Assessment of Patient-ventilator Asynchrony by Electric Impedance Tomography

Not yet recruiting

• Conditions: Acute Lung Injury
• Interventions: Device: EIT; Device: patient-ventilator asynchrony assessment

• Registration Number: NCT06290310
• Lead Sponsor: Kiskunhalas Semmelweis Hospital the Teaching Hospital of the University of Szeged

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

Study Timeline

• Study First Submitted: 2024-02-09
• Status Verified: 2024-03
• Study First Submitted QC: 2024-03-01
• Last Update Submitted: 2024-03-01
• Study First Posted: 2024-03-04
• Last Update Posted: 2024-03-04
• Study Start: 2024-04-12
• Primary Completion: 2024-09-01
• Study Completion: 2024-09-01

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 10

Inclusion Criteria

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

Exclusion Criteria

• age under 18

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
mechanically ventilated patients	EIT	Invasively or non-invasively ventilated patients.
mechanically ventilated patients	patient-ventilator asynchrony assessment	Invasively or non-invasively ventilated patients.

Primary Outcome Measures

Name	Time	Method
distribution	during mechanical ventilation	gas distribution in lungs assessed by electric impedance tomography

Secondary Outcome Measures

Name	Time	Method
connecting asysnchrony cycles with electric impedance tomography measurements	during mechanical ventilation	connecting machine learning assessed patient-ventilator asynchrony respiratory cycles with the inherent respiratory cycle recorded by the electric impedance tomography
identifying unic electric impedance tomography signs of asynchrony	during mechanical ventilation	following connection described under "outcome 2", identification if single patient-ventilator asynchrony types (delayed cycling, premature cycling, auto trigger, ineffective effort, double trigger) present specific electric impedance tomography changes

Trial Locations

Locations (1)

Kiskunhalas Semmelweis Hopsital the Teaching Hospital of the University of Szeged; 🇭🇺 Kiskunhalas, Hungary