Coughing Up Answers: Smartphones Predict COVID-19 Severity

Highlights:

A team of researchers pioneers a simple, accessible tool for assessing COVID-19 severity using cough sounds recorded on smartphones
This innovative method enables healthcare providers to identify patients at risk of developing severe disease
While initially focused on COVID-19, this breakthrough paves the way for using cough analysis as a diagnostic tool for various respiratory conditions

Although most people affected by COVID-19 experience mild symptoms and recover within a few weeks, the global pandemic caused by the SARS-CoV-2 virus remains a significant health challenge. Some individuals may progress to develop more severe illness and pneumonia, leading to a less favorable prognosis.

Currently, diagnostic and prognostic tools rely on costly and less accessible imaging methods like radiography, ultrasound, or CT scans. Therefore, there is a pressing need to create a simpler and more readily available tool that allows healthcare providers to identify patients at risk of developing severe disease. This would streamline patient assessment and enable early intervention, even in home or primary care settings ().

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A research team led by IBEC and Hospital del Mar, in collaboration with the Universitat Politècnica de Catalunya (UPC), CIBER-BBN, and CIBERES, has conducted a study focused on analyzing cough sounds in the early stages of COVID-19. This method is proposed as a potential straightforward and accessible tool for assessing the risk of severe pneumonia.

Smartphone Aids Covid-19 Diagnosis using Cough Sounds

The study involved recording voluntary coughs from 70 COVID-19 patients using smartphones, all within the first 24 hours of hospital admission. IBEC conducted an acoustic analysis of these recordings, revealing significant differences in cough sounds depending on the severity of the respiratory condition, as confirmed by imaging tests and the need for supplemental oxygen.

The results suggest that this analysis could categorize COVID-19 patients as having mild, moderate, or severe cases, as well as monitor patients with persistent COVID-19. The study was conducted between April 2020 and May 2021 at Hospital del Mar, and the findings have been published in the European Respiratory Journal Open Research.

Raimon Jané, a professor at UPC and the principal investigator at IBEC and CIBER-BBN, leads the Biomedical Signal Processing and Interpretation (BIOSPIN) group at IBEC. This group has developed the methodology and algorithms for the acoustic analysis of cough signals collected via smartphones

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Using a statistical model known as a linear mixed model, the team identified five parameters, based on sound frequencies, that exhibited significant differences in the coughs of patients with varying levels of disease severity and pneumonia progression. These differences may reflect the progressive respiratory system alterations in patients with COVID-19.

Linking Cough Acoustics to Severe Pneumonia in COVID

“While previous studies have proposed acoustic cough analysis for diagnosing respiratory diseases, our aim was to specifically investigate the link between cough acoustics and varying levels of pneumonia severity in COVID-19 patients," explains Jané, the senior co-author of the study.

The authors highlight that cough analysis can serve a dual purpose: early detection of severe COVID-19 cases and remote monitoring of their progression, including the assessment of potential complications. However, further research with a larger patient sample is needed to validate the findings of this cross-sectional study, which could pave the way for using cough analysis as a diagnostic tool for COVID-19 and other respiratory diseases.

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Dr. Joaquim Gea, emeritus head of the Pneumology Service and researcher at the Hospital del Mar Research Institute, and senior co-author of the study, emphasizes that these findings could be particularly beneficial "in regions with limited medical infrastructure or during emergency situations. This approach can aid in the prompt identification and isolation of COVID-19 patients, thus facilitating proper medical care and the implementation of control measures."

Another important aspect is that while the study primarily focused on COVID-19, it lays the foundation for applying this model to other respiratory conditions.

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Reference:

Nighttime Continuous Contactless Smartphone-Based Cough Monitoring for the Ward: Validation Study - (https://pubmed.ncbi.nlm.nih.gov/36655551/)

Source-Medindia