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The Influence of Smoking Status on Exhaled Breath Profiles in Asthma and COPD Patients.
Principe, Stefania; van Bragt, Job J M H; Longo, Cristina; de Vries, Rianne; Sterk, Peter J; Scichilone, Nicola; Vijverberg, Susanne J H; Maitland-van der Zee, Anke H.
Afiliação
  • Principe S; Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands.
  • van Bragt JJMH; Dipartimento Universitario di Promozione della Salute, Materno Infantile, University of Palermo, Medicina Interna e Specialistica di Eccellenza "G. D'Alessandro"(PROMISE) c/o Pneumologia, AOUP "Policlinico Paolo Giaccone", 90127 Palermo, Italy.
  • Longo C; Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands.
  • de Vries R; Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands.
  • Sterk PJ; Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands.
  • Scichilone N; Breathomix b.v., 2333 Leiden, The Netherlands.
  • Vijverberg SJH; Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands.
  • Maitland-van der Zee AH; Dipartimento Universitario di Promozione della Salute, Materno Infantile, University of Palermo, Medicina Interna e Specialistica di Eccellenza "G. D'Alessandro"(PROMISE) c/o Pneumologia, AOUP "Policlinico Paolo Giaccone", 90127 Palermo, Italy.
Molecules ; 26(5)2021 Mar 04.
Article em En | MEDLINE | ID: mdl-33806279
ABSTRACT
Breath analysis using eNose technology can be used to discriminate between asthma and COPD patients, but it remains unclear whether results are influenced by smoking status. We aim to study whether eNose can discriminate between ever- vs. never-smokers and smoking <24 vs. >24 h before the exhaled breath, and if smoking can be considered a confounder that influences eNose results. We performed a cross-sectional analysis in adults with asthma or chronic obstructive pulmonary disease (COPD), and healthy controls. Ever-smokers were defined as patients with current or past smoking habits. eNose measurements were performed by using the SpiroNose. The principal component (PC) described the eNose signals, and linear discriminant analysis determined if PCs classified ever-smokers vs. never-smokers and smoking <24 vs. >24 h. The area under the receiver-operator characteristic curve (AUC) assessed the accuracy of the models. We selected 593 ever-smokers (167 smoked <24 h before measurement) and 303 never-smokers and measured the exhaled breath profiles of discriminated ever- and never-smokers (AUC 0.74; 95% CI 0.66-0.81), and no cigarette consumption <24h (AUC 0.54, 95% CI 0.43-0.65). In healthy controls, the eNose did not discriminate between ever or never-smokers (AUC 0.54; 95% CI 0.49-0.60) and recent cigarette consumption (AUC 0.60; 95% CI 0.50-0.69). The eNose could distinguish between ever and never-smokers in asthma and COPD patients, but not recent smokers. Recent smoking is not a confounding factor of eNose breath profiles.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2021 Tipo de documento: Article