Monitoring Asthma in Young Children Using an AI-Aided Stethoscope

An artificial intelligence (AI)-aided stethoscope may improve home monitoring of asthma exacerbations in very young children, using measures of symptoms such as peak expiratory flow (PEF), a study finds.

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These findings offer to parents of children with asthma the ability to self-monitor at home, which may provide a more complete picture of their children’s disease than occasional in-person clinic visits.

This observational study is published in The Annals of Family Medicine.

“The aim of this study was to investigate which parameters are of crucial importance in exacerbation detection and monitoring of patients with asthma and to what extent a home AI-aided stethoscope can support this process, especially in children, for whom there is a lack of efficient tools,” wrote the researchers of the study.

A report in 2022 by the Global Initiative for Asthma (GINA) identified continuous respiratory sounds such as cough, wheeze, shortness of breath, and chest tightness, in addition to variable expiratory airflow limitation, are the best indicators of asthma exacerbation, especially among children younger than 5 years. However, assessment of these symptoms is still primarily done by doctors using stethoscopes in face-to-face visits.

In this study, researchers conducted a 6-month study on 149 home-monitored patients with asthma of various ages in Poland. Each patient or parent were asked to perform health status self-examinations using a home stethoscope, peak flow meter, and pulse oximeter. Additionally, these patients were asked to indicate breathing quality and additional symptoms through an online survey. Furthermore, more subjective, auditory symptoms and auscultatory sounds were recorded from standard chest points of all study participants using an AI-based home stethoscope. All sound recordings were then transferred to a cell phone app.

These recordings were automatically analyzed by an AI module, which generated results pertaining to the patient’s pathological auscultatory sound intensities, heart rate, and inspiration-to-expiration duration ratio, which were displayed in the app. The data were analyzed by physicians though an online platform to identify any exacerbation occurrences.

The analysis showed that the best single-parameter discriminators of exacerbations were wheeze intensity for children under 5 years (area under the curve [AUC], 84%; 95% CI, 82-85), rhonchi intensity for children older than 5 years (AUC, 81%; 95% CI, 79-84), and survey answers for adults (AUC, 92%; 95% CI, 89-95). However, the greatest efficacy in terms of AUC was identified for a combination of several parameters.

Because these results were based on large-scale data from intended-use cases by certified medical devices, their reliability is much greater than that of a laboratory study with limited participants and short-term monitoring. However, the researchers acknowledged that there were some limitations to the study. First, there are currently no definitive objective parameters or a specific set of objective parameters that can truly confirm an asthma exacerbation. Therefore, the reference standard used in the study was based on the experience and subjective decisions of individual physicians. Second, the study focused solely on Slavic patients, although no available data from GINA indicated any ethnic influence on exacerbation identification.

Despite these limitations, the researchers believe this study indicates that while combining multiple measurements is ideal, the parameters measured by an AI-aided home stethoscope may help detect asthma exacerbations more effectively than PEF measurements alone.

“The identification of asthma exacerbation relies on symptoms and indirect measures rather than concrete biomarkers,” wrote the researchers. “Thus, the reference standard we used was also established on the basis of the experience and subjective decisions of individual physicians. Nevertheless, this is fully consistent with the current clinical approach to asthma exacerbation detection.”

Reference

Emeryk A, Derom E, Janeczek K, et al. Home monitoring of asthma exacerbations in children and adults with use of an AI-aided stethoscope. The Annals of Family Medicine. 2023;21(6):517-525. doi:10.1370/afm.3039