Muscle Pressure Estimation With Artificial Intelligence During Mechanical Ventilation

Not Applicable

Recruiting

• Conditions: Respiratory Failure; E02.041.625

• Registration Number: RBR-3vsv5gs
• Lead Sponsor: Faculdade de Medicina da Universidade de São Paulo

Brief Summary

Not available

Detailed Description

Not available

Study Timeline

• Results First Posted: 1900-01-01
• Study Start: 2023-06-20
• Last Update Posted: 26 June 2023
• Study Completion: 2024-03-31

Recruitment & Eligibility

• Status: Recruiting
• Sex: Not specified
• Target Recruitment: Not specified

Inclusion Criteria

Patients under assisted or assist-control mechanical ventilation; Age > 18; both genders.

Exclusion Criteria

Contraindication to esophageal catheter insertion (esophageal cancer or bleeding, esophageal fistula, skull base fracture, uncontrolled coagulopathies); Contraindication to transient neuromuscular blockade; Bronchopleural fistula (persistent air leak); Hemodynamic instability (norepinephrine > 1mcg/kg/min); Gestation; Current sinus infection; Refusal from patient's family of attending physician; Palliative care

Study & Design

• Study Type: Intervention
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Evaluate concordance between muscle pressure amplitude (in cmH2O) estimation by artificial intelligence and esophageal balloon, verified by analysis of the bias and limits of agreement with Bland-Altman plot, with a prespecified margin of ±3 cmH2O as accurate limits of agreement. ;Evaluate correlation between muscle pressure amplitude estimation (in cmH2O) by artificial intelligence and esophageal balloon, verified by R-squared and a correlation plot, between amplitude in cmH2O of muscle pressure estimation by artificial intelligence and esophageal balloon.<br>;Evaluate detection of initiation time and ending time of a spontaneous breathing cycle by artificial intelligence compared with esophageal balloon, verified by time difference (in ms) analysis between initiation of a spontaneous breathing cycle and ending of a spontaneous breathing cycle between artificial intelligence and esophageal balloon.

Secondary Outcome Measures

Name	Time	Method
Evaluate sensitivity and specificity of patient-ventilator asynchrony automated detection using the Artificial Intelligence Muscle Pressure estimator, verified by adjudication of asynchronies by experts assessing airway pressure, flow and esophageal pressure waveforms.