TY - JOUR
T1 - Exhaled metabolite patterns to identify recent asthma exacerbations
AU - van Bragt, Job J. M. H.
AU - Principe, Stefania
AU - Hashimoto, Simone
AU - Versteeg, D. Naomi
AU - Brinkman, Paul
AU - Vijverberg, Susanne J. H.
AU - Weersink, Els J. M.
AU - Scichilone, Nicola
AU - der Zee, Anke H. Maitland-van
N1 - Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/12/1
Y1 - 2021/12/1
N2 - 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 (n = 252) and validation (n = 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.
AB - 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 (n = 252) and validation (n = 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.
KW - Asthma
KW - ENose
KW - Exacerbation
KW - Exhaled breath
UR - http://www.scopus.com/inward/record.url?scp=85121728154&partnerID=8YFLogxK
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85121728154&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/34940630
U2 - https://doi.org/10.3390/metabo11120872
DO - https://doi.org/10.3390/metabo11120872
M3 - Article
C2 - 34940630
SN - 2218-1989
VL - 11
JO - Metabolites
JF - Metabolites
IS - 12
M1 - 872
ER -