Skip to main content
Clinical Trials/NCT06290310
NCT06290310
Not yet recruiting
Not Applicable

Assessment of Patient-ventilator Asynchrony by Electric Impedance Tomography and Artificial Intelligence

Kiskunhalas Semmelweis Hospital the Teaching Hospital of the University of Szeged1 site in 1 country10 target enrollmentApril 12, 2024

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Acute Lung Injury
Sponsor
Kiskunhalas Semmelweis Hospital the Teaching Hospital of the University of Szeged
Enrollment
10
Locations
1
Primary Endpoint
distribution
Status
Not yet recruiting
Last Updated
2 years ago

Overview

Brief Summary

Patient-ventilator asynchrony (PVA) has deleterious effects on the lungs. PVA can lead to acute lung injury and worsening hypoxemia through biotrauma. Little is known about how PVA affects lung aeration estimated by electric impedance tomography (EIT). Artificial intelligence can promote the detection of PVA and with its help, EIT measurements can be correlated to asynchrony.

Detailed Description

Patient-ventilator asynchrony (PVA) is a common phenomenon with invasively- and non-invasively ventilated patients. PVA has deleterious effects on the lungs. It causes not just patient discomfort and distress but also leads to acute lung injury and worsening hypoxemia through biotrauma. The latter significantly impacts outcomes and increases the duration of mechanical ventilation and intensive care unit stay. However, PVA is a widely investigated incident related to mechanical ventilation, though little is known about how it affects lung aeration estimated by electric impedance tomography (EIT). EIT is a non-invasive, real-time monitoring technique suitable for detecting changes in lung volumes during ventilation. Artificial intelligence can promote the detection of PVA by flow versus time assessment. If continuous EIT recording is correlated with the latter, impedance tomography changes evoked by asynchrony can be estimated

Registry
clinicaltrials.gov
Start Date
April 12, 2024
End Date
September 1, 2024
Last Updated
2 years ago
Study Type
Observational
Sex
All

Investigators

Sponsor
Kiskunhalas Semmelweis Hospital the Teaching Hospital of the University of Szeged
Responsible Party
Sponsor

Eligibility Criteria

Inclusion Criteria

  • any patient ventilated invasively
  • any patient ventilated non-invasively

Exclusion Criteria

  • age under 18

Outcomes

Primary Outcomes

distribution

Time Frame: during mechanical ventilation

gas distribution in lungs assessed by electric impedance tomography

Secondary Outcomes

  • connecting asysnchrony cycles with electric impedance tomography measurements(during mechanical ventilation)
  • identifying unic electric impedance tomography signs of asynchrony(during mechanical ventilation)

Study Sites (1)

Loading locations...

Similar Trials