| Title: | Exhaled breath profiles to detect lung infection with Staphylococcus aureus in children with cystic fibrosis |
| Author(s): | Licht JC; Seidl E; Slingers G; Waters V; de Vries R; Post M; Ratjen F; Grasemann H; |
| Address: | "Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1 X 8, Canada and University of Toronto; Translational Medicine, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1 x 8, Canada. Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1 X 8, Canada and University of Toronto. Breathomix BV, Bargelaan 200, 2333 CW Leiden, the Netherlands. Translational Medicine, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1 x 8, Canada; Division of Infectious Diseases, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1 X 8, Canada and University of Toronto. Translational Medicine, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1 x 8, Canada. Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1 X 8, Canada and University of Toronto; Translational Medicine, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1 x 8, Canada. Electronic address: Hartmut.Grasemann@sickkids.ca" |
| DOI: | 10.1016/j.jcf.2023.02.010 |
| ISSN/ISBN: | 1873-5010 (Electronic) 1569-1993 (Linking) |
| Abstract: | "BACKGROUND: An electronic nose (eNose) can be used to detect volatile organic compounds (VOCs). Exhaled breath contains numerous VOCs and individuals' VOCs mixtures create distinct breath profiles. Previous reports have shown that eNose can detect lung infections. Whether eNose can detect Staphylococcus aureus airway infections in breath of children with cystic fibrosis (CF) is currently unclear. METHODS: In this cross-sectional observational study, a cloud-connected eNose was used for breath profile analysis of clinically stable paediatric CF patients with airway microbiology cultures positive or negative for CF pathogens. Data-analysis involved advanced signal processing, ambient correction and statistics based on linear discriminant and receiver operating characteristics (ROC) analyses. RESULTS: Breath profiles from 100 children with CF (median predicted FEV(1) 91%) were obtained and analysed. CF patients with positive airway cultures for any CF pathogen were distinguishable from no CF pathogens (no growth or usual respiratory flora) with accuracy of 79.0% (AUC-ROC 0.791; 95% CI: 0.669-0.913) and between patients positive for Staphylococcus aureus (SA) only and no CF pathogen with accuracy of 74.0% (AUC-ROC 0.797; 95% CI: 0.698-0.896). Similar differences were seen for Pseudomonas aeruginosa (PA) infection vs no CF pathogens (78.0% accuracy, AUC-ROC 0.876, 95% CI: 0.794-0.958). SA- and PA-specific signatures were driven by different sensors in the SpiroNose suggesting pathogen-specific breath signatures. CONCLUSIONS: Breath profiles of CF patients with SA in airway cultures are distinct from those with no infection or PA infection, suggesting the utility of eNose technology in the detection of this early CF pathogen in children with CF" |
| Keywords: | Cystic fibrosis Electronic nose Pseudomonas aeruginosa Respiratory disease Respiratory infections Staphylococcus aureus Volatile organic compounds; |
| Notes: | "PublisherLicht, Johann-Christoph Seidl, Elias Slingers, Gitte Waters, Valerie de Vries, Rianne Post, Martin Ratjen, Felix Grasemann, Hartmut eng Netherlands 2023/02/28 J Cyst Fibros. 2023 Feb 25:S1569-1993(23)00062-0. doi: 10.1016/j.jcf.2023.02.010" |
