Profil leicht verdampfender organischer Substanzen in der Ausatemluft von Kindern mit Mukoviszidose

Background Breath analysis by electronic nose technology has shown differences between healthy individuals and those with cystic fibrosis (CF), but whether these differences can be explained by airway infection alone is currently unclear.

Methods In this cross-sectional observational study, a cloud-connected eNose, the SpiroNose, 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 analysis and receiver operating characteristics (ROC) analysis.

Results Breath from 100 children with CF (median ppFEV₁ 91%) and 25 age matched healthy controls (HC) were analysed. The eNose distinguished between CF patients and HC with high accuracy (96.0%, AUC-ROC 0.985, 95% CI 0.966-1); similar differences from HC were also seen for CF with no CF pathogens (91.1%, AUC-ROC 0.994, CI 0.979-1) and for CFTR modulator treated patients (94.5%, AUC-ROC 0.999, CI 0.994-1). Within the CF group, eNose distinguished between those with airway cultures positive for any CF pathogen and no CF pathogens (79.0%, AUC-ROC 0.791, CI 0.669-0.913), as well as Staphylococcus aureus (SA) only vs. no CF pathogens on culture (78.1%, AUC-ROC 0.788, CI 0.665-0.91).

Conclusions Differences in breath profiles between children with CF and controls cannot be explained by presence of CF pathogens alone. Breath profiles of CF patients with SA in airway cultures are distinct from those with no infection, suggesting the utility of eNose technology in the detection of this early CF pathogen in children with CF.

Publication History

Article published online:
21 September 2022