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RationaleThe concentration of octane and acetaldehyde in exhaled breath has good diagnostic accuracy for Acute Respiratory Distress Syndrome (ARDS). We aimed to determine whether breath octane and acetaldehyde are able to distinguish the presence and absence of ARDS in critically ill patients suspected to have ventilator-associated pneumonia (VAP).MethodsThis is a secondary analysis of a prospective observational study into exhaled breath analysis using gas-chromatography-time of flight-mass spectrometry. Difference in the relative abundance of octane and acetaldehyde in exhaled breath was compared between patients with and without ARDS using the Mann-Whitney U-test and the association was quantified using logistic regression. The discriminative accuracy of octane and acetaldehyde, alone or in combination, was calculated using the area under the curve of the ROC (AUROCC).ResultsWe included 98 patients of whom 32 had ARDS and 66 did not. The area under the acetaldehyde peak was higher in patients with ARDS (p=0.03), and associated with the presence of ARDS (OR: 1.06 per 100000 count change (95% CI: 1.02–1.13), p=0.01). A combined model with octane and acetaldehyde showed a high specificity and low sensitivity (respectively, 90% and 40.6%), with a low accuracy (AUROCC: 0.65, 95% CI: 0.53–0.78).ConclusionPatients suspected to have VAP with ARDS had a higher acetaldehyde concentration in exhaled breath than patients suspected to have VAP without ARDS. However, in this patient population, discrimination of these breath biomarkers for ARDS was poor, indicating the difficulty of translating diagnostic tests between clinical settings.

Background: There is a demand for a non-invasive bedside method to diagnose Acute Respiratory Distress Syndrome (ARDS). Octane was discovered and validated as the most important breath biomarker for diagnosis of ARDS using gas-chromatography and mass-spectrometry (GC-MS). However, GC-MS is unsuitable as a point-of-care (POC) test in the intensive care unit (ICU). Therefore, we determined if a newly developed POC breath test can reliably detect octane in exhaled breath of invasively ventilated ICU patients. Methods: Two developmental steps were taken to design a POC breath test that relies on gas-chromatography using air as carrier gas with a photoionization detector. Calibration measurements were performed with a laboratory prototype in healthy subjects. Subsequently, invasively ventilated patients were included for validation and assessment of repeatability. After evolving to a POC breath test, this device was validated in a second group of invasively ventilated patients. Octane concentration was based on the area under the curve, which was extracted from the chromatogram and compared to known values from calibration measurements. Results: Five healthy subjects and 53 invasively ventilated patients were included. Calibration showed a linear relation (R2 = 1.0) between the octane concentration and the quantified octane peak in the low parts per billion (ppb) range. For the POC breath test the repeatability was excellent (R2 = 0.98, ICC = 0.97 (95% CI 0.94–0.99)). Conclusion: This is the first study to show that a POC breath test can rapidly and reliably detect octane, with excellent repeatability, at clinically relevant levels of low ppb in exhaled breath of ventilated ICU patients. This opens possibilities for targeted exhaled breath analysis to be used as a bedside test and makes it a potential diagnostic tool for the early detection of ARDS.

Many patients with acute respiratory failure fulfill the diagnosis of Acute Respiratory Distress Syndrome (ARDS), forming a very heterogeneous population. Clinical trials have not yielded beneficial treatment effects in ARDS, possibly caused by this heterogeneity. Dividing patients with ARDS into subgroups, each with similar characteristics, may result in improved treatment strategies as part of a precision medicine approach. In this systematic review, we summarize the subphenotypes identified so far, the current state, and future directions for precision medicine in ARDS. Multiple data-driven subphenotypes have been identified based on a wide range of variables. These subphenotypes are associated with differences in clinical outcomes, which could be used for prognostic- and predictive enrichment of future interventional studies. True treatable traits have not been identified yet, deeper phenotyping will hopefully reveal these along with mechanistic differences.