During mechanical ventilation (MV) of patients with acute respiratory distress syndrome (ARDS), the application of the most protective ventilatory strategy possible, based on the reduction of volotrauma and the personalized prescription of a positive end-expiratory pressure (PEEP) regime, is the guarantee of clinical benefit, demonstrated in terms of tidal volume in particular (reduced mortality and number of days without mechanical ventilation).
When a benefit for patients with ARDS is found in clinical trials, it is mainly related to a reduction in the damage caused by mechanical ventilation.
Through technological progress mechanical ventilation optimization is guided by advanced monitoring, including measurement of transpulmonary pressure (TPP or LP) and/or functional imaging data (e.g. Electro-impedance Tomography, EIT).
All these monitoring systems are now incorporated in the new generation of ventilators.
* Transpulmonary pressure (TPP); By estimating trans-pulmonary pressure, investigators can assess pulmonary stress and, without doubt, better interpret critical alveolar opening pressure.
* Continuous measurement of lung pressures and volumes (end-expiratory lung volume, EELV, as a substitute for functional respiratory capacity (FRC)) can also be obtained using more recent techniques based on the study of exhaled CO2 kinetics (volumetric capnography and dynamic capnometry).
* Electro-Impedance Tomography (EIT) ; Electrical impedance tomography (PulmoVista 500 ® , Drager, Germany; or integrated into the respirator, ELISA800VIT® , Lowenstein, Germany) provides totally non-invasive, cross-sectional visualization of part of pulmonary aeration, both dynamically and regionally.
This observational study on clinical physiological data is based on the reuse of pseudonymized recorded data in 1st-line care during sequential diagnostic maneuvers based on calibrated variations in PEEP and tidal volume and obtained by advanced respiratory monitoring in the acute phase of ARDS (esophageal manometry and/or EIT) and in accordance with the most recent recommendations.
No specific research procedures are planned for this study. This study will be conducted exclusively on the basis of personal data collected as part of the usual monitoring of a participant with ARDS undergoing advanced respiratory care. The analysis focuses on data recorded during recruitment maneuvers performed as part of care for this type of patient in the ICU.
Participants are informed individually, and their non-objection to the re-use of their data for research purposes is recorded in the file. Where applicable, information is given to the trusted support person/relative/parent if the participant is unable to express his/her wishes and does not object to the re-use of his/her data for research purposes. An information note is given to the patient or the trusted support person/relative/parent
Monitoring data is currently available in the Clinical Research Unit of our Intensive Care Departments, thanks to a data extraction system based on PHILIPS IntelliVue® or Mindray Benevision® monitoring solutions. It should be noted that the Data Warehouse Connect software solution enables all these data to be collected with fine sampling (2 ms for tracings, 1s for digital data), considerably extending the capabilities in terms of data analysis and exploitation. The extraction system is temporally coupled to patient events and medication (doses) administered, thanks to an IntelliSpace Critical Care and Anesthesia (ICCAA) information system that is operational in the ICU.
These data are downloaded onto a secure server with restricted access, then loaded into a database (SQL) for future processing of the pseudonymized data.
The data will be collected as part of routine care and is integrated in compliance with the RGPD.
Demographic data will be collected using the intensive care record (ORBIS or equivalent / computerized patient record).
Aim of the study Does the analysis of advanced monitoring data provide characteristic measured parameters that could help prevent or even reduce ventilator-induced lesions? Can these data be integrated into a model to build a digital twin for practical, simplified monitoring of ventilatory function?
