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Automated Analysis of EIT Data for PEEP Setting

NCT03653806 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 40

Last updated 2020-11-05

No results posted yet for this study

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.

Conditions

  • Acute Hypoxemic Respiratory Failure
  • Post-cardiac Surgery

Interventions

OTHER

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

Sponsors & Collaborators

  • University Hospital Schleswig-Holstein

    collaborator OTHER

  • Erasmus Medical Center

    collaborator OTHER

  • Maastricht University Medical Center

    lead OTHER

Principal Investigators

  • Dennis Bergmans · Maastricht University Medical Center

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2017-11-21
Primary Completion
2020-05-31
Completion
2020-05-31

Countries

  • Netherlands

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03653806 on ClinicalTrials.gov