Respiratory Failure Clinical Trial
Official title:
Validation of Inspiratory Muscle Pressure Estimation and Automated Detection of Asynchronies in Patients Under Assisted Mechanical Ventilation
Verified date | March 2023 |
Source | University of Sao Paulo General Hospital |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
The goal of this diagnostic study is to validate estimation of inspiratory muscle pressure by an artificial intelligence algorithm compared to the gold standard, the measure from an esophageal catheter balloon, in patients under assisted mechanical ventilation. The main questions it aims to answer are: • Are inspiratory muscle pressure estimates from an artificial intelligence algorithm accurate when compared to the direct measure from an esophageal balloon? Participants will be monitored with an esophageal balloon and with an artificial intelligence algorithm simultaneously, with inspiratory muscle pressure estimation during assisted mechanical ventilation with decremental levels of pressure support.
Status | Completed |
Enrollment | 50 |
Est. completion date | July 18, 2023 |
Est. primary completion date | July 18, 2023 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Patients under assisted or assist-control mechanical ventilation 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 |
Country | Name | City | State |
---|---|---|---|
Brazil | Heart Institute, University of São Paulo | Sao Paulo | SP |
Lead Sponsor | Collaborator |
---|---|
University of Sao Paulo General Hospital | Magnamed Tecnologia Medica S/A |
Brazil,
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Sousa MLA, Magrans R, Hayashi FK, Blanch L, Kacmarek RM, Ferreira JC. Predictors of asynchronies during assisted ventilation and its impact on clinical outcomes: The EPISYNC cohort study. J Crit Care. 2020 Jun;57:30-35. doi: 10.1016/j.jcrc.2020.01.023. Epub 2020 Jan 21. — View Citation
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* Note: There are 15 references in all — Click here to view all references
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Concordance between muscle pressure amplitude (in cmH2O) estimation by artificial intelligence and esophageal balloon | Analysis of the bias and limits of agreement (Bland-Altman plot) between muscle pressure estimated amplitude in cmH2O from artificial intelligence and measured by esophageal balloon. | 4 hours | |
Primary | Correlation between muscle pressure amplitude estimation (in cmH2O) by artificial intelligence and esophageal balloon | Correlation, reported as R-squared and a correlation plot, between amplitude in cmH2O of muscle pressure estimation by artificial intelligence and esophageal balloon. | 4 hours | |
Primary | Detection of initiation time and ending time of a spontaneous breathing cycle by artificial intelligence compared with esophageal balloon | Time difference (in ms) between initiation of a spontaneous breathing cycle and ending of a spontaneous breathing cycle between artificial intelligence and esophageal balloon. | 4 hours | |
Secondary | Sensitivity and specificity of patient-ventilator asynchrony automated detection using the Artificial Intelligence Muscle Pressure estimator | Number of patient-ventilator asynchronies detected using artificial intelligence compared with number of asynchronies detected by experts assessing airway pressure, flow and esophageal balloon waveforms. | 4 hours |
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