Grant: Project Grant

During the pandemic, an increasing number of critically ill patients require life-saving ventilators. Given that ventilators are limited and prolonged exposure to ventilators is associated with patient harm (i.e., infection, weakness), it is vital to rapidly transition patients from ventilators to breathing on their own (i.e., successful extubation). Failed attempts at extubation (i.e., requiring breathing tube reinsertion) are harmful (increase the chance that patients will die), costly (increase the time spent in critical care units), and in COVID-19 patients, threaten the well-being of health care providers. To assist with extubation-decision making, clinicians assess individual patient's readiness to be extubated, by conducting spontaneous breathing trials (SBTs). During SBTs, ventilator support is reduced and clinicians observe patient's breathing pattern to determine if they can breathe on their own. However, SBTs can be performed in several ways and current indices to help clinicians to predict extubation success are poor. Previously, we showed that loss of breathing rate variability (capacity to increase or decrease breathing rate) during an SBT was the best predictor of extubation failure. Based on breathing rate variability, we developed and evaluated the Extubation Advisor (EA) tool. This novel tool aims to reduce the risk of extubation failure for individual patients by combining clinician's assessments of extubation readiness with breathing rate variability to improve outcomes prediction. We aim to conduct a multicenter, pilot randomized trial comparing this tool to standard care. In this trial, we will assess whether we can enroll patients, with and without COVID-19, and implement the protocol as designed. This is the first trial of an extubation decision support tool and specifically, this new technology. The EA tool holds promise as a tool that will aid clinicians to rapidly and safely transition patients from ventilators to breathing independently.