Acute Hypoxemic Respiratory FailureNCT03653806
Automated Analysis of EIT Data for PEEP Setting
An observational study of Acute Hypoxemic Respiratory Failure and Post-cardiac Surgery, run by Maastricht University Medical Center at 1 site in Netherlands.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Acute Hypoxemic Respiratory Failure, Post-cardiac Surgery
- What is being tested?
- computerized algorithm for automated analysis
- How many people
- 40 participants
- Where
- 1 siteNetherlands
- Study dates
- 21 Nov 2017to 31 May 2020
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Post cardiac- surgery and patients with acute hypoxic respiratory failure
Who may be able to join
- Mechanically ventilated in a volume or pressure controlled mode
- ventilator settings guided by EIT
Who cannot join
- Participants who specifically opt-out regarding the use of the data for research purpose
- Internal pacemaker, Implantable Cardioverter Defibrillator
- Skin lesions, dressings at the thorax, hindering belt placement
- Thoracic circumference < 70 cm
- Thoracic circumference > 150 cm
- BMI > 50
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Comparing the Results of a Computer Analysis Algorithm With Clinical Decisions in a Patient With Electrical Impedance Tomography Guided Ventilator Settings Regarding Optimal Positive End Expiratory Pressure and Inspiratory Pressure
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.
Read the 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.
- Being tested
- computerized algorithm for automated analysis
- Keywords
- PEEP, Electrical Impedance Tomography
- Medical subject headings
- Respiratory Insufficiency
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
computerized algorithm for automated analysisOther
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
What is being measured
The primary outcome is the main question the study is designed to answer.
develop automated EIT data algorithm for PEEP setting
The automated algorithm will give an advise on PEEP and delta pressure settings, based upon the EIT data, which is in accordance with the decision of the investigator
Measured: 4 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Aug 2018
- Study start21 Nov 2017
- Primary completion31 May 2020
- Study completion31 May 2020
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Acute Hypoxemic Respiratory FailureStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Prospective
- Enrolment
- 40 participants (actual)
Sponsor and investigators
- Lead sponsor
- Maastricht University Medical Center
- Sponsor type
- University, hospital or other
- Collaborators
- University Hospital Schleswig-Holstein, Erasmus Medical Center
- Responsible party
- Sponsor
- Investigators
- Dennis Bergmans, Study chair, Maastricht University Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03653806
- Sponsor's protocol ID
- 17-4-053
- Status last verified
- Nov 2020
- First submitted
- 17 Aug 2018
- Last updated
- 5 Nov 2020
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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.
PubMed 19114889Costa 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.
PubMed 19255741Long 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.
PubMed 26021494
Study at a glance
From the registry record, last updated by the sponsor on 5 Nov 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Comparing the Results of a Computer Analysis Algorithm With Clinical Decisions in a Patient With Electrical Impedance Tomography Guided Ventilator Settings Regarding Optimal Positive End Expiratory Pressure and Inspiratory Pressure
- ClinicalTrials.gov ID
- NCT03653806
- Acronym / sponsor ID
- 17-4-053
- Keywords
- PEEP, Electrical Impedance Tomography
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 40 participants (actual)
- Lead sponsor
- Maastricht University Medical CenterUniversity, hospital or other
- Collaborators
- University Hospital Schleswig-Holstein, Erasmus Medical Center
- Study start
- 21 Nov 2017 (actual)
- Primary completion
- 31 May 2020 (actual)
- Study completion
- 31 May 2020 (actual)
- First posted
- 31 Aug 2018 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Other
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Post cardiac- surgery and patients with acute hypoxic respiratory failure
Key inclusion criteria (2 listed)
- Mechanically ventilated in a volume or pressure controlled mode
- ventilator settings guided by EIT
Key exclusion criteria (6 listed)
- Participants who specifically opt-out regarding the use of the data for research purpose
- Internal pacemaker, Implantable Cardioverter Defibrillator
- Skin lesions, dressings at the thorax, hindering belt placement
- Thoracic circumference < 70 cm
- Thoracic circumference > 150 cm
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| computerized algorithm for automated analysisFirst: 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 | Other | – |
Primary outcome
develop automated EIT data algorithm for PEEP setting
Time frame: 4 months
The automated algorithm will give an advise on PEEP and delta pressure settings, based upon the EIT data, which is in accordance with the decision of the investigator
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Nov 2020.
- Background: PubMed 19114889Bodenstein 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.
- Background: PubMed 19255741Costa 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.
- Background: PubMed 26021494Long 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.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Dennis Bergmans study chair
Maastricht University Medical Center
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Acute Hypoxemic Respiratory Failure and Post-cardiac Surgery, run by Maastricht University Medical Center at 1 site in Netherlands.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 5 Nov 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
develop automated EIT data algorithm for PEEP setting (time frame: 4 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03653806, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Nov 2020.