Knowing when to liberate critically ill patients from mechanical ventilation (i.e. extubation) is of great importance as both prolonged ventilation and failed extubation are associated with increased morbidity, mortality \& costs. The study objective is to improve the safety of extubation by harnessing hidden information contained in the patterns of variation of heart and respiratory rate measured over intervals-in-time.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Introduce Extubation Advisor TM (EA)
Timeframe: 1 year
Evaluate Respiratory Therapist (RTs) feedback on the Extubation Advisor TM (EA)
Timeframe: 1 year
Evaluate Intensivist (MD) feedback on the Extubation Advisor TM (EA) Report
Timeframe: 1 year
Evaluate technical feasibility of future real-time implementation of Extubation Advisor TM (EA)
Timeframe: 1 year