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

Abstract

Research QuestionWhat is the impact of the duration of cough monitoring on its accuracy in detecting changes in the cough frequency?Materials and MethodsThis 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.Results616 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.InterpretationDetecting 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.

Long-COVID severe refractory cough: discussion of a case with 6-week longitudinal cough characterization

“…He was also educated to try cough suppression techniques and improve vocal hygiene [ 7 8 9 ]. We started continuous cough monitoring using the Hyfe, a smartphone application-based cough tracker [ 10 ].…”

Performance evaluation of the smartphone-based AI cough monitoring app - Hyfe Cough Tracker against solicited respiratory sounds

“…This performance evaluation study was conducted at the University of Navarra, Spain, between September to November 2021 and was nested in a larger cohort study (Clinicaltrials.org NCT04762693). 12 Both the main and the nested study received approval by the Medical Research Ethics Committee of the chartered community of Navarra (PI_2020/107). Students and staff from the university of Navarra were invited to participate via email.…”

“…Recent advances in artificial intelligence (AI) allow the monitoring of cough in a non-obtrusive way using smartphones or other wearable digital devices. 6,[11][12][13][14] Unobtrusive and privacy preserving passive cough monitors could revolutionize clinical practice and research in the field of respiratory diseases.…”

“…14 Evaluating cough and its patterns with limited recording periods (e.g., 24 h) can be misleading, in particular, if only small changes in cough frequency are captured over the limited 24 h recording and in cases that have high variance of cough counts. 12 However, the nature and volume of data generated with protracted monitoring raises new challenges in technology validation. A central challenge in this work is establishing a gold standard against which automated devices' performance can be evaluated.…”

The Statistics of Counting Coughs: Easy as 1, 2, 3?

“…Some of the rhythms around us are more elusive, though, so routine as to be hidden in plain sight-or sound-in the case of cough. Cough is one of the most common reasons people seek medical care [1,2], and yet to date it is simply not measured continuously [3]…”