Longitudinal passive cough monitoring and its implications for detecting changes in clinical status

Research question What is the impact of the duration of cough monitoring on its accuracy in detecting changes in the cough frequency? Materials and methods This is a statistical analysis of a prospective cohort study. Participants were recruited in the city of Pamplona (Northern Spain), and their cough frequency was passively monitored using smartphone-based acoustic artificial intelligence software. Differences in cough frequency were compared using a one-tailed Mann-Whitney U test and a randomisation routine to simulate 24-h monitoring. Results 616 participants were monitored for an aggregated duration of over 9 person-years and registered 62 325 coughs. This empiric analysis found that an individual's cough patterns are stochastic, following a binomial distribution. When compared to continuous monitoring, limiting observation to 24 h can lead to inaccurate estimates of change in cough frequency, particularly in persons with low or small changes in rate. Interpretation Detecting changes in an individual's rate of coughing is complicated by significant stochastic variability within and between days. Assessing change based solely on intermittent sampling, including 24-h, can be misleading. This is particularly problematic in detecting small changes in individuals who have a low rate and/or high variance in cough pattern.

Automated summary

This study investigates the impact of duration of cough monitoring on its accuracy. The results show that individual cough patterns are stochastic and estimating changes in cough frequency is complicated by significant stochastic variability within and between days. Limiting observation to 24 hours can lead to inaccurate estimates, particularly for individuals with small changes in cough rate.