About this trial
The purpose of this research is to prospectively train and validate an artificial intelligence machine learning (ML) algorithm to detect the presence of adventitious lung sounds in adults. Clinicians will use the Eko CORE and/or Eko CORE 500 device(s) in real clinical settings to collect normal and abnormal lung sounds, as part of standard of care clinical practice, which will then be used to explore an ML algorithm for classifiers for wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough, as well as determine any correspondences between the type and/or location of adventitious lung sounds and the type of pulmonary conditions as reported by clinicians.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Suspected or diagnosed lower respiratory condition OR Presence of wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough discovered during routine auscultation
Normal patients with no adventitious lung sounds
Adults and pediatric patients (as available)
Disqualifiers
Unable to have multiple recordings taken on chest and back (e.g. compromised mobility)
On mechanical ventilation
Trial population
Potential research subjects with complaints of shortness of breath or relevant diagnoses like COPD/heart failure/asthma will be screened for eligibility from the upcoming clinic schedule and then recruited during their clinical appointment. Inpatients may also be identified from the EHR and recruited from inpatient units. In order to achieve the harder-to-fill buckets, it may be necessary to directly target existing registries or patient databases, and/or bring patients in for a research-specific visit. Additionally, patients seen in clinic or in hospital with no known respiratory condition will be recruited and evaluated.
Trial design
Cohort
Prospective
Treatments tested in this trial
Eko digital stethoscopes
DeviceUse of the Eko CORE 500 digital stethoscope and 3M Littmann CORE Digital Stethoscope to listen for and record lung sounds.
Treatment groups
Trial outcomes
Primary outcomes
Primary Objective
The primary objective of this study is to collect normal and abnormal lung sounds of up to 750 patients per study site, by having clinicians use the Eko CORE and/or Eko CORE 500 device(s) in real clinical settings, as part of standard of care clinical practice which will then be used to explore an ML algorithm for classifiers for wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough, as well as determine any correspondences between the type and/or location of adventitious lung sounds and the type of pulmonary conditions as reported by clinicians.
Sponsors and contacts
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