Respiratory Failure
Conditions
Interventions
All included subjects will be monitored simultaneously with the esophageal balloon (gold standard) and with the artificial intelligence algorithm integrated in the mechanical ventilator (FlexiMag, Mag
03.950
Sponsors
Faculdade de Medicina da Universidade de São Paulo
Faculdade de Medicina da Universidade de São Paulo
Eligibility
Age
18 Years to No maximum
Inclusion criteria
Inclusion criteria: Patients under assisted or assist-control mechanical ventilation; Age > 18; both genders.
Exclusion criteria
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
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| 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. ;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
| Measure | Time frame |
|---|---|
| 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. | — |
Countries
Brazil
Contacts
Public ContactGlauco Plens
Faculdade de Medicina da Universidade de São Paulo
Outcome results
None listed