Clinical Feasibility of a Non-invasive Wearable Acoustic Device for Measuring Air Trapping in COPD
- Conditions
- COPDCOPD Exacerbation
- Interventions
- Device: Sylvee
- Registration Number
- NCT04450368
- Lead Sponsor
- Respira Labs, Inc
- Brief Summary
This is a pilot observational study during which the investigators will conduct a longitudinal assessment of air trapping (with up to 2 visits) in 40 patients with COPD and variable degrees of air trapping and 20 healthy controls using ARIA. The investigators will characterize the clinical phenotype of the subjects by administering health and symptom-based questionnaires and obtaining lung function testing at rest and during exertion, and will then correlate and validate the ARIA-based indices with those of the more traditional physiologic measures of static and dynamic air trapping.
- Detailed Description
Chronic Obstructive Pulmonary Disease (COPD) is the fourth leading cause of hospitalization in the United States. Exacerbations, a worsening or "flare up" of symptoms cause most COPD hospitalizations. Early detection of lung function deterioration would facilitate early intervention and help prevent hospitalizations, since most exacerbations can be treated with changes of inhalers and/or oral medications. Air trapping, defined as an abnormal increase in the volume of air remaining in the lungs after exhalation, is a common finding in all forms of COPD. Air trapping has been shown to increase during exacerbations and decrease when exacerbations resolve. Moreover, increasing recent evidence indicates that air trapping is an earlier harbinger of deteriorating lung function than spirometric changes. Recent research shows that lung air trapping can be measured by low-frequency ultrasound (1-40 kHz). Thus, acoustic monitoring of air trapping could provide clinicians with a non-invasive tool to when medical intervention is needed to avoid unnecessary ER visits and hospitalizations. The investigators have developed a low-cost, non-invasive, acoustic-based wearable device, Sylvee that is capable of continuous monitoring of lung resonance. The device has machine-learning algorithms that can detect minor changes in lung resonance, which our preliminary results suggest corresponds to changes in air trapping. The overall objective of this pilot project is to validate Sylvee's algorithms in a cohort of 60 patients with COPD and variable degree of air trapping. Ultimately, Sylvee will allow physicians to remotely monitor their patients' lung function and adjust their medications to reduce healthcare costs and improve patients' quality of life.
Recruitment & Eligibility
- Status
- TERMINATED
- Sex
- All
- Target Recruitment
- 8
Not provided
- Inability to perform lung function testing.
- Inability to complete the study and return for follow-up visits.
- Pregnancy.
- A serious and active heart condition, defined by stable or unstable angina, recent myocardial infarction (within the last 2 years), active or decompensated congestive heart failure or cardiomyopathy.
- End-stage liver disease.
- Patients unable to do mild exercise (patients with orthopedic-neurologic problems; patients who have severe heart failure characterized by an ejection fraction of <20% or by New York Heart Association Class IV disease; patients who should be at complete rest, confined to a bed or chair; or patients for whom physical activity brings on discomfort and for whom symptoms occur at rest).
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Cases with Air Trapping Sylvee 20 COPD patients with lung volumes representing air trapping (RV/TLC and functional residual capacity to TLC \[FRC/TLC\]) Cases without Air Trapping Sylvee 20 COPD patients without lung volumes representing air trapping (RV/TLC and functional residual capacity to TLC \[FRC/TLC\]) Healthy Controls Sylvee Non COPD patients and non-smokers
- Primary Outcome Measures
Name Time Method Correlation between acoustic resonance measurements with clinical testing 2 hours The correlation between acoustic resonance measurements and other measurements from pulmonary function tests and wearable devices (respiratory rate, heart rate and oxygen saturation with 80% accuracy rate) before, during (every minute) and after all tests \[every session\]. Acoustic features will be extracted from the measurements with active acoustic sensors worn on the chest. Other measurements will be measured using medical graded devices such as pulse-oximeters and wearables.
Change and variability fo acoustic resonance 4 hours The change and variability of acoustic resonance features before, during, and after all pulmonary tests, including those where dynamic hyperinflation will be tested: metronome-paced IC, 6-minute walk test and cardio-pulmonary exercise \[every session\]. Acoustic features will be extracted from the measurements with an active acoustic sensor worn on the chest, establishing a baseline before and after all tests. Acoustic resonance changes and their rate of change will be recorded.
- Secondary Outcome Measures
Name Time Method Correlation between acoustic resonance and symptoms 1 hour The correlation between acoustic resonance measurements and patient symptoms and vitals before, during and after all pulmonary function tests, including those where dynamic hyperinflation will be tested: metronome-paced IC, 6-minute walk test and cardio-pulmonary exercise \[every session\]. Acoustic features will be extracted from the measurements with an active acoustic sensor worn on the chest. Patient symptoms and vitals will be collected before and after all tests.
Data quality and user experience with medical-grade adhesive 30 minutes The correlation between medical-grade adhesive options, session length, data quality and patient experience with sensor attachment and detachment procedures. For example: Medical-grade adhesive options will be presented to users at different sessions. Ease of setup, attachment, detachment and data quality will be recorded on a questionnaire for further correlation. A questionnaire with scales from easy-to-hard will be prepared to allow for quantification of different options. The correlation between companion app screens and flows: ease of performing tasks, reading measurements and free-form feedback. Pre-selected alternative application screens, flows and options will be shown to the user in the mobile app and their feedback recorded (free form notes) for User Experience iteration.
Trial Locations
- Locations (1)
El Camino Hospital
🇺🇸Mountain View, California, United States