Ignite Creation Date:
2025-12-26 @ 2:43 PM
Ignite Modification Date:
2026-03-01 @ 11:26 AM
Study NCT ID:
NCT03653806
Status:
COMPLETED
Last Update Posted:
2020-11-05
First Post:
2018-08-17
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Automated Analysis of EIT Data for PEEP Setting
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D012131', 'term': 'Respiratory Insufficiency'}], 'ancestors': [{'id': 'D012120', 'term': 'Respiration Disorders'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'OTHER'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 40}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2017-11-21', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2020-11', 'completionDateStruct': {'date': '2020-05-31', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2020-11-04', 'studyFirstSubmitDate': '2018-08-17', 'studyFirstSubmitQcDate': '2018-08-28', 'lastUpdatePostDateStruct': {'date': '2020-11-05', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2018-08-31', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2020-05-31', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'develop automated EIT data algorithm for PEEP setting', 'timeFrame': '4 months', 'description': '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'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['PEEP', 'Electrical Impedance Tomography'], 'conditions': ['Acute Hypoxemic Respiratory Failure', 'Post-cardiac Surgery']}, 'referencesModule': {'references': [{'pmid': '19114889', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '19255741', 'type': 'BACKGROUND', 'citation': '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.'}, {'pmid': '26021494', 'type': 'BACKGROUND', 'citation': '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.'}]}, 'descriptionModule': {'briefSummary': '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.\n\nSecond: to compare the results of the algorithm with the current standard of care clinical judgement of an experienced ventilation practitioner.', 'detailedDescription': '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 .\n\nAn 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.\n\nThe 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.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Post cardiac- surgery and patients with acute hypoxic respiratory failure', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Mechanically ventilated in a volume or pressure controlled mode\n* ventilator settings guided by EIT\n\nExclusion Criteria:\n\n* Participants who specifically opt-out regarding the use of the data for research purpose\n* Internal pacemaker, Implantable Cardioverter Defibrillator\n* Skin lesions, dressings at the thorax, hindering belt placement\n* Thoracic circumference \\< 70 cm\n* Thoracic circumference \\> 150 cm\n* BMI \\> 50'}, 'identificationModule': {'nctId': 'NCT03653806', 'briefTitle': 'Automated Analysis of EIT Data for PEEP Setting', 'organization': {'class': 'OTHER', 'fullName': 'Maastricht University Medical Center'}, 'officialTitle': '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', 'orgStudyIdInfo': {'id': '17-4-053'}}, 'armsInterventionsModule': {'interventions': [{'name': 'computerized algorithm for automated analysis', 'type': 'OTHER', 'description': '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.\n\nSecond: to compare the results of the algorithm with the current standard of care clinical judgement of experienced EIT users'}]}, 'contactsLocationsModule': {'locations': [{'zip': '622HX', 'city': 'Maastricht', 'country': 'Netherlands', 'facility': 'Serge Heines', 'geoPoint': {'lat': 50.84833, 'lon': 5.68889}}], 'overallOfficials': [{'name': 'Dennis Bergmans', 'role': 'STUDY_CHAIR', 'affiliation': 'Maastricht University Medical Center'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Maastricht University Medical Center', 'class': 'OTHER'}, 'collaborators': [{'name': 'University Hospital Schleswig-Holstein', 'class': 'OTHER'}, {'name': 'Erasmus Medical Center', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}