Exhaled Breath Metabolomics for the Diagnosis of Pneumonia in Intubated and Mechanically-Ventilated Intensive Care Unit (ICU)-Patients

Abstract

The diagnosis of hospital-acquired pneumonia remains challenging. We hypothesized that analysis of volatile organic compounds (VOCs) in exhaled breath could be used to diagnose pneumonia or the presence of pathogens in the respiratory tract in intubated and mechanically-ventilated intensive care unit patients. In this prospective, single-centre, cross-sectional cohort study breath from mechanically ventilated patients was analysed using gas chromatography-mass spectrometry. Potentially relevant VOCs were selected with a p-value < 0.05 and an area under the receiver operating characteristics curve (AUROC) above 0.7. These VOCs were used for principal component analysis and partial least square discriminant analysis (PLS-DA). AUROC was used as a measure of accuracy. Ninety-three patients were included in the study. Twelve of 145 identified VOCs were significantly altered in patients with pneumonia compared to controls. In colonized patients, 52 VOCs were significantly different. Partial least square discriminant analysis classified patients with modest accuracy (AUROC: 0.73 (95% confidence interval (CI): 0.57-0.88) after leave-one-out cross-validation). For determining the colonization status of patients, the model had an AUROC of 0.69 (95% CI: 0.57-0.82) after leave-one-out cross-validation. To conclude, exhaled breath analysis can be used to discriminate pneumonia from controls with a modest to good accuracy. Furthermore breath profiling could be used to predict the presence and absence of pathogens in the respiratory tract. These findings need to be validated externally.

Keywords: breathomics; critical care; diagnosis; intensive care; mechanical ventilation; respiratory infection; volatile organic compounds.

Figure 1

Flowchart of screened patients.

Figure 2

Ion count of volatile organic compounds (VOCs) in all four groups that showed a p-value < 0.05 between patients with probable pneumonia compared to controls.

Figure 3

Volcano plot for comparison of patients with probable/proven pneumonia vs. controls. Each dot represents a VOC. The y-axis shows the inverse of the 10-log transformed p-value: the higher on the axis, the more significant. The x-axis shows the fold change between the groups. The size of the dots represents the AUROC.

Figure 4

First (PC1) and second (PC2) principal component explained 35.1% and 22.4% of the variance, respectively. Predicted probability calculated by the PLSDA model. From left to right: controls, colonized controls, possible pneumonia, and probable pneumonia.

Figure 5

Ion count of VOCs that showed a p-value < 0.001.

Figure 6

Volcano plot for comparison of patients with probable/proven pneumonia vs. controls. Each dot represents a VOC. The y-axis shows the inverse of the 10-log transformed p-value: the higher on the axis, the more significant. The x-axis shows the fold change between the groups. The size of the dots represents the AUROC. The horizontal line shows p = 0.05 with dots above this line having p < 0.05.