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Introduction: Awake proning may result in lower intubation and mortality rates in COVID-19 patients with hypoxemia refractory to simple oxygen therapy. Aims. To summarize available evidence for benefit and develop a set of pragmatic recommendations for awake proning in COVID-19 patients. Methods. An international group of 43 healthcare professionals searched MEDLINE for articles on awake proning, and formulated recommendations for its use. Results. The professionals reached consensus regarding indications and contraindications, feasibility and safety; they recommended applying awake proning if SpO2/FiO2 < 315, or SpO2 < 93% under supplementary oxygen, and if patient is able to follow instructions. Severe hypoxemia (SpO2/FiO2 < 140) and hemodynamic instability are absolute contraindications in the ward, but relative contraindications in the ICU. Morbid obesity was also seen as a relative contraindication, depending on assistance needed to help turn the patient. Pregnancy was not seen as a contraindication, but extra monitoring in the last trimester was seen as mandatory, and extra pillows for stabilization and prevention of aortocaval compression are necessary. Five steps may improve safety: i. adequate patient information; ii. help in positioning; iii. ensuring oxygen supply and placing of tubing free at sight; iv. optimized position to prevent harm; and v. monitor oxygen saturation and respiratory rate. Dissensus remained regarding duration, and number of sessions per day, and use of sedation during prone positioning. Conclusion. Awake proning is an attractive, simple and safe way to improve oxygenation in hypoxemic COVID–19 patients. Studies remain needed to see if it effects intubation and mortality rates.

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.

Poster discussion sessions are one of the most exciting and interactive sessions at which to present and hear about the latest research. Presenters can benefit from the best of two worlds: the central podium of a lecture and an in-depth discussion normally only encountered at the thematic poster sessions., Poster discussion sessions are exciting, interactive sessions to present and hear about the latest research. This article provides an outline of how to chair such a session at the ERS International Congress. http://bit.ly/2UORJzg

International audience; Acute respiratory distress syndrome (ARDS) is a devastating critical illness that can be triggered by a wide range of insults and remains associated with a high mortality of around 40%. The search for targeted treatment for ARDS has been disappointing, possibly due to the enormous heterogeneity within the syndrome. In this perspective from the European Respiratory Society research seminar on "Precision medicine in ARDS", we will summarise the current evidence for heterogeneity, explore the evidence in favour of precision medicine and provide a roadmap for further research in ARDS. There is evident variation in the presentation of ARDS on three distinct levels: 1) aetiological; 2) physiological and 3) biological, which leads us to the conclusion that there is no typical ARDS. The lack of a common presentation implies that intervention studies in patients with ARDS need to be phenotype aware and apply a precision medicine approach in order to avoid the lack of success in therapeutic trials that we faced in recent decades. Deeper phenotyping and integrative analysis of the sources of variation might result in identification of additional treatable traits that represent specific pathobiological mechanisms, or so-called endotypes.

Background: Outcome prediction in invasively ventilated ICU patients remains challenging. Driving pressure (ΔP) and mechanical power of ventilation (MP) are associated with outcomes like mortality. The objective of this study was to assess the predictive validity for mortality of ΔP and MP at 24h after start of invasive ventilation. Methods: Posthoc analysis of MARS, a large observational study in two Dutch ICUs. Patients having received invasive ventilation >24h were selected. The primary outcome was 90–day mortality. The predictive validity of ΔP and MP was measured as incremental 90–day mortality beyond that predicted by the Acute Physiology, Age and Chronic Health Evaluation (APACHE) IV score or the Simplified Acute Physiology Score (SAPS) II. Results: A total of 839 patients were included; 90–day mortality was 42%. ΔP (OR for 1 cm H2O increase in ΔP, 1.05 [CI 1.03–1.08] p Conclusions: In this cohort of invasively ventilated ICU patients, ΔP and MP at 24h were associated with 90–day mortality. However, they have no predictive validity beyond that of the APACHE IV score and the SAPS II.

