Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
COMPLETED
40 participants
OBSERVATIONAL
2017-11-21
2020-05-31
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Second: to compare the results of the algorithm with the current standard of care clinical judgement of an experienced ventilation practitioner.
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
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.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
OTHER
PROSPECTIVE
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
computerized algorithm for automated analysis
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 experienced EIT users
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* ventilator settings guided by EIT
Exclusion Criteria
* Internal pacemaker, Implantable Cardioverter Defibrillator
* Skin lesions, dressings at the thorax, hindering belt placement
* Thoracic circumference \< 70 cm
* Thoracic circumference \> 150 cm
* BMI \> 50
18 Years
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
University Hospital Schleswig-Holstein
OTHER
Erasmus Medical Center
OTHER
Maastricht University Medical Center
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Dennis Bergmans
Role: STUDY_CHAIR
Maastricht University Medical Center
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Serge Heines
Maastricht, , Netherlands
Countries
Review the countries where the study has at least one active or historical site.
References
Explore related publications, articles, or registry entries linked to this study.
Bodenstein M, David M, Markstaller K. Principles of electrical impedance tomography and its clinical application. Crit Care Med. 2009 Feb;37(2):713-24. doi: 10.1097/CCM.0b013e3181958d2f.
Costa EL, Borges JB, Melo A, Suarez-Sipmann F, Toufen C Jr, Bohm SH, Amato MB. Bedside estimation of recruitable alveolar collapse and hyperdistension by electrical impedance tomography. Intensive Care Med. 2009 Jun;35(6):1132-7. doi: 10.1007/s00134-009-1447-y. Epub 2009 Mar 3.
Long Y, Liu DW, He HW, Zhao ZQ. Positive End-expiratory Pressure Titration after Alveolar Recruitment Directed by Electrical Impedance Tomography. Chin Med J (Engl). 2015 Jun 5;128(11):1421-7. doi: 10.4103/0366-6999.157626.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
17-4-053
Identifier Type: -
Identifier Source: org_study_id