Diagnostic performance of eNose technology in COVID-19 patients after hospitalization
Aim: To evaluate whether VOCs in exhaled breath detected with eNose technology can differentiate between previously hospitalized COVID-19 patients and healthy individuals, and discriminate subgroups with impaired lung diffusion capacity or patients with COVID-19-related CT abnormalities.
Take home message: eNose technology shows promise as a non-invasive tool to monitor long-term lung changes in individuals recovering from COVID-19, identifying persistent metabolic and inflammatory patterns that may support follow-up care and early detection of complications.
Introduction
This study examines the use of electronic nose (eNose) technology to analyze exhaled breath in individuals recovering from COVID-19 three months post-hospitalization, aiming to detect ongoing pulmonary changes. COVID-19 often leads to persistent lung issues even months after recovery, necessitating non-invasive tools to identify at-risk patients early. By analyzing volatile organic compounds (VOCs), eNose technology can provide a snapshot of metabolic and pathophysiological processes reflective of respiratory health.
Methods
The study followed 135 adults recovering from COVID-19 from Leiden University Medical Centre, three months post-discharge, and compared their breath profiles with 174 healthy controls. Using the SpiroNose®, participants provided breath samples, which were analyzed and stored on the BreathBase® platform. Pulmonary function tests and CT scans assessed lung health, with COVID-19 patients further stratified based on lung diffusion capacity and CT findings. VOC profiles were processed using principal component analysis (PCA) and linear discriminant analysis to classify results.
Results
The eNose successfully differentiated individuals recovering from COVID-19 from healthy controls with an AUC of 0.89, suggesting that eNose technology can detect lingering metabolic and inflammatory changes post-COVID-19. However, it did not distinguish between these individuals based on lung diffusion or CT abnormalities, indicating that the VOC signatures reflect a shared underlying pathophysiology rather than specific structural lung changes.
Discussion
This study highlights eNose technology’s potential as a non-invasive tool for monitoring COVID-19 recovery. The distinct breath profiles in individuals recovering from COVID-19 may indicate persistent inflammation or remodeling processes in the lungs, potentially aiding in identifying patients at risk for long-term sequelae. However, the inability to distinguish specific lung function impairments suggests that eNose profiles capture generalized, rather than condition-specific, post-COVID effects. Further studies are warranted to confirm these findings and explore the broader utility of eNose for tracking recovery and identifying complications in COVID-19 patients over time.
