BACKGROUND: Electronic nose (E-nose) technology has been successfully used to diagnose a number of microbial infections. We have investigated the potential use of an E-nose for the diagnosis of ventilator-associated pneumonia (VAP) by detecting micro-organisms in bronchoalveolar lavage (BAL) fluid in a prospective comparative study of E-nose analysis and microbiology. MATERIALS AND METHODS: BAL samples were collected using a blind technique from 44 patients following a minimum of 72 h mechanical ventilation. Control samples were collected from six patients mechanically ventilated on the intensive care unit (ICU) immediately following elective surgery. Quantitative microbiological culture and E-nose headspace analysis of the BAL samples were undertaken. Multivariate analysis was applied to correlate E-nose response with microbiological growth. RESULTS: E-nose fingerprints correctly classified 77% of the BAL samples, with and without microbiological growth from patients not on antibiotics. Inclusion of patients on antibiotics resulted in 68% correct classification. Seventy per cent of isolates, cultured in the laboratory from the clinical samples, were accurately discriminated into four clinically significant groups. CONCLUSIONS: E-nose technology can accurately discriminate between different microbial species in BAL samples from ventilated patients on ICU at risk of developing VAP with accuracy comparable with accepted microbiological techniques.
BACKGROUND: Electronic nose (E-nose) technology has been successfully used to diagnose a number of microbial infections. We have investigated the potential use of an E-nose for the diagnosis of ventilator-associated pneumonia (VAP) by detecting micro-organisms in bronchoalveolar lavage (BAL) fluid in a prospective comparative study of E-nose analysis and microbiology. MATERIALS AND METHODS: BAL samples were collected using a blind technique from 44 patients following a minimum of 72 h mechanical ventilation. Control samples were collected from six patients mechanically ventilated on the intensive care unit (ICU) immediately following elective surgery. Quantitative microbiological culture and E-nose headspace analysis of the BAL samples were undertaken. Multivariate analysis was applied to correlate E-nose response with microbiological growth. RESULTS: E-nose fingerprints correctly classified 77% of the BAL samples, with and without microbiological growth from patients not on antibiotics. Inclusion of patients on antibiotics resulted in 68% correct classification. Seventy per cent of isolates, cultured in the laboratory from the clinical samples, were accurately discriminated into four clinically significant groups. CONCLUSIONS: E-nose technology can accurately discriminate between different microbial species in BAL samples from ventilated patients on ICU at risk of developing VAP with accuracy comparable with accepted microbiological techniques.
Authors: I G van der Sar; N Wijbenga; M E Hellemons; C C Moor; G Nakshbandi; J G J V Aerts; O C Manintveld; M S Wijsenbeek Journal: Respir Res Date: 2021-09-17