Introduction: Reduced lung aeration is currently semi-quantified at the bedside by visual counting of vertical artifacts called B-lines on lung ultrasound (LUS) images. The accuracy of this method can be debated. We hypothesized that visual estimation of B-line coverage is a more accurate alternative to visual B-line counting in invasively ventilated ICU patients. Method: Invasively ventilated patients who received a clinical chest CT scan were included. A 12-region LUS exam was performed minutes before the CT scan. Lung regions scanned through LUS were compared to corresponding regions on CT. Lung aeration on CT was expressed in Hounsfield Units (HU). LUS images with a B-pattern, were visually scored by (a) estimating B-line coverage, expressed as the percentage of the screen covered by B-lines, and (b) counting the number of separately spaced B-lines. Associations between HU from the CT scan and the two B-line scores were tested with linear mixed effects model analysis. Results: The study included 23 patients, who had 87 LUS images with a B-pattern (median 3 [2-4] per patient). The B-line coverage was associated with the HU value from the CT scan; B-line count was not associated with the HU value. Conclusion: The visual B-line count on LUS images is an inaccurate score for lung aeration. Visual estimation of B-line coverage is a promising alternative for semi-quantification of aeration in LUS images.

Introduction: Differentiating ARDS from other forms of respiratory failure can be difficult. By advancing an optic fiber through a diagnostic bronchoscope, followed by an automatic pullback mechanism, OCT enables real-time 3D imaging of the alveolar compartment and peripheral airways. Aim: To investigate feasibility of bronchoscopic OCT, and to describe different OCT patterns of the alveolar compartment in mechanically ventilated patients. Methods: Observational study of OCT imaging in mechanically ventilated patients for non-resolving acute respiratory failure with an indication for diagnostic bronchoscopy. Results: 9 patients were included with clinical features of acute respiratory failure and bilateral pulmonary infiltrates not fully explained by cardiac failure (ARDS). Dominant CT patterns were ground glass(n=4), consolidation(n=3), reticulation(n=1), other(n=1). Total of 47 pullbacks were obtained without adverse events. Different patterns of the alveolar compartment (normal, alveolar filling, thickening of alveolar septae, loss of normal architecture of alveolar septae) were identified (Figure 1). Conclusions: This is the first study to show feasibility and safety of OCT imaging of alveolar compartment in mechanically ventilated patients. We identified different patterns, which could be helpful in the future to differentiate various causes of respiratory failure.

Introduction: Differentiating ARDS from other causes of respiratory failure can be challenging. CLE is a high resolution optical technique that, combined with conventional bronchoscopy, provides real-time, near-histology information about the alveolar compartment. Aim: To investigate feasibility and safety of CLE, and to describe different CLE characteristics of the alveolar compartment in patients with non-resolving respiratory failure on the ICU. Methods: Observational study of CLE imaging in mechanically ventilated patients with an indication for diagnostic bronchoscopy. Results: 10 patients were included with the clinical features of respiratory failure and bilateral chest opacities not fully explained by cardiac failure (ARDS). Dominant CT patterns were ground glass(n=4), consolidation(n=3), reticulation(n=1), other(n=2). High quality CLE imaging of the alveolar compartment was obtained in all patients without adverse events. 5 different CLE patterns (normal, alveolar filling with either fluid or cells, early and late fibrosis) were identified (Figure 1). Conclusion: This is the first study to show feasibility, safety and CLE characteristics of the alveolar compartment for various causes of respiratory failure in mechanically ventilated patients. CLE imaging has added value to chest CT and has the potential to distinguish between important causes of respiratory failure in critically ill patients at the ICU.

