Emerging respiratory diseases represent a global threat. Viruses such as influenza and coronaviruses have been the main drivers of pandemics over the past century. More broadly, the impact of these respiratory infections is not limited to pandemic risks. Indeed, some of them also trigger seasonal epidemics with a significant medical and economic burden. Consequently, it is essential to strengthen global surveillance, and diagnostic capacities for the pathogens responsible for respiratory infections.
The diagnosis of respiratory infections is even more important in cases of severe infection, as it helps guide and adapt patient management according to the responsible pathogen.
A promising and well-recognized approach is the analysis of exhaled breath, which contains a complex mixture of volatile organic compounds (VOCs), also known as the "volatilome." The volatilome is influenced by the patient's metabolism, immune system, and microbiome, and can be disrupted by the presence of a pathogen.
A parallel clinical study, VORTEX-1, aims to establish the performance of breath analysis for the diagnosis of respiratory infections in the context of the general population, or patient triage in emergency wards. This study targets patients with non-severe respiratory infections, mostly caused by viral pathogens.
Thanks to a specific technique, the VORTEX-1 study will make it possible to test a direct on-site sampling and analysis process, painless and with real-time chemical detection.
This methodology, highly suited to triage situations, remains difficult to apply in the case of respiratory infections requiring hospitalization. Indeed, hospitalized patients are usually admitted to different units depending on their clinical status, risk factors, or bed availability. This diversity of settings makes it impossible to implement a process that depends on an instrument which cannot be available or moved in real time across all units. To address this challenge, the investigators will use an alternative method.
In the VORTEX-2 trial, samples of exhaled gases will be collected directly at the patient's bedside using a single-use device for breath collection. The samples will then be transferred to a laboratory for analysis. This approach is more suitable for severe respiratory infections.
To be as comprehensive as possible in the study of the volatilome in the context of respiratory infections, it is important to include hospitalized patients and to develop a system that can also be implemented in routine clinical practice.
The link between the two studies (VORTEX-1 and VORTEX-2) will be established through a "control" group, consisting of healthy subjects (without respiratory infections or severe/chronic diseases), whose breath will be collected using both approaches.
Age ≥ 18 years old
Having signed a written informed consent
Presenting a NEWS-2 score of 5 (>4) or one of the individual score criteria rated 3
Hospitalized in one of the HCL (Hospices Civils de Lyon) departments participating in the study
Age: < 18 years
Alcohol consumption less than 12 hours
Person with co-morbidities such as chronic respiratory failure, type II diabetes, cancerous processes, chronic liver disease, chronic kidney disease
Clinical signs of acute respiratory infection
Parallel
Volatile Organic compounds (VOC) analysis in Exhaled breath using GC-MS
DeviceThe collection and analysis of exhaled air for VOC detection is a non-invasive, painless procedure carried out offline. It can be summarised as follows: 1. Collection of 0.5-1 litre of exhaled air in a single-use Tedlar® bag 2. Transfer the exhaled air sample to a thermodesorption tube. The thermodesorption tube will be sent to the laboratory responsible for the analysis within 1-5 days of collection. 3. The breath sample will be analysed in the laboratory using thermal desorption-GC/MS. 4. Processing of the raw data to determine the chemical composition of VOCs and identify the compounds present in the exhaled air sample. 5. Statistical analysis of all generated data will be performed to identify interesting VOC profiles.
Description of the breath composition based on the area under each peak of exhaled air according to three levels of classification
Levels of classification : * Patients with bacterial or viral respiratory infection vs. no respiratory infection (healthy subjects = control group) * Patients with viral vs. bacterial respiratory infection vs. undetermined respiratory infection vs. healthy subjects * Patients with respiratory infection due to Legionella spp vs another bacterium vs SARS-CoV-2 vs influenza vs another virus vs undetermined respiratory infection vs healthy subjects
Comparison of the overall properties of the test on exhaled air with the clinical classification of a severe respiratory infection used in practice. The test will therefore aim to differentiate patients with a respiratory infection who are hospitalized w
Overall properties of the exhaled air test in comparison with the clinical classification of severe respiratory infection as used in practice.The test will aim to differentiate between hospitalised patients with a respiratory infection and a NEWS-2 score of over 4, and a control group of healthy patients. The overall performance of the test will be evaluated on several models, based on the area under the ROC curve (AUC) calculated from model predictions. Predicted AUCs will be compared to an expected AUC of 0.7 by bootstrapping
Differentiation of the three groups of participants-those with a viral respiratory infection, those with a bacterial respiratory infection, and healthy subjects-will be evaluated using the area under the curve (AUC), in order to assess the performance
Evaluate the performance (same as secondary outcome 1) of the chemical analysis of exhaled air in differentiating between three groups of participants: those with a respiratory infection caused by a virus, those with a respiratory infection caused by bacteria, and healthy subjects.
Evaluation of viral load in respiratory samples will be performed by retesting all nasopharyngeal samples positive for an influenza virus, SARS-CoV-2, or Legionella. This criterion will correspond to the breath composition associated with viral load.
The study will be based on the overall properties of the breath test compared with the clinical classification of severe respiratory infection used in practice. The test will therefore aim to differentiate between six groups. These performances will be evaluated using the AUC. The AUCs calculated from the predictions of each model developed will be compared to an expected AUC of 0.7 by bootstrap.
Description of the breath composition based on the AUC of each peak
Analyse and describe the composition of patients'' exhaled air according to viral (influenza and SARS-CoV-2) or bacterial (Legionella) load, in order to identify biomarkers whose excretion correlates with viral and bacterial load.
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