and Care Excellence (NICE)) in the diagnosis of asthma in school-aged children.MethodsWe studied children aged 5–17 years who were referred consecutively to pulmonary outpatient clinics for evaluation of suspected asthma. Symptoms were assessed by parental questionnaire. The investigations included specific IgE measurement or skin prick tests, measurement of exhaled nitric oxide fraction (FeNO), spirometry, body plethysmography and bronchodilator reversibility (BDR). Asthma was diagnosed by paediatric pulmonologists based on all available data. We assessed diagnostic accuracy of symptoms, tests and diagnostic algorithms by calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the curve (AUC).ResultsAmong 514 participants, 357 (70%) were diagnosed with asthma. The combined sensitivity and specificity was highest for any wheeze (sensitivity=75%, specificity=65%), dyspnoea (sensitivity=56%, specificity=76%) and wheeze triggered by colds (sensitivity=58%, specificity=78%) or by exercise (sensitivity=55%, specificity=74%). Of the diagnostic tests, the AUC was highest for specific total airway resistance (sRtot; AUC=0.73) and lowest for the residual volume (RV)/total lung capacity (TLC) ratio (AUC=0.56). The NICE algorithm had sensitivity=69% and specificity=67%, whereas the GINA algorithm had sensitivity=42% and specificity=90%.ConclusionThis study confirms the limited usefulness of single tests and existing algorithms for the diagnosis of asthma. It highlights the need for new and more appropriate evidence-based guidance.

Funder

Allergiestiftung Ulrich Müller-Gierok

Lungeliga St. Gallen

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

European Respiratory Society (ERS)

Subject

Pulmonary and Respiratory Medicine

Reference24 articles.

1. Global Initiative for Asthma (GINA). Global strategy for asthma management and prevention, 2019. Available from: https://ginasthma.org/wp-content/uploads/2019/06/GINA-2019-main-report-June-2019-wms.pdf Date last accessed: August 07, 2019.

2. British Thoracic Society (BTS), Scottish Intercollegiate Guidelines Network (SIGN). British guideline on the management of asthma: a national clinical guideline. www.sign.ac.uk/media/1048/sign158.pdf Date last updated: July 2019. Date last accessed: August 07, 2019.

3. National Institute for Health and Care Excellence (NICE). Asthma: diagnosis, monitoring and chronic asthma management (guideline NG80) . www.nice.org.uk/guidance/ng80/resources/asthma-diagnosis-monitoring-and-chronic-asthma-management-pdf-1837687975621 Date last updated: February 12, 2020. Date last accessed: August 07, 2019.

4. Overdiagnosis of asthma in children in primary care: a retrospective analysis

5. Misdiagnosis of asthma in schoolchildren;Yang;Pediatr Pulmonol,2017

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