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Clinical Evaluation of AI-aided Auscultation With Automatic Classification of Respiratory System Sounds

Clinical Evaluation of AI-aided Auscultation With Automatic Classification of Respiratory System Sounds

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04208360
Acronym
AIR
Enrollment
84
Registered
2019-12-23
Start date
2021-03-31
Completion date
2021-10-31
Last updated
2020-10-22

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Crackle, Lung Sound, Rhonchi, Wheezing

Brief summary

In the present trial, the StethoMe electronic stethoscope will be used for pulmonary auscultation and recording of lung sounds in the pediatric study population.

Detailed description

Multicenter, international - 2 EU sites (max. 1 in Poland) and a single US site. Trial centers and investigators will be identified and selected based on their clinical and research experience. The trial objective is to assess whether use of the StethoMe AI lung sounds analysis software provides clinical benefit by improving the identification of abnormal lung sounds in the categories of wheezes, rhonchi, fine crackles and coarse as compared to pulmonary auscultation by experienced physicians (general practitioners (GPs) and pulmonologists). The recordings will be used to form a gold standard database of lung sounds as evaluated by an expert, independent panel according to the study protocol. The gold standard database will include approximately equal representation of wheezes, rhonchi, fine crackles and coarse crackles. Moreover, the database will also include recordings without any of the previous descripted pathological sounds. The results of these two analyses, by traditional physician listening and by the StethoMe AI software application, will be assessed for sensitivity and specificity to the gold standard database in detection of the four lung sounds and recordings without defined pathological sounds. The StethoMe AI will be considered to provide clinical benefit if it demonstrates statistically better sensitivity or specificity on any of the four lung sounds as compared to the traditional physician auscultation, together with F1 score analysis.

Interventions

DEVICEStethoMe stethoscope

Assessing whether use of the StethoMe AI lung sounds analysis software provides clinical benefit by improving the identification of abnormal lung sounds.

Sponsors

StethoMe
Lead SponsorINDUSTRY

Study design

Observational model
CASE_ONLY
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
3 Months to 18 Years
Healthy volunteers
No

Inclusion criteria

* Children between 3 months and 18 years old (inclusive) admitted and hospitalized in the pulmonary disease ward (PL and EU). * Children between 3 months and 18 years old (inclusive) admitted and hospitalized in the pulmonary disease ward or treated in an outpatient clinic (US). * Informed consent of parents or caregivers, according to local regulations.

Exclusion criteria

* Skin/soft tissue disease or local infection at the site of pulmonary auscultation or any other contraindication for the pulmonary auscultation. * Any concurrent disease or condition that, in the opinion of the investigator, would make the patient unsuitable for participation in the project.

Design outcomes

Primary

MeasureTime frameDescription
Collecting pulmonary auscultation recordings24 hoursSensitivity for detection of wheezes by StethoMe AI algorithms in comparison to gold standard

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026