Rationale: Analysis of exhaled volatile organic compounds (VOCs) by sensor-driven electronic nose (eNose) technology is a widely suggested measure for non-invasive monitoring of chronic airway diseases. While this technology allows probabilistic (clinical) advise, it is incapable of providing details regarding involved metabolites. Modelling sensor deflections by matching Gas Chromatography-Mass Spectrometry (GC-MS) samples could help to ascertain which VOCs induce a sensor response. Objective: To determine the association between eNose sensor deflections and exhaled VOCs measured by GC-MS. Methods: Paired samples of breath from asthma patients (n=22) were collected on sorbent tubes. One tube was analysed by four different eNoses and the second one by GC-MS. Pooling of resulting datasets consisted of 1) Partial Least Square Regression (PLSR) analysis and 2) clustered heat-mapping of PLSR loadings. Results: Matching data was available for 158 eNose sensors and 1025 GC-MS features, whereby PLSR resulted in R2‘s from 0.25 to 0.72. Figure 1 shows clustered heat-mapping outcomes. Conclusion: This explorative analysis revealed distinctive and associated patterns of exhaled VOCs between eNose and GC-MS. This data matching could help to identify which VOCs are responsible for clinically relevant results obtained by eNose and will facilitate valorisation of breathomics into clinical tests.

Pseudomonas aeruginosa (PA) is one of the most pathogenic bacteria infecting the airways of patients with cystic fibrosis (CF). Sputum culture is the gold standard for detecting PA. However, this method is time-consuming. In this study we hypothesized that volatile organic compounds (VOCs) in exhaled breath can discriminate between PA infected and non-infected CF patients. Design: Cross-sectional baseline analysis of longitudinal cohort study. We collected exhaled air of both pediatric and adult CF patients with and without PA airways infection, in which VOCs were identified using Gas Chromatography – Mass Spectrometry (GC-MS). Infection was defined as culturing PA on the day of breath sampling, or chronic colonization with PA (in >50% of cultures (minimum of 4 samples) over the previous 12 months, or chronic maintenance treatment for PA). To identify VOCs relevant for distinction between the groups, univariate analysis (Mann Withney U test) was applied for each GC-MS compound. Features with a p-value below 0.05 retained for linear discriminant analysis. Diagnostic performed was evaluated by calculation of the area under the receiver operating characteristic - curve including 95% confidence Interval (CI). Complete data was available of 18 pediatric and 22 adult CF patients; 20 with and 20 without PA infection. Exploratory analysis of unselected patients showed that 3 out of 138 VOCs were consistently different in PA infected and non-infected patients, resulting in an AUC of 0.75 (CI 0.59 – 0.92). We discriminated PA infected and non-infected CF patients based on 3 VOCs with moderate accuracy. However, these preliminary results need to be validated in an independent patient cohort.

Volatile organic compounds (VOCs) in breath can reflect host and pathogen metabolism and might be used to diagnose pneumonia (Oort J Breath Res 2018). We hypothesized that rats with Streptococcus pneumoniae (SP) or Pseudomonas aeruginosa (PA) pneumonia can be discriminated from uninfected controls by gas-chromatography mass-spectrometry (GC-MS) of exhaled breath. Male adult rats (N = 50) received an intra-tracheal inoculation of 1) 200µL saline, 2) 1x107 colony forming units (cfu) of SP or 3) 1x107 cfu of PA. 24 hours later the rats were anaesthetized, tracheotomized and mechanically ventilated. Exhaled breath was analyzed via GC-MS. Area under the receiver operating characteristic curve (AUROCC) was calculated after leave-one-out cross-validation of sparse partial least squares discriminant analysis (sPLS-DA). The AUROCC was 0.85 (95%-CI: 0.73-0.96) for infected vs. non-infected animals. The AUROCC was 0.98 (95%-CI: 0.94-1) for SP vs. PA, 0.92 (95%-CI: 0.83-1) for SP vs. controls and 0.97 (95%-CI: 0.92-1) for PA vs. controls. Exhaled breath analysis discriminated with good accuracy between respiratory infection and no infection, but with much better accuracy between the specific pathogens. Clinical studies should focus more on the discrimination between specific pathogens, instead of the general presence of respiratory infection.

