Mobile Phone Auscultation Accurately Diagnoses Chronic Obstructive Pulmonary Disease Using Nonlinear Respiratory Biofluid Dynamics.

Abstract

Background/Objectives: Chronic obstructive pulmonary disease (COPD) remains a condition with high morbidity, mortality, and misdiagnosis. The gold standard pulmonary function testing with spirometry has limited availability. This study seeks to test a novel diagnostic test based on auscultatory mapping of pulmonary dynamics. This NIH-funded study aimed to develop a COPD detection technology, using mobile phone auscultation, for situations in which spirometry is not available. Methods: This prospective study collected mobile phone auscultation data on patients presenting for spirometry and evaluation by a pulmonologist. All subjects had same-day or recent (less than 6 months) spirometry in one PFT laboratory. After informed consent, the subjects underwent respiratory auscultation using a selection of mobile phone brands. The auscultation methods included normal breathing observed at the left axillary site and egophony observed at the right supra clavicular fossa. The team created models from the recordings using Time Series Dynamics (TSD), proprietary software that uses computational nonlinear dynamics to characterize the respiratory biofluid dynamics implied by the acoustic data. Results: We enrolled a total of 108 patients (34.3% male), from 19 to 85 years of age (median 61 years). Among the patients, 64 (59.3%) subjects identified as White, 43 (39.8%) as Black, and 1 as Asian. Among the two cohorts with diverse comorbidities, 52 subjects had confirmed COPD and 56 did not. The cohorts differed significantly in age and body mass index, but not in race, number of comorbidities, or COPD assessment test scores. They had significant differences in forced expiratory volume in 1 s (FEV1), the FEV1/FVC (forced vital capacity) ratio, but not FVC. The recordings from the egophonic and axillary sites were initially modeled separately and then combined in a single composite model. The modeling produced excellent results with 90%+ AUC and sensitivity in both the test and train sets relative to the gold standard. Conclusions: Evidence suggests that a mobile phone auscultation device can accurately determine COPD diagnosis. In frontline applications where the availability of gold standard pulmonary function testing is limited, the device could improve the detection of COPD, a condition with significant over- and under-diagnosis. Future trials will investigate the ability of patients to self-record. Success would support remote COPD testing using transmitted telehealth recording data, bringing diagnosis to patients in underserved populations.