DOI: 10.1002/ppul.71768 ISSN: 8755-6863

Feasibility and Measurement Quality of Home‐Based Smartphone Spirometry in Children With Suspected Asthma: A Multicentre, Prospective Study

Antonia Knopek, Hanna Fabinyi, Viktoria Zach, Anna Beliveau, Nina Luisa Hoekstra, Carlotta Nüssing, Katharina Kainz, Swantje Weisser, Anna Zschocke, Angela Zacharasiewicz, Christiane Lex

ABSTRACT

Background

Diagnosing asthma in children is challenging due to the episodic nature of symptoms and limitations of in‐clinic lung function testing. Smartphone spirometry offers a potential solution by enabling repeated measurements in real‐life settings. However, data on its feasibility in children with suspected but unconfirmed asthma are limited.

Objective

To evaluate compliance, measurement quality, and agreement between manual and automated grading of smartphone spirometry in children with suspected asthma.

Methods

In this multicentre, prospective study, 102 children aged 5–16 years with suspected asthma received a smartphone spirometer and were instructed to perform daily spirometry for 7 days. Measurement quality was assessed using ATS/ERS 2019 criteria by both manual review and automated device grading. Associations with age, supervision, and social factors were analysed.

Results

Of 101 children with technically valid data, 93.1% performed at least one measurement series at home, while 31.7% completed measurements on all seven study days. Clinically usable measurement quality (grades A–C for both FEV 1 and FVC) was achieved at least once by 61.7% (manual grading) and 74.5% (automated grading). Automated grading showed strong correlation and high agreement with manual grading (ICC = 0.90), but slightly overestimated quality. Measurement quality was not significantly associated with age, supervision, or social factors.

Conclusion

Smartphone spirometry is feasible for home‐based lung function assessment in children with suspected asthma. Compliance and measurement quality were moderate but acceptable for clinical interpretation in most participants. Automated grading aligns well with manual review though potential discrepancies should be considered in clinical decision‐making.

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