Exhaled volatile organic compounds (VOCs) could potentially serve as non-invasive biomarkers for the diagnosis of respiratory infections. This study aims to discriminate rats infected with Pseudomonas aeruginosa (PA) or Streptococcus pneumoniae (SP) from non-infected rats. Exhaled breath was collected from 50 male rats 24h after intra-tracheal inoculation of 200µL saline, or 1x107 colony forming units of SP or PA. VOCs in exhaled breath trapped on sorbent tubes were analysed with Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) after thermal desorption. The pattern of reaction ions with mass/charge ratio 15 to 200 was analysed using sparse partial least squares discriminant analysis. Area under the receiver operating characteristic curve (AUROCC) calculated after leave-one-out cross-validation of the multivariate discriminant analysis was 0.73 (95%CI: 0.57-0.89) for infected vs. non-infected animals. For SP vs. PA the AUROCC was 0.97 (95%CI: 0.93-1) while for SP vs. controls and PA vs. controls it was 0.67 (95%CI: 0.47-0.86) and 0.72 (95%CI: 0.53-0.91), respectively. Exhaled breath analysis discriminated with higher accuracy between animals infected with specific respiratory pathogens compared to infected vs. non-infected animals. Similar findings were observed for VOCs analysed with Gas Chromatography Mass Spectrometry (see submitted ERS abstract from P. M. van Oort et al.). Our results suggest that breath analysis in infected patients may be helpful in discriminating different pathogens. Furthermore, SIFT-MS has potential as a point-of-care tool to assess respiratory infections in clinical practice.

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 mechanically ventilated Intensive Care Unit patients. In this prospective, single centre, cohort study, breath from mechanically ventilated patients was analysed using gas chromatography – mass spectrometry. VOCs were selected for partial least square discriminant analysis (PLS-DA) by a p-value 0.7. 93 patients were included in the study. 12 of 145 identified VOCs were significantly altered in patients with pneumonia compared to controls. PLS-DA classified patients with modest accuracy (AUROC: 0.73 [95%–confidence interval (CI): 0.57–0.88] after leave–one–out cross–validation). 52 VOCs were significantly different in colonized patients, resulting in 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 distinguish pneumonia from controls with a modest to good accuracy. These findings need to be validated externally.

A message from the new chair of the @ERStalk ECMC http://ow.ly/QmaL307Ykcx. ispartof: Breathe vol:13 issue:1 pages:51-52 ispartof: location:England status: published

Healthcare-associated infection, such as intensive care unit (ICU)-related respiratory infections, remain the most frequently encountered morbidity of ICU admission, prolonging hospital stay and increasing mortality rates. The epidemiology of ICU-related respiratory infections, particularly nonventilated ICU-associated pneumonia and ventilator-associated tracheobronchitis, appears to be quite different among different countries. European countries have different prevalence, patterns and mechanism of resistance, as well as different treatments chosen by different attending physicians. The classical clinical research process in respiratory infections consists of the following loop: 1) identification of knowledge gaps; 2) systematic review and search for adequate answers; 3) generation of study hypotheses; 4) design of study protocols; 5) collection clinical data; 6) analysis and interpretation of the results; and 7) implementation of the results in clinical practice., Learn about ENIRRI, an @ERStalk Clinical Research Collaboration http://ow.ly/ct6m30dbXiP

Immune-modulatory therapy in ARDS has been unsuccessful, despite promising results in animal studies. This might be due to poor biological phenotyping of the included patients. We hypothesized that ARDS patients can be clustered based on concentrations of 20 plasma biomarkers and that these unbiased biological phenotypes correspond to clinical outcomes. All ICU-patients were screened for ARDS for three years. Plasma was analyzed for 20 markers of inflammation, coagulation and endothelial activation. Cluster analysis based on biomarker concentrations alone was used to separate the biological phenotypes. A decision tree was used to predict cluster membership based on a limited set of biomarkers. The independent association of clusters with ICU-mortality was studied by logistic regression. 771 patients with ARDS were separated into three clusters: “mild” (N=383), “moderate” (N=224) and “strong responders” (N=164). ICU-mortality increased with response (16%, 26% and 47%, P In conclusion, three biological clusters were identified. “Strong responders” showed a profound cytokine and coagulation response, which was associated with higher mortality and more organ failure. These results may have important implications for inclusion of patients into future clinical trials. Cluster-analysis based on plasma biomarkers This abstract has been presented previously at the European Respiratory Society9s Lung Science Conference in March 2016.