RT Journal Article
SR Electronic
T1 Home Monitoring of Asthma Exacerbations in Children and Adults With Use of an AI-Aided Stethoscope
JF The Annals of Family Medicine
JO Ann Fam Med
FD American Academy of Family Physicians
SP 517
OP 525
DO 10.1370/afm.3039
VO 21
IS 6
A1 Emeryk, Andrzej
A1 Derom, Eric
A1 Janeczek, Kamil
A1 Kuźnar-Kamińska, Barbara
A1 Zelent, Anna
A1 Łukaszyk, Mateusz
A1 Grzywalski, Tomasz
A1 Pastusiak, Anna
A1 Biniakowski, Adam
A1 Szarzyński, Krzysztof
A1 Botteldooren, Dick
A1 Kociński, Jędrzej
A1 Hafke-Dys, Honorata
YR 2023
UL http://www.annfammed.org/content/21/6/517.abstract
AB PURPOSE The advent of new medical devices allows patients with asthma to self-monitor at home, providing a more complete picture of their disease than occasional in-person clinic visits. This raises a pertinent question: which devices and parameters perform best in exacerbation detection?METHODS A total of 149 patients with asthma (90 children, 59 adults) participated in a 6-month observational study. Participants (or parents) regularly (daily for the first 2 weeks and weekly for the next 5.5 months, with increased frequency during exacerbations) performed self-examinations using 3 devices: an artificial intelligence (AI)-aided home stethoscope (providing wheezes, rhonchi, and coarse and fine crackles intensity; respiratory and heart rate; and inspiration-to-expiration ratio), a peripheral capillary oxygen saturation (SpO2) meter, and a peak expiratory flow (PEF) meter and filled out a health state survey. The resulting 6,029 examinations were evaluated by physicians for the presence of exacerbations. For each registered parameter, a machine learning model was trained, and the area under the receiver operating characteristic curve (AUC) was calculated to assess its utility in exacerbation detection.RESULTS The best single-parameter discriminators of exacerbations were wheezes intensity for young children (AUC 84% [95% CI, 82%-85%]), rhonchi intensity for older children (AUC 81% [95% CI, 79%-84%]), and survey answers for adults (AUC 92% [95% CI, 89%-95%]). The greatest efficacy (in terms of AUC) was observed for a combination of several parameters.CONCLUSIONS The AI-aided home stethoscope provides reliable information on asthma exacerbations. The parameters provided are effective for children, especially those younger than 5 years of age. The introduction of this tool to the health care system might enhance asthma exacerbation detection substantially and make remote monitoring of patients easier.