TY - JOUR
T1 - Objective cough counting in clinical practice and public health
T2 - a scoping review
AU - Zimmer, Alexandra J.
AU - Das, Rishav
AU - Lopez, Patricia Espinoza
AU - Nafade, Vaidehi
AU - Gore, Genevieve
AU - Ugarte-Gil, César
AU - Chung, Kian Fan
AU - Song, Woo Jung
AU - Pai, Madhukar
AU - Grandjean Lapierre, Simon
N1 - Publisher Copyright:
Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.
PY - 2025/11/1
Y1 - 2025/11/1
N2 - Quantifying cough can offer value for respiratory disease assessment and monitoring. Traditionally, patient-reported outcomes have provided subjective insights into symptoms. Novel digital cough counting tools now enable objective assessments; however, their integration into clinical practice is limited. The aim of this scoping review was to address this gap in the literature by examining the use of automated and semiautomated cough counting tools in patient care and public health. A systematic search of six databases and preprint servers identified studies published up to Feb 12, 2025. From 6968 records found, 618 full-text articles were assessed for eligibility, and 77 were included. Five clinical use cases were identified-disease diagnosis, severity assessment, treatment monitoring, health outcome prediction, and syndromic surveillance-with scarce available evidence supporting each use case. Moderate correlations were found between objective cough frequency and patient-reported cough severity (median correlation coefficient of 0.42, IQR 0·38 to 0·59) and quality of life (median correlation coefficient of -0·49, -0·63 to -0·44), indicating a complex relationship between quantifiable measures and perceived symptoms. Feasibility challenges include device obtrusiveness, monitoring adherence, and addressing patient privacy concerns. Comprehensive studies are needed to validate these technologies in real-world settings and show their clinical value. Early feasibility and acceptability assessments are essential for successful integration.
AB - Quantifying cough can offer value for respiratory disease assessment and monitoring. Traditionally, patient-reported outcomes have provided subjective insights into symptoms. Novel digital cough counting tools now enable objective assessments; however, their integration into clinical practice is limited. The aim of this scoping review was to address this gap in the literature by examining the use of automated and semiautomated cough counting tools in patient care and public health. A systematic search of six databases and preprint servers identified studies published up to Feb 12, 2025. From 6968 records found, 618 full-text articles were assessed for eligibility, and 77 were included. Five clinical use cases were identified-disease diagnosis, severity assessment, treatment monitoring, health outcome prediction, and syndromic surveillance-with scarce available evidence supporting each use case. Moderate correlations were found between objective cough frequency and patient-reported cough severity (median correlation coefficient of 0.42, IQR 0·38 to 0·59) and quality of life (median correlation coefficient of -0·49, -0·63 to -0·44), indicating a complex relationship between quantifiable measures and perceived symptoms. Feasibility challenges include device obtrusiveness, monitoring adherence, and addressing patient privacy concerns. Comprehensive studies are needed to validate these technologies in real-world settings and show their clinical value. Early feasibility and acceptability assessments are essential for successful integration.
UR - https://www.scopus.com/pages/publications/105025226798
UR - https://www.scopus.com/pages/publications/105025226798#tab=citedBy
U2 - 10.1016/j.landig.2025.100908
DO - 10.1016/j.landig.2025.100908
M3 - Review article
C2 - 41274833
AN - SCOPUS:105025226798
SN - 2589-7500
VL - 7
SP - 100908
JO - The Lancet Digital Health
JF - The Lancet Digital Health
IS - 11
ER -