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| Name | Class |
|---|---|
| University Hospital Schleswig-Holstein | OTHER |
| Erasmus Medical Center | OTHER |
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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.
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.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| computerized algorithm for automated analysis | Other | 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 |
| Measure | Description | Time Frame |
|---|---|---|
| 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 | 4 months |
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Inclusion Criteria:
Exclusion Criteria:
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Post cardiac- surgery and patients with acute hypoxic respiratory failure
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| Name | Affiliation | Role |
|---|---|---|
| Dennis Bergmans | Maastricht University Medical Center | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Serge Heines | Maastricht | 622HX | Netherlands |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 19114889 | Background | 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. | |
| 19255741 | Background | 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. |
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| ID | Term |
|---|---|
| D012131 | Respiratory Insufficiency |
| ID | Term |
|---|---|
| D012120 | Respiration Disorders |
| D012140 | Respiratory Tract Diseases |
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| 26021494 | Background | 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. |