Clinical Feasibility of a Non-invasive Wearable Acoustic Device for Measuring Air Trapping in COPD

Clinical Feasibility of a Non-invasive Wearable Acoustic Device for Measuring Air Trapping in COPD

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.

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.

Inclusion criteria for cases (COPD patients) are:

1. Men or women over 40 years old.
2. Spirometric COPD.
3. A history of smoking at least 20 pack-years.

Exclusion Criteria:

1. Inability to perform lung function testing.
2. Inability to complete the study and return for follow-up visits.
3. Pregnancy.
4. 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.
5. End-stage liver disease.
6. 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).