Articles: mechanical-ventilation.
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Bedside monitors in the ICU routinely measure and collect patients' physiologic data in real time to continuously assess the health status of patients who are critically ill. With the advent of increased computational power and the ability to store and rapidly process big data sets in recent years, these physiologic data show promise in identifying specific outcomes and/or events during patients' ICU hospitalization. ⋯ Our proposed workflow may prove useful in the design of scalable approaches for real-time predictive systems in ICU environments, exploiting real-time vital sign information from bedside monitors. (ClinicalTrials.gov registration NCT02184208.).
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To increase the understanding of the self-extubation phenomena, we assessed its rate in our medical ICU and aimed to identify the risk factors of self-extubation and the risk factors for re-intubation. ⋯ Results of our study showed that, in the era of reduced use of sedatives in the ICU, clinicians must be vigilant of the risk of self-extubation in the first 2 d of mechanical ventilation in patients who are agitated and with a longer endotracheal tube to carina distance on chest radiograph.
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Detection of diaphragmatic muscle activity during invasive ventilation may provide valuable information about patient-ventilator interactions. Transesophageal electromyography of the diaphragm ([Formula: see text]) is used in neurally adjusted ventilatory assist. This technique is invasive and can only be applied with one specific ventilator. Surface electromyography of the diaphragm ([Formula: see text]) is noninvasive and can potentially be applied with all types of ventilators. The primary objective of our study was to compare the ability of diaphragm activity detection between [Formula: see text] and [Formula: see text]. ⋯ Analysis of our results showed that [Formula: see text] was not reliable for breathing effort detection in subjects who were invasively ventilated compared with [Formula: see text]. In stable recordings, however, [Formula: see text] and [Formula: see text] had excellent temporal correlation and good agreement. With optimization of signal stability, [Formula: see text] may become a useful monitoring tool.