Exhaled Metabolite Patterns to Identify Recent Asthma Exacerbations

Asthma is a chronic respiratory disease that can lead to exacerbations, defined as acute episodes of worsening respiratory symptoms and lung function. Predicting the occurrence of these exacerbations is an important goal in asthma management. The measurement of exhaled breath by electronic nose (eNo...

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Bibliographic Details
Published in:Metabolites 2021-12, Vol.11 (12), p.872
Main Authors: van Bragt, Job J M H, Principe, Stefania, Hashimoto, Simone, Versteeg, D Naomi, Brinkman, Paul, Vijverberg, Susanne J H, Weersink, Els J M, Scichilone, Nicola, Maitland-van der Zee, Anke H
Format: Article
Language:English
Subjects:
Accuracy
Antibiotics
Asthma
Bacterial infections
Biomarkers
Chronic illnesses
Chronic obstructive pulmonary disease
Datasets
Discriminant analysis
Electronic noses
eNose
exacerbation
exhaled breath
Hospital costs
Infections
Inflammation
Metabolites
Oxidative stress
Respiration
Respiratory diseases
Respiratory function
Sensitivity analysis
Steroids
Viral infections
VOCs
Volatile organic compounds
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Summary:Asthma is a chronic respiratory disease that can lead to exacerbations, defined as acute episodes of worsening respiratory symptoms and lung function. Predicting the occurrence of these exacerbations is an important goal in asthma management. The measurement of exhaled breath by electronic nose (eNose) may allow for the monitoring of clinically unstable asthma and exacerbations. However, data on its ability to perform this is lacking. We aimed to evaluate whether eNose could identify patients that recently had asthma exacerbations. We performed a cross-sectional study, measuring exhaled breath using the SpiroNose in adults with a physician-reported diagnosis of asthma. Patients were randomly divided into a training ( = 252) and validation ( = 109) set. For the analysis of eNose signals, principal component (PC) and linear discriminant analysis (LDA) were performed. LDA, based on PC1-4, reliably discriminated between patients who had a recent exacerbation from those who had not (training receiver operating characteristic (ROC)-area under the curve (AUC) = 0.76,95% CI 0.69-0.82), (validation AUC = 0.76, 95% CI 0.64-0.87). Our study showed that, exhaled breath analysis using eNose could accurately identify asthma patients who recently had an exacerbation, and could indicate that asthma exacerbations have a specific exhaled breath pattern detectable by eNose.
ISSN:2218-1989
2218-1989
DOI:10.3390/metabo11120872