Feasibility and Utility of a Smartphone Application-Based Longitudinal Cough Monitoring in Chronic Cough Patients in a Real-World Setting.

PURPOSE: This study evaluated the feasibility and utility of longitudinal cough frequency monitoring with the Hyfe Cough Tracker, a mobile application equipped with cough-counting artificial intelligence algorithms, in real-world patients with chronic cough. METHODS: Patients with chronic cough (> 8-week duration) were monitored continuously for cough frequency with the Hyfe app for at least one week. Cough was also evaluated using the Leicester Cough Questionnaire (LCQ) and daily cough severity scoring (0-10). The study analyzed adherence rate, the correlation between objective cough frequency and subjective scores, day-to-day variability, and patient experience. RESULTS: Of 65 subjects consecutively recruited, 43 completed the study. The median cough monitoring duration was 13.9 days, with a median adherence of 91%. Study completion was associated with baseline cough severity, and the adherence rate was higher in younger subjects. Cross-sectional correlation analyses showed modest correlations between objective and subjective cough measures at the group level. However, in time series correlation analyses, correlations between objective and subjective measures widely varied across individuals. Cough frequency had greater day-to-day variability than daily cough severity scores in most subjects. A patient experience survey found that 70% of participants found the cough monitoring helpful, 86% considered it acceptable, and 84% felt it was easy to use. CONCLUSION: Monitoring cough frequency longitudinally for at least one week may be feasible. The substantial day-to-day variability in objective cough frequency highlights the need for continuous monitoring. Grasping the implications of daily cough variability is crucial in both clinical practice and clinical trials.

Performance evaluation of human cough annotators: optimal metrics and sex differences.

INTRODUCTION: Despite its high prevalence and significance, there is still no widely available method to quantify cough. In order to demonstrate agreement with the current gold standard of human annotation, emerging automated techniques require a robust, reproducible approach to annotation. We describe the extent to which a human annotator of cough sounds (a) agrees with herself (intralabeller or intrarater agreement) and (b) agrees with other independent labellers (interlabeller or inter-rater agreement); we go on to describe significant sex differences in cough sound length and epochs size. MATERIALS AND METHODS: 24 participants wore an audiorecording smartwatch to capture 6-24 hours of continuous audio. A randomly selected sample of the whole audio was labelled twice by an expert annotator and a third time by six trained annotators. We collected 400 hours of audio and analysed 40 hours. The cough counts as well as cough seconds (any 1 s of time containing at least one cough) from different annotators were compared and summary statistics from linear and Bland-Altman analyses were used to quantify intraobserver and interobserver agreement. RESULTS: There was excellent intralabeller (less than two disagreements per hour monitored, Pearson's correlation 0.98) and interlabeller agreement (Pearson's correlation 0.96), using cough seconds as the unit of analysis decreased annotator discrepancies by 50% in comparison to coughs. Within this data set, it was observed that the length of cough sounds and epoch size (number of coughs per bout or attach) differed between women and men. CONCLUSION: Given the decreased interobserver variability in annotation when using cough seconds (vs just coughs) we propose their use for manually annotating cough when assessing of the performance of automatic cough monitoring systems. The differences in cough sound length and epochs size may have important implications for equality in the development of cough monitoring tools. TRIAL REGISTRATION NUMBER: NCT05042063.