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For critically ill patients, it is important to know when to liberate them from mechanical ventilation (the removal of breathing or endotracheal tube or extubation) and weaning (the progressive decrease of the amount of support that a patient receives from the mechanical ventilation). It is well recognized that prolonged ventilation and weaning harms patients and introduces significant increased costs to the health care system. The investigators objective is to improve the safety of removal of life support in critically ill patients by harnessing information from two new technologies; NM3 and Nexus device. In particular, the investigators are interested in the patterns of variation of respiratory and cardiac signals from the NM3 device, as well as monitor skin conductance with the Nexus device. The combination of these measures has not yet been investigated to date, and could represent a novel set of measures that can be used to help physicians better manage critically ill patients. The current standard of care dictates that once a patient is considered as a candidate for withdrawal from ventilation, a spontaneous breathing trial (SBTs) is performed, where the degree of ventilator support is decreased, and their response is observed to help predict if they will tolerate extubation.
Health is associated with a high degree of variation of physiologic parameters such as heart rate and respiratory rate, and illness & stress are associated with a loss of variability. The analysis of variability of biological signals measures the degree of fluctuations present over time. Previous studies have demonstrated that changes in variability (generally decreases) are observed in illness states, and the degree of this change correlates with illness severity. Several studies have reported that reduced heart or respiratory rate variability (HRV or RRV) during SBTs is associated with extubation failure. Until recently, variability analysis has traditionally been done only on heart rate (HRV), derived from analyzing beat-to-beat intervals from the ubiquitous electrocardiogram (ECG). The investigators aim to apply variability analysis to the respiratory and cardiac signals which represent a rich novel set of muti-organ variability measures whose utility in managing extubation and ventilator weaning has not been investigated to date.
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