Year: 2025
Type: article
Abstract: PURPOSE: Validation of an alert mechanism for COPD exacerbations based on coughing detected by a stationary unobtrusive nighttime monitor. METHODS: This prospective double-blind longitudinal study of cough monitoring included 40 chronic obstructive pulmonary disease (COPD) patients. Participants underwent cough monitoring and completed a daily questionnaire for 12 weeks. If no exacerbation occurred within that period patients were asked to continue being monitored for a further 12 weeks. The automated system identified deteriorating trends in cough based on a personalized cough classifier and the alerts were compared with patient reported exacerbation onsets. RESULTS: Thirty-eight patients [median age 72 (range 57-84)], median FEV-1% predicted 43% (range 20-106%) completed the study and had 41 exacerbations over a total of 3981 days. For 32 patients, the cough monitor data allowed classifier personalization, trend analysis, and alert generation. Based on the trend data, it is estimated that ∼30% of exacerbations are not associated with an increase in cough. The alert mechanism flagged 59% of the exacerbations. For the cases with alerts preceding the onset, the associated lead time was 4 days or more. CONCLUSION: Though based on a single variable only, the cough-based alert system captured more than half of the exacerbations in a passive, free-living scenario. No adherence issues were reported, and patients confirmed the unobtrusive and hassle-free nature of the approach.
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,650
Funder: Philips
OpenAlex ID: W4409440663