Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-26 @ 2:43 PM
Ignite Modification Date:
2025-12-26 @ 2:43 PM
NCT ID:
NCT03653806
Brief Summary:
First: to develop a computerized algorithm for automated analysis of the electrical impedance tomography (EIT) data. The algorithm calculates the "optimal" positive end-expiratory pressure (PEEP) and inspiratory pressure defined as the "optimal" balance between stretch, ventilation distribution and collapse.
Second: to compare the results of the algorithm with the current standard of care clinical judgement of an experienced ventilation practitioner.
Detailed Description:
The study will be performed at the Intensive Care Unit, Maastricht University Medical Centre. The investigators routinely apply EIT (Pulmovista, Dräger, Lübeck. Germany) in mechanically ventilated patients to optimize the ventilator settings .
An algorithm will be developed by the Institute of Technical Medicine, Furtwangen University, Germany. The algorithm will automatically detect changes in both PEEP and inspiratory pressures. For each PEEP step and/or changes in inspiratory pressure the difference in regional alveolar overdistension and alveolar collapse will be calculated. This makes it possible to select the optimal ventilator setting depending on the best compromise between alveolar overdistension and alveolar collapse.
The algorithm will be tested in 40 EIT guided mechanically ventilated patients. EIT measurements will be performed during an incremental and decremental PEEP trial. The EIT measurement will be performed in the same way as during standard clinical care. EIT data will be analysed offline by a ventilation practitioner with experience in EIT and with the newly developed algorithm. The resulting advice on optimal ventilator settings will be compared for inter-observer variability.
Study:
NCT03653806
Study Brief:
Protocol Section:
NCT03653806