ERJ Open Research (May 2023)

Differences in acoustic features of cough by pneumonia severity in patients with COVID-19: a cross-sectional study

  • Clare Davidson,
  • Oswaldo Antonio Caguana,
  • Manuel Lozano-García,
  • Mariela Arita Guevara,
  • Luis Estrada-Petrocelli,
  • Ignasi Ferrer-Lluis,
  • Yolanda Castillo-Escario,
  • Pilar Ausín,
  • Joaquim Gea,
  • Raimon Jané

DOI
https://doi.org/10.1183/23120541.00247-2022
Journal volume & issue
Vol. 9, no. 3

Abstract

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Background Acute respiratory syndrome due to coronavirus 2 (SARS-CoV-2) is characterised by heterogeneous levels of disease severity. It is not necessarily apparent whether a patient will develop severe disease or not. This cross-sectional study explores whether acoustic properties of the cough sound of patients with coronavirus disease 2019 (COVID-19), the illness caused by SARS-CoV-2, correlate with their disease and pneumonia severity, with the aim of identifying patients with severe disease. Methods Voluntary cough sounds were recorded using a smartphone in 70 COVID-19 patients within the first 24 h of their hospital arrival, between April 2020 and May 2021. Based on gas exchange abnormalities, patients were classified as mild, moderate or severe. Time- and frequency-based variables were obtained from each cough effort and analysed using a linear mixed-effects modelling approach. Results Records from 62 patients (37% female) were eligible for inclusion in the analysis, with mild, moderate and severe groups consisting of 31, 14 and 17 patients respectively. Five of the parameters examined were found to be significantly different in the cough of patients at different disease levels of severity, with a further two parameters found to be affected differently by the disease severity in men and women. Conclusions We suggest that all these differences reflect the progressive pathophysiological alterations occurring in the respiratory system of COVID-19 patients, and potentially would provide an easy and cost-effective way to initially stratify patients, identifying those with more severe disease, and thereby most effectively allocate healthcare resources.